Difference between revisions of "Agriculture"

From Wiki
Jump to: navigation, search
 
(498 intermediate revisions by 5 users not shown)
Line 1: Line 1:
The most recent and complete agriculture model documentation is available on Pardee's [http://pardee.du.edu/ifs-agriculture-model-documentation website]. Although the text in this interactive system is, for some IFs models, often significantly out of date, you may still find the basic description useful to you.
+
<span style="font-family:arial,helvetica,sans-serif;">Please cite as: Dale S. Rothman,&nbsp;Hughes, Barry&nbsp;B., and Kanishka Narayan. 2017.&nbsp;''"IFs Agriculture Model Documentation."&nbsp;''Working paper 2017.07.04. Pardee Center for International Futures, Josef Korbel School of International Studies, University of Denver, Denver, CO. Accessed DD Month YYYY <[https://pardee.du.edu/wiki/Agriculture https://pardee.du.edu/wiki/Agriculture]></span>
  
The IFs agriculture model tracks the supply and demand, including imports, exports, and prices, of three agricultural commodities: crops, meat, and fish. Crops have direct food, animal feed, and industrial uses. Meat and fish have only food use. The agriculture model is also where land use dynamics and water use are tracked in IFs, as these are key resources for the agricultural sector.
+
The IFs agricultural model tracks the supply and demand, including imports, exports, and prices, of three agricultural commodities: crops, meat, and fish. Crops, meat and fish have direct food, animal feed, industrial and food manufactu<span style="font-family:arial,helvetica,sans-serif;">ring</span> uses. The agricultural model is also where land use dynamics and water use are tracked in IFs, as these are key resources for the agricultural sector.
  
 
The structure of the agriculture model is very much like that of the economic model. It combines a growth process with a partial economic equilibrium process using stocks and prices to seek a balance between the demand and supply sides. As in the economic model, no effort is made in the standard adjustment mechanism to obtain a precise equilibrium in any time step. Instead stocks serve as a temporary buffer and the model chases equilibrium over time.
 
The structure of the agriculture model is very much like that of the economic model. It combines a growth process with a partial economic equilibrium process using stocks and prices to seek a balance between the demand and supply sides. As in the economic model, no effort is made in the standard adjustment mechanism to obtain a precise equilibrium in any time step. Instead stocks serve as a temporary buffer and the model chases equilibrium over time.
  
The most important linkages between the agriculture model and other models within IFs are with the economic model. The economic model provides forecasts of average income levels, labor supply, total consumer spending, and agricultural investment, as well as parameters such as the capital elasticity of substitution, all of which are used in the agriculture model. In turn, the agriculture model provides forecasts on agricultural production, imports, exports, and demand for investment, which override the sectoral computations in the economic model. The agriculture model also has important links to the population and health models, using population forecasts and providing forecasts of calorie availability.
+
The most important linkages between the agriculture model and other models within IFs are with the economic model. The economic model provides forecasts of average income levels, labor supply, total consumer spending, and agricultural investment, all of which are used in the agriculture model. In turn, the agriculture model provides forecasts on agricultural production, imports, exports, and demand for investment, which override the sectoral computations in the economic model. The agricultural model also has important links to the population and health models, using population forecasts and providing forecasts of calorie availability.
  
== Structure and Agent System: Agriculture ==
 
  
{| class="tableGrid" style="width: 100%" cellspacing="0" cellpadding="5" border="0"
+
 
 +
= <span style="font-size:xx-large;">Dominant Relations</span> =
 +
 
 +
Agricultural production is a function of the availability of resources, e.g. land, livestock, capital, and labor, as well as climate factors and technology. Technology is most directly seen in the changing productivity of land in terms of crop yields, and in the production of meat relative to the input level of feed grain. The model also accounts for lost production (such as spoilage in the fields or in the first stages of the food supply chain), distribution and transformation losses and consumption losses (which account for food lost at the household levels) which are all determined by average income.
 +
 
 +
Agricultural demand depends on average incomes, prices, and a number of other factors. For example, changing diets can affect the demand for meat, which in turn affects the demand for feed crops. The industrial demand for crops, some of which is directed to the production of biofuels, is also affected by energy prices.
 +
 
 +
Production and demand, along with existing and desired stocks and historical trade patterns determine the trade in agricultural products. The differences in the supply of crops, meat, and fish (production after accounting for losses and trade) and the demand for these commodities are reflected in shifts in agricultural stocks. Stock shortages feed forward to actual consumption, which is addressed in the population model of IFs. Stocks, particularly changes in stocks, are a key driver of changes in crop prices. Crop prices are also influenced by the returns to agricultural investment and therefore to the basic underlying cost structure. Meat prices are tied to, and track world crop prices, while changes in fish prices are driven by changes in fish stocks.
 +
 
 +
Stocks and stock changes also play a role, along with general economic and agricultural demand growth, in driving the demand for agricultural investment. The actual levels of investment are finalized in the economic model of IFs and subject to constraints there. The investment can be of two types – investment for expanding and maintaining cropland (extensification) and investment for increasing crop yields per unit area (intensification). The expected relative rates of return determine the split.
 +
 
 +
The final key dynamics addressed in the agriculture model relate to land, livestock, and water. The latter of these is very straightforward, driven only by crop production. Changes in livestock are determined by changes in the amount of available grazing land, changes in the demand for meat, and the ability of countries to meet this demand as reflected in changing stocks.
 +
 
 +
In the IFs model, land is divided into 5 categories: crop land, grazing land, forest land, ’other’ land, and urban or built-up land. First, changes in urban land are driven by changes in average income and population, and draws from all other land types. Second, the investment in cropland development is the primary driver of changes in cropland, with shifts being compensated by changes in forest and "other" land. Third, changes in grazing land are a function of average income, with shifts again being compensated by changes in forest and "other" land. Finally, conservation policies can influence the amount of forest land, with any necessary adjustments coming from crop and grazing land.&nbsp;
 +
 
 +
 
 +
 
 +
= <span style="font-size:xx-large;">Structure and Agent System</span> =
 +
 
 +
{| class="tableGrid" style="width:100%;" cellspacing="0" cellpadding="5" border="1"
 
|-
 
|-
| style="width: 50%" | <div>'''System/Subsystem'''</div>
+
| style="width: 50%" | <div><span style="font-size:small">'''System/Subsystem'''</span><br/></div>
 
| style="text-align: left; padding-left: 10px" align="center" | <div>Agriculture</div>
 
| style="text-align: left; padding-left: 10px" align="center" | <div>Agriculture</div>
 
|-
 
|-
| style="text-align: left" | <div>'''Organizing Structure'''</div>
+
| style="text-align: left" | <div><span style="font-size:small">'''Organizing Structure'''</span></div>
 
| style="text-align: left; padding-left: 10px" align="center" | <div>Partial market&nbsp;equilibrium</div>
 
| style="text-align: left; padding-left: 10px" align="center" | <div>Partial market&nbsp;equilibrium</div>
 
|-
 
|-
| style="text-align: left" | <div>'''Stocks'''</div>
+
| style="text-align: left" | <div><span style="font-size:small">'''Stocks'''</span></div>
 
| style="text-align: left; padding-left: 10px" align="center" | <div>Capital, labor, accumulated technology, agricultural commodities, land</div>
 
| style="text-align: left; padding-left: 10px" align="center" | <div>Capital, labor, accumulated technology, agricultural commodities, land</div>
 
|-
 
|-
| style="text-align: left" valign="center" | <div>'''Flows'''</div>
+
| style="text-align: left" | <div><span style="font-size:small">'''Flows'''</span></div>
 
| style="text-align: left; padding-left: 10px" align="center" | <div>Production,&nbsp;loss, consumption, trade, investment</div>
 
| style="text-align: left; padding-left: 10px" align="center" | <div>Production,&nbsp;loss, consumption, trade, investment</div>
 
|-
 
|-
| style="text-align: left" | <div>'''Key Aggregate&nbsp;''' '''Relationships&nbsp;'''</div><div>(illustrative, not comprehensive)</div>
+
| style="text-align: left" | <div><span style="font-size:small">'''Key Aggregate&nbsp;''' '''Relationships&nbsp;'''</span></div><div><span style="font-size:small">(illustrative, not comprehensive)</span></div>
| style="text-align: left; padding-left: 10px" align="center" |  
+
| style="text-align: left; padding-left: 10px" align="center" | <div>Production function with endogenous technological change&nbsp;<br/></div><div><br/></div><div>Price determination</div>
Production function with endogenous technological change&nbsp; Price determination
+
 
+
 
|-
 
|-
| style="text-align: left" valign="center" | <div style="text-align: left">'''Key Agent-Class Behavior&nbsp;''' '''Relationships'''</div><div style="text-align: left">(illustrative, not comprehensive)</div>
+
| style="text-align: left" | <div style="text-align: left"><span style="font-size:small">'''Key Agent-Class Behavioral&nbsp;''' '''Relationships'''</span></div><div style="text-align: left"><span style="font-size:small">(illustrative, not comprehensive)</span></div>
 
| style="text-align: left; padding-left: 10px" align="center" |  
 
| style="text-align: left; padding-left: 10px" align="center" |  
 
Household crop, meat, and fish consumption
 
Household crop, meat, and fish consumption
  
Industry crop use Livestock producers crop use
+
Industry crop use
 +
 
 +
Livestock producers crop use
  
 
|}
 
|}
  
== Dominant Relations: Agriculture ==
+
= <span style="font-size:xx-large;">Flow Charts</span> =
  
Agricultural production is a function of the availability of resources, e.g. land, livestock, capital, and labor, as well as climate factors and technology. Technology is most directly seen in the changing productivity of land in terms of crop yields, and in the production of meat relative to the input level of feed grain. The model also accounts for lost production (such as spoilage in the fields or in the food supply chain), which is determined by average income.
+
== <span style="font-size:medium;">Overview</span> ==
  
Agricultural demand depends on average incomes, prices, and a number of other factors. For example, changing diets can affect the demand for meat, which in turn affects the demand for feed crops. The industrial demand for crops, some of which is directed to the production of biofuels, is also affected by energy prices.
+
The agriculture model combines a growth process in production with a partial equilibrium process that replaces the agricultural sector in the full-equilibrium economic model unless the user disconnects it. The model represents three agricultural commodities: crop, meat, and fish.
  
Production and demand, along with existing and desired stocks and historical trade patterns determine the trade in agricultural products. The differences in the supply of crops, meat, and fish (production after accounting for losses and trade) and the demand for these commodities are reflected in shifts in agricultural stocks. Stock shortages feed forward to actual consumption, which is addressed in the population model of IFs. Stocks, particularly changes in stocks, are a key driver of changes in crop prices. Crop prices are also influenced by the returns to agricultural investment and therefore to the basic underlying cost structure. Meat prices are tie to, and track crop prices, while changes in fish prices are driven by changes in fish stocks.
+
The key equilibrating variables are the stocks of the three commodities. Equilibration works via investment to control capital stock and via prices to control domestic demand.
  
Stocks and stock changes also play a role, along with general economic and agricultural demand growth, in driving the demand for agricultural investment. The actual levels of investment are finalized in the economic model of IFs and subject to constraints there. The investment can be of two types – investment for expanding and maintaining cropland (extensification) and investment for increasing crop yields per unit area (intensification). The expected relative rates of return determine the split.
+
Specifically, as food stocks rise, investment falls, restraining capital stock and agricultural production, and thus holding down stocks. Also, as stocks rise, prices fall, thereby increasing domestic demand, further holding down stocks. Domestic production and demand also influence imports and exports directly, which further affect stocks.
  
The final key dynamics addressed in the agriculture model relate to land, livestock, and water. The latter of these is very straightforward, driven only by crop production. Changes in livestock are determined by changes in the amount of available grazing land, changes in the demand for meat, and the ability of countries to meet this demand as reflected in changing stocks.
+
== <span style="font-size:x-large;">Agricultural Production</span> ==
  
In the IFs model, land is divided into 5 categories: crop land, grazing land, forest land, ’other’ land, and urban or built-up land. First, changes in urban land are driven by changes in average income and population, and draws from all other land types. Second, the investment in cropland development is the primary driver of changes in cropland, with shifts being compensated by changes in forest and "other" land. Third, changes in grazing land are a function of average income, with shifts again being compensated by changes in forest and "other" land. Finally, conservation policies can influence the amount of forest land, with any necessary adjustments coming from crop and grazing land.
+
=== <span style="font-size:large;">Crop Production</span> ===
  
== Agriculture Flow Charts ==
+
Crop production is most simply a product of the land under cultivation (cropland) and the crop yield per hectare of land. Yield is determined in a Cobb-Douglas type production function, the inputs to which are agricultural capital, labor, and technical change. Technical change is conceptualized as being responsive to price signals, but the model uses food stocks in the computation to enhance control over the temporal dynamics of responsiveness.&nbsp; Specifically, technology responds to the imbalance between desired and actual food stocks globally.&nbsp; In addition there is a direct response of yield change to domestic food stocks that represents not so much technical change as farmer behavior in the fact of market conditions (e.g. planting more intensively). Overall, basic annual yield growth is bound by the maximum of the initial model year's yield growth and an exogenous parameter of maximum growth.
  
=== Overview ===
+
This basic yield function is further subject to a saturation factor that is computed internally to the model̶–investments in increasing yield are subject to diminishing rather than constant returns to scale. Moreover, changes in atmospheric carbon dioxide (CO<sub>2</sub>) will affect agricultural yields both directly through CO<sub>2</sub> and indirectly through changes in temperature and precipitation. Finally, the user can rely on parameters to increase or decrease yield patterns indirectly with a multiplier or to use parameters to control the saturation effect and the direct and indirect effects of CO<sub>2</sub> on crop yield.
  
The agriculture model combines a growth process in production with a partial equilibrium process that replaces the agricultural sector in the full-equilibrium economic model unless the user disconnects it. The model represents three agricultural commodities: crop, meat, and fish.
+
[[File:CropproductionFlowchartKN.png|frame|center|text-bottom|571x500px|Agricultural Production Flowchart]]
  
The key equilibrating variables are the stocks of the three commodities. Equilibration works via investment to control capital stock and via prices to control domestic demand.
+
=== <span style="font-size:large;">Meat and Fish Production</span> ===
  
Specifically, as food stocks rise, investment falls, restraining capital stock and agricultural production, and thus holding down stocks. Also, as stocks rise, prices fall, thereby increasing domestic demand, further holding down stocks. Domestic production and demand also influence imports and exports directly, which further affect stocks.
+
Meat and fish production are represented far more simply than crop production. Meat production is simply the product of livestock herd size and the slaughter rate. Meat production includes production of non-meat animal products (eg. Milk and eggs). The herd size changes over time in response to global and domestic meat stocks, as well as changes in the demand for meat and the amount of grazing land.
  
This section presents several block diagrams that provide an overview of the variables and dynamics of the agricultural model.
+
Fish production has two components: wild catch and aquaculture. The former is based on actual data and an exogenous parameter that allows the user to influence rate of catch. Aquaculture is assumed to continue to grow at a country-specific growth rate; a multiplier can also be used to increase or decrease aquaculture production. &nbsp; <!--[if gte mso 9]><xml>
 +
<o:OLEObject Type="Embed" ProgID="Visio.Drawing.15" ShapeID="_x0000_i1025"
 +
  DrawAspect="Content" ObjectID="_1564742691">
 +
</o:OLEObject>
 +
</xml><![endif]-->
  
== Agricultural Production ==
+
[[File:Meat and fish production FlowchartKN.png|frame|center|text-bottom|571x500px|Meat and Fish Production Flowchart]]
  
=== Crop Production ===
+
== <span style="font-size:x-large;">Agricultural Demand</span> ==
  
Crop production is most simply a product of the land under cultivation (cropland)[[File:Crop production.png|border|right|564x476px|Crop production]] and the crop yield per hectare of land. Yield is determined in a Cobb-Douglas type production function, the inputs to which are agricultural capital, labor, and technical change. Technical change is conceptualized as being responsive to price signals, but the model uses food stocks in the computation to enhance control over the temporal dynamics of responsiveness.&nbsp; Specifically, technology responds to the imbalance between desired and actual food stocks globally.&nbsp; In addition there is a direct response of yield change to domestic food stocks that represents not so much technical change as farmer behavior in the fact of market conditions (e.g. planting more intensively). Overall, basic annual yield growth is bound by the maximum of the initial model year's yield growth and an exogenous parameter of maximum growth.
+
=== <span style="font-size:large;">Overview</span> ===
  
This basic yield function is further subject to a saturation factor that is computed internally to the model̶–investments in increasing yield are subject to diminishing rather than constant returns to scale. Moreover, changes in atmospheric carbon dioxide (CO<sub>2</sub>) will affect agricultural yields both directly through CO<sub>2</sub> and indirectly through changes in temperature and precipitation. Finally, the user can rely on parameters to increase or decrease yield patterns indirectly with a multiplier or to use parameters to control the saturation effect and the direct and indirect effects of CO<sub>2</sub> on crop yield.
+
Agricultural demand is divided into crops, meat, and fish. Crop demand is further divided into industrial, animal feed, and human food demand.&nbsp;
  
=== Meat and Fish Production ===
+
Food demand from crops, meat and fish are responsive to calorie demand, which in turn responds to GDP per capita (as a proxy for income).&nbsp; The division of calorie demand between demand for calories from crops and from meat and fish changes in response also to GDP per capita (increasing with income). Caloric demand is used as the basis to compute food demand through conversion to food demand in terms of grams per capita. The caloric value of demand is also used to compute food demand in terms of proteins per capita.&nbsp;
  
Meat and fish production are represented far more simply than crop p[[File:Meat and fish production.png|border|right|451x298px|Meat and fish production]]roduction. Meat production is simply the product of livestock herd size and the slaughter rate. The herd size changes over time in response to global and domestic meat stocks, as well as changes in the demand for meat and the amount of grazing land.
+
In addition to food demand, demand for feed, industrial demand for meat, crops and fish and food manufacturing demand are also computed. When all components of agricultural demand are computed, the price of the food elements of it are checked to assure that the total household demand for food does not exceed a high percentage of total country-level household consumption expenditures.
  
Fish production has two components: wild catch and aquaculture. The former is based on global catch and the regional share, both of which are specified exogenously. Aquaculture is assumed to continue to grow at a country-specific growth rate; a multiplier can also be used to increase or decrease aquaculture production.
+
=== <font size="4">Calorie Demand</font> ===
  
== Agricultural Demand ==
+
Crop use for food and meat demand are both influenced by calorie demand. Total per capita calorie demand is driven by GDP per capita, but can be limited by calorie availability as well as by an exogenous parameter specifying maximum calorie need.[[File:Calorie Demand FlowchartKN.png|frame|center|text-bottom|571x500px|Calorie demand flowchart]]
  
=== Overview ===
+
The calculations of demand for meat, fish and food crop determine the ultimate division of calorie sources.&nbsp; There is also a limit to the share of calories that can come from meat. The demand for calories from crops is simply the residual obtained by subtracting the demand for calories from meat and fish from the demand for total calories. Caloric value of demand is used to compute food demand in terms of grams per capita and in terms of proteins per capita.&nbsp; Caloric value of demand is adjusted for elasticities to prices for all three categories namely crops, meat and fish.
  
Agricultural demand is divided into crops, meat, and fish. Crop demand is further divided into industrial, animal feed, and human food demand.&nbsp;
+
The user can manipulate calorie demand through the use of an exogenous calorie multiplier and can reduce undernourishment to 5 percent of the population over time through the usage of two other hunger elimination parameters.
  
Meat and food demand are responsive to calorie demand, which in turn responds to GDP per capita (as a proxy for income).&nbsp; The division of calorie demand between demand for calories from crops and from meat changes in response also to GDP per capita (increasing with income).&nbsp;
+
=== Food Demand for Crops, Meat and Fish ===
  
When all components of agricultural demand are computed, the price of the food elements of it are checked to assure that the total household demand for food does not exceed a high percentage of total country-level household consumption expenditures.
+
Food demand is driven by the demand for calories. A conversion factor translates calorie demand into food demand in terms of grams per capita.&nbsp; Crop prices and an elasticity affect the resultant food demand.&nbsp; So too does a constraint on the maximum calories per capita and the size of the population.&nbsp;
  
== Industrial Crop Demand ==
+
[[File:Food demand flowchart KN.png|frame|center|text-top|571x500px|Food demand flowchart]]
  
Industrial crop demand (examples would be textile use of cotton or beverage inputs use of barley) is driven primarily by GDP per capita and population.&nbsp; &nbsp;Another important use in recent years has been for [[File:Industrial crop demand.png|border|right|527x241px|Industrial crop demand.png]]biofuels, and that demand component is responsive to world energy price and an elasticity.
+
=== <span style="font-size:large;">Industrial Demand</span> ===
  
Crop prices also influence total industrial agricultural demand.&nbsp; A maximum per capita demand parameter constrains the total and an exogenous multiplier allows users to alter the total.
+
Industrial demand (examples would be textile use of cotton or beverage inputs use of barley) is driven primarily by GDP per capita and population.&nbsp;&nbsp; Another important use in recent years has been for biofuels, and that demand component is responsive to world energy price and an elasticity.
  
== Animal Feed Demand for Crops ==
+
Crop prices also influence total industrial demand for crops.&nbsp; A maximum per capita demand parameter constrains the total and an exogenous multiplier allows users to alter the total.
  
The total feed demand for the livestock herd is dependent on the weight of the livestock herd and the per weight unit feed requirements.&nbsp; The per unit feed requirements increase with GDP per capita as populations move from meat sources such as chickens to more feed intensive ones such as pork and especially beef.&nbsp; But they also are reduced by change in the efficiency of converting feed to animal weight.[[File:Animal feed demand for crops.png|border|right|text-bottom|Animal feed demand for crops]]
+
[[File:IndustrialdemflowchartKN.png|frame|center|text-bottom|200x300px|Industrial demand flowchart]]
 +
 
 +
=== <span style="font-size:large;">Feed Demand&nbsp;</span> ===
 +
 
 +
The total feed demand for the livestock herd is dependent on the weight of the livestock herd and per unit weight feed requirements.&nbsp; The per unit feed requirements increase with GDP per capita as populations move from meat sources such as chickens to more feed intensive ones such as pork and especially beef.&nbsp; But they also are reduced by change in the efficiency of converting feed to animal weight.
  
 
Some of the food requirements of livestock are met by grazing, thereby reducing the feed requirements.&nbsp; The feed equivalent of grazing depends on the amount of grazing land, the productivity of that land (computed in the initial year and highly variable across countries), and grazing intensity (which increases with crop prices).
 
Some of the food requirements of livestock are met by grazing, thereby reducing the feed requirements.&nbsp; The feed equivalent of grazing depends on the amount of grazing land, the productivity of that land (computed in the initial year and highly variable across countries), and grazing intensity (which increases with crop prices).
  
Finally, the feed demand can be modified directly by the same exogenous crop demand parameter that modifies industrial crop demand.
+
Finally, the feed demand can be modified directly by an exogenous demand parameter that modifies industrial crop demand. The feed demand for meat and fish are calculated using ratios of the food demand to feed demand which are calculated in the initial years of the model. In addition to industrial demand and feed demand, food manufacturing demand is also calculated in the model on the basis of the food demand for all three categories (meat, crops and fish)
  
== Calorie Demand ==
+
[[File:FeeddemandKN.png|frame|center|564x476px|Feed demand flowchart]]
  
Crop use for food and meat demand are both influenced by calorie demand. Total per capita calorie demand is driven by GDP per capita, but can be limited by calorie availability as well as by an exogenous parameter specifying maximum calorie need.&nbsp;[[File:Calorie demand.png|border|right|calorie demand]]
+
=== <font size="4">Total Agricultural Demand</font> ===
  
The calculations of demand for meat and food crop determine the ultimate division of calorie sources (shown in other topics).&nbsp; Calories from meat are connected to the demand for meat in tons, with adjustments for the conversion of meat to crop equivalents and then crop equivalents to calories. There is also a limit to the share of calories that can come from meat. The demand for calories from crops is simply the residual obtained by subtracting the demand for calories from meat from the demand for total calories.
+
Total Agricultural demand is the sum of demand for crops to serve industrial, animal feed, food manufacturing and human food purposes.&nbsp;
  
== Food Demand for Meat and Fish ==
+
[[File:Total Ag demand KN.png|frame|center|564x500px|Total Agricultural Demand Flowchart]]
  
Meat and fish demand are only for food. Fish demand is the simpler.&nbsp; It is driven by changes in population, GDP per capita, and fish prices (the elasticity of demand for prices is currently hard-coded in the model and should be made a parameter).[[File:Food dd for meat and fish.png|border|center|Food demandd for meat and fish.png]]
+
=== <span style="font-size:large;">Financial Constraint on Food Demand</span> ===
  
The demand for meat also increases with population and GDP per capita, and falls with increasing meat prices. Additionally, it is also subject to a maximum level per capita. &nbsp;Further it is subject to a constraint that the calories provided by meat cannot exceed an exogenously specified maximum share of total calorie demand; if it does upon first calculation, it is recalculated to be consistent with that share.&nbsp; Finally, meat demand can be modified with a multiplier.
+
Total food demand in million metric tons consists of the sum of crop demand, meat demand and food demand and fish demand.&nbsp; It can be, however, that the monetary value of those calculated demands is greater than the financial ability of households to pay for them.&nbsp; When that is the case, the food ,meat and fish demand are proportionately reduced.<br/>[[File:Financial constraint on food demand KN.png|frame|center|575x400px|Visual representation of financial constraint on food demand]]
  
== Food Demand for Crops ==
+
=== <span style="font-size:x-large;">Agricultural Investment and Capital</span> ===
  
Food demand is driven by the demand for calories from crops, which is the residual of the total calorie demand and the demand for meat. A conversion factor translates calorie demand into food demand.&nbsp; Crop prices and an elastici[[File:Food dd for crops.png|border|right|460x413px|Food dd for crops.png]]ty affect the resultant food demand.&nbsp; So too does a constraint on the maximum calories per capita and the size of the population.&nbsp; Finally, the crop demand for food can be modified directly by an exogenous crop demand parameter.
+
The level of total desired agricultural investment are driven by the rate of past investment as a portion of GDP, changes in global crop demand as a portion of GDP, and global crop stocks relative to desired levels. We have experimented also with tying investment to profit rates in agriculture, thereby linking it also to prices relative to costs. The user can use a multiplier to increase or decrease the desired level of investment.&nbsp; This desired amount of investment is passed to the economic model, where it must ‘compete’ with demands for investments in other sectors.&nbsp; The economic model returns a final investment level for use in agriculture.&nbsp;
  
== Financial Constraint on Food Demand ==
+
Investment in agriculture has two possible targets. The first is capital stock. The second is land. The split between the two destinations is a function of the relative returns to cropland development and agricultural capital, the latter of which is determined by the increased yield that could be expected from an additional unit of agricultural capital.
  
Total food demand in million metric tons consists of the sum of meat demand and food demand.&nbsp; It can be, however, that the monetary value of those calculated demands is greater than the financial ability of households to pay for them.&nbsp; When that is the case, the food and meat demand are proportionately reduced.
+
[[File:AginvandcapitalFlowchartKN.png|frame|center|564x476px|Visual representation of agricultural investment and capital]]
  
[[File:Financial constraint on food dd.png|border|left|435x211px|Financial constraint on food dd.png]]
+
== <span style="font-size:x-large;">Land Dynamics</span> ==
  
 +
In IFs, land use is divided into 5 categories: cropland, grazing land, forest land, "other" land, and urban or built-up land. Four key dynamics are involved in land use change. First, changes in urban land are driven by changes in average income and population, and draws from all other land types. Second, the investment in cropland development is the primary driver of changes in cropland, but this is also influenced by the cost of developing cropland, the depreciation rate, or maintenance cost, of cropland investment, and a user-controllable multiplier. The costs of developing cropland increase as the amount of cropland increases and, therefore, there is less other land available for conversion. Shifts in cropland are compensated by changes in forest and "other" land. Third, changes in grazing land are a function of average income, with shifts again being compensated by changes in forest and "other" land. Finally, conservation policies can influence the amount of forest land, with any necessary adjustments coming from crop and grazing land.<br/>[[File:Land dynamics.png|frame|center|Visual representation of land dynamics]]
  
 +
= <span style="font-size:xx-large;">Agricultural Equations</span> =
  
 +
=== <span style="font-size:large;">Overview</span> ===
  
 +
Briefly, each year the agriculture model begins by estimating the production (pre&nbsp;and post-production loss) of crops, meat, and fish. It then turns to the demand for these commodities. This begins with a computation of caloric demand from crops, meat, and fish, which is translated into demand for food going directly to consumers. Other demands for crops, meat, and fish are for feed, industrial uses (e.g. biofuels), and food manufacturing. Losses in the production, distribution and consumption of agricultural commodities are also accounted for. This is followed by computations for trade. The model then considers the balance between the demands and the available supply based on production, imports, and exports. Any excess supply increases stocks. In the case of excess demand, stocks are drawn down; this can result in shortages if there are not enough stocks, which leads to an inability to meet all of the demands. Levels of, and changes in, stocks influence prices for the coming year, as well as desired investment, which are passed to the economic model, which determines the actual amount of investment that will be available. With this knowledge, the model can then estimate values for changes in land development, agricultural capital, and livestock for the coming year.
  
 +
=== <span style="font-size:x-large;">Agricultural Supply</span> ===
  
 +
Crop, meat, and fish supply have very different bases and IFs determines them in separate procedures.
  
 +
==== <span style="font-size:large;">Crop Production</span> ====
  
 +
Crop production, pre-loss, (AGPppl<sub>f=1</sub>) i is the product of total yield and land devoted to crops (LD<sub>l=1</sub>).
  
 +
<math>AGPppl_{r,f=1}= YL_r*LD_{r,l=1}</math>
  
 +
We focus here on the determination of yield; the amount of land devoted to crops is addressed in the sections below.Yield functions are almost invariably some kind of saturating exponential that represents decreasing marginal returns on inputs such as fertilizer or farm machinery. Such functions have been used, for instance in World 3<ref>Meadows, Dennis L. et al. 1974. Dynamics of Growth in a Finite World. Cambridge, Mass: Wright-Allen Press.</ref> , SARUM<ref>Systems Analysis Research Unit (SARU). 1977. SARUM 76 Global Modeling Project. Departments of the Environment and Transport, 2 Marsham Street, London, 3WIP 3EB</ref>, the Bariloche Model <ref>Herrera, Amilcar O., et al. 1976. Catastrophe or New Society? A Latin American World Model. Ottawa: International Development Research Centre.</ref>, and AGRIMOD <ref>Levis, Alexander H., and Elizabeth R. Ducot. 1976. "AGRIMOD: A Simulation Model for the Analysis of U.S. Food Policies." Paper delivered at Conference on Systems Analysis of Grain Reserves, Joint Annual Meeting of GRSA and TIMS, Philadelphia, Pa., March 31-April 2.</ref>. IFs also uses a saturating exponential, but relies on a Cobb-Douglas form. The Cobb-Douglas function is used in part to maintain symmetry with the economic model but more fundamentally to introduce labor as a factor of production. Especially in less developed countries (LDCs) where a rural labor surplus exists, there is little question that labor, and especially labor efficiency improvement, can be an important production factor.
  
