The practice of economic forecasting arguably experienced its biggest whiff in modern times when the May U.S. unemployment report revealed a gain of 2.5 million jobs vs. an expected decrease of 7.5 million, resulting in a decrease in the unemployment rate to 13.3% instead of the forecasted increase to nearly 20%. Concurrently, as the S&P 500 flirts with 3,100, the index is roughly 6% above the average year-end price target of 2933 forecasted by some of Wall Street’s best and brightest minds.[i]
How did all this high-octane brainpower get it so wrong?
The coronavirus pandemic has introduced uncertainty into nearly every aspect of American society. Will hospitals and clinics hold up under the burden of new cases? When will scientists develop a vaccine, and how will it be distributed? When can employees safely return to their offices? The answers to these and many other questions seem to change daily, and with each change the prospects for the U.S. economy and financial markets rises or falls.
What Do We Really Know?
The reason there is so much divergence between forecasts and reality is simple; no one knows for sure what is going to happen. According to the Harvard Business Review, three factors are causing forecasters difficulties during the first half of 2020:[ii]
- The economic impact and speed of policy changes have never been higher. In normal times, most governments can be relied on to at least attempt to encourage economic growth and preserve employment. Today, however, they are deliberately provoking recessions to save lives, and containment measures are crushing domestic activity. Moreover, bills which generally endure months of parliamentary ping-pong are being rushed through legislatures in days as governments and central banks race to respond to the rapid advance of the virus. By the same token, the fiscal and monetary stimulus being announced to alleviate the downturn dwarfs that seen during the 2008-2009 financial crisis.
- The pandemic is undermining the reliability of economic and financial data. The credibility of data is the bedrock of any good forecasting model. In particular, survey-based data of businesses and households is suffering as lockdown measures reduce response rates, amplifying sampling error.
- Economists and strategists are unfamiliar with the science surrounding the virus. The reason the models are diverging so much is because economic forecasters are having to delve into the unfamiliar world of epidemiology to better understand the likely evolution of the coronavirus. However, this is a challenge even for health experts. Predicting the scope and effectiveness of future public health interventions is difficult. There is no firm timeline for the arrival of game-changing treatments or vaccines, or clarity over the likelihood or severity of a second wave of cases.
Each recession is unique, starting with the economic conditions that triggered it. That makes relying on history for guidance toward depth, duration, recovery, and solutions a tricky business. For example, the recession of 2008-2009 was connected to a financial crisis, whereas the current economic downturn is associated with a public health crisis.
Why the Divergence?
According to Bloomberg survey data going back to 1996, prior to May’s unemployment report, the biggest single month miss on the payrolls report was 318,000 in February 2003.[iii] The sudden nature of the downturn put a premium on real-time data to help produce in-the-ballpark estimates. However, small change in a few variables can make predictions almost impossibly complex. For example, May’s report incorporated weekly jobless claims indicating tens of millions of applications for jobless insurance, the extent of which the U.S. has never experience in such a short time span. However, economists’ models most likely failed to fully consider high frequency data pointing to a trough in economic activity since mid-April, as well as fiscal stimulus measures enacted by Congress, specifically the Paycheck Protection Program providing firms funding to keep workers on staff.
The S&P 500 has rallied more than 40% from its March 2020 low amid central bank stimulus, better-than-expected economic data, and a nationwide relief of shelter-in-place orders and social distancing restrictions. The stock market’s full recovery from bear market declines has defied bankruptcies, layoffs, dividend cuts, and the elimination of corporate buyback programs, as well as countless warnings about elevated valuations and a collapse in corporate profits. Based on a survey of 18 equity market forecasts, at 3200 the index exceeds all but four strategists’ year-end targets.[iv]
The divergence in economic and market forecasts should narrow going forward. Greater clarity will emerge on the effectiveness economic stimulus, and any further fiscal or monetary measures will likely be more modest in scope. The collection of credible economic data should be enhanced by the gradual lifting of lockdowns. However, one lesson forecasters’ have discovered is that it is more difficult to get a handle on the real-time changes related to hiring than it is on firing, especially when layoffs are considered only temporary.
Wall Street strategists’ record in forecasting the S&P 500 has been spotty at best. For example, they missed the benchmark’s gain in 2019 by more than 10% percentage points and overshot the market by a similar amount in the 2018. Their current stance echoes prevailing skepticism among institutional investors who have been reluctant to embrace the equity rally.
The financial crisis of 2008-2009 caught most economists and financial experts by surprise, but the insights gained in areas such as the economics of financial contagion and the impact of unconventional monetary measures improved the quality of forecasting models. In today’s pandemic environment, the knowledge of the coronavirus will shine new light on many notable topics, including how consumer spending is affected by fear of contagion, as well as the economic effects of radical fiscal policy.
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