Finance and COVID-19
Paper Session
Friday, Jan. 7, 2022 10:00 AM - 12:00 PM (EST)
- Chair: Wenlan Qian, National University of Singapore
Labor Force Telework Flexibility and Asset Prices: Evidence from COVID-19 Pandemic
Abstract
We show that labor force telework flexibility (LFTF) is a first-order effect in accounting for the variations of asset prices and firm policies during the Covid-19 pandemic. Specifically, firms in high LFTF industries signficantly outperform firms in low LFTF industries in stock returns. The positive LFTF-return relation extends to G7 countries and is stronger in countries with more severe pandemic. A decomposition analysis of the LFTF measure shows that the job characteristics associated with the central component of telework, information and communication technologies, are the main driving force of the result. A dynamic neoclassical model of firms operating multiple job tasks together with pandemic shocks captures the relationship between labor force flexibility and stock returns. The model mechanism highlights that i) job task flexibility is a key driving force of the cross-industry heterogeneity in firm value fluctuations, and ii) combining labor productivity (supply) and uncertainty shocks is crucial to generate large drop and persistent recovery in firm value and output.The Value of Big Data in a Pandemic
Abstract
Although big data technologies such as digital contact tracing and health certification apps have been widely used to combat the COVID-19 pandemic, little empirical evidence regarding their effectiveness is available. This paper studies the economic and public health effects of the ``Health Code'' app in China. By exploiting the staggered implementation of this technology across 322 Chinese cities, I find that this big data technology significantly reduced virus transmission and facilitated economic recovery during the pandemic. A macroeconomic Susceptible-Infectious-Recovered (SIR) model calibrated to the micro-level estimates shows that the technology reduced the economic loss by 0.5% of GDP and saved more than 200,000 lives by alleviating informational frictions during the COVID-19 outbreak.Discussant(s)
Lars Lochstoer
,
University of California-Los Angeles
Miao Ben Zhang
,
University of Southern California
Tianyue Ruan
,
National University of Singapore
JEL Classifications
- G0 - General