 +
===== Pre-processor and first year =====
  
 +
In the pre-processor, agricultural production is initialized using data from the FAO food balance sheets. For details of the series that are used in this initialization, refer Annex 1 of this document. In the first year of the model, total crop production is calculated by adjusting the initialized value of crop production for production losses, as the FAO data are for post-loss production. Yield (YL) is computed simply as the ratio of total crop production (AGPppl<sub>f=1</sub>) to cropland (LD<sub>l=1</sub>). It is bound, however, to be no greater than 100 tons per hectare in any country.
  
==  ==
+
In addition to yield, a number of other values related to production are calculated in the first year of the model that are used in forecast years.
  
== [[File:Total Crop dd.png|border|center|Total Crop dd.png]] ==
+
First, a scaling factor cD is calculated in the first year of the model. This is basically the constant in the Cobb-Douglas formulation for estimating yields. It is based upon the base year yield (YL), capital (KAG), and labor supply (LABS). The labor supply is adjusted using a Cobb-Douglass alpha exponent (CDALF) which is explained in detail below. &nbsp;cD is similar to the shift factors elsewhere in the model, which are used to match predicted values in the base year to actual values.&nbsp; It does not change over time. It is computed using the following equation,
  
== Agricultural Investment and Capital ==
+
<math>cD_r= YL_{r,t=1}/ KAG_{r,t=1} ^ {CDALF_{r,s=1}} * LABS_{r,S=1,t=1} ^ {(1-CDALF_{r,s=1})}</math>
  
The level of total desired agricultural investment are driven by the rate of past investment as a [[File:Agricultural Investment and Capital.png|border|right|Agricultural Investment and Capital.png]]portion of GDP, changes in global crop demand as a portion of GDP, and global crop stocks relative to desired levels. We have experimented also with tying investment to profit rates in agriculture, thereby linking it also to prices relative to costs. The user can use a multiplier to increase or decrease the desired level of investment. &nbsp;This desired amount of investment is passed to the economic model, where it must ‘compete’ with demands for investments in other sectors. &nbsp;The economic model returns a final investment level for use in agriculture.&nbsp;
+
Second, a target growth rate in yield is computed (TgrYli) which is used in forecast years to restrict the growth rate of the yield. This target growth is a function of current crop demand (AGDEM), expected crop demand (Etdem), and a target growth rate in cropland.
  
Investment in agriculture has two possible targets. The first is capital stock. The second is land. The split between the two destinations is a function of the relative returns to cropland development and agricultural capital, the latter of which is determined by the increased yield that could be expected from an additional unit of agricultural capital.
+
<math>Tgryli_{r}= (Etdem/AGDEM_{r,s=1}) -1-tgrld_{r} </math>
  
== Land Dynamics ==
+
where,
  
In IFs, land use is divided into 5 categories: cropland, grazing land, forest land, "other" land, and urban or built-up land. Four key dynamics are involved in land use change. First, changes in urban land are driven by changes in average income and population, and draws from all other land types. Second, the investment in cropland development is the primary driver of changes in cropland, but this is also influenced by the cost of developing cropland, the depreciation rate, or maintenance cost, of cropland investment, and a user-controllable multiplier. The costs of developing cropland increase as the amount of cropland increases and, therefore, there is less other land available for conversion. Shifts in cropland are compensated by changes in forest and "other" land. Third, changes in grazing land are a function of average income, with shifts again being compensated by changes in forest and "other" land. Finally, conservation policies can influence the amount of forest land, with any necessary adjustments coming from crop and grazing land.
+
'''''tgrld''''' is a country-specific parameter indicating target growth in crop land
  
== Agricultural Equations ==
+
Etdem is an initial year estimate of the sum of industrial, feed and food demand for crops in the following year
  
=== Overview ===
+
===== Forecast years =====
  
Briefly, each year the agriculture model begins by estimating the production of crops, meat, and fish. It then turns to the demand for these commodities, followed by trade. The model then looks at changes in stocks and potential shortages related to calorie availability. These influence prices for the coming year, as well as desired investment, which are passed to the economic model, which determines the actual amount of investment that will be available. With this knowledge, the model can then estimate values for changes in land development, agricultural capital, and livestock for the coming year.
+
In forecast years, IFs computes yield in stages. The first provides a basic yield (Byl) representing change in long-term factors such as capital, labor and technology. The second stage uses this basic yield as an input and modifies it based on prices, so as to represent changes in shorter-term factors (e.g. amounts of fertilizer used, even the percentage of land actually under cultivation). Finally, in a third stage, yields are adjusted in response to changing climate conditions.
  
This help section presents and discusses the equations that are central to each of these steps in the agricultural model. Along the way, it also presents information related to the actions in the pre-processor and first year of the agriculture model, which are important in setting the stage for the forecasts.
+
'''''<u>First stage (Adjustment for long-term factors)</u>'''''
  
== Agricultural Supply ==
+
The basic yield (Byl) relates yield to agriculture capital (KAG), agricultural labor (LABS), technological advance (Agtec), a scaling parameter (cD), an exponent (CDALF), and a saturation coefficient (Satk).
  
<span>Crop, meat, and fish supply have very different bases and IFs determines them in separate procedures.</span>
+
<math>Byl_{r}= cD_{r}*(1+Agtec_{r} )_{t-1}* KAG_{r}^ {CDALF_{r,s=1}} * LABS_{r,s=1} ^ {(1-CDALF)_{r,s=1}} * Satk_{r} </math>
  
== Crop Production ==
+
The equations for KAG and LABS are described elsewhere (see the sections below&nbsp; and the economic model, respectively).&nbsp;
  
Crop production (AGP<sub>f=1</sub>) i is the product of yield and land devoted to crops (LD<sub>l=1</sub>).
+
*cD is the scaling factor calculated in the first year of the model. Its calculation is described in the section above
  
<math>\{AGP_{r,f=1}}={YL_r}*{LD{r,l=1}}</math>
+
*CDALF is the standard Cobb-Douglas alpha reflecting the relative elasticities of yield to capital and labor.&nbsp; It is computed each year in a function, rooted in data on factor shares from the Global Trade and Analysis Project, driven by GDP per capita at PPP.<ref>Following table is used to update CDALF, GDP/Capita (PPP) Versus Cobb-Douglas Alpha (GTAP 5)</ref>
  
We focus here on the determination of yield; the amount of land devoted to crops is addressed in the [http://www.du.edu/ifs/help/understand/agriculture/equations/land/index.html Land Dynamics] section.
+
Agtec is a factor-neutral technological progress coefficient similar to a multifactor productivity coefficient. It is initially set to 1 and changes each year based upon a technological growth rate (YlGroTech). Its computation is described below.
  
Yield functions are almost invariably some kind of saturating exponential that represents decreasing marginal returns on inputs such as fertilizer or farm machinery. Such functions have been used, for instance in World 3 (Meadows, 1974), SARUM, (SARU, 1977), the Bariloche Model (Herrera, et al., 1976), and AGRIMOD (Levis, et al., 1977). IFs also uses a saturating exponential, but relies on a Cobb-Douglas form. The Cobb-Douglas function is used in part to maintain symmetry with the economic model but more fundamentally to introduce labor as a factor of production. Especially in less developed countries (LDCs) where a rural labor surplus exists, there is little question that labor, and especially labor efficiency improvement, can be an important production factor.
+
&nbsp;<math>Agtec_{r}= Agtec_{r,t-1}*(1+ YlGroTech_{r})</math>
  
In the first year of the model, yield (YL) is computed simply as the ratio of crop production (AGP<sub>f=1</sub>) to cropland (LD<sub>l=1</sub>). The determinations of the initial values of these variables are described elsewhere in this document. It is bound, however, to be no greater than 20 tons per hectare in any country.
+
*The saturation coefficient Satk is a multiplier of the Cobb-Douglas function and of the technological change element. It is the ratio of the gap between a maximum possible yield (YLLim) and a moving average of yields to the gap between a maximum possible yield and the initial yield, raised to an exogenous yield exponent ('''''ylexp'''''). With positive parameters the form produces decreasing marginal returns.
  
In forecast years, IFs computes yield in stages. The first provides a basic yield (BYL) representing change in long-term factors such as capital, labor and technology. The second stage uses this basic yield as an input and modifies it based on prices, so as to represent changes in shorter-term factors (e.g. amounts of fertilizer used, even the percentage of land actually under cultivation). Finally, in a third stage, yields are adjusted in response to changing climate conditions.
+
<math>Satk_{r+1}=(YLLim_{r}-Syl_{r}/YLLim_{r}-YL_{r,t=1})^ {ylexp}</math>
  
The basic yield (byl) relates yield to agriculture capital (KAG), agricultural labor (LABS), technological advance (AGTEC), a scaling parameter (CD), an exponent (CDALF), and a saturation coefficient (SATK).
+
where,
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq2.png http://www.du.edu/ifs/help/media/images/ag-module/ageq2.png]
+
Syl<sub>r</sub> is a moving average of byl, the historical component of which is weighted by 1 minus the user-controlled global parameter '''''ylhw'''''.
  
The equations for KAG and LABS are described elsewhere (see the [http://www.du.edu/ifs/help/understand/agriculture/equations/capital.html Capital Dynamics] and the economic model, respectively).&nbsp;
+
'''''ylexp&nbsp;'''''is a global parameter
  
cD is a scaling factor calculated in the first year of the model based upon the base year yield (YL), capital (KAG), and labor supply (LABS).&nbsp; It is similar to the shift factors elsewhere in the model, which are used to match predicted values in the base year to actual values.&nbsp; It does not change over time.
+
The maximum possible yield (YLLim) is estimated for each country and can change over time.&nbsp; It is calculated as the maximum of 1.5 times the initial yield (YL<sub>r,t=1</sub>) and the multiple of an external user-controlled parameter ('''''ylmax''''') and an adjustment factor (YLMaxM).
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq3.png http://www.du.edu/ifs/help/media/images/ag-module/ageq3.png]
+
<math>YLLim_{r} = max⁡(ylmax_{r}* YLMaxM_{r}, 1.5* YL_{r,t=1})</math>
  
CDALF is the standard Cobb-Douglas alpha reflecting the relative elasticities of yield to capital and labor.&nbsp; It is computed each year in a function, rooted in data on factor shares from the Global Trade and Analysis Project, driven by GDP per capita at PPP.
+
where,
  
AGTEC is a factor-neutral technological progress coefficient similar to a multifactor productivity coefficient. It is initially set to 1 and changes each year based upon a technological growth rate (TECHGROAG).
+
'''''ylmax''''' is a country-specific parameter
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq4.png http://www.du.edu/ifs/help/media/images/ag-module/ageq4.png]
+
The adjustment factor YLMaxM allows for some additional growth in the yields for poorer countries
  
The algorithmic structure for computing the annual values of TECHGRO involves four elements:
+
<math>YLMaxM_{r} = 1*((1-DevWeight_{r})+(YL_{r}/YlMaxFound)^ {0.35* DevWeight_{r}})</math>
  
The difference between a targeted yield growth calculated the first year and the portion of that growth not initially related to growth of capital and labor (hence the underlying initial technology element of agricultural production growth); call it AGTECHINIT.&nbsp; This element is assumed to decrease by half over100 years.
+
where,
  
The gap between desired global crop stock levels and actual stocks (hence the global pressure for technological advance in agriculture); call it AGTECHPRESS. This contribution is introduced by way of the ADJUSTR function of IFs.<sup>[http://www.du.edu/ifs/help/understand/agriculture/equations/supply/crop.html#footnote [1]]</sup>
+
DevWeight<sub>r</sub> is GDPPCP<sub>r</sub>/30, with a maximum value of 1
  
The difference between the productivity of the agricultural sector calculated in the economic model and the initial year's value of that (hence reflecting changes in the contributions of human, social, physical, and knowledge capital to technological advance of the society generally); call if AGMFPLT.
+
YlMaxFound is the maximum value of YL found in the first year
  
The degree to which crop production is approaching upper limits of potential; this again involves the saturation coefficient (SATK).
+
{| border="1" cellspacing="0" cellpadding="0"
 +
|-
 +
| style="width:575px;" |
 +
'''<u>Box1: Computation of technological growth rate for yield</u>'''
  
The algorithmic structure this is:
+
The algorithmic structure for computing the annual values of YlGroTech involves four elements:&nbsp;
 +
<ol style="list-style-type:lower-alpha;">
 +
<li>The difference between a targeted yield growth calculated the first year and the portion of that growth not initially related to growth of capital and labor (hence the underlying initial technology element of agricultural production growth); call it AgTechInit.</li>
 +
<li>The gap between desired global crop stock levels and actual stocks (hence the global pressure for technological advance in agriculture); call it AgTechPress. This contribution is introduced by way of the ADJUSTR function of IFs.<ref>The ADJSTR function, used throughout the model, is a PID controller that builds in some anticipatory and smoothing behavior to equilibrium processes by calculating an adjustment factor. It considers both the gap between the current value of the specific variable of interest, here crop stocks, and a target value, as well as change in the gap since the last time step. Two parameters control the degree to which these two "differences" affect the calculation of the adjustment factor. In this case, these are the global, user-controllable parameters elfdpr1 and elfdpr2.</ref></li>
 +
<li>The difference between the productivity of the agricultural sector calculated in the economic model and the initial year's value of that (hence reflecting changes in the contributions of human, social, physical, and knowledge capital to technological advance of the society generally); call if AgMfpLt.</li>
 +
<li>The degree to which crop production is approaching upper limits of potential; this again involves the saturation coefficient (Satk).</li>
 +
</ol>
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq5.png http://www.du.edu/ifs/help/media/images/ag-module/ageq5.png]
+
The algorithmic structure of&nbsp;this is:
  
The saturation coefficient is a multiplier of the Cobb-Douglas function and of the technological change element. It is the ratio of the gap between a maximum possible yield (YLLim) and a moving average of yields to the gap between a maximum possible yield and the initial yield, raised to an exogenous yield exponent ('''''ylexp'' '''). With positive parameters the form produces decreasing marginal returns.
+
<math>YlgroTech_{r} = F(AgTechInit_{r},AgTechPress_{r},AgMfpLt_{r},Satk_{r})</math>
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq6.png http://www.du.edu/ifs/help/media/images/ag-module/ageq6.png]
+
|}
  
''where''
+
'''''<u>Second stage of yield calculation (short term factors)</u>'''''
  
syl<sub>r</sub> is a moving average of byl, the historical component of which is weighted by 1 minus the user-controlled global parameter '''''ylhw'' '''.
+
Before moving to the next stage, a check is made to see if the growth in byl is within reason.&nbsp; Specifically, Byl is not allowed to exceed the moving average of Byl (Syl) times a given growth rate (YlGrbound).&nbsp; This bound is the maximum of a user-controlled global parameter&nbsp;&nbsp;'''''ylmaxgr''''' and an initial country specific target growth rate (Tgryli<sub>r</sub>).<ref>There is also an adjustment whereby ylmaxgr is reduced for countries with syl>5, falling to a value of 0.01 when syl>=8. Also, for countries with a yield greater than world yields, the additional growth rate in yields due to change in agricultural investment is restricted to a value that is equal to ylmaxgr.</ref>
  
'''''ylexp'' ''' global parameter
+
At this point, the basic yield (Byl) is further adjusted by a number of factors.&nbsp; The first of these is a simple country-specific user-controlled multiplier&nbsp;&nbsp;'''''ylm'''''. This can be used to represent the effects of any number of exogenous factors, such as political/social management (e.g., collectivization of agriculture).
  
The maximum possible yield (YLLim) is estimated for each country and can change over time.&nbsp; It is calculated as the maximum of 1.5 times the initial yield (YL<sub>r,t=1</sub>) and the multiple of an external user-controlled parameter ('''''ylmax'' ''') and an adjustment factor (YLMaxM).
+
<math>YL_r= YL_r*ylm </math>
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq7.png http://www.du.edu/ifs/help/media/images/ag-module/ageq7.png]
+
The basic yield represents the long-term tendency in yield but agricultural production levels are quite responsive to short-term factors such as fertilizer use levels and intensity of cultivation. Those short-term factors under farmer control (therefore excluding weather) depend in turn on prices, or more specifically on the profit (FPROFITR) that the farmer expects. Because of computational sequence, we use domestic food stocks as a proxy for profit level. Note that this adjustment is distinct from the adjustment above where global stocks affect the technological growth rate.
  
''where''
+
The stock adjustment factor uses the ADJSTR function to calculate an adjustment factor related to the current stocks, the recent change in stocks, and a desired stock level.&nbsp; The desired stock level is given as a fraction (Agdstl) of the sum of crop demand (AGDEM<sub>f=1</sub>) and crop production (AGP<sub>f=1</sub>). Agdstl is set to be 1.5 times '''''dstl''''', which is a global parameter that can be adjusted by the user.
  
'''''ylmax'' ''' is a country-specific parameter&nbsp;
+
The focus in IFs on yield response to prices differs somewhat from the normal use of price elasticities of supply. For reference, Rosegrant, Agcaoili-Sombila, and Perez (1995: 5) report that price elasticities for crops are quite small, in the range of .05 to .4.<ref>Rosegrant, Mark W., Mercedita Agcaoili-Sombilla, and Nicostrato D. Perez. 1995. "Global Food Projections to 2020: Implications for Investment." Washington, D.C.: International Food Policy Research Institute. Food, Agriculture, and the Environment Discussion Paper 5.</ref>
  
The adjustment factor YLMaxM allows for some additional growth in the yields for poorer countries
+
'''''<u>Third stage of yield calculation (Adjustment for a changing climate)</u>'''''
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq8.png http://www.du.edu/ifs/help/media/images/ag-module/ageq8.png]
+
In the third stage, IFs considers the potential effects of a changing climate on crop yields. This is introduced through the variable ENVYLCHG[[#_ftn4|[4]]] which is calculated in the environmental model. This variable consists of two parts: the direct effect of atmospheric carbon dioxide concentrations and the effects of changes in temperature and precipitation.
  
''where''
+
<math>ENVYLCHG_{r,f} =(((CO2Fert_{t}/100)+1)*((DeltaYClimate_{R,t}/100)+1)-1)*100</math>
  
DevWeight<sub>r</sub> is the GDPPCP<sub>r</sub>/30, with a maximum value of 1
+
The direct effect of atmospheric carbon dioxide assumes a linear relationship between changes in the atmospheric concentration from a base year of 1990 and the percentage change in crop yields.
  
YlMaxFound is the maximum value of YL found in the first year
+
<math>CO2Fert_{t+1} = envco2fert *((CO2PPM- CO2PPM_{t=1990})/CO2PPM_{t=1990} )</math>
  
Before moving to the next stage, a check is made to see if the growth in byl is within reason.&nbsp; Specifically, byl is not allowed to exceed the moving average of byl (syl) times a given growth rate (ylgrbound).&nbsp; This bound is the maximum of a user-controlled global parameter - '''''ylmaxgr'' ''' and an initial country specific target growth rate (tgryli<sub>r</sub>).<sup>[http://www.du.edu/ifs/help/understand/agriculture/equations/supply/crop.html#footnote [2]] </sup>&nbsp; This latter target growth rate in yield is set in the first year and is a function of current crop demand (AGDEM), expected crop demand (etdem), and a target growth rate in cropland.
+
where,
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq9.png http://www.du.edu/ifs/help/media/images/ag-module/ageq9.png]
+
'''''envco2fert''''' is a global, user-controllable parameter
  
''where''
+
CO2PPM<sub>t=1990</sub> is hard coded as 354.19 parts per million
  
'''''<span>tgrld</span> '' ''' <span>is a country-specific parameter indicating target growth in crop land</span>
+
The effect of changes in annual average temperature and precipitation are based upon two assumptions: 1) there is an optimal temperature (Topt) for crop growth, with yields falling both below and above this temperature and 2) there is a logarithmic relationship between precipitation and crop yields.&nbsp; The choice of this functional form was informed by work reviewed in Cline (2007)<ref>Cline, William R. 2007. Global warming and agriculture: Impact estimates by country. Washington, DC: Peterson Institute for International Economics.</ref>.&nbsp; Together, these result in the following equation:
  
<span>etdem is an initial year estimate of the sum of industrial, feed and food demand for crops in the following year</span>
+
<math>ClimateEffect_{t+1} = 100*{({e^{(-0.5*(T0_{r}+ DeltaT{r} - Topt)^2)/SigmaTsqd}*ln⁡(P0_{r}*(DeltaP_{r}/100+1))/e^{(-0.5*(T0_{r}-Topt)^2/SigmaTsqd}*ln⁡(P0_r))-1}} </math>
  
<span>At this point, the basic yield (BYL) is adjusted by a number of factors.&nbsp; The first of these is a simple country-specific user-controlled multiplier – '''''ylm'' '''. '''''ylm'' ''' can be used to represent the effects of any number of exogenous factors, such as political/social management (e.g., collectivization of agriculture).</span>
+
where,
  
<span>The basic yield represents the long-term tendency in yield but agricultural production levels are quite responsive to short-term factors such as fertilizer use levels and intensity of cultivation. Those short-term factors under farmer control (therefore excluding weather) depend in turn on prices, or more specifically on the profit (FPROFITR) that the farmer expects. Because of computational sequence, we use domestic food stocks as a proxy for profit level.</span>
+
T0 and P0 are country-specific annual average temperature (degrees C) and precipitation (mm/year) for the period 1980-99.
  
<span>In this second stage, the recomputed yield (YL) is multiplied by a stock adjustment factor.</span>
+
DeltaT and DeltaP are country specific changes in annual average temperature (degrees C) and precipitation (percent) compared to the period 1980-99.&nbsp; These are tied to global average temperature changes and described in the documentation of the IFs environment model.
  
<span>[http://www.du.edu/ifs/help/media/images/ag-module/ageq10.png http://www.du.edu/ifs/help/media/images/ag-module/ageq10.png]</span>
+
Topt is the average annual temperature at which yield is maximized.&nbsp; It is hard coded with a value of 0.602 degrees C.
  
<span>The stock adjustment factor uses the ADJSTR function to calculate an adjustment factor related to the current stocks, the recent change in stocks, and a desired stock level.&nbsp; The desired stock level is given as a fraction (agdstl) of the sum of crop demand (AGDEM<sub>f=1</sub>) and crop production (AGP<sub>f=1</sub>). agdstl is set to be 1.5 times '''''dstl'' ''', which is a global parameter that can be adjusted by the user.</span>
+
SigmaTsqd is a shape parameter determining how quickly yields decline when the temperature moves away from the optimum. It is hard coded with a value of 309.809.
  
<span>The focus in IFs on yield response to prices differs somewhat from the normal use of price elasticities of supply. For reference, Rosegrant, Agcaoili-Sombila, and Perez (1995: 5) report that price elasticities for crops are quite small, in the range of .05 to .4.</span>
+
CO2Fert and ClimateEffect are multiplied by each other to determine the effect on crop yields.
  
<span>In the third stage. IFs considers the potential effects of a changing climate on crop yields. This is separated into two parts: the direct effect of atmospheric carbon dioxide concentrations and the effects of changes in temperature and precipitation.</span>
+
There are two final checks on crop yields.&nbsp; They are not allowed to be less than one-fifth of the estimate of basic yield (Byl) and they cannot exceed the country-specific maximum ('''''ylmax''''') or 100 tons per hectare. Finally crop production is adjusted for production losses to arrive at post loss production (AGP). Losses are discussed in detail in the sections below
  
<span>The direct effect of atmospheric carbon dioxide assumes a linear relationship between changes in the atmospheric concentration from a base year of 1990 and the percentage change in crop yields.</span>
+
==== Meat Production ====
  
<span>[http://www.du.edu/ifs/help/media/images/ag-module/ageq11.png http://www.du.edu/ifs/help/media/images/ag-module/ageq11.png]</span>
+
Meat production in IFs is the sum of animal meat production and non-meat animal products (AGPMILKEGGS<sub>R</sub>). Animal meat production in a particular country is a function of the herd size and the slaughter rate and non-animal meat products are calculated by applying a ratio MilkEggstoMeatI<sub>R</sub>&nbsp;which is calculated in the first year of the model as the ratio of non-meat animal production to the meat production. Meat production is then adjusted for production losses which are described in detail in the sections below.
  
''where''
+
<math>AGP_{r,f=2} =((LVHERD_{r}* slr)+ AGPMILKEGGS_r )- AGLOSSPROD_{r,f=2}</math>
  
'''''<span>envco2fert</span> '' ''' <span>is a global, user-controllable parameter</span>
+
where,
  
<span>CO2PPM<sub>t=1990</sub> is hard coded as 354.19 parts per million</span>
+
LVHERD is the size of livestock in a particular country in a particular year
  
<span>The effect of changes in annual average temperature and precipitation are based upon two assumptions: 1) there is an optimal temperature (Topt) for crop growth, with yields falling both below and above this temperature and 2) there is a logarithmic relationship between precipitation and crop yields.&nbsp; The choice of this functional form was informed by work reviewed in Cline (2007).&nbsp; Together, these result in the following equation:&nbsp;</span>
+
'''''slr&nbsp;'''''is the slaughter rate which is a global parameter
  
<span>[http://www.du.edu/ifs/help/media/images/ag-module/ageq12.png http://www.du.edu/ifs/help/media/images/ag-module/ageq12.png]</span>
+
AGLOSSPROD is the meat production loss.
  
''where''
+
===== Pre-processor and first year =====
  
<span>T0 and P0 are country-specific annual average temperature (degrees C) and precipitation (mm/year) for the period 1980-99.</span>
+
In the pre-processor, meat production is initialized in the model using data from the FAO food balance sheets. Total meat production and animal meat production (which is the sum of bovine meat production, mutton and goat meat production, pig meat production, poultry meat production, and other meat production) are initialized separately. If data on all of the animal meat sub-categories is unavailable, then animal meat production is calculated as 30 percent of total meat production. Animal production is also not allowed to exceed 99% of the value of total meat production.
  
<span>DeltaT and DeltaP are country specific changes in annual average temperature (degrees C) and precipitation (percent) compared to the period 1980-99.&nbsp; These are tied to global average temperature changes and described in the documentation of the IFs environment model.</span>
+
&nbsp;
  
<span>Topt is the average annual temperature at which yield is maximized.&nbsp; It is hard coded with a value of 0.602 degrees C.</span>
+
AGPMILKEGGS<sub>R</sub>, which is the non-meat animal production is then calculated as total meat production minus total animal meat production. The non-meat production ratio MilkEggstoMeatI<sub>R</sub>&nbsp;is calculated as the ratio of the initialized value of AGPMILKANDEGGS<sub>R</sub> and meat production in the first year. This is used in forecast years to calculate the value of non-meat animal production, and is held constant over time.
  
<span>SigmaTsqd is a shape parameter determining how quickly yields decline when the temperature moves away from the optimum. It is hard coded with a value of 309.809.</span>
+
<math>MilkEggstoMeatI_{r} = AGPMILKEGGS_{r}/(AGP_{r,f=2}- AGPMILKEGGS_{r})</math>
  
<span>CO2Fert and ClimateEffect are multiplied by each other to determine the effect on crop yields.</span>
+
The size of the livestock (LVHERD<sub>R</sub>) is also computed in the first year using the initialized value of pre-loss meat production. This value of LVHERD<sub>R</sub> is used in forecast years to compute meat production.
  
<span>There are two final checks on crop yields.&nbsp; They are not allowed to be less than one-fifth of the estimate of basic yield (BYL) and they cannot exceed the country-specific maximum ('''''ylmax'' ''') or 50 tons per hectare.</span>
+
<math>LVHERD_{r} = (AGPppl_{r,f=2} - AGPMILKEGGS_{r} )/slr </math>
<div>
+
----
+
<div>
+
[file:///C:/Users/Ara/Desktop/Agricultural%20Documentation%20v19_AG.docx#_ftnref1 [1]] The ADJSTR function, used throughout the model, is a PID controller that builds in some anticipatory and smoothing behavior to equilibrium processes by calculating an adjustment factor.&nbsp; It considers both the gap between the current value of the specific variable of interest, here crop stocks, and a target value, as well as change in the gap since the last time step.&nbsp; Two parameters control the degree to which these two "differences" affect the calculation of the adjustment factor.&nbsp; In this case, these are the global, user-controllable parameters '''''elfdpr1'' ''' and '''''elfdpr2'' '''.
+
  
[file:///C:/Users/Ara/Desktop/Agricultural%20Documentation%20v19_AG.docx#_ftnref1 [2]]&nbsp;There is also an adjustment whereby&nbsp;'''''ylmaxgr'' '''&nbsp;is reduced for countries with syl>5, falling to a value of 0.01 when syl>=8.
+
For a detailed discussion on the dynamics of livestock herd, refer to this [[Section|section]].
  
== Meat Production ==
+
===== Forecast years =====
  
<span data-mce-mark="1">Meat production, in metric tons, is given as the multiple of the herd size (LVHERD) and the slaughter rate ('''''slr'' '''). The latter is a global parameter.</span>
+
Pre-production loss values for meat production are calculated in IFs as meat production (AGPppl<sub>R,f=2</sub>) and production of non-meat animal products (AGPMILKANDEGGS<sub>R</sub>). Meat production, in metric tons, is given as the multiple of the herd size (LVHERD<sub>R</sub>) and the slaughter rate ('''''slr'''''). The latter is a global parameter. These values are then adjusted for production losses for meat (AGPRODLOSS<sub>R,f=2</sub>) to arrive at post production loss values (AGP<sub>R,f=2</sub>). The same meat production loss percentage is also applied to the non-meat production to arrive at post loss production values for the variable. The dynamics of production losses are discussed here.
  
<span data-mce-mark="1">[http://www.du.edu/ifs/help/media/images/ag-module/ageq13.png http://www.du.edu/ifs/help/media/images/ag-module/ageq13.png]</span>
+
<math>AGP_{r,f=2} = AGPppl_{r,f=2} - AGLOSSPROD_ {r,f=2}</math>
  
<span data-mce-mark="1">The dynamics of the livestock herd are described in the [http://www.du.edu/ifs/help/understand/agriculture/equations/livestock.html Livestock Dynamics] section.</span>
+
where,
  
== Fish Production ==
+
<math>AGPppl_{r,f=2} = (AGPMILKANDEGGSppl_{r} +( LVHERD_{r}*slr)) </math>
  
The production of fish has two components, wild catch and aquaculture. Total global wild fish catch ('''''ofscth'' '''), and each region's share in it ('''''rfssh<sub>r</sub> '' ''') are exogenous parameters that can be set by the user.
+
Production of non-animal meat products is computed using the non-meat production ratio&nbsp;which is applied to the animal meat production.
  
