Real-time Forecasts of State and Local Government Budgets with an Application to the COVID-19 Pandemic

40 Pages Posted: 21 Apr 2020 Last revised: 21 Jul 2022

See all articles by Eric Ghysels

Eric Ghysels

University of North Carolina Kenan-Flagler Business School; University of North Carolina (UNC) at Chapel Hill - Department of Economics

Fotis Grigoris

University of Iowa - Department of Finance

Nazire Ozkan

Amazon Web Services, Inc.

Date Written: July 20, 2022

Abstract

Using a sample of the 48 contiguous United States, we consider the problem of forecasting state and local governments' revenues and expenditures in real time using models that feature mixed-frequency data. We find that single-equation mixed data sampling (MIDAS) regressions that predict low-frequency fiscal outcomes using high-frequency economic data historically outperform both traditional fiscal forecasting models and theoretically motivated multi-equation models. We also consider an application of forecasting fiscal outcomes in the face of the economic uncertainty induced by the 2019-2020 coronavirus pandemic. Overall, we show that MIDAS regressions provide a simple tool for predicting fiscal outcomes in real time.

Keywords: Fiscal Policy, Forecasting, Mixed-Frequency Bayesian VAR, MIDAS Regressions

JEL Classification: C22, C32, C50, C53, E62

Suggested Citation

Ghysels, Eric and Grigoris, Fotis and Ozkan, Nazire, Real-time Forecasts of State and Local Government Budgets with an Application to the COVID-19 Pandemic (July 20, 2022). Available at SSRN: https://ssrn.com/abstract=3580363 or http://dx.doi.org/10.2139/ssrn.3580363

Eric Ghysels (Contact Author)

University of North Carolina Kenan-Flagler Business School ( email )

Kenan-Flagler Business School
Chapel Hill, NC 27599-3490
United States

University of North Carolina (UNC) at Chapel Hill - Department of Economics ( email )

Gardner Hall, CB 3305
Chapel Hill, NC 27599
United States
919-966-5325 (Phone)
919-966-4986 (Fax)

HOME PAGE: http://https://eghysels.web.unc.edu/

Fotis Grigoris

University of Iowa - Department of Finance ( email )

Iowa City, IA 52242-1000
United States

Nazire Ozkan

Amazon Web Services, Inc. ( email )

United States

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