Perceptions of Local Government Fiscal Health and Fiscal Stress: Evidence From Quantile Regressions With Michigan Municipalities and Counties

Abstract

This study applies insights from open systems theory to explore how the perceptions of local officials can enhance our understanding of local government fiscal health—in particular, to understand differences between healthy and distressed jurisdictions. With a sample of local governments in Michigan from 2013 to 2019, we use quantile regression to investigate associations between subjective financial condition measures and objective indicators. The results show that these relationships are often more muted for lower-stress governments and more pronounced for higher-stress governments, a pattern that is not accounted for by traditional methods of measuring financial condition. The findings demonstrate the utility of open systems theory and quantile regression techniques to improve understanding of the financial condition and suggest that in order to avoid overlooking cases of fiscal distress, policymakers and analysts should incorporate these approaches into methods for diagnosing local fiscal health.