The amount of aquaculture (AQUACUL) in the first year is provided by historical data; these values can be modified by the user. Production is assumed to grow over time. The default growth rate in the first year for all countries is 3.5 percent, but this value can be modified by the user, by country, with the parameter '''''aquaculgr'' '''. This growth rate declines to 0 over a number of years given by the global parameter '''''aquaculconv'' '''. Finally, users can change the amount of aquaculture production, by country, with the multiplier '''''aquaculm'' '''.
+
<math>AGPMILKANDEGGSppl_{r} = MilkEggstoMeatI_{r} *( LVHERD_{r} * slr)</math>
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq14.png http://www.du.edu/ifs/help/media/images/ag-module/ageq14.png]
+
The dynamics of the [[Livestock|livestock]] herd are described below.
 +
<div></div>
 +
==== Fish Production ====
  
''where''
+
The production of fish has two components, wild catch and aquaculture. Fish caught through aquaculture is treated as a stock in the model and is a function of a growth component.&nbsp; Wild catch on the other hand is treated as a flow in the model.
  
''<span>aquaculgr<sub>r,t</sub> declines from aquaculgr<sub>r,t=1</sub> </span> '' <span>to 0 over '''''aquaculconv'' ''' years</span>
+
===== Pre-processor and first year =====
  
<span>Total fish production (FISH) is given as:</span>
+
Data for fish catch and aquaculture is derived through two main sources, namely the FAO food balance sheets and the FAO Fishstatj software. Data for fish production, imports and exports is initially extracted from the FAO Food Balance Sheets. However, no breakout is available for fish caught as wild catch and fish caught through aquaculture. This bifurcation is available in the dataset from the FAO Fishstatj database. The data from the FAO food balance sheets is broken down into fish catch (AGFISHCATCH) and aquaculture (AQUACUL) using data from the FAO fishstatj dataset.
  
<span>[http://www.du.edu/ifs/help/media/images/ag-module/ageq15.png http://www.du.edu/ifs/help/media/images/ag-module/ageq15.png]</span>
+
In the first year, the values for pre-loss production of wild fish, AGFISHCATCHppl and aquaculture, AQUACULppl, are calculated by adding in a level of catch loss, which is not reflected in the FAO and Fishstatj data. Separate parameters, '''''aglossprodperc'''''<i><sub>f=3</sub> </i>''and '''aglossprodperc'''<sub>f=4</sub>, ''are used for wild catch and aquaculture.
  
== Production Losses ==
+
===== Forecast years =====
  
<span>Some food production will never make it to markets, but will be lost in the field or in distribution systems to pests, spoilage, etc. For crops, an initial estimate of the loss in the first year, LOSSI, is given as a function of GDP per capita using a table function t</span><span>hat captures the tendency of loss to decrease with higher income levels (see figure below). </span>This is reset to 0 in the pre-processor if the estimate of cereal production in the first ye[[File:Production losses.png|border|right|Production losses.png]]ar is zero. If the loss seems too high, specifically if it is greater than or equal to 0.9 - cereal exports/cereal production, then the loss for crops is recomputed as the maximum of 0.05 and 0.9 – cereal exports/cereal production. The estimate of loss in the first year for meat<span>is assumed to be one-half of the initial estimate for crops; no losses are assumed for fish.</span> <span>In future years, for crops and meat, the loss is calculated as the loss in the first year multiplied by the ratio of the loss estimated from the table function above using current GDP per capita to GDP per capita in the first year; therefore, as GDP per capita increases relative to the first year, loss decreases. &nbsp;A common loss multiplier ('''''lossm'' ''') is also available, allowing users to adjust crop and meat losses.&nbsp; Finally, losses are bound between 0 and 0.8. &nbsp;At present, fish loss remains constant at 0 for all years.</span>
+
The amount of aquaculture (AQUACUL) in forecast years can be modified by the user. Production is assumed to grow over time. The default growth rate in the first year for all countries is 3.5 percent, but this value can be modified by the user, by country, with the parameter '''''aquaculgr'''''. This growth rate declines to 0 over a number of years given by the global parameter '''''aquaculconv'''''. Users can change the amount of aquaculture production, by country, with the multiplier '''''aquaculm<ref>In every year of the model, the effect of aquaculm is removed on the aquaculture variable. This is because the multiplier in this case is used on a stock rather than a flow due to which the effect of the multiplier needs to be removed in each time step.</ref>'''''. Finally, this is adjusted for production losses from aquaculture with Aquaculloss
  
<span>[http://www.du.edu/ifs/help/media/images/ag-module/ageq16.png http://www.du.edu/ifs/help/media/images/ag-module/ageq16.png]</span>
+
<math>AQUACUL_{r} = (AQUACULppl_{r,t-1} * (1+ aquaculgr_{r,t} )* aquaculm_{r})- Aquaculloss_{r} </math>
  
== Agricultural Demand ==
+
where
  
IFs computes demand for three agricultural categories—crops, meat, and fish. &nbsp;Total human food demand (for both crops and meat) is responsive to calorie demand, which in turn responds to GDP per capita (as a proxy for income).&nbsp; The division of calorie demand between demand for calories from crops and from meat changes in response also to GDP per capita (increasing in income).&nbsp; The calculation sequence of human food demand in IFs thus begins with determination of calorie demand, determines how much of that is satisfied by the typically increasing share from meat (bounding that share with reasonable upper limits), and how much remains to be satisfied from crops.&nbsp; At this point IFs does not track calories from fish. Once the remaining needed calories from crops are determined, the physical demand for crops in million metric tons can also be determined.&nbsp;
+
''aquaculgr<sub>r,t</sub> declines from '''aquaculgr'''<sub>r,t=1</sub>'' to 0 over '''''aquaculconv''''' years
  
Crop demand also involves demand for industrial use and animal feed.&nbsp; Total crop demand is the sum of those two demands and that for food crops.
+
Wild catch is initialized in the pre-processor as the variable AGFISHCATCH. The pre- production loss of wild catch is computed after applying a multiplier '''''fishcatchm''''' and this is adjusted for losses&nbsp;(Catchloss) to arrive at post production loss wild fish catch.
  
== Initial Agricultural Demands ==
+
<math>AGFISHCATCH_{r} = (AGFISHCATCHppl_{r,t-1} * fishcatchm_{r} )- Catchloss_{r} </math>
  
A common process across categories is used to estimate initial values for the first years. It relies upon the first year values of production, imports, exports, and losses, all of which are generated in the pre-processor and discussed elsewhere in this document, to compute an apparent level of demand or consumption. The reason for this is that demand data are much less available for food and agriculture than are production and trade data. An initial estimate of demand in each category is given as the sum of post-loss production and imports minus exports:
+
Total, post-production loss fish production (AGP) is then given as:
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq17.png http://www.du.edu/ifs/help/media/images/ag-module/ageq17.png]
+
<math>AGP_{r,t=3} = AQUACUL_{r} + AGFISHCATCH_{r} </math>
  
An initial portion of this first estimate of demand is set aside for the purposes of satisfying the need for growth in food stocks as underlying total food demand and supply change (using initial economic growth as a proxy for that annual stock growth). See also the section on stocks.&nbsp; That adjusted demand then becomes the basis, along with production, for an estimate of food stocks.
+
==== Losses and waste ====
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq18.png http://www.du.edu/ifs/help/media/images/ag-module/ageq18.png]
+
Losses can occur at several places along the chain from production. In earlier sections, we mentioned losses at the production stage. Losses can also occur in the process of transmission and distribution from the producer to the final consumer and at the consumer stage. The latter is sometimes referred to as food waste, but for our purposes, we will use the term loss for all three stages: production, transmission and distribution, and consumption.
  
''where''
+
The FAO Food Balance Sheets provide data on losses during transmission and distribution, but not at the production or consumption stages. Until we are able to find data showing a clear relationship between these losses and GDP per capita, or some other explanatory factor, we make an assumption of production losses and consumption losses of 10% for all countries. The user can make changes in these values with the parameters '''aglossprodperc'''and'''aglossconsperc'''respectively. The former can be set for crops, meat, wild catch, and aquaculture separately. The latter combines wild catch and aquaculture as fish, as we do not have separate data on the consumption of wild caught versus farmed fish. More details on the use of these parameters and the actual calculation of production and consumption losses are provided in sections 3.1.1-3.1.3 and 3.2.1, respectively.
  
agdstl is a parameter used to set desired stock levels for agricultural commodities.&nbsp; It is set to be 1.5 times '''''dstl'' ''', which is a global parameter that can be adjusted by the user
+
Turning to transmission and distribution losses, some agricultural commodities will never make it from the producer to the final consumer because of pests, spoilage, etc. &nbsp;The FAO food balance sheets provide data on food lost to waste for crops and meat , but not for fish. Thus, for now we assume that there are no losses in this stage for fish. For crops and meat, though we were able to establish relationships between transmission and distribution losses and GDP per capita. These are shown in the figures below:
  
igdpr is the initial growth rate in GDP
+
----
  
Given the resulting initial model year value for food stocks, it is then possible to calculate a more precise increment of stock change needed and add that back into the demand.
+
===== Pre-processor and first year =====
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq19.png http://www.du.edu/ifs/help/media/images/ag-module/ageq19.png]
+
The initial values for transmission and distribution losses are taken directly from the FAO Food balance sheets. For those countries without data, an assumed loss of 1 ton (0.000001 MMT) is used. These are given by the variable AGLOSSTRANS[[|<sub>r, f=1-3</sub>]]. As with consumption, wild catch and aquaculture are combined into a single category, fish, as we do not have separate data; also, for the moment the value of AGLOSSTRANS<sub>r, f=3</sub> is set to 0 for all countries.
  
== Total Calorie Demand (and the Share from Meat) ==
+
In the first year, a ratio of [[Transmission/distribution_loss_to_food_demand|transmission/distribution loss to food demand]], FDEM, &nbsp;is computed as:
  
In the first year of the model, a predicted level of calories per capita (CalPerCap) is estimated as an incre[[File:Total calorie dd and share from meat.png|border|right|Total calorie dd and share from meat.png]]asing function of average income.<sup>[http://www.du.edu/ifs/help/understand/agriculture/equations/demand/total.html#footnote [1]] </sup>&nbsp; This is bound from above by an assumed maximum value, given by the global parameter '''''calmax'' '''.
+
<math>AgLossTransToFoodRatI_{r,f=1to3} = AGLOSSTRANS_{r,f=1to3} / FDEM_{r,f=1to3} </math>
  
The predicted per capita value is converted to total calorie demand (caldem) by multiplying by the population (POP). A multiplicative shift factor (calactpredrat), used in the forecast years, is then calculated by dividing by the value of calories available (CLAVAL) by this demand.
 
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq20.png http://www.du.edu/ifs/help/media/images/ag-module/ageq20.png]
 
  
''where''
+
===== Forecast years =====
  
CLAVAL is calorie availability; its calculation is described below in the section on calorie availability
+
In future years, for crops and meat, the initial estimate for transmission and distribution losses are calculated as follows:
  
This value of calactpredrat gradually converges to 1 over a period given by the global parameter '''''agconv'' ''' and appears in future equations with the name adjustforinitialdevc.
+
·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Predictions are made for the ratio of transmission/distribution loss to food demand as a function of GDP per capita (predaglosstrans) for the first year and the current year.
  
In the forecast years, a predicted value of per capita calorie demand (CalPerCap) is once again calculated as a function of average income using the equation above, with a maximum value given by '''''calmax'' '''. A base level of calories per capita (calbase) is also calculated, which is given as the minimum of 3000 or '''''calmax'' ''' minus 300. Because comparative cross sections show a growth of around 4 calories per capita per year independent of average income, a factor representing this increase (caldgr) is calculated as:
+
·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; The ratio of the predicted values for the current year to the predicted value for the first year is multiplied by AgLossTransToFoodRatI.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq21.png http://www.du.edu/ifs/help/media/images/ag-module/ageq21.png]
+
·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; That result is multiplied by FDEM for the current year to get losses in MMT.
  
Thus, depending on the exact values of '''''calmax'' ''', calbase, and CalPerCap, caldgr grows each year by a value that centers around 4 calories. This value is then added to the predicted value in calculating the total demand for calories. The equation also takes into account '''''calmax'' ''' and the multiplicative shift factor on calories per capita noted above.
+
·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; That result is multipled by the parameter '''aglosstransm''', to get a final value.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq22.png http://www.du.edu/ifs/help/media/images/ag-module/ageq22.png]
+
&nbsp;
  
This total calorie demand is divided into demand from meat and demand from crops. Meat demand in tons (AGDEM, category 2) is discussed in the following section. Here we focus on how this is converted to calories. Two country-specific parameters, lvcfr and sclavf, calculated in the first year of the model are key to this conversion.
+
This can be expressed as:
  
lvcfr is a country-specific factor converting livestock in tons to calories. This is initially set equal to the global parameter '''''lvcf'' ''', but may be adjusted downward. This is done in cases where the initial estimate of the share of calories from meat exceeds a maximum value: given by t, i.e., if
+
<math>AGLOSSTRANS_{r,f=1,2,3} = FDEM_{r,f=1,2,3,t=1} * predaglosstrans_{r,f=1,2,3,t}/predaglosstrans_{r,f=1,2,3,t=1}*AgLossTransToFoodRatioI_{r,f=1,2,3}*aglosstransm_{r,f=1,2,3}</math>
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq23.png http://www.du.edu/ifs/help/media/images/ag-module/ageq23.png]
+
Some further adjustments may be made to AGLOSSTRANS in the process of balancing global trade and balancing domestic supply and demand. These are discussed later in this documentation.
  
''where''
+
== Agricultural Demand ==
  
'''''calmeatm'' ''' is a global parameter indicating the maximum share of calories to come from meat
+
IFs computes demand, or uses, for three agricultural categories—crops, meat, and fish. &nbsp;These commodities are used for direct human consumption (FDEM), animal feed (FEDEM), industrial uses, e.g. biofuels (INDEM), and food processing and manufacturing (FMDEM). IFs also tracks the losses in transmission and distribution (AGLOSSTRANS). Total demand (AGDEM) is the sum of these five use categories and is given in MMT per year.
  
In this case, lvcfr is repeated reduced by 10 percent until the share of total calories coming from meat falls below '''''calmeatm'' '''.
+
The sections above&nbsp;describe&nbsp;the calculation of AGLOSSTRANS, so that is not repeated here. The calculation of the demand for direct human consumption, FDEM begins with estimates of daily per capita calorie demand for crops, meat, and fish. Briefly, IFs first estimates total per capita calorie demand, which responds to GDP per capita (as a proxy for income).&nbsp;The division of total demand between demand for calories from crops and from meat and fish also changes in response to GDP per capita (more meat and fish demand with increasing income).&nbsp;Finally, the division of calories from meat and fish is calculated based on historic patterns. Using country and commodity specific factors, the daily per capita calorie demands are converted to grams per capita per day and protein per capita per day. The grams per capita per day are then multiplied by the size of the population, POP, and the number of days in a year, 365, to arrive at FDEM.
  
sclavf is a country-specific multiplicative shift factor that converts the total annual demand for food crops and crop equivalents from meat to daily calorie availability
+
The other demands, FEDEM, INDEM, and FMDEM are driven by factors such as the size of the livestock herd, LVHERD, and the use of crops for fuel production. In cases where information is lacking, these demands are determined in relation to FDEM. Finally, there may be some modifications to all of the demand categories due to shortages or other factors, as described in the rest of this section.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq24.png http://www.du.edu/ifs/help/media/images/ag-module/ageq24.png]
+
==== Daily per capita demands – calories, grams, and protein ====
  
Note that sclavf can take on a value greater that or less than 1.
+
IFs tracks one set of variables for agricultural demands, or uses, on a daily per capita basis. These are. specifically, calories (CLPC), protein (PROTEINPC), and grams (GRAMSPC), for each category – crops, meat, and fish.
  
lvcfr and sclavf maintain the same value in all the forecast years.
+
===== Pre-processor and first year =====
  
----
+
Daily calories per capita (CLPC), by category, are initialized in the IFs pre-processor using data from the FAO food balance sheets. Data on daily protein per capita and grams per capita are also read into the pre-processor.<ref>Note that although daily grams per capita are read in and used in the pre-processor, these are recalculated in the first year of the model</ref>&nbsp;If data are available for crops, meat, and fish, total values for calories, protein, and grams are calculated as sums of the three categories. For countries where no data are available for one or more of the categories, the model follows a set of procedures to fill in the missing data. These procedures uses, among other things, 1) equations that relate total calories per capita per day and the share of these calories from crops versus meat and fish to GDP per capita and 2) other ratios derived from global averages of those countries with data. Later in the pre-processor, CLAVAL, which represent the total calories (across all categories) per day for the population as a whole is also calculated.
<div>
+
[file:///C:/Users/Ara/Desktop/Agricultural%20Documentation%20v19_AG.docx#_ftnref1 [1]] Equation is CalPerCap = 2180.6+368.87*ln(GDPPCP).
+
</div>
+
== Meat Demand and Its Calorie Contribution ==
+
  
In the first model year apparent meat demand is used to compute the calories that its consumption contributes to the need of the population.&nbsp; In subsequent years the calculations begin with meat demand again, and conclude with calculation of the calories provided by it.&nbsp; This is needed subsequently to determine the calories required from crops.
+
The equation for total calories as a function of GDP per capita is stored as "GDP/Capita (PPP 2011) Versus Calorie Demand (fixed-effect)" and is illustrated below.<ref>Equation is CalPerCap = 2468.972+155.778*ln(GDPPCP). Because this equation was estimated using a fixed-effects model, the intercept does not have the same meaning as in a regular regression. Rather, it is the average of the fixed-effect across countries with data. This is not a problem for countries with data, as the shift factor in the first year will account for this. For countries without data, however, this can give a misleading estimate of initial daily calories per capita.</ref>
  
In the first year of the model's forecasts an apparent consumption of meat is calculated as for other agricultural demand components (in terms of production plus imports and subtracting exports).&nbsp; In the first year, two other country-specific values are calculated that are used to estimate this value in the forecast years—meatmaxr and meatactpredrat.
+
[[File:Calorie Demand vs GDP per capita.png|frame|center|200x250px|Calorie demand vs GDP per capita at PPP (fixed effect)]]
  
meatmaxr is a country-specific maximum for per capita meat demand in tons. It is calculated as the maximum of a global parameter ('''''meatmax'' ''') and per capita total meat demand (AGDEM, category 2 divided by POP).
+
The equation for the share of calories from meat and fish as a function of GDP per capita is stored as " GDP/Capita (PPP 2011) Versus CLPC from MeatandFish (2010) Log"
  
meatactpredrat, which acts as a shift factor, is the ratio of actual total meat demand (in tons) to a predicted value (MeatDem). First, a[[File:Meat demand.png|right|Meat demand.png]] predicted per capita value is estimated as an increasing function of GDP per capita<sup>[http://www.du.edu/ifs/help/understand/agriculture/equations/demand/meat.html#footnote [1]] </sup>:
+
Both of these are in a logarithmic form, indicating that both total calories and the share of calories from meat and fish increase with GDP per capita, but at a decreasing rate. As the data do not show a clear pattern for the breakdown between meat and fish, which is largely due to cultural patterns and geography, the model uses historical values rather than an estimated equation, as discussed below. In the pre-processor, an average global value is used for countries without data.
  
This is not allowed to exceed meatmaxr and is then multiplied by the population to yield the predicted value of total MeatDem. meatactpredrat is then calculated as
+
In the first year of the model, one of the first things that occurs is a recalculation of GRAMSPC as GRAMSPC = FDEM/(POP * 365) * 100000. This is to ensure the consistency between the daily per capita variable, GRAMSPC, and the annual national value, FDEM. This is necessary because FDEM may have been modified in the pre-processor as part of ensuring a balance between the initial year supply of agricultural produces and their use. This is described in more detail in Box 1.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq25.png http://www.du.edu/ifs/help/media/images/ag-module/ageq25.png]
+
In addition, a number of additional values related to calories to be used in the forecast period are calculated.
  
meatmaxr is held constant in all forecast years. For most countries, the value of meatactpredrat gradually converges to 1 over a period given by the global parameter '''''agconv'' '''. The exception is for certain countries in South Asia, specifically India, Nepal, and Mauritius, for which it does not converge. In either case, it is represented in equations in future year as adjustforinitialdevm.
+
#CalActPredRat: the ratio between actual calories available and the predicted value.<ref>In the model this is currently calculated as CLAVAL/caldem, where caldem = the predicted value of total CLPC (after accounting for calmax) times the total population. It could just as easily be calculated as the predicted value of total CLPC (after accounting for calmax) divided by the actual value of total CLPC from the pre-processor.</ref>&nbsp;It is used as a multiplicative shift factor. The predicted level of is estimated using the equation for total calories per capita as a function of GDP per capita described above. This is bound from above by an assumed maximum value, given by the global parameter '''''calmax'''''. The value of calactpredrat gradually converges to 1 over a period given by the global parameter&nbsp;'''''agconv&nbsp;'''''and appears in future equations with the name AdjustForInitialDevc.
 +
#MeatAndFishActPredRat: the ratio between actual share of calories from meat and fish to the predicted value. It is used as a multiplicative shift factor. The predicted level of is estimated using the equation for share of calories from meat and fish per capita as a function of GDP per capita described above.
 +
#MeatToMeatFishRatI: the ratio between calories from meat and calories from meat and fish. It is used to separate the future estimates of calories from meat and fish into separate values for meat and fish.
 +
#ProtToCalRatI: the ratio of daily per capita protein to daily per capita calories, by category. It is used to convert future estimates of calorie availability to protein availability. If for some reason the initial estimate of ProtToCalRatI is 0 for any category, the median value for that category based on 2010 is used.
 +
#GramsToCalRatI: the ratio of daily per capita grams to daily per capita calories, by category. It is used to convert future estimates of calorie availability to a value in grams, which is then used to estimate aggregate demand for food for direct human consumption. If for some reason the initial estimate of GramsToCalRatI is 0 for any category, the median value for that category based on 2010 is used.
  
In the forecast years, IFs then computes the demand for meat in tons as a function of population, average income, world food prices, the shift factor, and a multiplier that allows users to directly increase or decrease demand. As in the first year, per capita demand (tonspercap) is initially estimated as a function of average income, using the same function presented above. This is then converted to total demand in the following equation.
+
===== Forecast years =====
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq26.png http://www.du.edu/ifs/help/media/images/ag-module/ageq26.png]
+
In the forecast years, daily per capita calorie demand begins with a prediction of a total demand, CalPerCap, as a function of average income using the equation above, with a maximum value given by '''''calmax'''''. Two other values are also calculated at this point. First, a base level of calories per capita, CalBase, is also calculated, which is given as the minimum of 3000 or '''''calmax''&nbsp;'''minus 300. Second, because comparative cross sections show a growth of around 7.6 calories per capita per year independent of average income, a factor representing this increase (CaldGr) is calculated as:
  
''where''
+
<math>CaldGr_{r,t} = CaldGr_{r,t-1} +7.638*((calmax-MAX(CalBase,MIN(calmax, CalPerCap_{r} )))/(calmax-CalBase)</math>
  
'''''elasmd'' ''' is a global parameter representing the elasticity of meat demand to changes in the world price relative the first year
+
Thus, depending on the exact values of '''''calmax''''', CalBase, and CalPerCap, CaldGr grows each year by a value that centers around 7.6 calories. This value is then added to the predicted value in calculating the total demand for calories.
  
A number of further adjustments are made to the meat demand, in the following order:
+
The equation also takes into account '''''calmax''&nbsp;'''and the multiplicative shift factor on calories per capita calculated in the first year of the model. The latter is named AdjustForinitialDevc, which, as noted previously, is calculate as the value of calactpredrat gradually converging to 1 over a period given by the global parameter '''agconv'''
  
#The estimated value is restricted to be no greater than that given by multiplying the size of the population (POP) by the maximum for per capita meat demand in tons (meatmaxr)
+
<math>TotalCalPerCap_{r} = MIN('''''calmax''''',(CalPerCap_{r} + CaldGr_{r})* AdjustForInitialdevc_{r})* POP_r</math>
#This adjusted value is multiplied by a demand multiplier ('''''agdemm<sub>r,f=2</sub> '' '''), which can raise or lower demand.
+
#If the initial estimate of calories from meat (calfrommeat) exceeds the maximum amount of calories allowed to come from meat, given by '''''calmeatm'' ''' * caldem, then the demand for meat in tons is recalculated as:
+
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq27.png http://www.du.edu/ifs/help/media/images/ag-module/ageq27.png]
+
Finally, a value for the total calories per day, CalDem, is calculated by multiplying TotalCalPerCap times POP.
  
Note that this implies a reduction in the total demand for meat in tons.
+
The next step is to divide the total calories between crops and meat plus fish. First, a predicted value of the share of total calories going to meat and fish, MeatAndFishPctPred, is calculated as a function of GDP per capita, using the equation described earlier. Second, the ratio of between actual share of calories from meat and fish to the predicted value, MeatAndFishActPredRat, calculated in the first year is potentially modified. Specifically, a new variable, AdjustForInitialDevm, is assigned either the intial value of MeatAndFishActPredRat, or a value that reflects convergence of MeatAndFishActPredRat to a value of 1 over a period given by the global parameter '''agconv'''. The countries for which convergence does not occur are the South Asian countries – India, Nepal and Mauritius –&nbsp; which are traditionally low meat consuming countries. The actual share of calories from meat and fish is then calculated as:
  
In order to undertake the third adjustment, and to prepare for the calculation of calories needed from crops, the meat demand needs to be converted from tons to calories.&nbsp; An initial estimate of calories from meat (calfrommeat) is calculated from the total demand for meat in tons, adjusted by lvcfr and sclavf:
+
<math>MeatAndFishPctAct_{r} = MeatAndFishPctPred_{r} * AdjustForInitialDevm_r</math>
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq28.png http://www.du.edu/ifs/help/media/images/ag-module/ageq28.png]
+
A minimum value of 3.5 percent is also imposed.
  
Should this exceed the maximum amount of calories allowed to come from meat, given by '''''calmeatm'' ''' * caldem, then two adjustments are made. First, calfrommeat is set equal to this maximum amount
+
With this value for MeatAndFishPctAct, the model can divide the total calories between crops and the combination of meat and fish. Using the value for MeatToMeatFishRatioI, calculated in the first year, the model can then estimate the calories from meat and fish separately. The values are stored in the variable CLPC(<sub>r,f)</sub>
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq29.png http://www.du.edu/ifs/help/media/images/ag-module/ageq29.png]
+
At this point, these values are adjusted for changes in world food prices and elasticities to demand for these prices.
  
and the total demand for meat in tons is recalculated
+
<math>CLPC_{r,f=1-3} = CLPC_{r,f=1-3} *(WAP_{f=1-3}/WAP_{f=1-3,t=1} )^{X}</math>
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq30.png http://www.du.edu/ifs/help/media/images/ag-module/ageq30.png]
+
'''where,'''
  
Note that this implies a reduction in the total demand for meat in tons.
+
WAP<sub>f=1-3</sub> are the global food prices for crops, meat, and fish
  
Now that the demands for total calories and calories from meat are known, calories to be demanded from crops (mostly grain) can be calculated simply as&nbsp;
+
X is the price elasticity of demand and takes on the value of '''''elascd''''', '''''elasm''''', and '''''elasfd''&nbsp;'''for crops, meat, and fish, respectively
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq31.png http://www.du.edu/ifs/help/media/images/ag-module/ageq31.png]
+
Given these adjustments, TotalCalPerCap is recalculated as the sum of CLPC for crops, meat, and fish.
<div><br/>
+
----
+
<div>
+
[file:///C:/Users/Ara/Desktop/Agricultural%20Documentation%20v19_AG.docx#_ftnref1 [1]] Equation is Meat Demand per Capita = .0109999999403954GDPPCP<sup>0.684800028800964</sup>.
+
  
== Fish Demand ==
+
Finally, a parameter '''''clpcm''&nbsp;'''is applied to the final value of calories per capita that allows the user to manipulate demand for calories in addition to two parameters (that allow the user to eliminate hunger in a particular country over time) which are described below.
  
Currently IFs does not calculate calories from fish and determine that contribution to total calorie demand.&nbsp; We anticipate that model extension in the future.
+
&nbsp;The parameters '''''malnelimstartyr&nbsp;'''''and '''''malnelimtargetyr&nbsp;'''''allow the user to reduce hunger in any country over a specific period of time. The activation of these parameters by the user, calculates the required cumulative growth rate in calories to eliminate hunger (reduce the undernourished population to 5 percent of the total population) ClPCcum. This cumulative growth rate is calculated using a logarithmic function that computes the growth rate relative to the household income and unskilled labor in a country.<ref>The function used is as follows, Exp((Log(5) - 46.95226 + 0.18422 * Log(HHINC / labsups)) / -5.643)</ref>&nbsp; Also, the user can activate a switch '''''malelimprecisesw''''', which calculates the specific number of calories required to eliminate hunger for the most undernourished part of the population. An individual who consumes less than 1000 calories per day but is still alive is assumed to be the most undernourished person in the population.
  
The calculation of fish demand (AGDEM, category 3) in the first year was described at the start of the Demand section as having the same apparent consumption approach as used for other agricultural demands (production plus imports minus exports and adjustment stocks). In the first year, a calculation is also made of fish demand per capita (fishdemipc), which is simply the ratio of AGDEM, category 3 to population (POP).
+
Therefore the final equation is as follows,
  
In the forecast year, fish demand per capita is assumed to grow with growth in average income, with some adjustments. First, predicted values for fish demand per capita are calculated as a function of income in the first and current year using the function depicted in the diagram below<sup>[http://www.du.edu/ifs/help/understand/agriculture/equations/demand/fish.html#footnote [1]] </sup>.
+
<math>CLPC_{r,f} = (CLPC_{r,f} *clpcm_{r,f} * ClPCcum_{r} )+ Caldef_{r,f} </math>
  
[[File:Fish demand.png|right|Fish demand.png]]
+
where,
  
The initial estimate of fish demand per capita is the value for the initial year (fishdemipc) multiplied by the ratio of the predicted value in the current year (tonspercap) to the predicted value in the first year (tonspercapi)
+
'''''clpcm&nbsp;'''''is a multiplier that can be used to affect the demand for calories
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq32.png http://www.du.edu/ifs/help/media/images/ag-module/ageq32.png]
+
ClPCcum is the cumulative growth rate required in calories per capita to eliminate hunger over a specific time period determined by malnelimstartyr and malnelimtargetyr
  
Once the per capita demand exceeds 50 percent of the initial value, a new logic kicks in.
+
Caldef is the cumulative number of calories required to eliminate hunger for the most undernourished part of the population. This is calculated through the activation of '''''malelimprecisesw'''''.
  
fishdempc is also not allowed to exceed the value in the first year or 0.1, whichever is larger.
+
At this point, i.e., after dealing with the hunger targets, the values for daily grams per capita (GRAMSPC) and daily protein per capita (PROTEINPC) are calculated by multiplying the values for CLPC by GramsToCalRatI and ProtToCalRatI, respectively. Recall that these values were computed in the first year.
  
