Covid-19, Stay-at-Home Orders and Employment: Evidence from CPS Data

Abstract

In this paper, we examine the short-term consequences of COVID-19 and evaluate the impacts of stay-at-home orders on employment and wages in the United States. Guided by a pre-analysis plan, we document that COVID-19 increased the unemployment rate, decreased hours of work and labor force participation, especially for younger workers, non-white, not married and less-educated workers. We built four indexes (exposure to disease, proximity to coworkers, work remotely and critical workers) to study the impact of COVID-19. We find that workers that can work remotely are significantly less likely to have their labor market outcomes affected, while workers working in proximity to coworkers are more affected. The unemployment effects are significantly larger for states that implemented stay-at-home orders. Our estimates suggest that, as of early May, these policies increased unemployment by nearly 4 percentage points, but reduced COVID-19 cases by 186,600-311,000, and deaths by 17,851-23,325. We apply our estimates to compute lost income ($18.6-$21.4 billion), reduced government income tax revenues

The intensity of COVID‐19 nonpharmaceutical interventions and labor market outcomes in the public sector

“…The CPS is the main source of labor force statistics for the population in the United States, sponsored by the US Census Bureau and the BLS. Several papers examine the short‐term impact of COVID‐19 on US employment with the CPS (Béland et al, 2020; Gupta, Montenovo, et al, 2020) because it provides enough observations to obtain reliable estimations. COVID‐19 impacted the data collection with the response rate dropping by 10 (March), 13 (April), and 15 (May) percentage points in 2020 with respect to the same months in 2019.…”

“…The rest of the variables are defined as in Equation (). The length of the event‐time “window” is not so long in comparison to those papers using data since 2015 or 2016 (Béland et al, 2020) to avoid bias in the coefficients because of the composition change of groups in the pre‐event.…”

“…We combine this with the out‐of‐home mobility data provided by Google (Google LLC, 2020) to capture, in an easy way, the intensity of the NPIs by using one index for state and month. Prior literature on the impact of NPIs on employment considers only an indicator variable focusing mainly on stay‐at‐home orders and/or business closures (Béland et al, 2020; Gupta, Montenovo, et al, 2020), which is not able to capture the differences across states in the NPI enforcement. We add to this line of research by extending the number of NPIs and better measuring the enforcement of the NPIs in an easy way with one index for state and month.…”

COVID‐19 and housing market effects: Evidence from U.S. shutdown orders

“…Governments worldwide responded by imposing shutdown orders that restricted the operation of businesses and encouraged (or even required) households to “stay at home” and practice social distancing in an effort to curtail the spread of COVID‐19. While these response measures helped mitigate the spread of infection, they triggered or abetted recessions worldwide, as made evident by the sharp decreases in consumer spending (Chetty et al., 2020; Horvath et al., 2020), increases in unemployment (Beland et al., 2020; Borjas & Cassidy, 2020; Dingel & Neiman, 2020; Koren & Pető, 2020), and volatility in equity returns (Alfaro et al., 2020; Baker et al., 2020; Hassan et al., 2020; Ling et al., 2020; Milcheva, 2021; Ramelli & Wagner, 2020; van Dijk et al., 2020). To reverse these economic repercussions of pandemic mitigation efforts, additional government interventions were designed.…”

“…Policymakers and economists, among many other stakeholders, have shown an interest in better understanding the economic effects of shutdowns and related nonpharmaceutical interventions. As a result, a rapidly growing body of literature on the economic effects of COVID‐19 investigates whether recent policy interventions have been successful (e.g., Agarwal et al., 2020; Beland et al., 2020; Capponi & Rios, 2020; Dave et al., 2020; Granja et al., 2020).…”