The objective of this research is to answer the questions:
1. Are enterprise zones efficient if adopted by high-unemployment areas?
2. What are the effects of the EZ or tax incentives on the unemployment rates of areas?
The research applies these questions to Ohio's enterprise zone program because of the policy debate in the various state enterprise zone programs regarding the zero-sum nature of such policies.
A theoretical model is developed that addresses the research questions. In the model I point to the cause of unemployment in the EZ. I show the relationship between the reservation wage and unemployment rate, following Jones (1989). I then show the general equilibrium response to the tax abatement provided in EZs, in a generalized framework incorporating capital mobility, following Harberger (1962). Because the framework considers the enterprise zone and the rest of the economy, it attempts to capture the effects as to what could happen in areas without the enterprise zone. I thus use the framework to analyze the impact of enterprise zones on the economy that adopts it.
In the empirical work, reservation wages are estimated as a function of unemployment rate and other variables, using the Panel Study of Income Dynamics (PSID), taking into account sample selection bias. The estimation indicates that the area's unemployment rate does not have a significant impact on the reservation wage of individuals residing in the area. Based on this estimation, reservation wages are predicted for Ohio's enterprise zones and net benefits from employment created in the enterprise zones of Ohio are estimated. The benefits are compared to the costs of the program (that include taxes foregone, other local incentives and infrastructure provided to firms by local governments under the program) under various scenarios.
The benefit-cost analysis shows that on average, the unemployment rate adjusted B-C ratio is less than 1, if only created jobs are taken into account. The efficiency loss under this assumption is estimated to be around $45 million. This implies that it is not a good strategy for all areas to adopt tax incentives to create employment. It could be beneficial for high-unemployment areas to use tax incentives because, when adjusted rather than absolute B-C ratios are used to assess net benefits from employment, high-unemployment areas perform better than other areas.
Finally the estimation of area unemployment rates using Census data for Ohio at the block group level, shows that tax incentives have a statistically significant impact in reducing the unemployment rate of areas. This shows that tax incentive programs are mostly successful in the objective for which they were created in the state. Moreover, the B-C analyses show that the net benefits from employment are likely to be higher than the costs of creating them if such programs were to be adopted by high-unemployment areas.