Finally, total demand for fish is determined by multiplying the per capita value by the population (POP), with a price adjustment.
+
A final adjustment to CLPC, PROTEINPC, and GRAMSPC can occur as a result of shortages. This begins with a reduction in FDEM, as described in the&nbsp; Stocks section below, which is then translated into new values for GRAMSPC, which are then used to recalculate CLPC and PROTEINPC.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq33.png http://www.du.edu/ifs/help/media/images/ag-module/ageq33.png]
+
One final variable, CLAVAL, which represent the total calories (across all categories) per day for the population as a whole is then calculated as total calories per capita times the population.
<div><div><br/>
+
----
+
<div>
+
[file:///C:/Users/Ara/Desktop/Agricultural%20Documentation%20v19_AG.docx#_ftnref1 [1]] Equation is Fish Demand per Capita = 0.0121 + 0.00102*GDPPCP
+
  
== Crop Demand for Food (FDEM) and Its Calorie Contribution ==
+
==== Agricultural demand for direct human consumption (FDEM'')'' ====
  
Total crop demand (AGDEM, category 1) has three components: feed (FEDDEM), industrial (INDEM) and food (FDEM). Here we describe the basic calculations for food use of crops. Note that in forecast years additional adjustments are made to a number of the demand variables, so the discussion here will not fully complete the determination of FDEM.
+
FDEM represents the amount of agricultural commodities going directly to consumers, presumably for consumption.
  
The demand for crops for food in the base year is not computed in the pre-processor.&nbsp; Rather, in the first year of the model, the demand for crops for food (FDEM) is calculated as the residual of total agricultural demand for crops minus the demand for crops for feed and for industry.<sup>[http://www.du.edu/ifs/help/understand/agriculture/equations/demand/crop.html#footnote [1]]</sup>
+
===== Pre-processor and first year =====
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq34.png http://www.du.edu/ifs/help/media/images/ag-module/ageq34.png]
+
The pre-processor reads in data from the FAO Food Balance Sheets and initializes values for the amount of agricultural commodities used for direct human consumption, FDEM. If these data are missing for any commodity, a value is calculated by multiplying the daily grams per capita by the size of the population (POP) and the numbers of days in a year (365), and then divided by 100000 to get the units correct. As noted in Box 1, certain adjustments may be made to ensure consistencies between supply and demand in individual countries, as well as between imports and exports across countries.
  
Given earlier calculations of the total demand for calories and of the share of that demand to be met by meat, it was possible to calculate the calories needed from crops, mostly grain around the world (calfromgrain). From this it is possible to calculate food demand using the factor relating the conversion from crops to calories (sclavf), an adjustment based on world crop prices, and a multiplier that can be used to increase or decrease demand.
+
No adjustments are made to FDEM in the first year.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq35.png http://www.du.edu/ifs/help/media/images/ag-module/ageq35.png]
+
===== Forecast years =====
  
FDEM is bound from above based on the assumed maximum calories per capita ('''''calmax'' '''), and the multiplicative shift factor on calories per capita (adjustforinitialdevc).
+
In the forecast years, FDEM is initially calculated based upon the calculation of daily grams per capita described in this section below:
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq36.png http://www.du.edu/ifs/help/media/images/ag-module/ageq36.png]
+
<math>FDEM_{r,f=1-3} = GRAMSPC_{r,f=1-3} * POP_{r}* 365⁄100000 </math>
<div><br/>
+
----
+
<div>
+
[file:///C:/Users/Ara/Desktop/Agricultural%20Documentation%20v19_AG.docx#_ftnref1 [1]] It is bound to be between 0.1 and 1000.
+
  
== Feed Demand for Crops ==
+
There are two situations where the value of FDEM might be adjusted. The first case is where more than 85 percent of consumers’ expenditures are on food stuffs. If this is the case, the values of FDEM for crops and meat and fish are reduced proportionately, as described in this section below.
  
Feed demand represents the amount of crops that need to be produced to complement what livestock receive from grazing.
+
The second case is when a country faces absolute shortages, i.e., the total domestic supply, AGDEM, is not adequate to meet all of the demands, FDEM + FEDEM + INDEM + AGLOSSTRANS even after drawing down stocks to 0. Here, each of these demands/uses are reduced proportionately to restore the balance as described in Section 3.4: Stocks. In both cases, the decreases in FDEM are fed forward to reduce the actual calories available, as described here.
  
In the pre-processor, feed demand (FeedDem) is initially estimated as a percentage of the apparent consumption of cereals, which grows with average income, implying that as countries develop, more of their grain production i[[File:Feed demand for crops.png|right|Feed demand for crops.png]]s used to feed livestock. The function&nbsp;is depicted on the right<sup>[http://www.du.edu/ifs/help/understand/agriculture/equations/demand/feed.html#footnote [1]] </sup>:
+
=== Feed demand for crops, meat and fish ===
  
If the model estimates that the productivity of grazing land in terms of feed equivalent produced per unit area is below a minimum level, however, then FeedDem is adjusted downward. It determines this by first estimating the feed requirements per unit livestock (fedreq). This is estimated as an increasing function of average income as shown in the figure below.
+
Feed demand, FEDDEM, represents: 1) the amount of crops that are used to complement what livestock receive from grazing, and 2) an unspecified use of meat and fish, which appears in the FAO Food Balance Sheets.
  
[[File:Feed demand for crops 2.png|center|Feed demand for crops 2.png]]
+
===== Pre-processor and first year =====
  
This function takes into account the fact that at low levels of income most meat consumption is typically poultry (with a conversion ratio of grain to meat of about 2-to-1), while at higher levels of income, pork (4-to-1) and then beef (7-to-1) become increasing portions of meat demand (Brown, 1995: 45-47).
+
The pre-processor reads in data from the FAO Food Balance Sheets and initializes values for the amount of agricultural commodities used as feed for other agricultural production, usually meat. If data are missing, a minimum value of 1 ton, or .000001 MMT is used.
  
With the value of fedreq, the productivity of grazing land can be estimated as the difference between the total feed requirement for the number of livestock minus the feed demand divided by the amount of grazing land.
+
An initial adjustment to feed demand for crops can occur in the pre-processor. This occurs when the production from grazing land is not being fully utilized. Specifically, this is when the amount of equivalent feed from grazing land, i.e. grazing land productivity, here named GLandCAP, implies a lower than assumed minimum value of 0.01 tons of crop equivalents per hectare, here named MinLDProd. The implied value of GLandCap is calculated as the difference between the total feed requirement for the number of livestock minus the feed demand divided by the amount of grazing land.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq37.png http://www.du.edu/ifs/help/media/images/ag-module/ageq37.png]
+
<math>GLandCAP_{r} = LiveHerd_r* fedreq_r-FEDDEM_{r,f=1}/ LDGraz_{r} </math>
  
''where''
+
'''where,'''
  
LiveHerd is the size of the livestock herd
+
LiveHerd is the size of the livestock herd (discussed in this section&nbsp;)
  
LDGraz is the amount of grazing land
+
LDGraz is the amount of grazing land (discussed in this section under Land Dynamics)
  
If the value of GLandCAP is less than a minimum (MinLDProd—currently hard coded as 0.01 tons of meat per hectare, based on values for the Saudi desert), then FeedDem is recalculated as the difference between the total feed requirement for the number of livestock minus the amount of feed equivalent produced by grazing using the minimum productivity.
+
FEDDEM<sub>r,f=1</sub> is the value for demand for crops for feed
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq38.png http://www.du.edu/ifs/help/media/images/ag-module/ageq38.png]
+
''Fedreq is an estimate of the per animal feed requirements, which is a function of GDP per capita. The function is depicted in the figure below<ref>The specific equation is stored as “GDP/Capita (PPP) Versus Feed Requirements” and is defined by the two points (GDP/capita, fedreq) = (0, 2.5) and (30, 3.5).</ref>:''
  
Note that this occurs when the feed from crops meets most, if not all, of the total feed requirements, implying little or no need for feed equivalents from grazing land.
+
[[File:Feed demand for crops 2.png|frame|center|Feed demand as a function of GDP per capita at PPP]]<br/>If the value of GLandCAP is less than the minimum, MinLDProd—currently hard coded as 0.01 tons of crop equivalents per hectare, based on values for the Saudi desert), then CFEDDEM<sub>r,f=1</sub> is recalculated as the difference between the total feed requirement for the number of livestock minus the amount of feed equivalent produced by grazing using the minimum productivity.
  
In the first year of the model, grazing land productivity (now called GLDCAP) and an adjustment to feed requirements per unit livestock (fedreqm) are calculated for each country. GLDCAP is initially back-calculated based on the known values of the size of the livestock herd (now called LVHERD), the feed requirement per unit livestock (fedreq —calculated as a function of GDPPC as shown above), the feed demand (now called FEDDEM), and the amount of grazing land (now called LD<sub>l=2</sub>):
+
<math>CFEDDEM_{r,f=1} = LiveHerd_{r} * fedreq_{r} - MinLDProd* LDGraz_{r}</math>
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq39.png http://www.du.edu/ifs/help/media/images/ag-module/ageq39.png]
+
Note that this occurs when the feed from crops meets most, if not all, of the total feed requirements, implying little or no need for feed equivalents from grazing land. Also a minimum value of 0.01 MMT is set for CFEDDEM.
  
This yields a productivity of grazing land that perfectly meets the difference between the total feed requirement and that provided by crops.
+
Finally, as noted in Box 1, certain adjustments may be made in the pre-processor to ensure consistencies between supply and demand in individual countries, as well as between imports and exports across countries.
  
Again, if the calculated value of GLDCAP is less than the assumed minimum level (MinLDProd), however, then adjustments are made. First, an adjustment factor (fedreqm) is calculated by assuming that a minimum amount of feed equivalents from grazing land are produced even if this results in a total amount of feed that is larger than necessary to meet the total feed requirement:
+
In the first year, the model once again checks to make sure that the grazing land productivity exceeds a minimum value and this time stores this value for future use. A parallel equation to that in the pre-processor is used to get an initial estimate for grazing land productivity, now named GldCap:
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq40.png http://www.du.edu/ifs/help/media/images/ag-module/ageq40.png]
+
<math>GLdCAP_{r} = (LVHERD_{r,t=1} * Fedreq_{r,t=1} -FEDDEM_{r,t=1})/LD_{r,l=2,t=1}</math>
  
Note that this value is always greater than or equal to 1 given the condition for making the adjustment. When no adjustment is made, fedreqm is set to 1.
+
'''where,'''
  
After the calculation of this adjustment factor, GLDCAP is recalculated as&nbsp;
+
LVHERD<sub>r,t=1</sub> replaces LiveHerd from the equation in the pre-processor
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq41.png http://www.du.edu/ifs/help/media/images/ag-module/ageq41.png]
+
LD<sub>r,l=2,t=1</sub> replaces LDGraz from the equation in the pre-processor
  
which basically implies that GLDCAP will always at least as large as MinLDProd after the adjustment.
+
FEDDEM<sub>r,f=1</sub> replaces CFEDDEM<sub>r,f=1</sub> from the equation in the pre-processor
  
The values of GLDCAP and fedreqm calculated in the first year are held constant for all forecast years
+
Fedreq<sub>r</sub> is the same as in the equation in the pre-processor
  
In the forecast years, FEDDEM is calculated as a function of the size of the livestock herd (LVHERD), the feed requirements per unit livestock (fedreq), the amount of grazing land (LD<sub>l=2</sub>), and the productivity of grazing land (GLDCAP), but adjustments are also made reflecting the effect of global crop prices on grazing intensity (WAP<sub>f=1</sub>), changes in the efficiency with which feed is converted into. meat, and the adjustment factor fedreqm calculated in the first year. There is also a parameter with which the user can cause a brute force increase or decrease in FEDDEM ('''''agdemm<sub>f=1</sub> '' ''').
+
Now, if the model estimates that GldCAP is below the minimum level, still called MinLDProd and hard coded to a value of 0.01, a new value of GldCAP&nbsp; calculated:
  
<span>The model first calculates the amount of crop equivalent produced from grazing land using the following equation:</span>
+
<math>GLdCAP_{r} = LVHERD_{r,t=1} * Fedreq_{r,t=1} -FEDDEM_{r,t=1}/LD_{r,l=2,t=1} </math>
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq42.png http://www.du.edu/ifs/help/media/images/ag-module/ageq42.png]
+
'''where,'''
  
''where''
+
LVHERD<sub>r,t=1</sub>, LD<sub>r,l=2,t=1</sub>, FEDDEM<sub>r,f=1</sub>, and fedreq<sub>r</sub> are defined as above
  
'''''elglinpr'' '''&nbsp;is a global parameter for the elasticity of livestock grazing intensity to annual changes in world crop prices; the basic assumption is that increasing prices should lead to increased grazing intensity and therefore greater productivity of grazing land<sup>[http://www.du.edu/ifs/help/understand/agriculture/equations/demand/feed.html#footnote [2]] </sup>.
+
'''''fedreqm'''<sub>r</sub> is a multiplier required to ensure that the grazing land productivity meets the difference between the total feed requirement and that provided by crops in the initial year. It is calculated as:''
<div>
+
This production of crop equivalents from grazing land is then subtracted from total feed requirement in the following equation:
+
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq43.png http://www.du.edu/ifs/help/media/images/ag-module/ageq43.png]
+
<math>fedreqm_{r} = LD_{r,l=2,t=1} * MinLDProd + FEDDEM_{r,t=1} /(LVHERD_{r,t=1} * fedreq_{r,t=1} )</math>
  
''where''
+
Note that this value is always greater than or equal to 1 given the condition for making the adjustment. When no adjustment is made, fedreqm is set to 1. These values of GldCAP and fedreqm, calculated in the first year, are held constant for all forecast years
  
'''''livhdpro'' ''' is a global parameter related to the rate at which the productivity of crops in producing meat improves over time. This part of the equation implies that the amount of feed needed to produce a unit of meat declines over time to a minimum of half the original amount required
+
Finally, one other value is calculated in the first year – FeedToFoodRatI, which is the ratio between FEDDEM and FDEM. This is calculated for crops, meat, and fish, but is only used for the latter two categories in the forecast years, as described below.
  
'''''agdemm'' '''(category 1) is a country-specific multiplier that can be used to increase or decrease crop demand
+
==== Forecast years ====
</div><div><br/>
+
----
+
<div>
+
[file:///C:/Users/Ara/Desktop/Agricultural%20Documentation%20v19_AG.docx#_ftnref1 [1]] The specific equation is 13.427 +14.421*ln(GDPPCP), up to GDPPCP=35. The code sets minimum and maximum values of 1 and 80 percent, respectively.
+
  
[file:///C:/Users/Ara/Desktop/Agricultural%20Documentation%20v19_AG.docx#_ftnref1 [2]]&nbsp;The code, as written, ignores price effects that would reduce GLFeedEq. Since&nbsp;'''''elglinpr'' '''&nbsp;is generally positive, this implies that decreases in world crop prices are ignored.
+
In the forecast years, FEDDEM is calculated as a function of the size of the livestock herd (LVHERD), the feed requirements per unit livestock (fedreq), the amount of grazing land (LD<sub>l=2</sub>), and the productivity of grazing land (GldCAP), but adjustments are also made reflecting the effect of global crop prices on grazing intensity (WAP<sub>f=1</sub>), changes in the efficiency with which feed is converted into. meat, and the adjustment factor fedreqm calculated in the first year. There is also a parameter with which the user can cause a brute force increase or decrease in FEDDEM ('''feddemm''')
  
== Industrial Demand for Crops ==
+
The model first calculates the amount of crop equivalent produced from grazing land using the following equation:
  
Industrial demand for crops (IndDem) is initially estimated for the first year in the pre-processor. It is determined, arbitrarily, as one tenth of crop supply, which equals post loss crop production plus imports minus exports.
+
<math>GLFeedEq_{r} =(LD_{r,l=2} * GLdCAP_{r} )*( WAP_{f=1} / WAP_{f=1,t-1} )^{elglinpr} </math>
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq44.png http://www.du.edu/ifs/help/media/images/ag-module/ageq44.png]
+
'''where'''''<b>,</b>''
  
It can then be decreased (increased) if the initial estimates of crop demand for food are considered too low (high).
+
''LD<sub>r,l=2</sub> is the amount of grazing land; the dynamics of this variable is discussed in section 3.10: Land Dynamics''
  
In the first year, two values related to industrial demand for crops (now called INDEM) are calculated. The first of these is a multiplicative shift factor (INDEMK), which is calculated as the ratio of relates actual to predicted industrial demand for crops.&nbsp; The predicted value is given by a function that relates per capita industrial demand to GDP per capita, which is shown below.<sup>[http://www.du.edu/ifs/help/understand/agriculture/equations/demand/industrial.html#footnote [1]] </sup> This multiplicative shift factor remains constant over time.[[File:Industrial demand for crops.png|right|Industrial demand for crops.png]]
+
''GldCAP<sub>r</sub> is the country value for grazing land capacity initialized in the first year''
  
The same function is used to calculate an expected demand for the next year (eindem).&nbsp; The predicted value from the function is computed using the expected level of GDP per capita (egdppcp); this value is multiplied by the expected population (epop) and the multiplicative shift factor (INDEMK) to calculate the expected demand. This expected demand is used in conjunction with the expected demands for crops for feed and crops for food to determine the initial target growth rate in yield (tgryli) discussed in the section on crop production above.
+
''WAP<sub>t,f=1</sub> is global price for crops; and''
  
In the forecast years, the initial value of industrial demand for crops is also estimated using the table function above to get a predicted value for industrial demand per capita, which is then multiplied by population (POP) and the multiplicative shift factor (INDEMK). At this point, a region-specific multiplier ('''''agdemm<sub>f=1</sub> '' ''') can either increase or decrease the initial estimate of INDEM.
+
'''''elglinpr''' is a global parameter for the elasticity of livestock grazing intensity to annual changes in world crop prices; the basic assumption is that increasing prices should lead to increased grazing intensity and therefore greater productivity of grazing land<ref>The code, as written, ignores price effects that would reduce GLFeedEq. Since elglinpr is generally positive, this implies that decreases in world crop prices are ignored.</ref>''
  
The first adjustment to INDEM is related to the world energy price (WEP) and reflects the use of crops for fuel production. Specifically, as the world energy price increases relative to the price in the first year, the industrial demand for crops increases.
+
''This production of crop equivalents from grazing land is then subtracted from total feed requirement in the following equation:''
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq45.png http://www.du.edu/ifs/help/media/images/ag-module/ageq45.png]
+
''<math>FEDDEM_{r,f=1} =(LVHERD_{r} * Fedreq_{r} * fedreqm_{r}*max⁡{0.5,(1-livhdpro/100)^(t-1) }-〖GLFeedEq〗_r )*feddemm</math>''
  
''where''
+
'''where,'''
 +
 
 +
LVHERD, fedreq, and fedreqm are as previously described. LVHERD and fedreq are updated each year as described in section 3.11: Livestock Dynamics and as a function of GDP per capita, respectively. fedreqm, determined in the first year, does not change over time.
 +
 
 +
'''''livhdpro''' is a global parameter related to the rate at which the productivity of crops in producing meat improves over time. This part of the equation implies that the amount of feed needed to produce a unit of meat declines over time to a minimum of half the original amount required''
 +
 
 +
'''''feddemm''' is a country-specific multiplier that can be used to increase or decrease crop demand for feed purposes''
 +
 
 +
For meat and fish, a simpler process is used. The feed to food ratio, FeedToFoodRatI, calculated in the initial years of the model is used to calculate the share of feed demand for meat and fish respectively.
 +
 
 +
<math>FEDDEM_{r,f} = FeedToFoodRatI_{r,f} * FDEM_{r,f}</math>
 +
 
 +
Note that there is no multiplier equivalent to '''feddemm'''for meat and fish.
 +
 
 +
Finally, as with FDEM, FEDDEM may be adjusted to account for excessive consumer spending on food, as described in Box 2 or due to shortages in crops, meat, or fish as described in Section 3.4: Stocks.
 +
 
 +
=== Industrial demand for crops, meat and fish ===
 +
 
 +
Industrial demand, INDEM, represents the amount of crops, meat, and fish that are used in industrial processes.
 +
 
 +
==== Pre-processor and first year ====
 +
 
 +
The pre-processor reads in data from the FAO Food Balance Sheets and initializes values for the amount of agricultural commodities used in industrial processes. If data are missing, a minimum value of 1 ton, or .000001 MMT is used.
 +
 
 +
Finally, as noted in Box 1, certain adjustments may be made in the pre-processor to ensure consistencies between supply and demand in individual countries, as well as between imports and exports across countries.
 +
 
 +
[[File:Industrial demand for crops.png|frame|center|Industrial demand for crops]]<br/>In the first year, two values related to industrial demand for crops are calculated. The first of these is a multiplicative shift factor (INDEMK), which is calculated as the ratio of actual to predicted industrial demand for crops.&nbsp; The predicted value is given by a function that relates per capita industrial demand to GDP per capita, which is shown above.<ref>Equation is INDEM = 0.0376 + 0.000704 * GDPPCP</ref>&nbsp;This multiplicative shift factor remains constant over time. As with FEDDEM, one other value is calculated in the first year – IndToFoodRatI, which is the ratio between INDEM and FDEM. This is calculated for crops, meat, and fish, but is only used for the latter two categories in the forecast years, as described below.
 +
 
 +
==== Forecast years ====
 +
 
 +
In the forecast years, for crops, the initial value of industrial demand is updated using the table function above to get a predicted value for industrial demand per capita, which is then multiplied by population (POP) and the multiplicative shift factor (IndemK). At this point, a region-specific multiplier ('''indemm''') can either increase or decrease the initial estimate of INDEM.
 +
 
 +
A first adjustment to INDEM is related to the world energy price (WEP) and reflects the use of crops for fuel production. Specifically, as the world energy price increases relative to the price in the first year, the industrial demand for crops increases.
 +
 
 +
<math>INDEM_{r} = INDEM_{r} *(1+ WEP_{t}/WEP_{t=1}) *FoodforFuel)</math>
 +
 
 +
'''Where'''
  
 
WEP is world energy price
 
WEP is world energy price
  
FoodforFuel is the elasticity of industrial use of crops to world energy prices. It starts at a value given by the global parameter '''''elagind'' ''', and declines to a value of 0 over 50 years.
+
FoodforFuel is the elasticity of industrial use of crops to world energy prices. It starts at a value given by the global parameter '''elagind''', and declines to a value of 0 over 50 years.
  
 
The second adjustment relates to the world crop price (WAP<sub>f=1</sub>); as this increases relative to the price in the first year, industrial demand for crops declines.
 
The second adjustment relates to the world crop price (WAP<sub>f=1</sub>); as this increases relative to the price in the first year, industrial demand for crops declines.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq46.png http://www.du.edu/ifs/help/media/images/ag-module/ageq46.png]
+
<math>INDEM_{r} = INDEM_{r} *(WAP_{f=1,t}/WAP_{f=1,t=1} )^{elascd}</math>
  
''where''
+
''''Where''''
  
 
WAP is world crop price
 
WAP is world crop price
  
'''''elascd'' ''' is a global parameter specifying the elasticity of crop demand to global food prices
+
'''''elascd''' is a global parameter specifying the elasticity of crop demand to global food prices''
  
A third adjustment is based on an assumed cap on per capita industrial demand for crops (IndemCapperPop&nbsp;—hard coded, declines from 0.17 to 0.12 over 50 years). Specifically, INDEM is not allowed to exceed IndemCapperPop * POP.
+
A third adjustment is based on an assumed cap on per capita industrial demand for crops (IndemCapperPop—hard coded as 2. Specifically, INDEM is not allowed to exceed IndemCapperPop * POP.
  
Finally, INDEM can be reduced if the sum of expenditures on food crops at world prices (FDEM*WAP<sub>f=1</sub>) and meat (AGDEM<sub>f=2</sub>*WAP<sub>f=2</sub>) exceeds 85 percent of household consumption expenditures&nbsp;as calculated in the economic model.
+
For meat and fish, industrial demand is initially calculated by applying the Industrial demand to food ratio, IndToFoodRatI (calculated in the initial year of the model) to the value of food demand.
  
 +
<math>INDEM_{r,f} = IndToFoodRatI_{r} * FDEM_{r,f} </math>
  
<div>
+
Note that there is no multiplier equivalent to '''indemm'''for meat and fish.
----
+
 
<div>
+
Finally, as with FDEM and FEDDEM, INDEM may be adjusted to account for excessive consumer spending on food, as described in section 3.2.5 or due to shortages in crops, meat, or fish as described in this Section below.
[file:///C:/Users/Ara/Desktop/Agricultural%20Documentation%20v19_AG.docx#_ftnref1 [1]] Equation is INDEM = 0.0376 + 0.000704 * GDPPCP
+
 
 +
=== Food manufacturing demand ===
 +
 
 +
The final demand category, FMDEM, relates to the use of crops, meat, and fish in food manufacturing and processing.
 +
 
 +
==== Pre-processor and first year ====
 +
 
 +
The pre-processor reads in data from the FAO Food Balance Sheets and initializes values for the amount of agricultural commodities used in food manufacturing and processing.<ref>Note that the FAO Food Balance Sheets include data for agricultural commodities used for food manufacturing and as seed separately. We combine these into a single food manufacturing category.</ref> Note that If data are missing, a minimum value of 1 ton, or .000001 MMT is used.
 +
 
 +
As noted in Box 1, certain adjustments may be made in the pre-processor to ensure consistencies between supply and demand in individual countries, as well as between imports and exports across countries.
 +
 
 +
Paralleling the case for INDEM, FEDDEM, and AGLOSSTRANS, one other value is calculated in the first year –FManToFoodRatI, which is the ratio between INDEM and FDEM. This is calculated for crops, meat, and fish, and used for all three in the forecast years, as described below.
 +
 
 +
<math>FMDEM_{r,f} = FManToFoodRatI_{r,f} * FDEM_{r,f} </math>
 +
 
 +
==== Forecast years ====
 +
 
 +
In the forecast years, for all three categories, demand is calculated using the Food manufacturing to food demand ratio, FManToFoodRatI, calculated in the first year of the model and the value of food demand.
 +
 
 +
<math>FMDEM_{r,f} = FManToFoodRatI_{r,f} * FDEM_{r,f} </math>
 +
 
 +
As with FDEM, INDEM, and FEDDEM, FMDEM may be adjusted to account for any shortages in crops, meat, or fish as described in Section 3.4: Stocks. It is not currently affected by excessive consumer spending on food, as described in Box 2
 +
 
 +
=== Total agricultural demand and final adjustment to demand ===
 +
 
 +
==== Pre-processor and first year ====
 +
 
 +
AGDEM, which represents the sum of all uses. It is initialized in the first year of the model to ensure the balance with production, imports, and exports:
 +
 
 +
<math>AGDEM_{r,f=1-3,t=1} = AGP_{r,f=1-3,t=1} + AGM_{r,f=1-3,t=1} - AGX_{r,f=1-3,t=1} </math>
 +
 
 +
==== Forecast years ====
  
== Final Agricultural Demand Adjustments in Forecast Years ==
+
In the forecast years, AGDEM, is recalculated as the sum of the final values of feed, industry, and food demand and transmission losses:
  
Two final adjustments are made to a number of the agricultural demand variables in the forecast years. First, if the total per capita calories from meat and crops exceed the maximum calories, i.e.
+
<math>AGDEM_{r,f=1-3} = FEDDEM_{r,f=1-3} + INDEM_{r,f=1-3} + FDEM_{r,f=1-3} + FMDEM_{r,f=1-3} + AGLOSSTRANS_{r,f=1-3} </math>
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq47.png http://www.du.edu/ifs/help/media/images/ag-module/ageq47.png]
+
Note that this occurs after any adjustments to the demand values as a result of excessive consumer spending on food, (described below), but before adjustments as a result of shortages, describe in Section 3.4: Stocks. Thus, it can be the case that the final value of AGDEM may exceed the sum of the individual demand values.
  
then the demand for crops for food and the demand for meat in tons are scaled by the ratio of the maximum to the estimated calories
+
'''<u>Final agricultural demand adjustment based on levels of consumer spending</u>'''
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq48.png http://www.du.edu/ifs/help/media/images/ag-module/ageq48.png]
+
One final adjustment is made to the agricultural demand variables in the forecast years.
  
Second, if the preliminary estimate of total food demand in monetary terms (csprelim), is too large of a share of consumption, i.e., if
+
If the preliminary estimate of total food demand in monetary terms (csprelim), is too large of a share of consumption, i.e., if
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq49.png http://www.du.edu/ifs/help/media/images/ag-module/ageq49.png]
+
<math>CsPrelim_{r} = CSF_{r} *(FDEM_{r} * WAP_{f=1,t=1} + FDEM_{r,f=2} * WAP_{f=2,t=1} + FDEM_{r,f=3} * WAP_{f=3,t=1} )>0.85*C_{r,t=1}</math>
  
''where''
+
'''Where,'''
  
CSF is the ratio of consumer spending in the agricultural sector in the first year (CS<sub>r,s=1,t=1</sub>) to DemVal<sub>r</sub>, a weighted sum of demands for agricultural products for food in the first year
+
CSF is the ratio of consumer spending in the agricultural sector in the first year (CS<sub>r,s=1,t=1</sub>) to DemVal<sub>r</sub>, a weighted sum of demands for agricultural products for food in the first year;
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq50.png http://www.du.edu/ifs/help/media/images/ag-module/ageq50.png]
+
<math>DemVal_{r} = FDEM_{r,t-1} *WAP_{f=1,t-1} + FDEM_{r,f=2,t-1} * WAP_{f=2,t-1} + FDEM_{r,f=3,t-1} * WAP_{f=3,t-1} </math>
  
 
C is total household consumption in the first year
 
C is total household consumption in the first year
Line 636: Line 727:
 
When this is the case, a series of steps are taken to bring these values back in line.
 
