In response to the COVID-19 outbreak, governments and public health authorities worldwide implemented confinement and mitigation measures such as social distancing. These measures effectively led to the controlled shutdown of entire sectors of the economy, especially those that supply economic activities and services involving high physical contact with other people, such as restaurants, hairdressers, airlines, etc. On the one hand, authorities forced many such establishments to close and send their workers home (the so-called lockdowns). On the other hand, consumers themselves also reduced their consumption of these services, regardless of public health policy recommendations.1 Furthermore, as workers in some of these services lose their jobs and income, they also reduce their purchases of other goods and services. This, combined with uncertainty about the pandemic's evolution, leads to a reduction in demand for goods and services across the board, affecting not just these locked down sectors (Gourinchas 2020).

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For this reason, most economists would agree that the economic effects of the outbreak and mitigation measures combine aspects of so-called ‘supply’ and‘demand’ shocks (Baldwin and Weder di Mauro 2020). A supply shock is something that reduces the economy’s ability to produce goods and services at given prices. Public health authorities and employers preventing service workers from doing their jobs can be thought of as a supply shock. On the other hand, a demand shock reduces consumers’ ability or willingness to purchases goods and services at given prices. People staying at home and not going to restaurants or movie theaters for fear of contagion is an example of a demand shock. Additionally,as service workers lose their jobs they may stop purchasing other goods such as cars or appliances, which can also be thought of as a demand shock in those specific sectors.

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Conventional monetary and fiscal policy can be used to offset aggregate demand shocks, but other policies may be more appropriate to stabilize the economy after a supply shock. Understanding whether a shock is caused by supply or demand is therefor every important for the design and implementation of stabilization policies. Due to the nature of this specific shock, it is not clear that the government wants to stimulate/stabilize activity in certain service sectors, as that could run counter to the objectives of public health policy. However, the government could target policies (such as fiscal or credit policy) to sectors that are not part of the lockdown but are subject to aggregate shocks. This implies that it is not just important to understand whether this shock in the aggregate has to do with supply and demand, but it is also crucial to understand this at the sector level (Guerrieri et al. 2020).

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In a recent paper (Brinca et al. 2020), we try to answer these questions using data on hours worked and wages to estimate labor demand and supply shocks for the aggregate economy and different sectors, using an econometric model.2 The basic assumptions we use for identifying supply and demand shocks are very simple: if we observe hours and wages (prices and quantities) moving in the same direction, we assign more probability to those movements being caused by a demand shock. On the other hand, if we observe hours and wages moving in opposite directions, we assign that to a supply shock.

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Figure 1 plots the shock decomposition we estimate for March 2020, when the lockdown began, for the growth rate of hours worked. The sum of the red and blue bars is the percentage point change in the growth rate of hours worked relative to its historical average; the red bar's size relative to the blue bar shows how important supply shocks were relative to demand shocks in that sector. The first ‘sector’ is total private employment, and our results show that two-thirds of the decline in hours were attributable to supply shocks. By far,the most affected sector was leisure and hospitality, where the growth rate of hours worked fell by almost ten percentage points. Again, supply played as lightly larger role than demand. While most sectors experienced negative supply shocks, some sectors experienced positive demand shocks; for example,retail trade likely benefitted as people stopped going to restaurants and started buying more groceries and cooking at home. The information sector also benefitted, likely due to firms' increased interest by telework software and arrangements.

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Figure 2 repeats the exercise for April 2020, the first full month of lockdown. The total effect on hours worked during this month was much larger across sectors,with total private employment falling by almost 17 percentage points. Again,for most sectors, two-thirds of the decrease seemed to be associated with supply. Also, during this month, the positive demand shocks in sectors such as retail and information vanished or even reversed.

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Our approach has some potential caveats, ranging from potential non linearities caused by such large shocks (our model is linear), and composition effects driving the joint dynamics of hours and earnings. To address these, we take our estimated shock measures in April 2020 and compare them to a sectoral measure of how many jobs can be done at home (Dingel and Neiman 2020), something that should affect labor supply more than labor demand. We show a stronger (positive) correlation between the April 2020 supply shocks and the fraction of jobs that can be done at home.3 We believe that this helps validate our methodology and decomposition.

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All in all, our results seem to suggest that labor supply shocks account for a larger share of the fall in hours caused by the pandemic shock in March and April, but that both shocks were important. In particular, there were significant demand shocks in sectors that should not be directly affected by the lockdown, such as manufacturing. This suggests that a targeted stabilization policy could help assuage some of the effects of the current crisis.‍

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This content was originally published in VoxEU

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