Learning from Friends in a Pandemic: Social Networks and the Macroeconomic Response of Consumption

82 Pages Posted: 17 May 2020 Last revised: 17 Apr 2021

See all articles by Christos Makridis

Christos Makridis

Stanford University; Arizona State University (ASU); Massachusetts Institute of Technology (MIT) - Sloan School of Management; Department of Veterans Affairs (VA)

Tao Wang

Department of Economics, Johns Hopkins University

Date Written: May 15, 2020

Abstract

This paper studies how local shocks can have aggregate effects through the effects of social networks on expectations. First, using plausibly exogenous variation in the exposure of counties to COVID-19 shocks in their social network, we find that a 10% rise in SCI-weighted cases and deaths is associated with a 0.15% and 0.42% decline in consumption expenditures. These effects are concentrated among consumer goods & services that rely more on social-contact and are not driven by local shocks. Second, we augment a quantitative pandemic-consumption model under incomplete market with a tractable mechanism of belief formation through social communications. The model is general enough to nest a number of workhorse theories of expectation formations featuring overreaction, rational updating, or stickiness. We find that, while social communication slows the speed of aggregate belief adjustment in responses to fundamentally relevant shocks, it also moderates overreaction to local noises in aggregation. We demonstrate how the dynamic and average size of aggregate responses depend on the location of the initial shocks and the structure of the network.

Keywords: Aggregate Demand, Consumption, Coronavirus, COVID-19, Expectations, Peer Effects, Social Networks

JEL Classification: D14, E21, E71, G51

Suggested Citation

Makridis, Christos and Wang, Tao, Learning from Friends in a Pandemic: Social Networks and the Macroeconomic Response of Consumption (May 15, 2020). Available at SSRN: https://ssrn.com/abstract=3601500 or http://dx.doi.org/10.2139/ssrn.3601500

Christos Makridis (Contact Author)

Stanford University ( email )

Stanford, CA 94305
United States

Arizona State University (ASU) ( email )

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Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

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Department of Veterans Affairs (VA) ( email )

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Washington, DC 20420
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Tao Wang

Department of Economics, Johns Hopkins University ( email )

Baltimore, MD 20036-1984
United States

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