When this is the case, a series of steps are taken to bring these values back in line.
  
1. The necessary reduction (necreduc<sub>r</sub>), which is in monetary terms, is calculated as csprelim<sub>r</sub> – 0.85*C<sub>r</sub>
+
#The necessary reduction (NecReduc<sub>r</sub>), which is in monetary terms, is calculated as CsPrelim<sub>r</sub> – 0.85*C<sub>r</sub>
 +
#A reduction factor (ReducFact) for meat and fish, assuming cuts would disproportionately be there, &nbsp;is calculated as,
  
2. A reduction factor (reducfact) is calculated as
+
<math>ReducFact_(r,)=(NecReduc_{r}/csprelim)*2</math>
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq51.png http://www.du.edu/ifs/help/media/images/ag-module/ageq51.png]
+
with a maximum value of 1 or full elimination
  
with a maximum value of 1
+
#The physical demands for crops for meat and fish in tons (FDEM, categories 2 and 3) are reduced by reducfact, and the values of the meat and fish reduction are saved for the next step
  
3.&nbsp;The physical demands for crops for feed (FEDDEM), crops for industry (INDEM), and meat in tons (AGP, category 2) are all reduced by reducfact, and the value of the meat reduction is saved for the next step&nbsp;
+
<math>Meatreduc_{r} = FDEM_{r,f=2} *ReducFact_{r}</math> <math> Fishreduc_{r} = FDEM_{r,f=3} *ReducFact_{r}</math>
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq52.png http://www.du.edu/ifs/help/media/images/ag-module/ageq52.png]
+
<math>FDEM_{r,f=2,3} = FDEM_{r,f=2,3} *(1-Reducfact)_{r}</math>
  
4.&nbsp;An estimate of the necessary reductions in crops for food, in monetary terms is estimated by subtracting the savings obtained through the reduction in meat demand
 
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq53.png http://www.du.edu/ifs/help/media/images/ag-module/ageq53.png]
 
  
5.&nbsp;The physical demand for crops for food (FDEM) is then reduced as follows
+
#An estimate of the necessary reductions in crops for food, in monetary terms is estimated by subtracting the savings obtained through the reduction in meat demand
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq54.png http://www.du.edu/ifs/help/media/images/ag-module/ageq54.png]
+
<math>FoodReduc_{r}= NecReduc_{r} - MeatReduc_{r}* CSF_{r} *WAP_{f=2,t=1} - FishReduc_{r} * CSF_{r} *WAP_{f=3,t=1} </math>
 +
 
 +
The physical demand for crops for food (FDEM) is then reduced as follows
 +
 
 +
<math>FDEM_{r,f=1} = Max(0.1*FDEM_{r,f=1} , FDEM_{r,f=1} - FoodReduc_{r}/(CSF_{r} *WAP_{f=1,t=1} ))</math>
  
 
Note that this ensures that FDEM is not reduced by more than ninety percent.
 
Note that this ensures that FDEM is not reduced by more than ninety percent.
  
Finally, given the changes above, the total demand for crops is recalculated as the sum of the final values of feed, industry, and food demand.
+
Finally, given the changes above, the total demand is recalculated as the sum of the final values of feed, industry, and food demand and transmission losses
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq55.png http://www.du.edu/ifs/help/media/images/ag-module/ageq55.png]
+
<math>AGDEM_{r,f} = FEDDEM_{r,f} + INDEM_{r,f} + FDEM_{r,f} + FMDEM_{r,f} + AGLOSSTRANS_{r,f}</math>
 +
 
 +
 
 +
 
 +
{| cellpadding="0" cellspacing="0" width="100%" align="center" border="1"
 +
|-
 +
|
 +
'''Box 1: Adjustments in the Pre-processor to Ensure Proper Balances'''
 +
 
 +
The pre-processor reads in data from the FAO Food Balance Sheets and initializes values for the amount of agricultural commodities used for direct human consumption, FDEM, feed (FEDEM), industry (INDEM), food manufacturing (FMDEM), as well as transmission losses (AGLOSSTRANS). All of these are measured in MMT per year. At the same time, it reads in data for production (AGP), imports (AGM), exports (AGX), and total domestic supply (AGDOMSUPP)[1].
 +
 
 +
A set of conditions should be meet for these variables for each category:
 +
 
 +
#AGDOMSUPP = AGP + AGM – AGX. This says that total domestic supply equals production plus imports minus exports. This equivalence can be broken if there are changes in stocks, which we will see in forecast years. Currently, however, we assume there are no such changes in the first year. Thus it may be necessary to make adjustment for the equivalence to hold in first year. This is done in the pre-processor, by keeping AGDOMSUPP the same and applying the following three rules:<ol style="list-style-type:lower-alpha;">
 +
 
 +
*If AGDOMSUPP > AGP + AGM – AGX, i.e., stocks were being drawn down, increase AGP and AGM while reducing AGX.
 +
*If AGDOMSUPP < AGP + AGM – AGX, i.e., stocks were being added to, decrease AGP and AGM while increasing AGX.
 +
*Make sure that AGP, AGM, and AGX do not fall below a minimum value.
 +
*Sum of AGM across countries = Sum of AGX across countries. This says that imports and exports need to match. If they do not, the model calculates the average of the two sums and adjusts AGM and AGX in each country proportionately.
 +
*AGP + AGM – AGX = FDEM + FEDEM + INDEM + FMDEM + AGLOSSTRANS. This says that the total domestic supply, which accounts for production losses, has to match the total uses (including losses in transmission and distribution).
 +
 
 +
The pre-processor includes procedures to ensure that these three conditions hold for the initial values in each country. This can lead to minor adjustments in the values for the supply and demand categories. These processes can also lead to changes in related variables, including the production of non-animal meat products (CAGPMILKEGGS), fish catch (AGFISHCATCH), aquaculture production (AQUACUL), the size of the livestock herd (LVHERD), and the breakdown of land areas (LD). The latter occurs because we do not want these processes to change crop yields (YL).&nbsp;
 +
 
 +
|}
  
 
== Trade ==
 
== Trade ==
Line 668: Line 785:
 
Price differentials across countries do not influence agricultural trade. Although the IFs project has experimented over time with making such trade responsive to prices, there is an increasing tendency globally for food prices to be more closely aligned across countries than was true historically.&nbsp; Moreover, the use within IFs of local relative food surpluses or deficits (as indicated by stock levels) to adjust trade patterns is an effective proxy for the use of prices.
 
Price differentials across countries do not influence agricultural trade. Although the IFs project has experimented over time with making such trade responsive to prices, there is an increasing tendency globally for food prices to be more closely aligned across countries than was true historically.&nbsp; Moreover, the use within IFs of local relative food surpluses or deficits (as indicated by stock levels) to adjust trade patterns is an effective proxy for the use of prices.
  
The initial year values of the imports (AGM) and exports (AGX) of the three agricultural commodities in physical quantities are determined in the pre-processor. Since we only have historical data on the imports and exports of fish in monetary terms, these need to be converted to physical terms. This is done by multiplying the monetary values, which are in $billion, by 1000*/2200&nbsp;to get physical values in million tons. In addition, exports of fish are limited to be less than 70 percent of total fish available and imports less than 1 percent of total fish available. For each of the three agricultural commodity groupings, if there is an imbalance between global imports and global exports in the preprocessor, the latter takes precedence and national imports are adjusted to bring global imports into line with global exports.
+
The initial year values of the imports (AGM) and exports (AGX) of the three agricultural commodities in physical quantities are determined in the pre-processor. Since we only have historical data on the imports and exports of fish in monetary terms, these need to be converted to physical terms. This is done by multiplying the monetary values, which are in $billion, by 1000*/2200 to get physical values in million tons. In addition, exports of fish are limited to be less than 70 percent of total fish available and imports less than 1 percent of total fish available. For each of the three agricultural commodity groupings, if there is an imbalance between global imports and global exports in the preprocessor, the latter takes precedence and national imports are adjusted to bring global imports into line with global exports.
  
In the first year, seven variables are set related to trade for each commodity: XKAVE, MKAVE, XKAVMAX, MKAVMAX at the country level and &nbsp;wxc<sub>t=1</sub>, wmd<sub>t=1</sub>, and WAP<sub>t=1</sub> at the global level.
+
In the first year, seven variables are set related to trade for each commodity: XKAVE, MKAVE, XKAVMAX, MKAVMAX at the country level and wxct<sub>=1</sub>, wmd<sub>t=1</sub>, and WAP<sub>t=1</sub> at the global level.
  
 
XKAVE and MKAVE are moving average values of export and import propensity, respectively. They are specified as the ratio of agricultural exports and imports to a base value (xbase) for each commodity. For exports, this is basically the sum of production and demand for that commodity; for imports, it is just demand.
 
XKAVE and MKAVE are moving average values of export and import propensity, respectively. They are specified as the ratio of agricultural exports and imports to a base value (xbase) for each commodity. For exports, this is basically the sum of production and demand for that commodity; for imports, it is just demand.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq56.png http://www.du.edu/ifs/help/media/images/ag-module/ageq56.png]
+
<math>XKAVE_{r,f=1-3,t=1} = AGX_{r,f=1-3,t=1}/(AGP_{r,f=1-3,t=1} + AGDEM_{r,f=1-3,t=1} )</math>
 +
 
 +
<math>MKAVE_{r,f=1-3,t=1} = AGM_{r,f=1-3,t=1}/ AGDEM_{r,f=1-3,t=1} </math>
  
 
XKAVMAX and MKAVMAX are maximum values of XKAVE and MKAVE. For crops and meat, XKAVMAX is set to 1.1 times XKAVE, but is not allowed to exceed a value of 0.7; MKAVMAX is set to 1.5 times XKAVE, but also is not allowed to exceed a value of 0.7. For fish, XKAVMAX is set to 1.1 times XKAVE, with a bound of 0.95; MKAVE is set to 1.5 times MKAVE, with a bound of 2. These values are held constant for all future years.
 
XKAVMAX and MKAVMAX are maximum values of XKAVE and MKAVE. For crops and meat, XKAVMAX is set to 1.1 times XKAVE, but is not allowed to exceed a value of 0.7; MKAVMAX is set to 1.5 times XKAVE, but also is not allowed to exceed a value of 0.7. For fish, XKAVMAX is set to 1.1 times XKAVE, with a bound of 0.95; MKAVE is set to 1.5 times MKAVE, with a bound of 2. These values are held constant for all future years.
Line 688: Line 807:
 
The agricultural export capacity is estimated by multiplying the export propensity (XKAVE) by the current year’s production and demand. It is also limited by XKAVMAX:
 
The agricultural export capacity is estimated by multiplying the export propensity (XKAVE) by the current year’s production and demand. It is also limited by XKAVMAX:
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq57.png http://www.du.edu/ifs/help/media/images/ag-module/ageq57.png]
+
<math>AGX_{r,f=1-3} = MIN(XKAVE_{r,f=1-3}, XKAVMAX_{r,f=1-3} )*(AGP_{r,f=1-3} + AGDEM_{r,f=1-3} )</math>
  
 
Similarly, the agricultural import demand is estimated by multiplying the import propensity (MKAVE) by the current year’s demand, with a limit set by MKAVMAX
 
Similarly, the agricultural import demand is estimated by multiplying the import propensity (MKAVE) by the current year’s demand, with a limit set by MKAVMAX
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq58.png http://www.du.edu/ifs/help/media/images/ag-module/ageq58.png]
+
<math>AGM_{r,f=1-3} =MIN(MKAVE_{r,f=1-3}, MKAVMAX_{r,f=1-3} )* AGDEM_{r,f=1-3} </math>
  
 
For each country, values are also estimated for its net surplus or deficit (surpdef) for each commodity. This is based on the following factors: 1) post-loss production, 2) domestic demand, 3) the difference between current and desired stocks, and 4) a trade term
 
For each country, values are also estimated for its net surplus or deficit (surpdef) for each commodity. This is based on the following factors: 1) post-loss production, 2) domestic demand, 3) the difference between current and desired stocks, and 4) a trade term
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq59.png http://www.du.edu/ifs/help/media/images/ag-module/ageq59.png]
+
<math>surpdef_{r,f=1-3} = AGP_{r,f=1-3} * (1-LOSS_{r,f=1-3}) -AGDEM_{r,f=1-3}
 +
+ cumstk_{r,f=1-3} - agdstl*(AGP_{r,f=1-3} + AGDEM_{r,f=1-3})
 +
+TradeTerm_{r,f=1-3}
 +
)</math>
  
 
The first three factors are straightforward. Production minus demand reflects a basic net surplus, which is then adjusted by any net surplus in stocks. The TradeTerm is related the relative role a country plays in global imports and exports and is given as:
 
The first three factors are straightforward. Production minus demand reflects a basic net surplus, which is then adjusted by any net surplus in stocks. The TradeTerm is related the relative role a country plays in global imports and exports and is given as:
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq60.png http://www.du.edu/ifs/help/media/images/ag-module/ageq60.png]
+
<math>TradeTerm_{r,f=1-3} =(AGM_{r,f=1-3}/wmd_{f=1-3,t-1} - AGX_{r,f=1-3}/wxc_{f=1-3,t-1} )*(wmd_{f=1-3,t-1}+ wxc_{f=1-3,t-1})/2</math>
  
The TradeTerm is positive (negative) when a country has a larger (smaller) share of the global imports than it does of the global exports of a particular commodity and vice versa. Since the TradeTerm is is added to surpdef, it acts as a balancing mechanism; countries that appear as relatively larger (smaller) importers get a positive (negative) boost to their estimated net surplus, which tends to reduce (increase) imports as shown below.&nbsp;
+
The TradeTerm is positive (negative) when a country has a larger (smaller) share of the global imports than it does of the global exports of a particular commodity and vice versa. Since the TradeTerm is added to surpdef, it acts as a balancing mechanism; countries that appear as relatively larger (smaller) importers get a positive (negative) boost to their estimated net surplus, which tends to reduce (increase) imports as shown below.
  
 
At this point, the global sum of exports and imports across countries will likely differ. Therefore, a procedure is required to balance these. In preparation for this one more global variable and several country-level variables are calculated. The global variable is globalsurdefrate, which is the ratio of the sum across countries of net surplus divided by the sum across countries of demand and production, which is the stock base.
 
At this point, the global sum of exports and imports across countries will likely differ. Therefore, a procedure is required to balance these. In preparation for this one more global variable and several country-level variables are calculated. The global variable is globalsurdefrate, which is the ratio of the sum across countries of net surplus divided by the sum across countries of demand and production, which is the stock base.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq61.png http://www.du.edu/ifs/help/media/images/ag-module/ageq61.png]
+
<math>globalsurdefrate_{f=1-3} =(∑_r(surpdef_{r,f=1-3} )/(∑_r(AGDEM_{r,f=1-3} + AGP_{r,f=1-3}))</math>
  
 
The country-level variables are as follows:
 
The country-level variables are as follows:
Line 712: Line 834:
 
The first term modifies the country’s net surplus, increasing (decreasing) it when the global net surplus is negative (positive).
 
The first term modifies the country’s net surplus, increasing (decreasing) it when the global net surplus is negative (positive).
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq62.png http://www.du.edu/ifs/help/media/images/ag-module/ageq62.png]
+
<math>countryextrasurdef_{r,f=1-3} = surpdef_{r,f=1-3} - globalsurdefrate_{f=1-3} *(AGDEM_{r,f=1-3}+ AGP_{r,f=1-3})</math>
  
 
The second term modifies how rapidly the net surplus is closed.
 
The second term modifies how rapidly the net surplus is closed.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq63.png http://www.du.edu/ifs/help/media/images/ag-module/ageq63.png]
+
<math>countryextrasurdefadj_{r,f=1-3} = countryextrasurdef_{r,f=1-3}/5</math>
  
 
The third term is simply the ratio of exports to the sum of imports and exports.
 
The third term is simply the ratio of exports to the sum of imports and exports.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq64.png http://www.du.edu/ifs/help/media/images/ag-module/ageq64.png]
+
<math>exportshare_{r,f=1-3} = AGX_{r,f=1-3}/(AGX_{r,f=1-3} + AGM_{r,f=1-3} )</math>
  
 
The next step is to calculate whether it is necessary to increase (decrease) imports and decrease (increase) exports for each country, and by how much. Whether a country needs to increase its initial estimates of imports and decrease its initial estimates of exports, or vice versa, is determined by the sign of countryextrasurdef. If this value is negative, i.e., the country has a net deficit, it will need to reduce exports and increase imports. The opposite holds for when countryextrasurdef is positive.
 
The next step is to calculate whether it is necessary to increase (decrease) imports and decrease (increase) exports for each country, and by how much. Whether a country needs to increase its initial estimates of imports and decrease its initial estimates of exports, or vice versa, is determined by the sign of countryextrasurdef. If this value is negative, i.e., the country has a net deficit, it will need to reduce exports and increase imports. The opposite holds for when countryextrasurdef is positive.
Line 726: Line 848:
 
As for the amount by which imports and exports need to be increased or decreased, this is a function, in general, of the size of the necessary adjustment and the export share:
 
As for the amount by which imports and exports need to be increased or decreased, this is a function, in general, of the size of the necessary adjustment and the export share:
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq65.png http://www.du.edu/ifs/help/media/images/ag-module/ageq65.png]
+
<math>AGX_{r,f=1-3} = AGX_{r,f=1-3} + countryextrasurfdefadj_{f=1-3} * exportshare_{r,f=1-3}</math> <math>AGM_{r,f=1-3} = AGM_{r,f=1-3}- countryextrasurfdefadj_{f=1-3} * (1-exportshare_{r,f=1-3})</math>
  
Note that the sign of countryextrasurdef and the fact that exportshare is a value between 0 and 1 ensure that when exports increases, imports fall, and vice versa.<sup>[http://www.du.edu/ifs/help/understand/agriculture/equations/trade.html#footnote [1]] </sup> Finally, in this adjustment process, exports and imports are not allowed to fall by more than half or more than double.
+
Note that the sign of countryextrasurdef and the fact that exportshare is a value between 0 and 1 ensure that when exports increases, imports fall, and vice versa.<ref>Two other variables, defadjmul and ImportBoost, are included in the calculations to make some finer adjustments to the changes in exports and imports; these relate to the observed behavior for specific countries and are not discussed in detail here.</ref>Finally, in this adjustment process, exports and imports are not allowed to fall by more than half or more than double.
  
 
This process may not fully reconcile global trade, so a final adjustment is made by setting world trade (WT) as the average of global exports and imports and then adjusting the country values accordingly:
 
This process may not fully reconcile global trade, so a final adjustment is made by setting world trade (WT) as the average of global exports and imports and then adjusting the country values accordingly:
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq66.png http://www.du.edu/ifs/help/media/images/ag-module/ageq66.png]
+
<math>WT_{f=1-3} =(∑_r(AGX_{r,f=1-3}) +∑_r(AGM_{r,f=1-3}) )/2</math> <math> AGX_{r,f=1-3} = AGX_{r,f=1-3} * WT_{f=1-3}/(∑_r(AGX_{r,f=1-3}) )</math> <math> AGM_{r,f=1-3} = AGM_{r,f=1-3} * WT_{f=1-3}/(∑_r(AGM_{r,f=1-3}) )</math>
  
IFs can now update the moving average export (XKAVE) and import (MKAVE) propensities for the next time step. The weights given to history are set by the global parameters '''''xhw'' ''' and '''''mhw'' '''. For small exporters, i.e., where exports are less than one tenth of the sum of production and demand, '''''xhw'' ''' is reduced by 40 percent, allowing for faster adjustment. XKAVE and MKAVE are updated as
+
IFs can now update the moving average export (XKAVE) and import (MKAVE) propensities for the next time step. The weights given to history are set by the global parameters '''xhw'''and '''mhw'''. For small exporters, i.e., where exports are less than one tenth of the sum of production and demand, '''xhw'''is reduced by 40 percent, allowing for faster adjustment. XKAVE and MKAVE are updated as
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq67.png http://www.du.edu/ifs/help/media/images/ag-module/ageq67.png]
+
<math>XKAVE_{r,f=1-3,t+1} = XKAVE_{r,f=1-3}+(1-xhw)* AGX_{r,f=1-3}/(AGP_{r,f=1-3} + AGDEM_{r,f=1-3} )</math>
 +
 
 +
<math>MKAVE_{r,f=1-3,t+1} = XMAVE_{r,f=1-3}+ {1-mhw} * AGM_{r,f=1-3}/AGDEM_{r,f=1-3} </math>
  
 
For crops, the import propensity is bound from below by a factor given by potential GDP (GDPPOT), demand (AGDEM), the conversion factor between agricultural imports in physical terms and dollar values (msf, see section on links to the economic model), and the initial world price for agriculture (WAP).
 
For crops, the import propensity is bound from below by a factor given by potential GDP (GDPPOT), demand (AGDEM), the conversion factor between agricultural imports in physical terms and dollar values (msf, see section on links to the economic model), and the initial world price for agriculture (WAP).
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq68.png http://www.du.edu/ifs/help/media/images/ag-module/ageq68.png]
+
<math>XKAVE_{r,f=1-3,t+1} ≥ (0.6*GDPPOT_{r})/(AGDEM_{r,f=1-3} * msf_{r}*WAP_{f,t=1})</math>
  
 
Finally, XKAVE and MKAVE are bound from above by XKAVMAX and MKAVMAX, respectively.
 
Finally, XKAVE and MKAVE are bound from above by XKAVMAX and MKAVMAX, respectively.
<div>
 
----
 
<div>
 
[file:///C:/Users/Ara/Desktop/Agricultural%20Documentation%20v19_AG.docx#_ftnref1 [1]] Two other variables, defadjmul and ImportBoost, are included in the calculations to make some finer adjustments to the changes in exports and imports; these relate to the observed behavior for specific countries and are not discussed in detail here. <header><hgroup>
 
  
 
== Stocks ==
 
== Stocks ==
  
</hgroup></header> Due to a lack of good historical data, in the first year, stocks for all three agricultural commodities are assumed to equal desired stocks. These are set to a fraction (''agdstl) ''of total production (AGP) and demand (AGDEM) for each commodity.
+
==== First year ====
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq69.png http://www.du.edu/ifs/help/media/images/ag-module/ageq69.png]
+
Due to a lack of good historical data, in the first year, stocks for all three agricultural commodities are assumed to equal desired stocks. These are set to a fraction (agdstl) of total production (AGP) and demand (AGDEM) for each commodity.
  
''where''
+
<math>FSTOCK_{r,f=1-3} =(AGP_{r,f=1-3} + AGDEM_{r,f=1-3} )*Agdstl</math>
  
agdstl is a parameter used to set desired stock levels for agricultural commodities.&nbsp; It is set to be 1.5 times '''''dstl'' ''', which is a global parameter that can be adjusted by the user
+
Where
  
In future years, basic stock levels (cumstk) increase with production (AGP) as adjusted for loss before reaching market (LOSS), decrease with demand or consumption (AGDEM), and adjust for net imports (AGM-AGX).
+
Agdstl is a parameter used to set desired stock levels for agricultural commodities.&nbsp; It is set to be 1.5 times '''dstl''', which is a global parameter that can be adjusted by the user
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq70.png http://www.du.edu/ifs/help/media/images/ag-module/ageq70.png]
+
==== Forecast years ====
  
Of course, the actual stock values (FSTOCK) are not allowed to go negative. If the basic stock level is negative, stocks are set at zero and a shortage (SHO) exists, which affects calorie availability. If the basic stock level is positive there is no shortage and stocks equal the basic level.
+
In future years, basic stock levels (CumStk) increase with production (AGP), decrease with demand or consumption (AGDEM), and adjust for net imports (AGM-AGX).
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq71.png http://www.du.edu/ifs/help/media/images/ag-module/ageq71.png]
+
<math>CumStk_{r=1-3} = FSTOCK_{r,f=1-3,t-1} + StkAdj_{r,f=1-3}</math> <math>StkAdj_{r,f=1-3} = AGP_{r,f=1-3} - AGDEM_{r,f=1-3}+ (AGM_{r,f}- AGX_{r,f=1-3})</math>
  
== Calorie Availability ==
+
Of course, the actual stock values (FSTOCK) are not allowed to go negative. If the basic stock level is negative, stocks are set at zero and a shortage (Sho) exists, which affects calorie availability. If the basic stock level is positive there is no shortage and stocks equal the basic level.
  
Daily per capita calorie availability (CLPC) is initialized in the pre-processor. Where available, data is taken from the FAO<sup>[http://www.du.edu/ifs/help/understand/agriculture/equations/calorie.html#footnote [1]] </sup>. It is multiplied by population (POP) to yield total daily calorie availability and brought into the model with the name CLAVAL. We already saw that this first year value is used in the calculation of two country-specific factors: 1) calactpredrat, which is a shift factor determined as the ratio of calorie availability to predicted calorie demand in the first year, and 2) sclavf, which is a conversion factor relating the total annual demand for food crops and crop equivalents from meat to daily calorie availability.
+
<math>if cumstk_{r,f=1-3}<0 then Sho_{r,f=1-3} =-StkAdj_{r,f=1-3} and FSTOCK_{r,f=1-3}= 0</math> <math>if cumstk_{r,f=1-3} > 0 then Sho_{r,f=1-3} = 0 and FSTOCK_{r,f=1-3} = cumstk_{r,f}</math>
  
In the forecast years, CLAVAL depends upon the demand for food crops and meat, but also any shortages in crops or meat. The specific shortage is calculated as
+
Also, if shortages are greater than 0, a reduction factor (ReductionFactor''')'''is computed which is then used to adjust demand and losses.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq72.png http://www.du.edu/ifs/help/media/images/ag-module/ageq72.png]
+
<math>if SHO_{r,f}>0, ReductionFactor_{r,f} =(AGDEM_{r,f}- SHO_{r,f})/ AGDEM_{r,f}</math> <math> FDEM_{r,f}= FDEM_{r,f} * ReductionFactor_{r,f} </math> <math> FEDDEM_{r,f} = FEDDEM_{r,f} * ReductionFactor_{r,f} </math> <math> INDEM_{r,f} = INDEM_{r,f} * ReductionFactor_{r,f} </math> <math> FMDEM_{r,f} = FMDEM_{r,f} * ReductionFactor_{r,f} </math> <math> AGLOSSTRANS_{r,f} = AGLOSSTRANS_{r,f} * ReductionFactor_{r,f} </math>
  
CLAVAL is then calculated as
+
== Calorie Availability ==
 +
 
 +
Daily per capita calorie availability (CLPC) is initialized in the pre-processor. Where available, data is taken from the FAO<ref>Note this occurs in DATAPOP, not DATAAGRI. The historic data series is SERIESCalPCap. Missing data are estimated based on access to water and sanitation or average income.</ref>&nbsp;It is multiplied by population (POP) to yield total daily calorie availability and brought into the model with the name CLAVAL. We already saw that this first year value is used in the calculation of two country-specific factors: 1) calactpredrat, which is a shift factor determined as the ratio of calorie availability to predicted calorie demand in the first year, and 2) sclavf, which is a conversion factor relating the total annual demand for food crops and crop equivalents from meat to daily calorie availability.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq73.png http://www.du.edu/ifs/help/media/images/ag-module/ageq73.png]
+
In the forecast years, CLAVAL is calculated using the final value of calories per capita.
  
Calorie availability combines with regional calorie need in the population model for the calculation of possible starvation deaths&nbsp;(a seldom used variable because in official death statistics people do not die of starvation but rather of diseases associated with undernutrition); the population and health models therefore look instead to the impact of calorie availability on undernutrition and health.
+
<math>CLAVAL_r= CLPC_{r,f=4}* POP_{r} </math>
  
[file:///C:/Users/Ara/Desktop/Agricultural%20Documentation%20v19_AG.docx#_ftnref1 [1]] Note this occurs in DATAPOP, not DATAAGRI. The historic data series is SERIESCalPCap. Missing data are estimated based on access to water and sanitation or average income.
+
Calorie availability combines with regional calorie need in the population model for the calculation of possible starvation deaths (a seldom used variable because in official death statistics people do not die of starvation but rather of diseases associated with undernutrition); the population and health models therefore look instead to the impact of calorie availability on undernutrition and health.
  
 
== Prices ==
 
== Prices ==
Line 788: Line 910:
 
The national crop price indices (FPRI, category (1) respond to: 1) changes in global costs of crop production, the latter being expressed as the ratio of global accumulated capital investment in crops to global production and 2) changes in the level of domestic crop stocks. The first factor should provide a long-term basis for rising or falling prices tied to changing technology and other factors of production; the second factor generally should represent shorter-term market variations from that long-term level.
 
The national crop price indices (FPRI, category (1) respond to: 1) changes in global costs of crop production, the latter being expressed as the ratio of global accumulated capital investment in crops to global production and 2) changes in the level of domestic crop stocks. The first factor should provide a long-term basis for rising or falling prices tied to changing technology and other factors of production; the second factor generally should represent shorter-term market variations from that long-term level.
  
The impact of global costs is given by dividing the ratio of global investment in crops to global production (wkagagpr) in the current year to that same ratio in the first year.&nbsp; The effect of stocks on crop prices (Mul) is calculated using the same ADJSTR function introduced in the description of crop supply, which considers the difference between both the current crop stocks and a desired vale and between current crop stocks and those in the previous year. Two parameters control the degree to which these two ‘differences’ affect the calculation of the adjustment factor. In this case, these are the global, user-controllable parameters '''''fpricr1'' ''' and '''''fpricr2'' '''. All together the equation for domestic crop price indices in the coming year is given as
+
The impact of global costs is given by dividing the ratio of global investment in crops to global production (wkagagpr) in the current year to that same ratio in the first year.&nbsp; The effect of stocks on crop prices (Mul) is calculated using the same ADJSTR function introduced in the description of crop supply, which considers the difference between both the current crop stocks and a desired vale and between current crop stocks and those in the previous year. Two parameters control the degree to which these two ‘differences’ affect the calculation of the adjustment factor. In this case, these are the global, user-controllable parameters '''fpricr1'''and '''fpricr2'''. All together the equation for domestic crop price indices in the coming year is given as
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq74.png http://www.du.edu/ifs/help/media/images/ag-module/ageq74.png]
+
<math>FPRI_{r,f=1,t+1} = WAP_{f=1,t=1} * wkagagpr_{r,t}/wkagagpr_{r,t=1} * Mul_{r} </math>
  
 
The domestic crop price indices are also bound between 0.01 and 1000.
 
The domestic crop price indices are also bound between 0.01 and 1000.
  
