The Dynamic Effects of Local Labor Market Shocks on Small Firms in The United States

IMF Working Papers, March 22, 2024

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Canonical URL: The Dynamic Effects of Local Labor Market Shocks on Small Firms in The United States

Data: payroll data on over 1 million workers at 80,000 small firms.
Constructed measures: county-month measures of employment, hours, and wages that correct for dynamic changes in sample composition in response to business cycle fluctuations.
Main finding: following tighter local labor market conditions, employment and hours per worker fall and wages rise.
Interpretation: results are consistent with the predictions of the response to a demand shock in the “jobs ladder” model of labor markets.
Robustness: results hold when instrumenting for local demand using county-level Department of Defense contract spending.
Importance of correction: without correction for dynamic sample bias, the hours fall by only one third as much and wages increase by double.

Empirical strategy: use corrected county-month measures from payroll panel data to estimate small firms' employment, hours, and wage responses to local labor market tightening.
Instrumental variable: county-level Department of Defense contract spending is used to instrument for local demand to check interpretation of results.
Sample coverage: over 1 million workers across 80,000 small firms, aggregated to county-month measures.

Employment: falls following tighter local labor market conditions (explicit magnitudes preserved in source: employment falls; no additional numeric magnitude provided in source text).
Hours per worker: fall following tighter local labor market conditions.
Wages: rise following tighter local labor market conditions.
Bias without correction:
- Hours fall by only one third as much.
- Wages increase by double.

Aligns with the “jobs ladder” model: the pattern of declining employment and hours alongside rising wages matches model predictions for a demand shock.
Demonstrates the necessity of correcting for dynamic sample composition when using establishment-level panel payroll data to study business cycle responses.