Predicting US county economic resilience from industry input-output accounts

Yicheol Han, Stephan J. Goetz

Research output: Contribution to journalArticlepeer-review

27 Scopus citations


Resilience is defined as a system’s ability to initially resist and then recover from a shock. Here we apply this concept to examine the performance of U.S. counties during the Great Recession. The response of local economies to manmade and natural shocks is hypothesized to depend on the centrality of local industries within the economy, or how well connected they are to the other industries. We first calculate a centrality value for each industry using the national Input-Output accounts. We then ‘step down’ these values to the county level using industry employment data. We then test empirically whether local economies containing more centralized industries were more resilient, using a resilience measure that compares the local employment rebound and decline during the Great Recession. Our results suggest that measures of economic centrality adopted from the study of complex networks provide new insights when applied to the fields of regional science and spatial analysis, and economic growth more generally.

Original languageEnglish (US)
Pages (from-to)2019-2028
Number of pages10
JournalApplied Economics
Issue number19
StatePublished - Apr 21 2019

All Science Journal Classification (ASJC) codes

  • Economics and Econometrics


Dive into the research topics of 'Predicting US county economic resilience from industry input-output accounts'. Together they form a unique fingerprint.

Cite this