Working Paper: CEPR ID: DP15396
Authors: Dilip Mookherjee; Ruochen Dai; Yingyue Quan; Xiaobo Zhang
Abstract: We examine how exposure of Chinese firms to the Covid-19 shock varied with a cluster index (measuring spatial agglomeration of firms in related industries) at the county level. Two data sources are used: entry flows of newly registered firms in the entire country, and an entrepreneur survey regarding operation of existing firms. Both show greater resilience in counties with a higher cluster index, after controlling for industry dummies and local infection rates, besides county and time dummies in the entry data. Reliance of clusters on informal entrepreneur hometown networks and closer proximity to suppliers and customers help explain these findings.
Keywords: clusters; covid19; china; firms; social networks
JEL Codes: J12; J16; D31; I3
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Clustering (C38) | Firm Resilience (D21) |
| Higher Clustering (C38) | Decreased Negative Impact on Firm Entry Rates (L26) |
| One Standard Deviation Increase in Cluster Index (C38) | Entry Rates (J39) |
| 1% Increase in Cluster Index (C43) | Likelihood of Reopening (J63) |
| Higher Infection Rates (I14) | Entry Rates (J39) |
| Higher Infection Rates (I14) | Likelihood of Reopening (J63) |
| Clustering (C38) | Better Outcomes for Firms (L25) |