The national meat price indices are linked the global crop price. Specifically, they are given as a moving average of the global crop price index.
+
The national meat price indices are linked the global crop price. Specifically, they are given as a moving average of the global crop price index
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq75.png http://www.du.edu/ifs/help/media/images/ag-module/ageq75.png]
+
<math>FPRI_{r,f=2,t+1} = fprihw* FPRI_{r,f=2,t} +(1-fprihw)* WAP_{f=1,t}</math>
  
''where''
+
Where
  
'''''fprihw'' ''' is a global parameter used to control the speed at which the domestic meat price changes.
+
'''''fprihw''' is a global parameter used to control the speed at which the domestic meat price changes.''
  
The national fish price indices are all set equal to the global fish price index. The determination of the global fish price is similar to that for the national crop price, but here the stock of interest is the global stock and there is no effect related to costs. The ADJSTR function is used once again to calculate the adjustment factor (MUL), this time focusing on the desired global fish stock, the difference between this and the current global fish stock, and the change in the global fish stock in the past year. Again, two parameters control the degree to which these two "differences" affect the calculation of the adjustment factor. In this case, these are the global, user-controllable parameters '''''fprim1'' ''' and '''''fprim2'' ''' [file:///C:/Users/Ara/Desktop/Agricultural%20Documentation%20v19_AG.docx#_msocom_1 [U1]]&nbsp;. The global and national fish prices are thus calculated as
+
The national fish price indices are all set equal to the global fish price index. The determination of the global fish price is similar to that for the national crop price, but here the stock of interest is the global stock and there is no effect related to costs. The ADJSTR function is used once again to calculate the adjustment factor (MUL), this time focusing on the desired global fish stock, the difference between this and the current global fish stock, and the change in the global fish stock in the past year. Again, two parameters control the degree to which these two "differences" affect the calculation of the adjustment factor. In this case, these are the global, user-controllable parameters '''fprim1'''and '''fprim2'''. The global and national fish prices are thus calculated as
 
+
[http://www.du.edu/ifs/help/media/images/ag-module/ageq76.png http://www.du.edu/ifs/help/media/images/ag-module/ageq76.png]
+
  
 
The world price indices for crops and meat are computed, in the following year, as a weighted average of the domestic prices, with the weights given by crop and meat production:
 
The world price indices for crops and meat are computed, in the following year, as a weighted average of the domestic prices, with the weights given by crop and meat production:
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq77.png http://www.du.edu/ifs/help/media/images/ag-module/ageq77.png]
+
<math>WAP_{r,f=1-2,t+1} =(∑_r(FPRI_{r,f=1-2,t+1} * AGP_{r,f=1-2,t+1} ) )/(∑_r(AGP_{r,f=1-2,t+1}) )</math>
  
 
== Returns and Profits ==
 
== Returns and Profits ==
  
IFs estimates the net returns in agriculture (AGReturn) for each commodity, based upon production costs and net revenues. Agricultural profits (FPROFIT) depend on the gross returns to production (GReturn) relative to the costs of production. At some points in the evolution of IFs we have used these profits as a guide to rates of investment; the current formulation for investment does not use them.
+
IFs estimates the net returns in agriculture (AGReturn) for each commodity as the ratio of gross returns (GReturn) to production costs (ProdCost and MProdCost). The agricultural profit ratios (FPROFITR) are then estimated as the ratio of AGReturn in the current year to its value in the initial year. At some points in the evolution of IFs we have used FPROFITR as a guide to rates of investment (see the calculation of mulrprof in All but First 2: Investment); the current formulation for investment does not do so. For completeness, however, we provide a description of these processes in the model, as they still exist as live code.
 +
 
 +
==== Pre-processor and first year ====
 +
 
 +
In the first year, values for FPROFITR, sfprofitr, and FPRofitR are all set to 1.
 +
 
 +
==== Forecast years ====
  
 
The production costs for crops are estimated as the cost of cropland, priced at the cost of new land development (CLD), plus the investment in agricultural capital (KAG). The net revenues are given as total yield times the domestic crop price index. This results in
 
The production costs for crops are estimated as the cost of cropland, priced at the cost of new land development (CLD), plus the investment in agricultural capital (KAG). The net revenues are given as total yield times the domestic crop price index. This results in
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq78.png http://www.du.edu/ifs/help/media/images/ag-module/ageq78.png]
+
<math>ProdCost_{r,f=1,t} = LD_{r,l=1,t} * CLD_{r,t}+ KAG_{r,t} </math>
 +
 
 +
<math>GReturn_{r,f=1,t} = (byl_{r,f}* LD_{r,f=1} * FPRI_{r,f=1} * (AGLOSSPROD_{r,f=1} /AGP_{r,f=1}))/ProdCost_{r,f=1,t}</math>
  
 
For meat, production costs are estimated by the value of the crop equivalents produced by grazing and the cost of feed, where the value is given by the domestic meat price index. The net revenues are based on the size of the herd and the domestic meat price index. This results in
 
For meat, production costs are estimated by the value of the crop equivalents produced by grazing and the cost of feed, where the value is given by the domestic meat price index. The net revenues are based on the size of the herd and the domestic meat price index. This results in
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq79.png http://www.du.edu/ifs/help/media/images/ag-module/ageq79.png]
+
<math>MProdCost_{r,f=2,t} =(LD_{r,l=2,t} * GLDCAP_{r,t} + FEDDEM_{r,t} )* FPRI_{r,f=2,t+1} </math> <math> GReturn_{r,f=2,t}=(LVHERD_{r,t} * FPRI_{r,f=2,t+1})/ProdCost_(r,f=2,t)</math>
  
 
For fish, the production costs are simply estimated by the total production of fish times the domestic meat price index. The net revenues are given as the total production of fish times the domestic fish price index. This implies
 
For fish, the production costs are simply estimated by the total production of fish times the domestic meat price index. The net revenues are given as the total production of fish times the domestic fish price index. This implies
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq80.png http://www.du.edu/ifs/help/media/images/ag-module/ageq80.png]
+
<math>MProdCost_{r,f=3,t}= FISH_{r,t} * FPRI_{r,f=2,t+1} </math> <math>GReturn_{r,f=3,t} =(AGP_{r,f=3}* FPRI_{r,f=3,t+1})/ProdCost_{r,f=3,t}</math>
  
 
The net returns for each commodity can then be calculated as
 
The net returns for each commodity can then be calculated as
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq81.png http://www.du.edu/ifs/help/media/images/ag-module/ageq81.png]
+
<math>AGReturn_{r,f=1-3,t} = GReturn_{r,f=1-3,t}/ProdCost_{r,f=1-3,t} </math>
  
 
These net returns are used to account for changes in profits over time, using the variable FPROFITR, which influences investment in agriculture. This variable is calculated for each commodity as
 
These net returns are used to account for changes in profits over time, using the variable FPROFITR, which influences investment in agriculture. This variable is calculated for each commodity as
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq82.png http://www.du.edu/ifs/help/media/images/ag-module/ageq82.png]
+
<math>FPROFIT_{r,f=1-3,t} = AGReturn_{r,f=1-3,t}/ARGeturn_{r,f=1-3,t=1} </math>
  
 
A similar variable (wfprofitr) is calculated at the global level as a production weighted average of country/region values, but only for crops.
 
A similar variable (wfprofitr) is calculated at the global level as a production weighted average of country/region values, but only for crops.
Line 840: Line 968:
 
Investment in agriculture is relatively complex in IFs, because changes in investment are the key factor that allows us to clear the agricultural market in the long term. It is very similar to investment in energy, except that we do not need to compute type-specific investments—capital in agriculture is only used for the production function of crops.
 
Investment in agriculture is relatively complex in IFs, because changes in investment are the key factor that allows us to clear the agricultural market in the long term. It is very similar to investment in energy, except that we do not need to compute type-specific investments—capital in agriculture is only used for the production function of crops.
  
We calculate a total agricultural investment need (INAG) to take to the economic model and place into the computation for investment among sectors. This investment involves multiple factors. These begin with the rate of investment within GDP of the previous year applied to the GDP of the current year, adjustment factors related to domestic and global crop stocks, and changes in the ratio of global crop demand to global GDP. This is expressed as
+
We calculate a total agricultural investment need (INAG) to take to the economic model and place into the computation for investment among sectors. This calculation involves multiple factors. &nbsp;These begin with an initial estimate or targeted level of investment (TInAg) that is the product of the ratio of investment to GDP in the previous year times the GDP in the current year.
 +
 
 +
Three factors modify that basic or target investment level.&nbsp; Two of those are global and one is regional.&nbsp; The first global factor is a multiplier linked to year-to-year change in the ratio of agricultural demand to GDP (WAgDemRMul); typically agricultural demand grows more slowly than GDP.&nbsp; The second is a multiplier responsive to the level of global stocks (MulWSt); if those drop below target levels it would increase production globally and vice versa.&nbsp; The model could use a global price average instead of stocks, but in the recursive structure stocks determine prices and therefore use of stocks accelerates responsiveness of investment.&nbsp; Similarly, the regional factor represents a multiplier tied to regional stock levels (MulSt).
 +
 
 +
<math>TInAg_{r,t} = INAG_{r,t-1}/GDP_{r,t-1} * GDP_{r,t}* WAgDemRMul_{t} * MulWSt_{t}* MulSt_{r,t}</math>
 +
 
 +
where,&nbsp;<math> WAgDemRMul_{t} =((∑_R(AGDEM_{r,t} )⁄WGDP_{t} )/((∑_R(AGDEM_{r,t-1})⁄WGDP_{t-1})</math>
 +
 
 +
To elaborate, MulWSt and MulSt are adjustment factors related to global and domestic crop stocks, respectively. Both use the PID ADJSTR function described earlier, just as changes in prices use it in order to set prices that change year-to-year so as to chase supply-demand equilibration over time. For MulWSt, the controlling parameters in the PID function for stocks versus targets and changes in stocks are hard coded with values of -0.3 and -0.9, respectively. For MulSt, these parameters are hard coded with values of -0.2 and -0.4, respectively.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq83.png http://www.du.edu/ifs/help/media/images/ag-module/ageq83.png]
+
Experience with that initial estimate, however, shows that it can be overly responsive to one or more of the multiplicative adjustment factors, thereby setting up behavior that oscillates.&nbsp; Therefore the next step is to compute a smoothed rate of investment as a share of GDP (SmInAgR).&nbsp; That rate gives more weight (60 percent) to the final investment rate in the previous year than it does to the rate that results from the initial target investment calculation.&nbsp; The overall result of this process is to smooth changes in the rate of investment over time.&nbsp; Desired investment (INAG) is the product of that smoothed rate and GDP.
  
''where''
+
<math>INAG_{r,t}= SmInAgR_{r,t} * GDP_{r,t} </math>
  
mulwst and mulst are adjustment factors related to global and domestic crop stocks, respectively. Both use the ADJSTR function described earlier. For mulwst, the values for the effects of the gaps between existing and desired stocks, and for the change in stocks, are hard coded with values of -0.3 and -0.9, respectively. For mulst, these parameters are hard coded with values of -0.2 and -0.4, respectively.
+
where,
  
WAGDEM is the total global demand for crops
+
<math>SmInAgR_{r,t} = INAG_{r,t-1}/GDP_{r,t-1} *0.6+ TInAg_{r,t}/GDP_{r,t} *0.4)</math>
  
As an initial check against too rapid of a shift in demand for agricultural investment, INAG is not allowed to increase by more than 30 percent or decrease by more than 25 percent from the actual investment in the current year. A second check ensures that the demand is no less than 0.5 percent and no greater than 40 percent of current agricultural capital (KAG).
+
To further prevent too rapid of a shift in demand for agricultural investment, INAG is not allowed to increase by more than 30 percent or decrease by more than 25 percent from the actual investment in the current year. A second check ensures that the demand is no less than 0.5 percent and no greater than 40 percent of current agricultural capital (KAG).
  
At this point the country-specific multiplier '''''aginvm'' ''' can boost or reduce INAG. One final check ensures that as long as GDP in the country is larger than it was in the first year, the demand for agricultural investment is not allowed to decline at an annual rate of more than 1 percent per year from the first year.
+
At this point a user-controlled country-specific multiplier '''aginvm'''can boost or reduce INAG. One final check ensures that as long as GDP in the country is larger than it was in the first year, the demand for agricultural investment is not allowed to decline at an annual rate of more than 1 percent per year from the first year.
  
Investment need (INAG) then enters the economic model, which returns an adjusted value that feeds into further calculations in the agriculture model.
+
Investment need (INAG) then enters the economic model, which returns a value reconciled with all other investment needs and that feeds into further calculations in the agriculture model.
  
 
== Economic Linkages ==
 
== Economic Linkages ==
Line 860: Line 996:
 
Several variables, such as gross production, stocks, consumer spending, trade, prices and investment, are common to both the economic model and the two physical models. But hardly ever will the economic and physical models produce identical values, even during the first time step when both utilize "data." Thus, although we want the physical model value to override that of the economic model, it cannot simply replace it. Instead IFs extensively uses a procedure of computing an adjustment coefficient during the first time step. That coefficient is the ratio of the value in the economic model to the value in the physical model. In subsequent years IFs uses that coefficient to adjust the value from the physical model before its introduction into the economic model.
 
Several variables, such as gross production, stocks, consumer spending, trade, prices and investment, are common to both the economic model and the two physical models. But hardly ever will the economic and physical models produce identical values, even during the first time step when both utilize "data." Thus, although we want the physical model value to override that of the economic model, it cannot simply replace it. Instead IFs extensively uses a procedure of computing an adjustment coefficient during the first time step. That coefficient is the ratio of the value in the economic model to the value in the physical model. In subsequent years IFs uses that coefficient to adjust the value from the physical model before its introduction into the economic model.
  
Gross production (ZS) in the agricultural sector illustrates this procedure. The value of gross production in the agricultural model is the sum of the products of agricultural production (AGP) and prices (WAP) in each agricultural category. Multiplying that times an adjustment factor (ZSF) computed in the first time stop to assure inter-model consistency produces gross production for the economic &nbsp;(ZS). World average prices (WAP) are used in all the economic/physical model conversions because they assure that global sums (e.g. of exports and imports) will balance.<sup>[http://www.du.edu/ifs/help/understand/agriculture/equations/linkages.html#footnote [1]]</sup>
+
Gross production (ZS) in the agricultural sector illustrates this procedure. The value of gross production in the agricultural model is the sum of the products of agricultural production (AGP) and prices (WAP) in each agricultural category. Multiplying that times an adjustment factor (ZSF) computed in the first time stop to assure inter-model consistency produces gross production for the economic (ZS). World average prices (WAP) are used in all the economic/physical model conversions because they assure that global sums (e.g. of exports and imports) will balance.<ref>s in the subscript represents economic sector. s = 1 is defined as the agriculture sector.</ref>
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq84.png http://www.du.edu/ifs/help/media/images/ag-module/ageq84.png]
+
<math>ZS_{r,s=1}=ZSF_{r}*∑_f(WAP_{f,t=1}*AGP_{r,f,t} ) </math>
  
''where''
+
'''Where,'''
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq85.png http://www.du.edu/ifs/help/media/images/ag-module/ageq85.png]
+
<math>ZSF_{r} =ZS_{r,s=1}/(∑_f(WAP_{f,t=1}*AGP_{r,f,t=1} ) )</math>
  
 
Similarly, food stocks in each category (FSTOCK) and an adjustment factor (FSF) produce stocks (ST) for the economic model.
 
Similarly, food stocks in each category (FSTOCK) and an adjustment factor (FSF) produce stocks (ST) for the economic model.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq86.png http://www.du.edu/ifs/help/media/images/ag-module/ageq86.png]
+
<math>ST_{r,s=1}=FSF_{r}*∑_{f}(FSTOCK_{r,f,t}* WAP_{f,t=1} ) </math>
  
''where''
+
'''Where,'''
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq87.png http://www.du.edu/ifs/help/media/images/ag-module/ageq87.png]
+
<math>FSF_{r} = ST_{r,s=1}/(∑_{f}(FSTOCK_{r,f,t=1}* WAP_{f,t=1} ) )</math>
  
 
A similar translation is made for consumer spending on agricultural commodities, recognizing that not all crop demand is directly by consumers.
 
A similar translation is made for consumer spending on agricultural commodities, recognizing that not all crop demand is directly by consumers.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq88.png http://www.du.edu/ifs/help/media/images/ag-module/ageq88.png]
+
<math>CS_{r,s=1} = CSF_{r} *(FDEM_{r,t} * WAP_{f=1,t=1} +∑_{f=2,3}(AGDEM_{r,f,t}* WAP_{f,t=1} ) )</math>
  
''where''
+
'''Where'''
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq89.png http://www.du.edu/ifs/help/media/images/ag-module/ageq89.png]
+
<math>CSF_{r} = CS_{r,s=1} /(FDEM_{r,t=1}* WAP_{f=1,t=1} +∑_{f=2,3}(AGDEM_{r,f,t}* WAP_{f,t=1} ) )</math>
  
 
In the same fashion exports (AGX) and imports (AGM) from the agricultural model allow calculation of exports (XS) and imports (MS) for the economic model.
 
In the same fashion exports (AGX) and imports (AGM) from the agricultural model allow calculation of exports (XS) and imports (MS) for the economic model.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq90.png http://www.du.edu/ifs/help/media/images/ag-module/ageq90.png]
+
<math>XS_{r,s=1}= xsf_{r} *∑_f(AGX_{r,f,t}* WAP_{f,t=1} ) </math>
  
''where''
+
'''Where'''
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq91.png http://www.du.edu/ifs/help/media/images/ag-module/ageq91.png]
+
<math>xsf_{r}= XS_{r,s=1}/(∑_{f}(AGX_{r,f,t=1}* WAP_{f,t=1} ) )</math>
  
 
and
 
and
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq92.png http://www.du.edu/ifs/help/media/images/ag-module/ageq92.png]
+
<math>MS_{r,s=1} = msf_{r} *∑_f(AGX_{r,f,t}* WAP_{f,t=1} ) </math>
  
''where''
+
'''where'''
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq93.png http://www.du.edu/ifs/help/media/images/ag-module/ageq93.png]
+
<math>msf_{r}= MS_{r,s=1}/(∑_f(AGN_{r,f,t}* WAP_{f,t=1} ) )</math>
  
 
A check and, if necessary, adjustment is made ensure that the monetary values of imports and exports match up at the global level.
 
A check and, if necessary, adjustment is made ensure that the monetary values of imports and exports match up at the global level.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq94.png http://www.du.edu/ifs/help/media/images/ag-module/ageq94.png]
+
<math>XS_{r,s=1} = XS_{r,s=1} * ((∑_{r}(XS_{r,s=1} ) +∑_{r}(MS_{r,s=1} ) )⁄2)/(∑_{r}(XS_{r,s=1} ) )</math>
  
 
and
 
and
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq95.png http://www.du.edu/ifs/help/media/images/ag-module/ageq95.png]
+
<math>MS_{r,s=1}= MS_{r,s=1} *((∑_{r}(XS_{r,s=1} ) +∑_r(MS_{r,s=1} ) )⁄2)/(∑_{r}(MS_{r,s=1} ) )</math>
  
 
With respect to prices, the agriculture model passes to the economic model a value (PRI), which reflects the ratio of the current domestic crop price index to the initial world crop price index.
 
With respect to prices, the agriculture model passes to the economic model a value (PRI), which reflects the ratio of the current domestic crop price index to the initial world crop price index.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq96.png http://www.du.edu/ifs/help/media/images/ag-module/ageq96.png]
+
<math>PRI_{r,s=1} = FPRI_{r,f=1}/ WAP_{r,f=1,t=1} </math>
  
 
Finally, investment need (INAG) is passed to the economic model under the variable name IDS, category 1 (agriculture).
 
Finally, investment need (INAG) is passed to the economic model under the variable name IDS, category 1 (agriculture).
<div><br/>
 
----
 
<div>
 
[file:///C:/Users/Ara/Desktop/Agricultural%20Documentation%20v19_AG.docx#_ftnref1 [1]] s in the subscript represents economic sector. s = 1 is defined as the agriculture sector.
 
  
 
== Capital Dynamics ==
 
== Capital Dynamics ==
  
The economic model of IFs returns a (potentially) modified value of IDS, category 1, reflecting the total amount of capital available for agriculture. This value is assigned to the variable iaval, which overrides the value of INAG calculated earlier (earlier it was basically investment demand; after return from the economic model it becomes investment supply).<sup>[http://www.du.edu/ifs/help/understand/agriculture/equations/capital.html#footnote [1]] </sup> The agriculture model divides the investment available for agriculture (iaval) into investment for cropland development and investment for other agriculture capital. The coefficient IALK indicates the portion going to cropland development.
+
The economic model of IFs returns a (potentially) modified value of IDS, category 1, reflecting the total amount of capital available for agriculture. This value is assigned to the variable IAval, which overrides the value of INAG calculated earlier (earlier it was basically investment demand; after return from the economic model it becomes investment supply).<ref>Fs does have a global parameter agon that can be used to break the link between the agriculture and economic model, in which case INAG is not overwritten. This is done by setting agon to a value less than 0.5. Doing so treats the agriculture model as a partial equilibrium model rather than a general equilibrium model.</ref>&nbsp;The agriculture model divides the investment available for agriculture (IAval) into investment for cropland development and investment for other agriculture capital. The coefficient IALK indicates the portion going to cropland development.
  
 
IALK is set to a default value of 0.25 for all countries in the pre-processor. In forecast years, IALK changes from this initial value depending on change in the ratio of return on land (RETR) to return on capital (RETK).
 
IALK is set to a default value of 0.25 for all countries in the pre-processor. In forecast years, IALK changes from this initial value depending on change in the ratio of return on land (RETR) to return on capital (RETK).
Line 926: Line 1,058:
 
IFs calculates the return rate on land as the crop yield (YL) in the first year divided by the current cost of developing a unit of cropland (CLD).
 
IFs calculates the return rate on land as the crop yield (YL) in the first year divided by the current cost of developing a unit of cropland (CLD).
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq97.png http://www.du.edu/ifs/help/media/images/ag-module/ageq97.png]
+
<math>RETLD_{r} = YL_{r,t=1}/ CLD_{r,t} </math>
  
The return on capital depends on the difference between the hypothetical level of crop yield (HYL) that could be obtained from an additional unit investment in agricultural capital and the current crop yield. Recalling how crop yield is estimated, the hypothetical crop yield is given as
+
The return on capital depends on the difference between the hypothetical level of crop yield (HYL) that could be obtained from an additional unit investment in agricultural capital and the crop yield without that increment (CompYl). Recalling how crop yield is estimated, the hypothetical crop yield is given as
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq98.png http://www.du.edu/ifs/help/media/images/ag-module/ageq98.png]
+
<math>HypothYl_{r} = cD_{r} * agtec_{r} *(KAG_{r+1})^( ALPHA_{r} )*(labagi_{r} )^((1-ALPHA_{r} ) )* satk_{r}</math> <math> CompYl_{r} = cD_{r} * agtec_{r} *(KAG_{r} )^(ALPHA_{r} )*(labagi_{r} )^((1-ALPHA_{r} ) )* satk_{r}</math>
  
 
and the return on capital is given as
 
and the return on capital is given as
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq99.png http://www.du.edu/ifs/help/media/images/ag-module/ageq99.png]
+
<math>RETCap_{r} = LD_{r,l=1} *(HypothYLl_{r}- CompYl_{r} )</math>
  
 
The ratio of the return to land to the return to capital (RETRAT) is given as
 
The ratio of the return to land to the return to capital (RETRAT) is given as
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq100.png http://www.du.edu/ifs/help/media/images/ag-module/ageq100.png]
+
<math>RETRAT_{r} = RETLD_{r}/ RETCap_{r} </math>
  
 
The adjustment of IALK uses the same first and second order adjustment mechanism that we have seen before with the ADJSTR function. Here the ‘target’ level is the ratio of the return to land to the return to capital in the first year.
 
The adjustment of IALK uses the same first and second order adjustment mechanism that we have seen before with the ADJSTR function. Here the ‘target’ level is the ratio of the return to land to the return to capital in the first year.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq101.png http://www.du.edu/ifs/help/media/images/ag-module/ageq101.png]
+
<math>IALK_{r,t+1} = IALK_{r,t=1} *(1+(RETRAT_{r}-RETRAT_{r,t=1}/1))^{eliasp1}*(1+(RETRAT_{r}-RETRAT_{r,t-1}/1))^{eliasp2}</math>
  
''where''
+
'''where,'''
  
'''''eliasp1'' ''' and '''''eliasp2'' ''' are global parameters
+
'''''eliasp1''' and '''eliasp2''' are global parameters''
  
Two final checks are made on the value of IALK. First, it is not allowed to exceed a value related to the cost of replacing depreciated investment in land
+
Two final checks are made on the value of IALK. First, it is not allowed to exceed a value related to the cost of replacing depreciated investment in land and bringing a portion of grazing or forested land into production.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq102.png http://www.du.edu/ifs/help/media/images/ag-module/ageq102.png]
+
<math>IALK_{r,t+1} ≤((0.04* LD_{r,l=3} +0.04* LD_{r,l=4} +dkl* LD_{r,l=1} )* CLD_{r})/ IAval_{r} </math>
  
 
Second, IALK is bound between 0.1 and 0.8.
 
Second, IALK is bound between 0.1 and 0.8.
  
Finally the model updates agricultural capital (KAG) for the next year by subtracting depreciation as represented by agricultural capital lifetime ('''''lks'' '''), adding the residual (non-land) investment, and adjusting for any civilian damage from warfare (CIVDM – see international politics model documentation).
+
Finally the model updates agricultural capital (KAG) for the next year by subtracting depreciation as represented by agricultural capital lifetime ('''lks'''), adding the residual (non-land) investment, and adjusting for any civilian damage from warfare (CIVDM – see international politics model documentation).
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq103.png http://www.du.edu/ifs/help/media/images/ag-module/ageq103.png]
+
<math>KAG_{r,t+1} = KAG_{r,t}- KAG_{r,t} /lks_{s=1} + IAval_{r}*(1-IALK_{r,t+1} )*(1- CIVDM_{r})</math>
 
+
[file:///C:/Users/Ara/Desktop/Agricultural%20Documentation%20v19_AG.docx#_ftnref1 [1]]IFs does have a global parameter '''''agon'' ''' that can be used to break the link between the agriculture and economic model, in which case INAG is not overwritten. This is done by setting '''''agon'' ''' to a value less than 0.5. Doing so treats the agriculture model as a partial equilibrium model rather than a general equilibrium model.&nbsp;
+
  
 
== Land Dynamics ==
 
== Land Dynamics ==
  
Land in IFs is divided into five categories—crop, grazing, forest, urban, and other land. Historical data on total land area (LDTot), crop land (LD<sub>l=1</sub>), grazing land (LD<sub>l=2</sub>), forest land (LD<sub>l=3</sub>), and other land (LD<sub>l=4</sub>) are taken from FAO data. Historical data on urban land (LD<sub>l=5</sub>) is taken from WRI. A few adjustments to the historical data are made in the pre-processor.
+
&nbsp;Land in IFs is divided into five categories—crop, grazing, forest, urban, and other land. Historical data on total land area (LDTot), crop land (LD<sub>l=1</sub>), grazing land (LD<sub>l=2</sub>), forest land (LD<sub>l=3</sub>), and other land (LD<sub>l=4</sub>) are taken from FAO data. Historical data on urban land (LD<sub>l=5</sub>) is taken from WRI.
 +
 
 +
==== Pre-processor and first year ====
  
*Cropland is not allowed to exceed total crop production divided by 14, which places an effective limit on yield of 14 tons per hectare.
+
A few adjustments to the historical data are made in the pre-processor.
*Grazing land, forest land, and other land are bound from below to be at least 1000 hectares.
+
 
 +
*In the pre-processor total production of food is reconciled with the total trade. In cases where, demand is greater than domestic supply of crops, crop production is increased to reconcile demand with supply of food production. Crop land is also increased proportionately.&nbsp;
 
*If urban land is more than three quarters the area of other land, land is shifted from urban to other land
 
*If urban land is more than three quarters the area of other land, land is shifted from urban to other land
 +
*If no data is available for crop land, the same is set to 30 percent of total land area. If no data is available for grazing land, same is set to 5 percent of total land area. If no data is available for other land, same is set to 30 percent of total land area.
  
 
After these changes, total land area is recomputed as the sum of the area of the individual land categories.
 
After these changes, total land area is recomputed as the sum of the area of the individual land categories.
  
The pre-processor also reads in a value for potentially arable land (landarablepot), which affects the amount of potential cropland in the model.
+
The pre-processor also reads in a value for potentially arable land ('''landarablepot'''), which affects the amount of potential cropland in the model. The share of agricultural capital going to land (IALK) is set to 0.25 in the pre-processor.
  
One final variable is estimated related to land in the pre-processor. This is the target rate of growth of cropland (tgrld). When data is available, this is currently estimated as the growth rate of cropland between the years 1992 and 2001.
+
One final parameter is estimated related to land in the pre-processor. This is the target rate of growth of cropland ('''tgrld'''). When data is available, this is currently estimated as the growth rate of cropland between the year 2015 and the year 2005.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq104.png http://www.du.edu/ifs/help/media/images/ag-module/ageq104.png]
+
<math>tgrld_{r} =(LD_{r,l=1,yr=2015}/LD_{r,l=1,yr=2005} )^{1⁄10}-1</math>
  
<span>When no data are available for cropland in either 1992 or 2001, the target rate of growth of cropland is estimated as a function of average income</span>
+
When no data are available for cropland in either 2015 or 2005, the target rate of growth of cropland is estimated as a function of average income
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq105.png http://www.du.edu/ifs/help/media/images/ag-module/ageq105.png]
+
<math>tgrld_{r} =0.009-0.011*MIN(1,GDPPCP_{r}/30)</math>
  
<span>with a maximum growth rate given as a function of cropland as a share of total land</span>
+
with a maximum growth rate given as a function of cropland as a share of total land
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq106.png http://www.du.edu/ifs/help/media/images/ag-module/ageq106.png]
+
<math>tgrld_{r} ≤ tmaxgrow_{r} =0.015-0.01*MIN(1,0.5* LD_{r,l=1}/LDTot_{r} )</math>
  
 
Finally, this target growth rate is restricted to fall between -0.003 and +0.01.
 
