Estimating the economic effects of US state and local fiscal policy: A synthetic control method matching‐regression approach

Dan Rickman and Hongbo Wang

Growth and Change, 2024, vol. 55, issue 2

Abstract: In this paper, we advance the empirical literature on US state and local fiscal policymaking by using the synthetic control method (SCM) to create pairwise matches for states in subsequent regression analysis of the relationships between state and local fiscal policies and several state economic outcomes. Additional contributions include the use of principal component analysis to construct broader narratives of state economic performance and to reduce the dimensionality of the characteristics used in SCM matching, while the regressions also include variables to control for post‐matching economic shocks. Compared to conventional regression analysis, the SCM matching‐regression approach better addresses potential endogeneity, reduces interpolation bias, and creates fiscal policy measures that better reflect policy differences. The SCM‐matched regressions produce more statistically significant relationships between state and local fiscal variables and economic outcomes than do the conventional unmatched regressions, suggesting improved identification of state and local fiscal policy effects on economic outcomes. Robust relationships found include negative economic effects of the own‐source revenue burden and property taxes. Consistent with the existing literature, the estimated fiscal policy effects are quantitatively small and unlikely to drive differences in state economic performance.

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1111/grow.12717

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:growch:v:55:y:2024:i:2:n:e12717

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0017-4815

Access Statistics for this article

Growth and Change is currently edited by Dan Rickman and Barney Warf

More articles in Growth and Change from Wiley Blackwell
Bibliographic data for series maintained by Wiley Content Delivery ().