Despite the surreal lives we have been leading for the past few months, one thing is certain: this is an interesting time to be an economist. People have endless questions about what is happening in the economy and what follows, and it is the aim of economists and their models to answer such queries. However, macroeconomic models are simplifications of reality, and as such their predictions and conclusions are often inaccurate The pandemic has only served to highlight this fact, but why exactly are neoclassical models unfit to determine the impact of coronavirus on the economy?
The COVID-19 outbreak has impacted the global economy through many channels, but I will focus on one: uncertainty. Uncertainty is an inherent part of economics, and many models have dealt with its implications in the wake of past disturbances. According to macroeconomic theory, in the wake of uncertainty, households choose to increase their savings and decrease consumption and investment. Due to the decrease in consumption, businesses make fewer profits and are more likely to close, introduce a hiring freeze, and lay-off workers. As such, unemployment increases, and output decreases. Prices adjust to the new reality of the labour market, and there is temporary deflation (Leduc and Liu, March 2020).
However, the effects of COVID-19 are not so straight-forward. The shock does not fit the simplistic concept of a “demand-side shock”, as it also affects suppliers: businesses closing or temporarily changing the delivery of their services signifies a further decrease in output through channels not mentioned in models.
Furthermore, it is difficult to quantify uncertainty and to separate the initial impact of a shock from the impact of uncertainty it induces in the long run. Measures used by macroeconomists are often simplistic and lead to dubious predictions. For example, in March, Leduc and Liu (2020) developed a model where they used only VIX (a measure of stock market volatility) as a scale of uncertainty and completely ignored the “supply-side” effects of coronavirus. They predicted that USA unemployment rate would increase by 1 pp in the space of 12 months due to COVID-19-related uncertainty, when in fact the rate increased from 3.5% in February to 14.7% in April (US Department of Labour, 2020).
Moreover, uncertainty models which successfully dealt with previous shocks are not helpful in the current situation, since the world has never faced anything like this before. Of course, there have been disruptive plagues which brought economies to a halt in the past. But these usually disproportionately affected developing economies, and the global economy was not as integrated as it presently is and thus national economic crises were not as “contagious” (Baldwin and Mauro, 2020). Additionally, the bewildering speed at which the pandemic hit nations caused trends to change almost overnight. Hence, historical data is unlikely to be an accurate predictor of the future effects of the pandemic.
One of the most interesting models so far was developed by Baker et al. (2020) this May, which relies on business-cycle theory. They used a more complex measurement of uncertainty than Leduc and Liu (2020) by considering not only stock market volatility, but also newspaper coverage, forecast disagreement among different entities, and business expectation surveys. They also isolated the impact of uncertainty from the first-moment shock.
However, even this model is imperfect and its predictions for GDP questionable. After all, it was based on data from past unexpected shocks such as natural disasters and terrorist attacks, even though – as discussed above – these significantly differ from the phenomenon we now face. Moreover, they did not include certain economic factors.
All in all, neoclassical models are unfit to measure the impacts of the uncertainty induced by the coronavirus outbreak, despite considerable efforts from economists all over the world. If you are curious about this topic, why not check out the interesting and commendable work economists are doing on coronavirus for yourself?
References
Baker, S., Bloom, N. and Terry, S. (2020). Using disasters to estimate the impact of uncertainty.
Baldwin, R. and Mauro, B. (2020). Economics in the time of COVID-19. VoxEU.
Leduc, S. and Liu, Z. (2020). The Uncertainty Channel of the Corona Virus. FRBSF Economic Letter, 2020 – 07.
US Department of Labor. (2020). The employment situation – April 2020. USDL-20-0815.