Local Government Fiscal Early Warning Surveys: Lessons From COVID-19





Yang (2020) recently argued for enhanced evidence–based decision making during sudden and widespread economic shocks such as the COVID-19 pandemic, but he lamented the difficulty of acquiring such data in a timely manner. One strategy is to implement an early warning survey system. This article describes Colorado’s experience with a survey the state administered to local government officials shortly after the governor’s stay-at-home order. The state used the survey to inform its fiscal response policies. We describe the advantages and challenges of using surveys as a statewide, rapid information collection strategy as well as offer evidence that the survey yielded relatively accurate data about local fiscal impacts. We also provide an empirical analysis of the survey, employing the Heckman correction technique to account for selection bias, to illustrate how the survey responses can improve state decision making.

Author Biographies

Geoffrey Propheter, University of Colorado-Denver

Geoffrey Propheter is an assistant professor in the School of Public Affairs at the University of Colorado Denver. His research interests are in property tax policy and administration, economic development, and sports and urban affairs.

Melissa Mata, Colorado Municipal League

Melissa Mata is the municipal research analyst for the Colorado Municipal League, where she tracks trends and best practices in local government policy, including issues such as elections, finance, transportation, and marijuana. She graduated with a Master in Public Administration from University of Colorado Denver in 2015.






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