Finally, this target growth rate is restricted to fall between -0.003 and +0.01.
Line 988: Line 1,122:
 
In the first year, IFs estimates an initial unit cost of cropland development (CLD) as
 
In the first year, IFs estimates an initial unit cost of cropland development (CLD) as
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq107.png http://www.du.edu/ifs/help/media/images/ag-module/ageq107.png]
+
<math>CLD_{r,t=1}=(IDS_{r,s=1,t=1} * IALK_{r,t=1})/(LD_{r,l=1,t=1}*(dkl+tgrld_{r} ) )</math>
  
''where''
+
'''where,'''
  
 
IDS is the total investment in agriculture
 
IDS is the total investment in agriculture
Line 996: Line 1,130:
 
IALK is the share of agricultural investment going to cropland development
 
IALK is the share of agricultural investment going to cropland development
  
'''dkl''' is a global parameter indicating the depreciation rate of investment in cropland, essentially a maintenance cost for existing cropland
+
'''''dkl''' is a global parameter indicating the depreciation rate of investment in cropland, essentially a maintenance cost for existing cropland''
  
''tgrld is the target growth rate for cropland''
+
'''''tgrld''' is the target growth rate for cropland''
  
A related factor (SCLDF), to be used in determining the cost of land development in future years, is also calculated in the first year
+
A related factor (SCLdF), to be used in determining the cost of land development in future years, is also calculated in the first year
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq108.png http://www.du.edu/ifs/help/media/images/ag-module/ageq108.png]
+
<math>SCLdF_{r} = CLD_{r,t=1}/LD_{r,l=1,t=1} </math>
  
<span>IFs calculates changes in land use for the coming year as a result of four key dynamic processes. First, changes in urban land may result from income and population changes. Second, economic shifts related to investment, particularly in the agricultural sector, can affect the amount of cropland. Third, IFs there can be expansion or retirement of grazing land for undefined reasons. Finally, in certain scenarios, specific changes in forest land can result from policies related to issues such as conservation and environmental protection</span>
+
==== Forecast years ====
  
== Changes in Urban Land from Income and Population Changes ==
+
IFs calculates changes in land use for the coming year as a result of four key dynamic processes. First, changes in urban land may result from income and population changes. Second, economic shifts related to investment, particularly in the agricultural sector, can affect the amount of cropland. Third, IFs there can be expansion or retirement of grazing land for undefined reasons. Finally, in certain scenarios, specific changes in forest land can result from policies related to issues such as conservation and environmental protection.
  
Changes in urban land result from changes in population and income. IFs first estimates a predicted level of urban land (LandUrbanPred), which is then compared to current urban land. Any changes are assumed to affect all other land types proportionately, unless this leads to not enough land in a particular category. The assumptions about the drivers of the predicted level of urban land differ somewhat between countrie[[File:Changes in Urban land from Y and population changes.png|right|Changes in Urban land from Y and population changes.png]]s depending upon their state of development, as measured by average income, in the base year.
+
====== Changes in urban land from income and population changes ======
  
For initially not as well off countries, GDPPCP in the base year < 5, the predicted level of urban land (LandUrbanPred) is estimated as a function of population and income growth. The growth with income is based on an estimated relationship between income and urban land per capita (landurbanr) summarized in the figure on the right<sup>[http://www.du.edu/ifs/help/understand/agriculture/equations/land/urban.html#footnote [1]] </sup>.
+
Changes in urban land result from changes in population and income. IFs first estimates a predicted level of urban land (LandUrbanPred), which is then compared to current urban land. Any changes are assumed to affect all other land types proportionately, unless this leads to not enough land in a particular category. The growth with income is based on an estimated relationship between income and urban land per capita (LandUrbanR)
  
 
The predicted level of urban land (LandUrbanPred) is then given as
 
The predicted level of urban land (LandUrbanPred) is then given as
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq109.png http://www.du.edu/ifs/help/media/images/ag-module/ageq109.png]
+
<math>LandUrbanPred_{r} = LD_{r,l=4,t=1} *(POP_{r,t}/POP_{r,t=1} )*(LandUrbanR_{r,t}/LandUrbanR_{r,t=1} )</math>
 
+
For initially well off countries, GDPPCP in the base year > 5, the predicted level of urban land is estimated as a function of population change. If population increases from the base year, is assumed to be same as urban land in the base year. If population declines from the base year, the predicted urban land area is estimated to decline, but only half as much as the population decline
+
 
+
[http://www.du.edu/ifs/help/media/images/ag-module/ageq110.png http://www.du.edu/ifs/help/media/images/ag-module/ageq110.png]
+
  
 
The change in urban land (NUrbLD) is then calculated as
 
The change in urban land (NUrbLD) is then calculated as
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq111.png http://www.du.edu/ifs/help/media/images/ag-module/ageq111.png]
+
<math>NUrbLD_{r} = LandUrbanPred_{r} - LD_{r,l=4}</math>
  
 
Limits are placed on the change in urban land area. First, if urban land is growing, the amount of increase in a single year cannot exceed 1/100<sup>th</sup> of a variable that is related to the change in the non-urban share of all other land from the base year (NonUrbanShrR)
 
Limits are placed on the change in urban land area. First, if urban land is growing, the amount of increase in a single year cannot exceed 1/100<sup>th</sup> of a variable that is related to the change in the non-urban share of all other land from the base year (NonUrbanShrR)
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq112.png http://www.du.edu/ifs/help/media/images/ag-module/ageq112.png]
+
<math>NonUrbanShrR_{r} = (NonUrbanShr_{r,t}/NonUrbanShr_{r,t=1} )^{2}</math>
  
''where''
+
'''where,'''
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq113.png http://www.du.edu/ifs/help/media/images/ag-module/ageq113.png]
+
<math>NonUrbanShr_{r,t=1,t} =(∑_{l}LD_{r,l=1-4,t} )/(∑_{l}LD_{r,l=1-5,t} )</math>
  
Second, if urban land is declining, it is not permitted to fall below 10,000 hectares.&nbsp;Third, the changes are assumed to affect all other land categories proportionately.
+
Second, if urban land is declining, it is not permitted to fall below 10,000 hectares. Third, the changes in Urban land are assumed to affect all other land categories proportionately
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq114.png http://www.du.edu/ifs/help/media/images/ag-module/ageq114.png]
+
<math>Reduc_{r,l=1-4} = NUrbLD_{r} * LD_{r,l=1-4}/(∑_{l}LD_{r,l=1-4} )</math>
  
 
However, this is not allowed to result in the area for a given land category falling below 1,000 hectares. Thus, there may be a slight reduction in the amount of new urban land in certain cases.
 
However, this is not allowed to result in the area for a given land category falling below 1,000 hectares. Thus, there may be a slight reduction in the amount of new urban land in certain cases.
  
----
+
====== Changes in cropland due to investment and/or depreciation. ======
<div>
+
[file:///C:/Users/Ara/Desktop/Agricultural%20Documentation%20v19_AG.docx#_ftnref1 [1]] Equation is Urban land per Capita = 0.021 + 0.0039*GDPPCP when GDPPCP < 1.92 in the base year and Urban land per Capita = 0.01 + 0.0283*ln(GDPPCP) when GDPPCP >= 1.92 in the base year.
+
</div>
+
== Changes in Cropland due to Investment and/or Depreciation ==
+
  
 
The changes in cropland are driven by the economics of land. Specifically, they are a function of the profitability of cropland. Also, they are assumed to affect, at least directly, only the forest and the other land categories.
 
The changes in cropland are driven by the economics of land. Specifically, they are a function of the profitability of cropland. Also, they are assumed to affect, at least directly, only the forest and the other land categories.
Line 1,048: Line 1,174:
 
A maximum amount of cropland expansion each year (MaxLandExpansion) is fixed by the amount of forest land, the amount of other lands, the amount of potential arable land, and the existing amount of cropland. The maximum amount of expansion must be at least 2/100<sup>th</sup> of the existing cropland, but beyond that it cannot exceed either the total amount of forest and other land or the difference between 110% of the potential arable land (landarablepot) and current cropland.
 
A maximum amount of cropland expansion each year (MaxLandExpansion) is fixed by the amount of forest land, the amount of other lands, the amount of potential arable land, and the existing amount of cropland. The maximum amount of expansion must be at least 2/100<sup>th</sup> of the existing cropland, but beyond that it cannot exceed either the total amount of forest and other land or the difference between 110% of the potential arable land (landarablepot) and current cropland.
  
The change in the amount of cropland and the initially estimated share of agricultural investment going to cropland in the following year are computed differently depending upon the maximum amount of cropland expansion relative to the amount of existing cropland and the current level of average income in a country. Specifically, if the maximum amount of cropland expansion is less than 10 percent of existing cropland or if the average income in the country is greater than $10,000 (GDPPCP > 10), then it is assumed that there is no change in cropland (lddev = 0) and that no agricultural investment is targeted for cropland development (IALK = 0).
+
The change in the amount of cropland and the initially estimated share of agricultural investment going to cropland in the following year are computed differently depending upon the maximum amount of cropland expansion relative to the amount of existing cropland and the current level of average income in a country. Specifically, if the maximum amount of cropland expansion is less than 10 percent of existing cropland then it is assumed that there is no change in cropland (lddev = 0) and that no agricultural investment is targeted for cropland development (IALK = 0).
  
If neither of the conditions mentioned in the previous paragraph is met, i.e., if the country is not too wealthy and there is an ‘adequate’ amount of land for expanding cropland, the amount of change in cropland (lddev) is initially calculated as
+
If the condition mentioned in the previous paragraph is met, i.e., there is an ‘adequate’ amount of land for expanding cropland, the amount of change in cropland (lddev) is initially calculated as
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq115.png http://www.du.edu/ifs/help/media/images/ag-module/ageq115.png]
+
<math>LdDev_{r} =(((IAval_{r} * IALK_{r})/CLD_{r} )* ldcropm_{r})-(LD_{r,l=1}*dkl)</math>
  
''where''
+
'''where'''
  
iaval is the total amount of funds available for investment in agriculture
+
IAval is the total amount of funds available for investment in agriculture which is equal to IDS
  
 
IALK is the share of agricultural investment going to cropland development
 
IALK is the share of agricultural investment going to cropland development
Line 1,062: Line 1,188:
 
CLD is the unit cost of cropland development
 
CLD is the unit cost of cropland development
  
'''''dkl'' ''' is the depreciation rate of investment in cropland (essential a maintenance cost for existing cropland)
+
'''''dkl''' is the depreciation rate of investment in cropland (essential a maintenance cost for existing cropland)''
  
'''''ldcropm'' ''' is a country-specific multiplier that can be used to increase or decrease changes in cropland
+
'''''ldcropm''' is a country-specific multiplier that can be used to increase or decrease changes in cropland''
  
Note that this equation takes into account the need to maintain existing cropland. Also, at this point, the value of lddev is bound from below to ensure that it does not imply a greater than 10 percent decrease in existing cropland. For relatively poor countries (GDPPCP < 10), the constraint is even stricter. Specifically, IFs calls for a shift in funds to ensure that no cropland is lost. The desired shift in funds is given as
+
Note that this equation takes into account the need to maintain existing cropland. Also, at this point, the value of LdDev is bound from below to ensure that it does not imply a greater than 10 percent decrease in existing cropland. For relatively poor countries (GDPPCP < 10), the constraint is even stricter. Specifically, IFs calls for a shift in funds to ensure that no cropland is lost. The desired shift in funds is given as
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq116.png http://www.du.edu/ifs/help/media/images/ag-module/ageq116.png]
+
<math>DesShift_{r} =-CLD_{r} * LdDev_{r} </math>
  
 
The actual shift in funds is limited to 90 percent of the available funds, however, where the available funds are the investment in agriculture not initially designated for cropland development
 
The actual shift in funds is limited to 90 percent of the available funds, however, where the available funds are the investment in agriculture not initially designated for cropland development
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq117.png http://www.du.edu/ifs/help/media/images/ag-module/ageq117.png]
+
<math>Shift_r = MIN(0.9* IAval_{r} *(1-IALK_{r} ),DesShift_{r} )</math>
  
 
The value of lddev given the actual shift in funds is given as
 
The value of lddev given the actual shift in funds is given as
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq118.png http://www.du.edu/ifs/help/media/images/ag-module/ageq118.png]
+
<math>LdDev_{r} = LdDev_{r} + Shift_{r}/ CLD_{r} </math>
  
In addition, the share of investment in agriculture designated for cropland development is updated to be<sup>[http://www.du.edu/ifs/help/understand/agriculture/equations/land/crop.html#footnote [1]]</sup>
+
In addition, the share of investment in agriculture designated for cropland development is updated to be
<div>[http://www.du.edu/ifs/help/media/images/ag-module/ageq119.png http://www.du.edu/ifs/help/media/images/ag-module/ageq119.png]</div><div>
+
The changes in cropland are linked to changes in land in the forest and ‘other’ categories. The amount coming from/going to forests reflects the share of forest land relative to ‘other’ land, as well as the current level of development
+
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq120.png http://www.du.edu/ifs/help/media/images/ag-module/ageq120.png]
+
<math>IALK_{r}= IALK_{r}+ Shift_{r}/IAval_{r} </math>
  
''where''
+
The changes in cropland are linked to changes in land in the forest and ‘other’ categories. The amount coming from/going to forests reflects the share of forest land relative to ‘other’ land, as well as the current level of development. For countries with a GDP per capita higher than 15,000 dollars and where LdDev is less than 0, more is given back to forest land and the ForShrPar is set to 0.25.
  
ForShrPar is given by the function depicted below that&nbsp;
+
<math>LDDEVFor_{r}=LdDev_{r}* LD_{r,l=3}/(LD_{r,l=3} + LD_{r,l=4} )* ForShrPar_{r}</math>
  
[[File:Changes in cropland due to Investment and or Depreciation.png|center|Changes in cropland due to Investment and or Depreciation.png]]
+
'''where,'''
<div>
+
The solid line holds when land is being converted from forests to cropland (lddev > 0) and the dotted line holds when land is being converted from cropland to forests (lddev < 0). In either case, this implies that the less of the change is related to forest land than would be expected by its share. Two other qualifiers are that the changes in forest land (LDDEVFor) and the changes in ‘other’ land cannot exceed 90 percent of existing land in these categories and the shifts cannot result in either land category falling below 1,000 hectares. These limits feedback to the change in cropland, finally resulting in the following
+
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq121.png http://www.du.edu/ifs/help/media/images/ag-module/ageq121.png]
+
<br/>ForShrPar is given by the function depicted below;
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq122.png http://www.du.edu/ifs/help/media/images/ag-module/ageq122.png]
+
[[File:Changes in cropland due to Investment and or Depreciation.png|frame|center|Changes in crop land due to investment and or depreciation]]
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq123.png http://www.du.edu/ifs/help/media/images/ag-module/ageq123.png]
+
The solid line holds when land is being converted from forests to cropland (lddev > 0) and the dotted line holds when land is being converted from cropland to forests (LdDev < 0). In either case, this implies that the less of the change is related to forest land than would be expected by its share.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq124.png http://www.du.edu/ifs/help/media/images/ag-module/ageq124.png]
+
Two other qualifiers are that the changes in forest land (LDDEVFor) and the changes in ‘other’ land cannot exceed 90 percent of existing land in these categories and the shifts cannot result in either land category falling below 1,000 hectares. These limits feedback to the change in cropland, finally resulting in the following
 +
 
 +
<math>LdDev_{r}= LDDEVFor_{r} + LDDEVOth_{r}</math>
 +
 
 +
<math>LD_{r,l=1}= LD_{r,l=1}+ LdDev_{r}</math>
 +
 
 +
<math>LD_{r,l=3}= LD_{r,l=3} - LDDEVFor_{r} </math>
 +
 
 +
<math>LD_{r,l=4}= LD_{r,l=4}- LDDEVOth_{r} </math>
  
 
Turning back to the future cost of cropland development, this is estimated differently based only on whether there is ‘adequate’ room for cropland land expansion, defined as when the maximum amount of cropland expansion is greater than 10 percent of existing cropland. If this is the case, the future price of cropland is estimated as
 
Turning back to the future cost of cropland development, this is estimated differently based only on whether there is ‘adequate’ room for cropland land expansion, defined as when the maximum amount of cropland expansion is greater than 10 percent of existing cropland. If this is the case, the future price of cropland is estimated as
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq125.png http://www.du.edu/ifs/help/media/images/ag-module/ageq125.png]
+
<math>CLD_{r,t+1}= CLD_{r,t=1}* LD_{r,l=1,t}/ LD_{r,l=1,t=1} * RemRat_{r}^{0.2}</math>
  
''where''
+
'''where'''
  
 
RemRat is the ratio of the maximum land for expansion in the first year to the maximum land for expansion in the current year, with a maximum value of 10
 
RemRat is the ratio of the maximum land for expansion in the first year to the maximum land for expansion in the current year, with a maximum value of 10
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq126.png http://www.du.edu/ifs/help/media/images/ag-module/ageq126.png]
+
<math>RemRat_{r} = MaxLandExpansion_{r,t=1}/MAX(0.1* MaxLandExpansion_{r,t=1},MaxLandExpansion_{r,t} ) </math>
  
 
This basically states that the price of cropland development grows linearly with growth in cropland and exponentially with declines in available land for cropland expansion.
 
This basically states that the price of cropland development grows linearly with growth in cropland and exponentially with declines in available land for cropland expansion.
  
Alternatively, if the maximum amount of cropland expansion in a given year is less than or equal to10 percent of existing cropland, the cost of bringing new land under cultivation is assumed to grow at the maximum of either 2 percent per year from the cost in the first year or the growth of cropland from the first year. Furthermore, it is not allowed to decline. Thus,
+
Alternatively, if the maximum amount of cropland expansion in a given year is less than or equal to10 percent of existing cropland, the cost of bringing new land under cultivation is assumed to grow at the maximum of either 2 percent per year from the cost in the first year or the growth of cropland from the first year. Furthermore, it is not allowed to decline. Thus
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq127.png http://www.du.edu/ifs/help/media/images/ag-module/ageq127.png]
+
<math>〖CLD〗_{r,t+1}=MAX(CLD_{r,t}, CLD_{r,t=1} * LD_{r,l=1,t}/ LD_{r,l=1,t=1} , CLD_{r,t=1}*(1+2*(t-2015)/100))</math>
</div>
+
 
----
+
====== Changes in grazing land ======
<div>
+
[file:///C:/Users/Ara/Desktop/Agricultural%20Documentation%20v19_AG.docx#_ftnref1 [1]] Given that IALK represents a share value, it is also bound to be <= 1.
+
</div><header><hgroup>
+
== Changes in Grazing Land ==
+
  
</hgroup></header> IFs assumes that relatively poor countries (GDPPCP < 10) will continue to develop additional grazing land, whereas relatively rich countries (GDPPCP > 15) will retire grazing land. No change is expected in countries with average income between $10,000 and $15,000. The annual expansion of grazing land in poor countries is initially estimated as 0.5 percent of the amount of grazing land in the first year. The retirement of grazing land in richer countries is initially estimated as 0.2 percent of current grazing land.
+
IFs assumes that relatively poor countries (GDPPCP &lt; 10) will continue to develop additional grazing land, whereas relatively rich countries (GDPPCP &gt; 15) will retire grazing land. No change is expected in countries with average income between $10,000 and $15,000. The annual expansion of grazing land in poor countries is initially estimated as 0.5 percent of the amount of grazing land in the first year. The retirement of grazing land in richer countries is initially estimated as 0.2 percent of current grazing land.
  
As with cropland, any changes in grazing land will be compensated by changes in forest and ‘other’ land. Each category is initially assumed to be affected proportionately, e.g.,&nbsp;
+
As with cropland, any changes in grazing land will be compensated by changes in forest and ‘other’ land. Each category is initially assumed to be affected proportionately, e.g.,
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq127.png http://www.du.edu/ifs/help/media/images/ag-module/ageq127.png]
+
<math>ForestShr_{r}= LD_{r,l=3}/(LD_{r,l=3} + LD_{r,l=4} )</math>
  
 
Unlike the case for changes in cropland, there is no adjustment to the forest share as a function of income or the direction of change in grazing land. As with the changes in cropland, however, the changes in forest and ‘other’ land cannot exceed 90 percent of existing land in these categories and the shifts cannot result in either land category falling below 1,000 hectares. Again, these limits feed back to the change in grazing land.
 
Unlike the case for changes in cropland, there is no adjustment to the forest share as a function of income or the direction of change in grazing land. As with the changes in cropland, however, the changes in forest and ‘other’ land cannot exceed 90 percent of existing land in these categories and the shifts cannot result in either land category falling below 1,000 hectares. Again, these limits feed back to the change in grazing land.
  
== Change in Forest Land due to a Policy Choice ==
+
====== Change in forest land due to a policy choice ======
  
The model user can also force the land in forest area to increase or decrease at the expense of crop and grazing land via a forest multiplier '''''forestm'' '''. The change in forestland, LDSHIFT, is bound. In the case of an increase, i.e., '''''forestm'' ''' > 1, the amount of added land is limited to 20 percent of crop and grazing land; in the case of a decrease, i.e., '''''forestm'' ''' < 1, the amount of forest land removed is limited to 20 percent of existing forest land.
+
The model user can also force the land in forest area to increase or decrease at the expense of crop and grazing land via a forest multiplier '''forestm'''. The change in forestland, LDSHIFT, is bound. In the case of an increase, i.e., '''forestm'''> 1, the amount of added land is limited to 20 percent of crop and grazing land; in the case of a decrease, i.e., '''forestm'''< 1, the amount of forest land removed is limited to 20 percent of existing forest land.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq128.png http://www.du.edu/ifs/help/media/images/ag-module/ageq128.png]
+
<math>- LD_{r,l=3}/5< LANDSHIFT_{r} <(LD_{r,l=1}+ LD_{r,l=2})/5</math>
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq129.png http://www.du.edu/ifs/help/media/images/ag-module/ageq129.png]
+
<math>LD_{r,l=3}= LD_{r,l=3}+ LANDSHIFT_{r}</math>
  
 
The amount of land taken from cropland and grazing land is proportional to the amount of each.
 
The amount of land taken from cropland and grazing land is proportional to the amount of each.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq130.png http://www.du.edu/ifs/help/media/images/ag-module/ageq130.png]
+
<math>CropShare_{r}=LD_{r,l=1}/(LD_{r,l=1}+ LD_{r,l=2} )</math>
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq131.png http://www.du.edu/ifs/help/media/images/ag-module/ageq131.png]
+
<math>LD_{r,l=1}= LD_{r,l=1}+LANDSHIFT_{r}* CROPSHARE_{r}</math>
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq132.png http://www.du.edu/ifs/help/media/images/ag-module/ageq132.png]
+
<math>LD_{r,l=2}= LD_{r,l=2}+ LANDSHIFT_{r} *(1-CROPSHARE_{r})</math>
  
== Final Checks and Renormalization of Land Use ==
+
====== Final checks and renormalization of land use ======
  
 
Two final adjustments are made to the land area values to clean up any quirks that might have be introduced in the previous processes. First, the values for each category are bound between one thousand and ten billion hectares. Second, the values are normalized so that the sum of the categories equals the total amount of land.
 
Two final adjustments are made to the land area values to clean up any quirks that might have be introduced in the previous processes. First, the values for each category are bound between one thousand and ten billion hectares. Second, the values are normalized so that the sum of the categories equals the total amount of land.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq133.png http://www.du.edu/ifs/help/media/images/ag-module/ageq133.png]
+
<math>〖LD〗_{r,l=1-5,t+1}=LD{r,l=1-5} * LD_{r,l=1-5}/(∑_{l}LD_{r,l=1-5} )</math>
  
 
Finally, a value for world forest area (WFORST) is calculated at the end of this process by summing forestland area across all countries.
 
Finally, a value for world forest area (WFORST) is calculated at the end of this process by summing forestland area across all countries.
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq134.png http://www.du.edu/ifs/help/media/images/ag-module/ageq134.png]
+
<math>WFORST_{t+1}=∑_{l}LD_{r,l=3} </math>
  
 
== Livestock Dynamics ==
 
== Livestock Dynamics ==
  
In addition to capital and land, the other "stock" or "level" variable with important temporal dynamics is the livestock herd (LVHERD). The size of the herd size (LVHERD) in the first year is calculated simply as the base year value of meat production divided by the slaughter rate, '''''slr'' '''.<sup>[http://www.du.edu/ifs/help/understand/agriculture/equations/livestock.html#footnote [1]]</sup>
+
In addition to capital and land, the other "stock" or "level" variable with important temporal dynamics is the livestock herd (LVHERD).
  
The growth of the herd size in future years is driven by changes in meat demand at both the national and global levels, changes in meat stocks at both the national and global levels, and changes in grazing land at the national level.
+
==== Pre-processor and first year ====
  
At the national level, herd sizes for the next year are first estimated as a function of changes in national meat demand, national meat stocks, national grazing land, and an adjustment factor related to national meat stocks:
+
In the pre-processor, as explained earlier, the values for total meat production and animal meat production are initialized. From these values, IFs calculates the value for livestock by dividing the total animal meat by the slaughter rate ('''slr''')
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq135.png http://www.du.edu/ifs/help/media/images/ag-module/ageq135.png]
+
==== Forecast years ====
  
The forecasts of meat demand (AGDEM<sub>r,f=2</sub>) and grazing land (LD<sub>r,l=2</sub>) are described in the [http://www.du.edu/ifs/help/understand/agriculture/equations/demand/meat.html Meat Demand] section&nbsp;and the [http://www.du.edu/ifs/help/understand/agriculture/equations/land/grazing.html Changes in Grazing Land] section, respectively. The national stock adjustment factors are calculated using the same ADJSTR function as used to adjust crop yields. In this case, the desired stock level is given as agdstltimes the sum of national meat demand (AGDEM<sub>r,f=2</sub>) and&nbsp; national meat production (AGP<sub>r,f=2</sub>). As mentioned previously, agdstl is set to be 1.5 times '''''dstl'' ''', which is a global parameter that can be adjusted by the user. Also, the two parameters that determine how much of an adjustment there is due to changes in stock levels from the previous years and the difference between the actual and desired stock levels are hard coded with values of -0.05 and -0.1, respectively.
+
The value of LVHERD is calculated by using pre-production loss meat production (AGPppl), adjusting the same for animal products produced (AGPMILKEGGS). This gives total animal meat production. The animal meat production is then divided by the slaughter rate '''slr<ref>For details on the base year value of meat production, which is based on historical data related to production, imports, exports, and assumptions about expected meat consumption and production losses, see the description of agricultural data initialization in the pre-processor.</ref>'''
  
At the global level, herd sizes for the next year are estimated as a function of changes in global meat demand, global meat stocks, and an adjustment factor related to global meat stocks:
+
<math>LVHERD_{r}=(AGPppl_{r,f=2}- AGPMILKEGGS_{r})/slr</math>
<div>
+
[http://www.du.edu/ifs/help/media/images/ag-module/ageq136.png http://www.du.edu/ifs/help/media/images/ag-module/ageq136.png]
+
</div>
+
<span>The global stock adjustment factor is calculated in the same manner as the national stock adjustment factors, only using global values for actual and desired stocks.</span>
+
  
<span>Finally, the herd sizes for the next year are normalized so that the sum of the national values equals the global value:</span>
+
== Water Dynamics ==
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq137.png http://www.du.edu/ifs/help/media/images/ag-module/ageq137.png]
+
Water use begins with data on total water withdrawals from FAO Aquastat.&nbsp; These are divided by the size of the population to get an estimate of water use per capita.
  
