There is no conflict of interest.
Highlights
- The study's objective was to examine the impact of Opportunity Zones (OZ) on job vacancies and wages.
- The study used a nonexperimental matched comparison group design. Using data from the American Community Survey, Housing and Urban Development's zip code files, and Burning Glass Technologies, the authors conducted statistical models to compare the differences in outcomes between the treatment and comparison groups.
- The study found no significant differences in the number of job vacancies and median wages posted on job notifications between OZs and non-designated OZs.
- This study receives a moderate evidence rating. This means we are somewhat confident that the estimated effects would be attributable to Opportunity Zones (OZ), but other factors might also have contributed. However, the study did not find any statistically significant effects.
Intervention Examined
Features of the Intervention
The Opportunity Zone (OZ) program was established in 2017 as part of the Tax Cut and Jobs Act. OZs offer tax incentives to investors who, through Opportunity Funds, invest in real estate or businesses in designated economically distressed communities. The investments create jobs and promote economic growth for the people living in those communities.
OZs must meet certain criteria related to low-income status. This status is determined by median family income or poverty rates set by federal agencies such as the Internal Revenue Service (IRS) and Housing and Community Development (HCD). State governors nominate these zones, and there are over 8,700 OZs across the U.S. While census tracts next to low-income communities were also eligible, this study included only low-income census tracts.
Features of the Study
The study used a nonexperimental design with a matched comparison group to examine the impact of OZs on job vacancies and wages. The authors matched zip codes with OZs (treatment group) with similar zip codes that do not have OZs but contain eligible census tracts (comparison group). They ensured that the groups were similar on features of the population (size, poverty level, income, racial composition, education level, growth rates of population and income, and if the area is urban or rural). The analysis sample included 364,282 observations across the U.S.
The study authors used data from the U.S. Census Bureau's American Community Survey (ACS), Housing and Urban Development (HUD)'s zip code files, and Burning Glass Technologies (BGT). ACS data from 2015 and 2016 were used to create the treatment and comparison groups, while BGT data from January 2015 to September 2020 provided wage information. HUD files were used to crosswalk census tracts to zip codes. Data from 2018 were excluded because it was the year that the program started. The authors used statistical models to compare the number of job vacancies and the median of the minimum posted wage in job announcements in the OZs and non-designated OZs.
Findings
Employment
- The study did not find a statistically significant difference in the number of job vacancies between the OZs and non-designated OZs.
Earnings and Wages
- The study did not find a statistically significant difference in the median wages of posted job notifications between the OZs and non-designated OZs.
Considerations for Interpreting the Findings
The census tracts designated as OZs either received investments or could have received investments. The study authors noted that only a few hundred actually received investments, although 8,700 tracts were designated as OZs, contributing to the lack of significant findings. This suggests that the program’s impacts may be understated.
Causal Evidence Rating
Research Guidelines
Review Protocol: Living Systematic Annual Search and Review Protocol
Review Guidelines: Causal Evidence Guidelines