The impacts of the coronavirus on the global economy: Part V Is a comparison with the Great Depression possible?

More and more commentators and economists are comparing the current economic crisis to the 1929 depression (also known as the Great Depression). For some of them, the current crisis is even worse. Are they right? In my humble opinion, they are wrong.

First of all, the Great Depression was caused by a stock market crash (that started on October 24, 1929). On the other hand, the current economic crisis is voluntarily induced by governments as a policy response to a global health crisis. Thus, the turbulence we are observing on stock exchanges around the globe is the consequence but not the cause of the current economic situation. The causes of the stock market crash of October 24, 1929 were mainly consumerism, easy credit, and speculation. Its consequences were mainly bank failures, hoarding, massive job losses, and poverty. Second, if the causes of the Great Depression and those of the current crisis are not the same, their consequences are not similar either. Currently, investors have fear, but they have not lost confidence in financial institutions. Millions of people are not currently employed, but they have not definitely lost their jobs. Third, the Great Depression lasted almost a decade (from 1929 till the outbreak of World War II), whereas the current crisis is hopefully coming to an end, since governments have started preparing plans to exit the lockdown restrictions they imposed some months ago.

It is true that the stock markets have been very turbulent since the outbreak of the coronavirus disease. On March 13, the situation on the major exchanges was the worst record over the past two decades (see Figure 1). Since then, it has been gradually improving. Between March 27 and April 3, the global financial turbulence score fell from 8.03 to 7.70 (a 4% decrease). The decrease in the VIX, the fear index, was much higher. This latter index went down from 46.8 to 41.67 (an 11% decrease). This situation is explained by the rise in the major benchmark indices. On the New York Stock Exchange, the NASDAQ, the Bombay Stock Exchange, the Toronto Stock Exchange, and the Brazil Stock Exchange, the benchmark indices increased by more than 10%.

Figure 1: Global Financial Turbulence Scores and VIX, Jan 8, 2000 - Apr 3, 2020

Oil markets are also suffering severely from the on-going crisis. On March 13, in the heat of the financial turbulence, the spot price of the West Texas Intermediate (WTI) and the Brent fell by 28.9% and 33.5%, respectively. (The WTI and the Brent are both sweet light crude oil serving as benchmark in pricing.) The following week they further declined by 25.3% and 23.9%, respectively. As one can see in Figure 2, the prices of these crude oil keep falling. This price crash is due to thee overproduction of oil and the decrease in its demand after the lockdown of several economies. This situation is affecting not only oil producing firms and the industries depending directly on this activity, but also public finance. In Canada, the provinces of Alberta and Newfoundland and Labrador are the most affected by this unexpected oil price crash.

Weekly Cushing, Oklahoma WTI and Europe Brent Spot Prices, Jan 1, 2000 - Apr 3, 2020

Dataset and Code

The Latest Global Financial Turbulence Scores.

Date	Score
Feb 14, 2020	1.36
Feb 21, 2020	6.23
Feb 28, 2020	3.68
Mar 6, 2020	9.74
Mar 13, 2020	12.89
Mar 20, 2020	9.37
Mar 27, 2020	8.03
Apr 3, 2020	7.70

The components indices of the global financial turbulence score

(1) NYA: the New York Stock Exchange composite index, (2) IXIC: the NASDAQ composite, (3) N225, the Tokyo Stock Exchange average index, (4) FTAS, the London Stock Exchange FTSE all share, (5) HSI, the Hong Kong Stock Exchange index, (6) N150, the Euronext Next 150 index, (7) GSPTSE, the Toronto Stock Exchange composite index, (8) BSESN, the Bombay Stock Exchange sensitive index, (9) GDAXI, the Frankfurt Stock Exchange performance index, (10) AXJO, the Australian Securities Exchange S&P 200, (11) SSMI, the SIX Swiss exchange mid-cap index, and (12) IBOVESPA, the Brazil Stock Exchange index.

Formula

$$d_t² = (r_t - μ ) Σ ^-1 (r_t - μ )',

where $d$ denotes the turbulence score, the vector $r$_t lists the current growth rates of the benchmark indices, the vector $$ μ their historical averages, and $$ Σ designates their variance-covariance matrix. For further details, see Mark Kritzman and Li Yuanzhen (2010).