[file:///C:/Users/Ara/Desktop/Agricultural%20Documentation%20v19_AG.docx#_ftnref1 [1]] For details on the base year value of meat production, which is based on historical data related to production, imports, exports, and assumptions about expected meat consumption and production losses, see the description of agricultural data initialization in the pre-processor.
+
In future years, water use per capita is forecast to increase in parallel with crop production per capita.&nbsp; Specifically, an expected level of water use per capita as a function of crop production per capita (see figure below) is calculated for crop production in the current year (CropPC) and crop production in the first year (CropPCI).&nbsp; The ratio of these values is multiplied by the water use per capita in the first year (WatUsePCI) to get water use per capita in the current year (WatUsePC).&nbsp; This is multiplied by population (POP) to get total water use (WATUSE)
  
== Water Dynamics ==
+
<math>WatUsePC_{r}= WatUsePCI_{r}*f(CropPC_{r} )/f(CropPCI_{r} </math>
  
<span>Water use begins with data on total water withdrawals from FAO Aquastat.&nbsp; These are divided by the size of the po</span>[[File:Water dynamics.png|right|Water dynamics.png]]<span>pulation to get an estimate of water use per capita.</span>
+
<math>WATUSE_{r}= WatUsePC_{r} * POP_{r}</math>
  
<span>In future years, water use per capita is forecast to increase in parallel with crop production per capita.&nbsp; Specifically, an expected level of water use per capita as a function of crop production per capita (see figure below) is calculated for crop production in the current year (CropPC) and c</span><span>rop production in the first year (CropPCI).&nbsp; The ratio of these values is multiplied by the water use per capita in the first year (WatUsePCI) to get water use per capita in the current year (WatUsePC).&nbsp; This is multiplied by population (POP) to get total water use (WATUSE).</span>
+
[[File:Water dynamics.png|Water Use per capita compared to GDP per capita]]
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq138.png http://www.du.edu/ifs/help/media/images/ag-module/ageq138.png]
+
= Data Tables read in Agricultural Pre-Processor – DATAGRI.BAS =
  
[http://www.du.edu/ifs/help/media/images/ag-module/ageq139.png http://www.du.edu/ifs/help/media/images/ag-module/ageq139.png]
+
{| border="1" cellspacing="0" cellpadding="0" width="0"
</div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><br/></div></div><br/>
+
|-
 +
| nowrap="nowrap" style="width:234px;height:35px;" |
 +
'''Table'''
 +
 
 +
| nowrap="nowrap" style="width:142px;height:35px;" |
 +
'''Definition'''
 +
 
 +
| nowrap="nowrap" style="width: 212px; height: 35px;" |
 +
'''Original Source'''
 +
 
 +
| style="width: 406px; height: 35px;" |
 +
'''Variable to which series relates in PP/How the series is used in the PP'''
 +
 
 +
|-
 +
| style="width:234px;height:20px;" |
 +
SeriesLandArea
 +
 
 +
| style="width:142px;height:20px;" |
 +
Land Area
 +
 
 +
| style="width: 212px; height: 20px;" |
 +
WDI
 +
 
 +
| style="width: 406px; height: 20px;" |
 +
LandArea
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesMalnChil%WeightWB
 +
 
 +
| style="width:142px;height:69px;" |
 +
Percentage of children under 5 malnourished based on weight; US benchmark
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
World Health Organization.
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Malnourished children
 +
 
 +
|-
 +
| style="width:234px;height:35px;" |
 +
SeriesMalnPop%WB
 +
 
 +
| style="width:142px;height:35px;" |
 +
Percentage of population malnourished
 +
 
 +
| style="width: 212px; height: 35px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 35px;" |
 +
Malnourished population
 +
 
 +
|-
 +
| style="width:234px;height:20px;" |
 +
SeriesLandCrop
 +
 
 +
| style="width:142px;height:20px;" |
 +
Land, crop
 +
 
 +
| style="width: 212px; height: 20px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 20px;" |
 +
LDCrop
 +
 
 +
|-
 +
| style="width:234px;height:20px;" |
 +
SeriesLandForest
 +
 
 +
| style="width:142px;height:20px;" |
 +
Land, forest
 +
 
 +
| style="width: 212px; height: 20px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 20px;" |
 +
LdFor
 +
 
 +
|-
 +
| style="width:234px;height:20px;" |
 +
SeriesLandGrazing
 +
 
 +
| style="width:142px;height:20px;" |
 +
Land, grazing
 +
 
 +
| style="width: 212px; height: 20px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 20px;" |
 +
LdGraz
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishAquaProdAqAnimalsFSJ
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Aquatic Animals Aquaculture Production (tonnes) from FishstatJ
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO&nbsp; Global Aquaculture Production Quantity data
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Break down data from FAO into aquaculture and catch stat using data from fish stat j
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishAquaProdAqPlantsFSJ
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Aquatic Plants Aquaculture Production (tonnes) from FishstatJ
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO&nbsp; Global Aquaculture Production Quantity data
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Break down data from FAO into aquaculture and catch stat using data from fish stat j
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishAquaProdCephalopodsFSJ
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Cephalopods Aquaculture Production (tonnes) from FishstatJ
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO&nbsp; Global Aquaculture Production Quantity data
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Break down data from FAO into aquaculture and catch stat using data from fish stat j
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishAquaProdCrustaceansFSJ
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Crustaceans Aquaculture Production (tonnes) from FishstatJ
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO&nbsp; Global Aquaculture Production Quantity data
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Break down data from FAO into aquaculture and catch stat using data from fish stat j
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishAquaProdDemersalFSJ
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total&nbsp; Demersal Aquaculture Production (tonnes) from FishstatJ
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO&nbsp; Global Aquaculture Production Quantity data
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Break down data from FAO into aquaculture and catch stat using data from fish stat j
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishAquaProdFreshwaterFSJ
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Freshwater Aquaculture Production (tonnes) from FishstatJ
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO&nbsp; Global Aquaculture Production Quantity data
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Break down data from FAO into aquaculture and catch stat using data from fish stat j
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishAquaProdMarineFSJ
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Marine Aquaculture Production (tonnes) from FishstatJ
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO&nbsp; Global Aquaculture Production Quantity data
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Break down data from FAO into aquaculture and catch stat using data from fish stat j
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishAquaProdMolluscsFSJ
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Molluscs Aquaculture Production (tonnes) from FishstatJ
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO&nbsp; Global Aquaculture Production Quantity data
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Break down data from FAO into aquaculture and catch stat using data from fish stat j
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishAquaProdPelagicFSJ
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Pelagic Aquaculture Production (tonnes) from FishstatJ
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO&nbsp; Global Aquaculture Production Quantity data
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Break down data from FAO into aquaculture and catch stat using data from fish stat j
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishCalPerCapPerDayAqAnimalsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Aquatic Animals used for Calories/capita/day (kcal/capita/day)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishCalPerCapPerDayAqPlantsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Aquatic Plants used for Calories/capita/day (kcal/capita/day)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishCalPerCapPerDayBodyOilFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Body Oil used for Calories/capita/day (kcal/capita/day)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishCalPerCapPerDayLiverOilFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Fish Liver Oil used for Calories/capita/day (kcal/capita/day)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishCatchProdAqAnimalsFSJ
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Aquatic Animals Catch Production (tonnes) from FishstatJ
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO&nbsp; Global Aquaculture Production Quantity data
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Break down data from FAO into aquaculture and catch stat using data from fish stat j
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishCatchProdAqPlantsFSJ
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Aquatic Plants Catch Production (tonnes) from FishstatJ
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO&nbsp; Global Aquaculture Production Quantity data
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Break down data from FAO into aquaculture and catch stat using data from fish stat j
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishCatchProdCephalopodsFSJ
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Cephalopods Capture Production from FishstatJ
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO&nbsp; Global Aquaculture Production Quantity data
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Break down data from FAO into aquaculture and catch stat using data from fish stat j
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishCatchProdCrustaceansFSJ
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Crustaceans Capture Production from FishstatJ
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO&nbsp; Global Aquaculture Production Quantity data
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Break down data from FAO into aquaculture and catch stat using data from fish stat j
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishCatchProdDemersalFSJ
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Demersal Capture Production from FishstatJ
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO&nbsp; Global Aquaculture Production Quantity data
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Break down data from FAO into aquaculture and catch stat using data from fish stat j
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishCatchProdFreshwaterFSJ
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Freshwater Capture Production from FishstatJ
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO&nbsp; Global Aquaculture Production Quantity data
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Break down data from FAO into aquaculture and catch stat using data from fish stat j
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishCatchProdMarineFSJ
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Marine Capture Production from FishstatJ
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO&nbsp; Global Aquaculture Production Quantity data
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Break down data from FAO into aquaculture and catch stat using data from fish stat j
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishCatchProdMolluscsFSJ
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Molluscs Capture Production from FishstatJ
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO&nbsp; Global Aquaculture Production Quantity data
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Break down data from FAO into aquaculture and catch stat using data from fish stat j
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishCatchProdPelagicFSJ
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Pelagic Capture Production (tonnes) from Fishstatj
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO&nbsp; Global Aquaculture Production Quantity data
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Break down data from FAO into aquaculture and catch stat using data from fish stat j
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishDomesticSupplyAqPlantsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Domestic Supply Quantity of Aquatic Plants (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishDomesticSupplyBodyOilFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Domestic Supply Quantity ofl Body Oil (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishDomesticSupplyLiverOilFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Domestic Supply Quantity of Fish Liver Oil (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishDomesticSupplyMealFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Domestic Supply Production of Fish Meal (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishExportsAqPlantsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Aquatic Plants Exports (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishExportsBodyOilFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Body Oil Exports (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishExportsLiverOilFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Fish Liver Oil EXports (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishExportsMealFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Fish Meal Exports (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishFoodSupplyPerCapPerDayAqAnimalsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Aquatic Animals used for Food Supply/capita/day (g/capita/day)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishFoodSupplyPerCapPerDayAqPlantsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Aquatic Plants used for Food Supply/capita/day (g/capita/day)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishFoodSupplyPerCapPerDayBodyOilFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Body Oil used for Food Supply/capita/day (g/capita/day)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishFoodSupplyPerCapPerDayLiverOilFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Fish Liver Oil used for Food Supply/capita/day (g/capita/day)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishImportsAqPlantsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Aquatic Plants Imports (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishImportsBodyOilFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Body Oil Imports (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishImportsLiverOilFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Fish Liver Oil Imports (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishImportsMealFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Fish Meal Imports (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishProdAqPlantsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Production Quantity of Aquatic Plants (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishProdBodyOilFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Production Quantity of (Fish) Body Oil (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishProdLiverOilFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Production Quantityt of Fish Liver Oil (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishProdMealFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Production Quantity of Fish Meal (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishProteinPerCapPerDayAqAnimalsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Aquatic Animals used for Protein/capita/day (g/capita/day)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishProteinPerCapPerDayAqPlantsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Aquatic Plants used for Protein/capita/day (g/capita/day)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishProteinPerCapPerDayBodyOilFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Body Oil used for Protein/capita/day (g/capita/day)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishProteinPerCapPerDayLiverOilFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Fish Liver Oil used for Protein/capita/day (g/capita/day)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoFeedAqPlantsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Aquatic Plants used for Feed (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoFeedBodyOilFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Body Oil used for Feed (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoFeedLiverOilFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Fish Liver Oil used for Feed (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoFeedMealFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Fish Meal used for Feed (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoFoodAqAnimalsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Aquatic Animals used for Food (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoFoodAqPlantsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Aquatic Plants used for Food (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoFoodBodyOilFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Body Oil for Food (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoFoodLiverOilFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Fish Liver Oil used for Food (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoOtherUtilAqAnimalsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Aquatic Animals used for Other Utilities (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoOtherUtilAqPlantsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Aquatic Plants used for Other Utilities (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoOtherUtilBodyOilFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Body Oil used for Other Utilities (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoOtherUtilLiverOilFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Fish Liver Oil used for Other Utilities (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoOtherUtilMealFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Fish Meal used for Other Utilities (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoSeedAqAnimalsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Aquatic Animals used for Seed (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishCalPerCapPerDayCephalopodsFAO
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Cephalopods Fish Quantity used for Calories/capita/day (kcal/capita/day)
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishCalPerCapPerDayCrustaceansFAO
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Crustaceans Fish used for Calories/capita/day (kcal/capita/day)
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishCalPerCapPerDayDemersalFAO
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Demersal Fish consumed for Calories/cap/day (kcal/capita/day)
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishCalPerCapPerDayFreshwaterFAO
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Freshwater Fish consumed for calories/cap/day (kcal/capita/day)
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishCalPerCapPerDayMarineFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Marine Fish used for Calories/capita/day (kcal/capita/day)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishCalPerCapPerDayMolluscsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Molluscs Fish used for Calories/capita/day (kcal/capita/day)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishCalPerCapPerDayPelagicFAO
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Pelagic Fish consumed for Calories/capita/day (Tonnes)
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishDomesticSupplyAqAnimalsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Domestic Supply Quantity ofAquatic Animals (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishDomesticSupplyCephalopodsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Domestic Supply Quantity of Cephalopods Fish (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishDomesticSupplyCrustaceansFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Domestic Supply of Crustaceans Fish (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishDomesticSupplyDemersalFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Demersal Fish used for Food(Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishDomesticSupplyFreshwaterFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Domestic Supply of Freshwater Fish (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishDomesticSupplyMarineFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Domestic Supply Quantity of Marine Fish (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishDomesticSupplyMolluscsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Domestic Supply of Molluscs Fish (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishDomesticSupplyPelagicFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Domestic Supply Quantity of Pelagic Fish (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishExportsAqAnimalsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Aquatic Animals Exports (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishExportsCephalopodsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Exports of Cephalopods Fish (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishExportsCrustaceansFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Crustaceans Fish Exports (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishExportsDemersalFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Demersal Fish Exports (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishExportsFreshwaterFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Freshwater Fish Exports (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishExportsMarineFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Marine Fish Exports (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishExportsMolluscsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Molluscs Fish Exports (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishExportsPelagicFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Pelagic Fish Exports (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishFoodSupplyPerCapPerDayCephalopodsFAO
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Cephalopods Fish Quantity used for Food/capita/day (g/capita/day)
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishFoodSupplyPerCapPerDayCrustaceansFAO
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Crustaceans Fish used for Food Supply/capita/day (g/capita/day)
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishFoodSupplyPerCapPerDayDemersalFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Demersal Fish for Food Supply/cap/day (g/capita/day)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishFoodSupplyPerCapPerDayFreshwaterFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Freshwater Fish used for Food Supply/cap/day&nbsp; (g/capita/day)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishFoodSupplyPerCapPerDayMarineFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Marine Fish used for Food Suply/capita/day (g/capita/day)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishFoodSupplyPerCapPerDayMolluscsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Molluscs Fish used for Food Supply/capita/day (g/capita/day)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishFoodSupplyPerCapPerDayPelagicFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Pelagic Fish used for Food Supply/capita/day (g/capita/day)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishImportsAqAnimalsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Aquatic Animals Imports (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishImportsCephalopodsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Imports of Cephalopods Fish (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishImportsCrustaceansFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Crustaceans Fish Imports (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishImportsDemersalFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Demersal Fish Imports (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishImportsFreshwaterFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Freshwater Fish Imports (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishImportsMarineFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Marine Fish Imports (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishImportsMolluscsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Molluscs Fish Imports (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishImportsPelagicFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Pelagic Fish Imports (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishProdAqAnimalsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Production Quantity Aquatic Animals (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishProdCephalopodsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Production Quantity of Cephalopods Fish (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishProdCrustaceansFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Production Quantity of Crustaceans Fish (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishProdDemersalFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Production quantity of Demersal Fish (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishProdFreshwaterFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Domestic Freshwater Fish Production (tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishProdMarineFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Production Quantity of Marine Fish (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishProdMolluscsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Production Quantity of Molluscs Fish (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishProdPelagicFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Production quantity of Pelagic Fish (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishProteinPerCapPerDayCephalopodsFAO
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Cephalopods Fish Quantity used for Protein/capita/day (g/capita/day)
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishProteinPerCapPerDayCrustaceansFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Crustaceans Fish used for Protein/capita/day (g/capita/day)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishProteinPerCapPerDayDemersalFAO
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Demersal Fish consumed for Protein/cap/day (g/capita/day)
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishProteinPerCapPerDayFreshwaterFAO
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Freshwater Fish consumed for protein/cap/day (g/capita/day)
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishProteinPerCapPerDayMarineFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Marine Fish used for Protein/capita/day (g/capita/day)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishProteinPerCapPerDayMolluscsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Molluscs Fish used for Protein/capita/day (g/capita/day)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:69px;" |
 +
SeriesAgFishProteinPerCapPerDayPelagicFAO
 +
 
 +
| style="width:142px;height:69px;" |
 +
Total Pelagic Fish consumed for Protein/capita/day (g/capita/day)
 +
 
 +
| style="width: 212px; height: 69px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 69px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoFeedCephalopodsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Cephalopods Fish Quantity used for Feed (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoFeedCrustaceansFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Crustaceans Fish used for Feed (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoFeedDemersalFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Demersal Fish used for Feed(Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoFeedFreshwaterFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Freshwater Fish used for feed&nbsp; (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoFeedMarineFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Marine Fish used for Feed (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoFeedMolluscsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Molluscs Fish used for Feed (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoFeedPelagicFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Pelagic Fish used for Feed (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoFoodCephalopodsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Cephalopods Fish Quantity used for Food (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoFoodCrustaceansFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Crustaceans Fish used for Food (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoFoodDemersalFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Demersal Fish used for Food(Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoFoodFreshwaterFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Freshwater Fish for food&nbsp; (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoFoodMarineFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Marine Fish used for Food (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoFoodMolluscsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Molluscs Fish used for Food (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoFoodPelagicFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Pelagic Fish used for Food (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoOtherUtilCephalopodsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Cephalopods Fish Quantity used for Other Utilities (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoOtherUtilCrustaceansFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Crustaceans Fish used for Other Utilities (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoOtherUtilDemersalFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Demersal Fish used for other Utilities(Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoOtherUtilFreshwaterFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Freshwater Fish used for other Utilities (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoOtherUtilMarineFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Marine Fish used for Other Utilities (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoOtherUtilMolluscsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Molluscs Fish used for Other Utilities (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoOtherUtilPelagicFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Pelagic Fish used for Other Utilities (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoSeedCephalopodsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Cephalopods Fish Quantity used for Seed (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoSeedCrustaceansFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Crustaceans Fish used for Seed (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoSeedDemersalFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Demersal Fish used for Feed(Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoSeedFreshwaterFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Freshwater Fish used for Seed&nbsp; (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoSeedMarineFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Marine Fish used for Seed (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoSeedMolluscsFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Molluscs Fish used for Seed (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishtoSeedPelagicFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Pelagic Fish used for Seed (Tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Read in all fish series from FAO Food Balance Sheets
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgFishExportQuantityFAOTrade
 +
 
 +
| style="width:142px;height:52px;" |
 +
Quantity of fish exported(Tonnes) from FishstatJ
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO, FishstatJ
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
AGXFishQuantTradetbl
 +
 
 +
|-
 +
| style="width:234px;height:35px;" |
 +
SeriesAgFishExportValueFAOTrade
 +
 
 +
| style="width:142px;height:35px;" |
 +
Export value of fish ($1000 US)&nbsp; from FishstatJ software
 +
 
 +
| style="width: 212px; height: 35px;" |
 +
FAO, FishstatJ
 +
 
 +
| style="width: 406px; height: 35px;" |
 +
Fish imports and exports
 +
 
 +
|-
 +
| style="width:234px;height:35px;" |
 +
SeriesAgFishImportQuantityFAOTrade
 +
 
 +
| style="width:142px;height:35px;" |
 +
Quantity of fish imported (Tonnes) from FishstatJ
 +
 
 +
| style="width: 212px; height: 35px;" |
 +
FAO, FishstatJ
 +
 
 +
| style="width: 406px; height: 35px;" |
 +
Fish imports and exports
 +
 
 +
|-
 +
| style="width:234px;height:35px;" |
 +
SeriesAgFishImportValueFAOTrade
 +
 
 +
| style="width:142px;height:35px;" |
 +
Import value of fish ($1000 US)&nbsp; from FishstatJ software
 +
 
 +
| style="width: 212px; height: 35px;" |
 +
FAO, FishstatJ
 +
 
 +
| style="width: 406px; height: 35px;" |
 +
Fish imports and exports
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgCropExportQuantityFAOTrade
 +
 
 +
| style="width:142px;height:52px;" |
 +
Quantity of Crops exported (Tonnes) from FAO Trade Domain
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Crop trade
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgCropExportValueFAOTrade
 +
 
 +
| style="width:142px;height:52px;" |
 +
Value of Crops exported (1000$ US) from FAO Trade Domain
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Crop trade
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgCropImportQuantityFAOTrade
 +
 
 +
| style="width:142px;height:52px;" |
 +
Quantity of Crops Imported (Tonnes) from FAO Trade Domain
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Crop trade
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgCropImportValueFAOTrade
 +
 
 +
| style="width:142px;height:52px;" |
 +
Value of Crops Imported(1000$ USD) from FAO Trade Domain
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Crop trade
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgMeatExportQuantityFAOTrade
 +
 
 +
| style="width:142px;height:52px;" |
 +
Quantity of meat exported (Tonnes) from FAO Trade Domain
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Meat trade
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgMeatExportValueFAOTrade
 +
 
 +
| style="width:142px;height:52px;" |
 +
Value of meat exported (1000$ US) from FAO Trade Domain
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Meat trade
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgMeatImportQuantityFAOTrade
 +
 
 +
| style="width:142px;height:52px;" |
 +
Quantity of Meat Imported (Tonnes) from FAO Trade Domain
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Meat trade
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgMeatImportValueFAOTrade
 +
 
 +
| style="width:142px;height:52px;" |
 +
Value of Meat Imported (1000$ US) from FAO Trade Domain
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Meat trade
 +
 
 +
|-
 +
| style="width:234px;height:20px;" |
 +
SeriesAgProdCereals
 +
 
 +
| style="width:142px;height:20px;" |
 +
Cereal production
 +
 
 +
| style="width: 212px; height: 20px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 20px;" |
 +
Crop production (AGP)
 +
 
 +
|-
 +
| style="width:234px;height:35px;" |
 +
SeriesAgProdFruitsExclMelons
 +
 
 +
| style="width:142px;height:35px;" |
 +
Production of fruit, excluding melons
 +
 
 +
| style="width: 212px; height: 35px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 35px;" |
 +
Crop production (AGP)
 +
 
 +
|-
 +
| style="width:234px;height:20px;" |
 +
SeriesAgProdPulses
 +
 
 +
| style="width:142px;height:20px;" |
 +
Pulses production
 +
 
 +
| style="width: 212px; height: 20px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 20px;" |
 +
Crop production (AGP)
 +
 
 +
|-
 +
| style="width:234px;height:35px;" |
 +
SeriesAgProdRootsTub
 +
 
 +
| style="width:142px;height:35px;" |
 +
Root and tuber production
 +
 
 +
| style="width: 212px; height: 35px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 35px;" |
 +
Crop production (AGP)
 +
 
 +
|-
 +
| style="width:234px;height:35px;" |
 +
SeriesAgProdVegMel
 +
 
 +
| style="width:142px;height:35px;" |
 +
Vegetable, melon production
 +
 
 +
| style="width: 212px; height: 35px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 35px;" |
 +
Crop production (AGP)
 +
 
 +
|-
 +
| style="width:234px;height:20px;" |
 +
SeriesLandOther
 +
 
 +
| style="width:142px;height:20px;" |
 +
Land, other
 +
 
 +
| style="width: 212px; height: 20px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 20px;" |
 +
LdOth
 +
 
 +
|-
 +
| style="width:234px;height:35px;" |
 +
SeriesLandBuiltGFNcorine
 +
 
 +
| style="width:142px;height:35px;" |
 +
Land Area, Artificial Land
 +
 
 +
| style="width: 212px; height: 35px;" |
 +
CORINE Land Cover
 +
 
 +
| style="width: 406px; height: 35px;" |
 +
LdUrbTbl
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesLandBuiltGFNgaez
 +
 
 +
| style="width:142px;height:52px;" |
 +
Land Area, Settlement and Infrastructure
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
Global Agro-Ecological Zones (GAEZ) Model
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
LdUrbTbl
 +
 
 +
|-
 +
| style="width:234px;height:35px;" |
 +
SeriesLandBuiltGFNglc
 +
 
 +
| style="width:142px;height:35px;" |
 +
Land Area, Infrastructure aggregated
 +
 
 +
| style="width: 212px; height: 35px;" |
 +
Global Land Cover (GLC) 2000
 +
 
 +
| style="width: 406px; height: 35px;" |
 +
LdUrbTbl
 +
 
 +
|-
 +
| style="width:234px;height:103px;" |
 +
SeriesLandBuiltGFNsage
 +
 
 +
| style="width:142px;height:103px;" |
 +
Land Area, Buit area
 +
 
 +
| style="width: 212px; height: 103px;" |
 +
Sustainability and the Global Environment (SAGE) at University of Wisconsin
 +
 
 +
| style="width: 406px; height: 103px;" |
 +
LdUrbTbl
 +
 
 +
|-
 +
| style="width:234px;height:20px;" |
 +
SeriesAgProdMeat
 +
 
 +
| style="width:142px;height:20px;" |
 +
Meat production
 +
 
 +
| style="width: 212px; height: 20px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 20px;" |
 +
Meat production (AGP)
 +
 
 +
|-
 +
| style="width:234px;height:20px;" |
 +
SeriesAgFruVegEx
 +
 
 +
| style="width:142px;height:20px;" |
 +
Fruit, vegetable exports
 +
 
 +
| style="width: 212px; height: 20px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 20px;" |
 +
Food imports
 +
 
 +
|-
 +
| style="width:234px;height:20px;" |
 +
SeriesAgFruVegIm
 +
 
 +
| style="width:142px;height:20px;" |
 +
Fruit, vegetable imports
 +
 
 +
| style="width: 212px; height: 20px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 20px;" |
 +
Food imports
 +
 
 +
|-
 +
| style="width:234px;height:35px;" |
 +
SeriesLandPotentialArable
 +
 
 +
| style="width:142px;height:35px;" |
 +
total potential arable land
 +
 
 +
| style="width: 212px; height: 35px;" |
 +
FAOTERRASTAT
 +
 
 +
| style="width: 406px; height: 35px;" |
 +
LandArablePot
 +
 
 +
|-
 +
| style="width:234px;height:341px;" |
 +
SeriesWaterAnRenResources
 +
 
 +
| style="width:142px;height:341px;" |
 +
Annually renewable water resources
 +
 
 +
| style="width: 212px; height: 341px;" |
 +
FAO: Water Resources, Development and Management Service. AQUASTAT Information System on Water in Agriculture: Review of Water Resource Statistics by Country.&nbsp; [http://www.fao.org/waicent/faoinfo/agricult/agl/aglw/aquastat/water_res/index.htm http://www.fao.org/waicent/faoinfo/agricult/agl/aglw/aquastat/water_res/index.htm].
 +
 
 +
| style="width: 406px; height: 341px;" |
 +
Water resources
 +
 
 +
|-
 +
| style="width:234px;height:341px;" |
 +
SeriesWaterAnWithdrawals
 +
 
 +
| style="width:142px;height:341px;" |
 +
Annual water withdrawals/use (1990=70-99;2000=update, mostly 2000)
 +
 
 +
| style="width: 212px; height: 341px;" |
 +
FAO: Water Resources, Development and Management Service. AQUASTAT Information System on Water in Agriculture: Review of Water Resource Statistics by Country.&nbsp; [http://www.fao.org/waicent/faoinfo/agricult/agl/aglw/aquastat/water_res/index.htm http://www.fao.org/waicent/faoinfo/agricult/agl/aglw/aquastat/water_res/index.htm].
 +
 
 +
| style="width: 406px; height: 341px;" |
 +
Water use
 +
 
 +
|-
 +
| style="width:234px;height:341px;" |
 +
SeriesWaterAnRenResourcesOld
 +
 
 +
| style="width:142px;height:341px;" |
 +
Annually renewable water resources
 +
 
 +
| style="width: 212px; height: 341px;" |
 +
FAO: Water Resources, Development and Management Service. AQUASTAT Information System on Water in Agriculture: Review of Water Resource Statistics by Country.&nbsp; [http://www.fao.org/waicent/faoinfo/agricult/agl/aglw/aquastat/water_res/index.htm http://www.fao.org/waicent/faoinfo/agricult/agl/aglw/aquastat/water_res/index.htm].
 +
 
 +
| style="width: 406px; height: 341px;" |
 +
Water resources
 +
 
 +
|-
 +
| style="width:234px;height:222px;" |
 +
SeriesLandUrban&Built
 +
 
 +
| style="width:142px;height:222px;" |
 +
Land, urban and built-up areas
 +
 
 +
| style="width: 212px; height: 222px;" |
 +
Loveland, T.R., Reed, B.C., J.F., Brown, J.F., Ohlen, D.O., Zhu, Z., Yang, L.&nbsp; Merchant. J. 2000. &lt;i&gt;Global Land Cover Characteristics Database&nbsp; V 2.0. [http://edcdaac.usgs.gov/glcc/globdoc2_0.html http://edcdaac.usgs.gov/glcc/globdoc2_0.html]
 +
 
 +
| style="width: 406px; height: 222px;" |
 +
LdUrbTbl
 +
 
 +
|-
 +
| style="width:234px;height:40px;" |
 +
SeriesAgBovineMeatProductionFAO
 +
 
 +
| style="width:142px;height:40px;" |
 +
Total Domestic Bovine Meat Production (tonnes)
 +
 
 +
| style="width: 212px; height: 40px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 40px;" |
 +
Meat production (AGP)
 +
 
 +
|-
 +
| style="width:234px;height:40px;" |
 +
SeriesAgCerealsEx
 +
 
 +
| style="width:142px;height:40px;" |
 +
Cereal exports
 +
 
 +
| style="width: 212px; height: 40px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 40px;" |
 +
Trade data
 +
 
 +
|-
 +
| style="width:234px;height:40px;" |
 +
SeriesAgCerealsIm
 +
 
 +
| style="width:142px;height:40px;" |
 +
Cereal imports
 +
 
 +
| style="width: 212px; height: 40px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 40px;" |
 +
Trade data
 +
 
 +
|-
 +
| style="width:234px;height:40px;" |
 +
SeriesAgCerealSupply
 +
 
 +
| style="width:142px;height:40px;" |
 +
Cereal, domestic supply quantity
 +
 
 +
| style="width: 212px; height: 40px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 40px;" |
 +
Trade data
 +
 
 +
|-
 +
| style="width:234px;height:40px;" |
 +
SeriesAgCerealWaste
 +
 
 +
| style="width:142px;height:40px;" |
 +
FAO Cereal Waste
 +
 
 +
| style="width: 212px; height: 40px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 40px;" |
 +
Trade data
 +
 
 +
|-
 +
| style="width:234px;height:40px;" |
 +
SeriesAgMeatEx
 +
 
 +
| style="width:142px;height:40px;" |
 +
Meat exports
 +
 
 +
| style="width: 212px; height: 40px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 40px;" |
 +
Trade data
 +
 
 +
|-
 +
| style="width:234px;height:40px;" |
 +
SeriesAgMeatIm
 +
 
 +
| style="width:142px;height:40px;" |
 +
Meat imports
 +
 
 +
| style="width: 212px; height: 40px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 40px;" |
 +
Trade data
 +
 
 +
|-
 +
| style="width:234px;height:40px;" |
 +
SeriesAgMeatOtherProductionFAO
 +
 
 +
| style="width:142px;height:40px;" |
 +
Total Domestic Meat (Other) Production (tonnes)
 +
 
 +
| style="width: 212px; height: 40px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 40px;" |
 +
Meat production (AGP)
 +
 
 +
|-
 +
| style="width:234px;height:52px;" |
 +
SeriesAgMuttonandGoatMeatProductionFAO
 +
 
 +
| style="width:142px;height:52px;" |
 +
Total Domestic Mutton and Goat Meat Production (million metric tonnes)
 +
 
 +
| style="width: 212px; height: 52px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 52px;" |
 +
Meat production (AGP)
 +
 
 +
|-
 +
| style="width:234px;height:40px;" |
 +
SeriesAgPigMeatProductionFAO
 +
 
 +
| style="width:142px;height:40px;" |
 +
Total Domestic Pigmeat Production (tonnes)
 +
 
 +
| style="width: 212px; height: 40px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 40px;" |
 +
Meat production (AGP)
 +
 
 +
|-
 +
| style="width:234px;height:40px;" |
 +
SeriesAgPoultryMeatProductionFAO
 +
 
 +
| style="width:142px;height:40px;" |
 +
Total Domestic Poultry Meat Production (tonnes)
 +
 
 +
| style="width: 212px; height: 40px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 40px;" |
 +
Meat production (AGP)
 +
 
 +
|-
 +
| style="width:234px;height:40px;" |
 +
SeriesAgPulsesEx
 +
 
 +
| style="width:142px;height:40px;" |
 +
Pulse exports
 +
 
 +
| style="width: 212px; height: 40px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 40px;" |
 +
Trade data
 +
 
 +
|-
 +
| style="width:234px;height:40px;" |
 +
SeriesAgPulsesIm
 +
 
 +
| style="width:142px;height:40px;" |
 +
Pulseimports
 +
 
 +
| style="width: 212px; height: 40px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 40px;" |
 +
Trade data
 +
 
 +
|-
 +
| style="width:234px;height:40px;" |
 +
SeriesAgVegetableSupply
 +
 
 +
| style="width:142px;height:40px;" |
 +
FAO Vegetable Supply
 +
 
 +
| style="width: 212px; height: 40px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 40px;" |
 +
Trade data
 +
 
 +
|-
 +
| style="width:234px;height:40px;" |
 +
SeriesAgVegetableWaste
 +
 
 +
| style="width:142px;height:40px;" |
 +
FAO Vegetable Waste
 +
 
 +
| style="width: 212px; height: 40px;" |
 +
FAO
 +
 
 +
| style="width: 406px; height: 40px;" |
 +
Trade data
 +
 
 +
|-
 +