From Wiki
Jump to: navigation, search

The EconDash is an interactive data visualization created by the Pardee Center for International Futures. The purpose of this visualization is to allow the user to explore relevant indicators of financial and economic instability and resilience. The EconDash uses both monadic and dyadic data across time, and includes some forecasted variables from the International Futures (IFs) system. 

The data comes from various source, including: Bank for International Settlements (BIS),  Balance of Payments and International Investment Position statistics (BoP/IIP) from IMFPenn World Tables (PWT), and the UN Conference on Trade and Development (UNCTAD).

Defining the Variables

The different categories of relevant indicators are listed below, with a justification for their inclusion in the EconDash visualization.

Dependent Variable- Types of Crises

The dependent variable is defined as an economic crisis that occurs as a result of strictly economic phenomenon. This excludes economic instability resulting from political instability or natural disasters. Ecoomic crises are further categorized under the following variables:

  1. Resource induced (i.e. decreased commodity prices for countries lacking in market diversity)
  2. Debt Crisis (i.e. sovereign debt crisis, Euro debt crisis, credit crisis)
  3. Banking Crisis
  4. Financial Crisis (i.e. Asian financial crisis, global financial crisis, currency crisis)
  5. Economic Crisis (i.e. macroeconomic imbalance, economic mismanagement, low production leading to revenue shortfall)
  6. Policy-induced crisis (i.e. financial liberalization, economic sanction, post-integration economic crisis)

Independent Variable- Drivers of Crises

Variable name Category Source Definition
GDP Growth Rate GDP growth IFs GDP calculated using data from the IMF World Economic Outlook
GDP at MER GDP growth IFs GDP calculated using data from the IMF World Economic Outlook
GDPPCP GDP growth IFs GDP calculated using data from the IMF World Economic Outlook
BIS Consumer Prices Inflation BIS The data used from BIS is the year-on-year percentage changes. The year-on-year changes capture the rise and fall of consumer prices more accurately than the 2010-100 index. Some of the BIS data goes back to the 1800s.
Real Effective ER (CPI based) Inflation UNCTAD Real Effective Exchange Rate deflated by CPI; with 2005 as the base year
Real effective exchange rate indices (GDP deflator based), annual, 1998-2014
Currency Shocks UNCTAD Real Effective Exchange Rate deflated by GDP with 2005 as the base year
Nominal Effective Exchange Rate, annual, 1998-2013 Currency Shocks UNCTAD Nominal Effective Exchange based on 2000 dollars
Balance of Payments Current account deficit UNCTAD The balance of payments is a statistical statement that summarizes transactions between residents and nonresidents during a period. It consists of the goods and services account, the primary income account, the secondary income account, the capital account, and the financial account.
Current Account total balance Current account deficit IMF Three series available for both goods and services (six total). They are broken down into Goods, Credit; Goods, Debit; Goods, balance; Services, Credit; Services Debit; Services, Balance.
Credits to the non-financial sector Size of the financial sector relative to the non-financial sector BIS BIS' publication captures different subsets for the 32 countries listed in the report. These subsets include Households and NPISHs, Non-Financial Corporations, and Private Non-Financial Sector.
Debt service ratio (private sector) Size of the financial sector relative to the non-financial sector
BIS BIS' publication captures different subsets for the 32 countries listed in the report. These subsets include Households and NPISHs, Non-Financial Corporations, and Private Non-Financial Sector.
Debt service ratio (households) Size of the financial sector relative to the non-financial sector
BIS BIS' publication captures different subsets for the 32 countries listed in the report. These subsets include Households and NPISHs, Non-Financial Corporations, and Private Non-Financial Sector.
Economic Freedom Levels of economic freedom IFs Economic freedom level on scale of 1 to 10 (most free)
Socio-Political Freedom Score Levels of economic freedom IFs Civil and political freedom level on scale of 2 to 14 (lower is freer)
Capital Account Balance Capital flows IMF Three series available for the capital account: Credit, Debit, and Net

