Combining rules and discretion in economic development policy: Evidence on the impacts of the California Competes Tax Credit

https://doi.org/10.1016/j.jpubeco.2022.104777Get rights and content
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Highlights

  • The California Competes Tax Credit (CCTC) is one of a new generation of economic development programs to spur local job creation.

  • The CCTC incorporates best practices from previous programs, combining explicit eligibility thresholds with some discretion on the part of program officials to select tax credit recipients, and allowing clawbacks for firms that do not meet their job creation obligations.

  • We study detailed data on accepted and rejected applicants to the CCTC, including information on the scoring of applicants with regard to program goals as well as on funding decisions.

  • Using restricted-access American Community Survey (ACS) data and a difference-in-differences approach, we find that each CCTC-incentivized job in a census tract increases the number of individuals working in that tract by close to three – a significant local multiplier. Local multipliers are larger for non-manufacturing awards than for manufacturing awards.

  • CCTC awards increase employment among workers across socioeconomic groups and in more- as well as less-advantaged neighborhoods, but have limited impact on residents of affected communities.

Abstract

We evaluate the effects of one of a new generation of economic development programs, the California Competes Tax Credit (CCTC), on local job creation. Incorporating perceived best practices from previous initiatives, the CCTC combines explicit eligibility thresholds with some discretion on the part of program officials to select tax credit recipients. The structure and implementation of the program facilitates rigorous evaluation. We exploit detailed data on accepted and rejected applicants to the CCTC, including information on the scoring of applicants with regard to program goals as well as on funding decisions, together with restricted-access American Community Survey (ACS) data on local economic conditions. Using a difference-in-differences approach, we find that each CCTC-incentivized job in a census tract increases the number of individuals working in that tract by close to 3 – a significant local multiplier. Local multipliers are larger for non-manufacturing awards than for manufacturing awards. CCTC awards increase employment among workers across socioeconomic groups and in more- as well as less-advantaged neighborhoods, but have limited impact on residents of affected communities. We validate our empirical strategy and confirm our core results using an alternative dataset and recently developed difference-in-differences methods that correct for potential biases generated by variation in treatment timing and treatment effect heterogeneity.

Keywords

Economic development
Business incentives
Tax credits
Hiring incentives
Place-based policies

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We are grateful for funding from the Laura and John Arnold Foundation and the Smith Richardson Foundation. Any views expressed are ours only, and do not reflect the views of these foundations. We thank Carlos Anguiano, Jessica Deitchman, Ben Hyman, Toni Symonds, Brian Uhler, Brian Weatherford, Timothy Young, seminar participants at UCI, and the editor and anonymous reviewers for helpful comments and assistance. We also thank current and former staff of the California Governor's Office of Business and Economic Development, including Cheryl Akin, Scott Dosick, Kristen Kane, Van Nguyen, Jonathan Sievers, and Austin Sihoe, for numerous useful discussions. The views expressed are our own; GO-Biz provided program data, and had no control over our analysis, interpretation, or conclusions. The research in this paper was conducted while the authors were Special Sworn Status researchers of the U.S. Census Bureau at the Federal Statistical Research Data Center at the University of California, Irvine. Any views expressed are those of the authors and not those of the U.S. Census Bureau. The Census Bureau's Disclosure Review Board and Disclosure Avoidance Officers have reviewed this information product for unauthorized disclosure of confidential information and have approved the disclosure avoidance practices applied to this release. This research was performed at a Federal Statistical Research Data Center under FSRDC Project Number 2146 (CBDRB-FY21-P2146-R8762, CBDRB-FY21-P2146-R8879, CBDRB-FY22-P2146-R9680, and CBDRB-FY22-P2146-R9836).