Sometimes, no matter how hard you try, it's impossible to make a silk purse out of a sow's ear. A pair of California-based economists probably recognized this following an attempt to construct an “early warning system” to predict another global financial crisis in the wake of the 2008 catastrophe.
In the National Bureau of Economic Research’s forthcoming paper, “
“If the causes of the crises differ across countries, there is little hope of finding a common statistical model to predict them,” they wrote.
The authors say there are two keys essential to a good early warning system. The system must:
1. Predict what countries will be most affected (i.e. the cross-sectional component)
2. Predict when the crisis will occur, or the timing factor
By using a Multiple-Indicator Multiple-Cause model, Rose and Spiegel’s study focuses on the countries most dramatically affected by the crisis, as well as those countries less affected in order to serve as control data.
The severity of the crisis in each country was measured by four variables:
1. The 2008 real gross domestic product (GDP) growth
2. The percentage change in a broad measure of the national stock market over 2008
3. The 2008 percentage change in the special drawing right (SDR) exchange rate
4. The change in a country’s credit-worthiness rating from Institutional Investor, a business news and research publisher
According to the International Monetary Fund (IMF), the SDR is an international reserve asset, created by the IMF in 1969, to supplement its member countries' official reserves. The SDR's value is based on a basket of four key international currencies, and they can be exchanged for freely usable currencies.
“Our research found that size, from an economic perspective, had no significant impact on the incidence of crises across countries, while income has a significantly negative impact,” Rose says. “Richer counties experienced more severe crises.”
Having taken the initial steps, the authors then compiled a list of characteristics that may have impacted a country’s economic performance during the crisis. Collected using data from 2006 and earlier, the characteristics included financial policies and conditions, domestic macroeconomic policies, and appreciation in equity and real estate markets.
For example, in the United States, many fault-inflated real estate values and the sub prime credit market for causing the American economy’s failure and subsequent recession. Rose and Spiegel found that while an economic collapse occurred in countries where the real estate bubble burst, other countries, including Germany and Japan, had an equally serious crisis despite the fact that both nations failed to see a significant decline in housing prices.
Rose also highlights that the bubble in real estate prices was mirrored by an increase in stock prices. Notably, equity appreciation emerged as the only variable that could robustly help predict crisis severity. The sample countries’ geography and proximity to strong neighboring economies were also considered in the study, but did little to consistently predict a future meltdown.
The authors go on to note that their results suggest “measurable pre-existing conditions across countries had little common impact on the relative severity of these countries’ crisis experience."
There are three possible reasons for the predictive failure, according to Rose:
1. The causes of the 2008 crisis may have differed across countries
2. The crisis might have been the result of a “truly global shock” unrelated to the characteristics considered in the study
3. The shock may be of a national origin that eventually spreads to other countries
“Politicians seek a magic instrument to prevent another serious economic crisis, but our findings show there is no mechanical easy way to predict major downturns in the future,” Rose concludes.