Size of Financial Sector Relative to Non-Financial Sector

The financial crisis of 2008 occurred at a time of vast deregulation. Flawed institutions and practices of the New Financial Architecture (NFA) and light government regulation are seen as the cause of the financial aspects of the crisis. These factors combined with rapid financial innovation and moral hazard resulting from periodic government bailouts contributed to creating conditions that led to the crisis. Rapid financial innovation manifested itself in the form of inflated financial markets relative to the real economy. This means that asset prices were highly overvalued, a sign that a crash was bound to occur at any moment. Debt to GDP rose from 22% in 1981 to 117% in 2008. Corporate profits rose from 10% to 40% in the financial sector in roughly the same period. Data on debt service ratio and credit to the non-financial sector reveal the size of the financial sector relative to the non-financial sector by highlighting the ratio between the value of the real economy and the value of financial markets [1].

Currency Shocks

Exchange rate data reveals currency value fluctuations by exposing a currency’s value relative to another. As a result, this data is helpful for revealing currency shocks. Depreciation of the Thai baht is believed to have led to the East Asian currency crisis[2]. Some models have shown that a speculative attack resulting in one country devaluing their currency might threaten the competitiveness of a trading partner[3]. The significance of this risk lies in the exchange rate regime that a country pursues and how deeply their economic system is integrated into the global economy. This is because certain exchange rate mechanisms can impede monetary policy attempts at stabilizing economic instability.

GDP Growth

GDP growth rates are used to identify levels of economic growth due to the fact that dramatic changes in GDP are strong signifiers of economic health. For instance, a study of 77 countries, found that low GDP growth, high real interest rates, and high inflation strongly correlate with banking crises[4]. This study reveals that a combination of periods of weak economic growth and loss of monetary control are large contributors to economic crises. They also find that banking fragility can result from real interest rate risk. This is associated with the idea that, during the 1980’s and 1990’s, more volatile interest rates may have contributed to banking crises. While low GDP growth can be a sign of economic downturn, increased risk can result from economic booms. At some point in the cycle risks materialize, reversing financial agents’ risk taking behavior, triggering deleveraging and, consequently, financial turmoil in the form of huge stocks of accumulated debt.  [5]


We use BIS consumer prices to chart inflation because changes in consumer prices are strong indicators for inflationary pressures. We also incorporate real effective exchange rates in order to identify inflation through relative currency values. Economic data from 20 countries was analyzed to find what drives economic crises. The study found that governments’ attempts at spurring economic growth through expanding the money supply, known as expansionary monetary policy, often result in currency crises[6]. More specifically, these countries attempt monetary policies that cause high inflation and reserve losses in an attempt to try and remedy domestic economic problems such as unemployment. 

Capital Flows

The East Asia financial crisis is a significant example of a financial system gone haywire.  Three key points relating to the dynamics between micro and macroeconomic integration factors contributed to vulnerability in the region. First, the policies used to mitigate excess demand pressures, resulting from heavy capital inflows, highlighted incentives for superfluous borrowing, and for the build-up of risky liabilities. Second, financial sector weakness combined with improper financial sector liberalization and inadequate regulation led to risky lending and poor management of balance sheet risk by financial intermediaries. Third, poor governance and false guarantees from corporates spurred speculative excessive borrowing and lending. The combination of these factors fomented financial and macroeconomic susceptibility to volatility[7]. The capital account balance reveals how much how much capital countries spend and receive.

Current Account Deficit

Preceding the Mexican Peso crisis, the Mexican current account deficit rose to 8 percent of GDP and Mexico’s international reserves declined by two-thirds, resulting in a depreciated peso. After attempting, to no avail, to stabilize the peso through devaluation, the Mexican authorities left the peso to float freely, resulting in a diminished external value of the currency[8]. Current account and balance of payments data are used to analyze countries’ current account deficits.

