Understand the Interconnected World

The real world is a staggeringly complex place, comprised of level upon level of dynamic, interacting systems. Population growth is a good example of this. Populations size changes over time due to births and deaths and migration to and from a given population. To study population growth researchers must calculate how many births, deaths, and migrantions occur in a given year. Many factors go into calculating the number of births. First, we need to know how many women of childbearing age are in the population, how many of those women will actually have children, and how many children each will have. Childbearing rates are driven by a number of factors, including female education levels, contraception use, and income. Each of these, in turn, is driven by other factors including governance (education spending, health spending, reproductive and family planning policies), health (high infant mortality tends to drive more births), and access to infrastructure (access to clean water and sanitation reduces infant mortality)—and all this just for the number of births! 

Clearly, no model can capture the real world’s every detail, but models are still powerful tools for understanding how the world works, and IFs includes more variables and connections from a wider range of key development systems than any other forecasting model available today (and it does so for 186 countries). Given its complexity, we have tried to keep IFs as transparent as possible. Below is an interactive diagram of the IFs model structure, designed to help you understand how IFs builds its forecasts.

The network diagram begins with a bird’s-eye-view of the main submodules within IFs: agriculture, economy, education, energy, environment, socio-politcal, health, infrastructure, international politics, population, and human development, and the basic connections between each. You can use the interface controls to drill down through categories and subcategories within each module to individual variables and parameters, follow connections from one variable or category to another, or even search for specific variables and connections. Click the image below to explore our network diagram beta version.

Each main module can be expanded into its constituent segments by either double clicking the node or by using the tree on the right side of the screen. The nodes can be collapsed by either right-clicking the node or by using the tree. A single click on any node will display information about the module, segment, or variable/parameter in the information tab at the bottom of the screen. Links to the help system of IFs will also appear in the information tab. We encourage you to load saved states using the "action" option in the top left corner of the screen or make your own diagrams using the "save" option.

IFs can help you better recognize possible unintended long-term consequences of action or inaction today. In the same vein, IFs can help you identify more effective avenues for achieving your goals. At the Pardee Center, we try to reduce some of the uncertainty inherent in long-term planning and policy formation. With IFs, we hope to strengthen the mental models that underlie pivotal decisions affecting sustainable human and social development around the world.