Economic vulnerability in US metropolitan areas

This paper examines various aspects of recent employment vulnerability in US metropolitan areas. Based on the three decades preceding COVID-19, an estimate is made of the volatility (sensitivity) in each area's unemployment rate, relative to the national rate, and this reflects the area's overall employment vulnerability to external events. Using the Brechling-Thirlwall time-series approach, the monthly change in each area's unemployment rate is first compared to the monthly change in the nation's unemployment rate. Regression analysis is then used to tie the volatility seen in those metropolitan unemployment rates to various initial conditions: degree of specialization in primary (+), manufacturing (+), and government (-) activities; initial unemployment (+); human-created (-) and natural amenities (+); real wages (-); self-employment (-); and the presence of major colleges or universities (-). An alternative specification reassesses these estimates after including the volatility of unemployment rates across the nation's various states. A short discussion then addresses the issue of vulnerability in specific activities. Selecting four industries that were identified at risk during early COVID events, ranked employment specialization indices (LQs) are correlated with ranked volatility estimates of unemployment rates. In the more advanced economies, metropolitan areas typically specialize in, and trade across, different industries, but this specialization can create overall employment vulnerability.

Automated summary

This paper examines the employment vulnerability in US metropolitan areas by analyzing the volatility of unemployment rates and its sensitivity to external events. The study uses a time-series approach and regression analysis to investigate the impact of initial conditions on the volatility of unemployment rates, and discusses the vulnerability of specific activities. The research finds that specialization in metropolitan areas can create overall employment vulnerability.