Levels of Economic Freedom

Financial liberalization is seen by some researchers as an instigator of financial fragility [9]). This is because financial liberalization allows banks to take on greater risk without suffering from the potential negative effects of risky, short term lending. Countries that have liberalized financial systems are more likely to experience banking crises[10]. It is important to note, however, that such crises are less likely if liberalization coincides with sufficient regulation and institutions in place to guarantee adequate supervision. The Economic freedom index from Freedom House and socio-political freedom scores are used to calculate levels of economic freedom by showing how liberalized an economy is. Some factors that play into the index include access to capital, tax rates, and tariffs. 

Trade Data and Centrality Scores

Eigenvector centrality was used to analyze centrality of trade data. Centrality is defined as:

  1. Reach- Ability of entity to reach other vertices
  2. Flow-Quantity/ weight of walks passing through entity
  3. Vitality- Effect of removing entity from network
  4. Feedback- A recursive function of alter centralities

Eigenvector centrality is defined as the centrality of each vertex being proportional to the sum of the centralities of its neighbor.

The basic idea behind eigenvector centrality is that a central actor is connected to other central actors.

Variable Series*

Trade in agriculture as percent of GDP [xag_pctgdpb]


Total agricultural trade [xag]


Trade in manufacturing as percent of GDP [xman_pctgdpb]


Total manufacturing trade [xman]


Trade in materials as percent of GDP [xmat_pctgdpb]

Materials Total materials trade [xmat]

Trade in services as percent of GDP [xserv_pctgdpb]


Total Trade in Services [xserv]


Trade in energy as percent of GDP [xene_pctgdpb]

Information and Communications Technology Trade in information and communications technology as percent of GDP [xict_pctgdpb]
Information and Communications Technology

Total trade in Information and communications technology [xict]

Total Trade

Total trade- all sectors as Percent GDP [xtot_pctgdp]

Total Trade

Total trade- all sectors [xtot]

*All trade data incorporated into centrality scoring derived from UNCTAD database


  1. Crotty, J. (2009). Structural causes of the global financial crisis: a critical assessment of the “new financial architecture.” Cambridge Journal of Economics, 33(4), 563–580
  2. Khan, H. (2004). Global Markets and Financial Crises in Asia Towards a Theory for the 21st Century. Basingstoke: Palgrave Macmillan
  3. Gerlach, S., & Smets, F. (1995). Contagious speculative attacks. European Journal of Political Economy, 11(1), 45-63
  4. Demirgüç-Kunt, A., & Detragiache, E. (2005). CROSS-COUNTRY EMPIRICAL STUDIES OF SYSTEMIC BANK DISTRESS: A SURVEY. National Institute Economic Review, (192), 68–83
  5. Benlialper, Ahmet, and Hasan Cömert. "Implicit Asymmetric Exchange Rate Peg under Inflation Targeting Regimes: The Case of Turkey." Cambridge Journal Of Economics 40.6 (2016): 1553-580. Web.fckLR
  6. Eichengreen, B., Rose, A. K., Wyplosz, C., Dumas, B., & Weber, A. (1995). Exchange Market Mayhem: The Antecedents and Aftermath of Speculative Attacks. Economic Policy, 10(21), 249–312.
  7. Alba, Pedro, Bhattacharya, Amar, Claessens, Stijn, Ghosh, Swati, & Hernandez, Leonardo. (1999). ‘The role of macroeconomic and financial sector linkages in East Asia’s financial crisis’, The Asian financial crisis: causes, contagion and consequences. Cambridge ; New York: Cambridge University Press.
  8. Truman, E. M. (1996). The Mexican peso crisis: Implications for international finance. Federal Reserve Bulletin; Washington, 82(3), 199.
  9. Stiglitz, J. (1993). THE ROLE OF THE STATE IN FINANCIAL-MARKETS. World Bank Economic Review, 19–52.
  10. Demirgüç-Kunt, A., & Detragiache, E. (1998). The Determinants of Banking Crises in Developing and Developed Countries. International Monetary Fund, Staff Papers; Washington, 45(1), 81–109.