Economic Effects of the Pandemic
Sunday, Jan. 3, 2021 3:45 PM - 5:45 PM (EST)
- Chair: Andrew Greenland, Elon University
Online Prices and Stay-at-Home Economy: Evidence from Prices of 107 Chinese Websites during the COVID-19 Quarantine Period
AbstractWith the frozen offline economy in COVID-19 quarantine period, online prices provide new insights for analyzing the impact of the pandemic on the economy. We obtain online prices from 107 websites in China to investigate the price adjustment behavior in China during the COVID-19 quarantine period. Using a DiD method, we show that the pandemic leads to a 0.6% surge in overall price index, but a 20% decrease in the price change frequency, and 1% drop in the absolute price change size. Moreover, significant differences show up among various sectors as the pandemic has heterogeneous impacts on their demand and supply sides. Specifically, the “stay-at-home” (or Zhai) economy is developing rapidly during the quarantine period, especially for contactless online service, including remote working, online education, online medical services and online games et al. For example, the price index of online games increases by 121% after the COVID-19 outbreak, together with an 18% rise of the price change frequency, in sharp contrast to other sectors. Overall, the COVID-19 pandemic causes structural changes in price movements and adjustments for pure online products, online-to-offline (O2O) products and pure offline products in China. These heterogeneous impacts call for heterogeneous policies for various sectors to alleviate the damage of the COVID-19 pandemic.
Small Business Survival Capabilities and Policy Effectiveness: Evidence from Oakland
AbstractUsing unique City of Oakland data during COVID-19, we document that small business survival capabilities vary by firm size as a function of revenue resiliency, labor flexibility, and committed costs. Nonemployer businesses rely on low cost structures to survive 73% declines in own-store foot traffic. Microbusinesses (1-to-5 employees) depend on 14% greater revenue resiliency. Enterprises (6-to-50 employees) have twice-as-much labor flexibility, but face 11%-to-22% higher residual closure risk from committed costs. Finally, inconsistent with the spirit of Chetty-Friedman-Hendren-Sterner (2020) and Granja-Makridis-Yannelis-Zwick (2020), PPP application success increased medium-run survival probability by 20.5%, but only for microbusinesses, arguing for size-targeting of policies.
Central Bank Communication in Times of Pandemics
AbstractMost central banks declared they would take "all necessary steps" to mitigate the impact of the COVID-19 virus outbreak on their economy and decreased their interest rates to the zero-lower bound. While conventional monetary policy tools remain almost ineffective during this unprecedented economic crisis, unconventional monetary policy communication drastically changed both within and between central banks. Among prevention and policy steps central bankers implemented, the central bank communication apparatus became the primary policy tool to convey unconventional monetary policies and sentiment to the public. Using state-of-the-art text mining methodologies, we analyze the communication of the Federal Reserve, the European Central Bank, the Bank of England, the Reserve Bank of Australia and the Bank of Israel in 2020 to show how central bank communication was uncertain and heterogeneous during the COVID-19 crisis. Additionally, we also show that similar unconventional monetary policy steps were formulated differently, conveying very different sentiments and topics to the public among central banks. Using COVID-19 epidemics data, we show how central bank communication was related to the virus outbreak. We derive some policy implications from this study. The central bank and government decisions are often related and sometimes coordinated, questioning the central bank role and independence hypotheses that appear to be relaxed during such a crisis. Small open economy central banks are less active compared to leading central banks. To conclude, the central bank communication and actions were more reactive during the COVID-19 crisis compared to the Global Financial Crisis, and those very communications and actions may help predict epidemic data.
Measuring Spread of Economic News on Social Media Using HIV Model
AbstractAn important debate in macroeconomics is how people form expectations. Rational expectations and adaptive learning approaches assume that all agents in the economy are as good as econometrics. In reality, most people learn by talking to their neighbors, relatives, and friends. However, obtaining data on expectations is extremely difficult. Most of the surveys of expectations are limited to a few economic variables like inflation, unemployment, etc. This paper proposes a new way of modeling social learning by using Twitter data on recent economic news items and fitting it on HIV model to estimate the speed of transmission. Information spread is modeled using the source of infection as an important parameter. The population on Twitter is divided into compartments like Susceptible and Infected who are at high risk and low risk of transmitting news. Corresponding definitions for Twitter data are analyzed wherein influencers with a following of ten thousand or more followers are categorized as high risk and less active users are categorized as low risk in terms of receiving and spreading information on social media. Initial results using maximum likelihood estimation suggest that unlike HIV disease, information spread on social media spreads at a faster rate than expected among high risk groups and low risk groups. This has important policy implications in terms of major outcomes like consumer sentiment, investment etc as people's expectations are directly influenced by social media that might represent misinformation and fake news rather than pure fundamentals.
- E0 - General