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This presentation by Chuck Swenson, a professor at USC Marshall School of Business, provides an analysis of the national landscape of Enterprise Zones (EZs) in the U.S. It compares studies by Swenson, Ham, Imrohoroglu, Kolko, Neumark, and others to assess the impact of EZ programs on employment, wages, poverty rates, and income. The findings suggest that EZs can lead to a decrease in unemployment rates, poverty rates, and an increase in household income. Further research is recommended to explore additional benefits of EZ programs.
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California Enterprise Zone Program: A Review and Analysis Presentation By: Chuck Swenson Professor and Leventhal Research Fellow, Marshall School of Business, USC
Outline • EZs: The National Landscape • Swenson (2009) and Ham, Imrohoroglu, and Swenson(2009) • Kolko and Neumark (2009) vs. Ham et al • Conclusions
EZs: The National Landscape • Connecticut had first program in 1983 • In 2003, 38 states had EZs • Currently, 43 states have EZs (or EZ type programs) • By-state benefits vary widely: from modest hiring credits (AZ, Utah) to comprehensive income, property, and sales/use tax benefits (NY, PA, MN). See my Treatise chapter handout.
Swenson (2009) • Hiring credits should: • Increase employment (decrease unemployment rates) • Increase wages • Increase capital expenditures • Increase firm after-tax income • Increase business retention
Ham, Imrohoroglu, and Swenson (2009) • About the authors • National study (all 43 states with EZs) over 20 years • Geo-coding of 8000+ EZ census tracts and cohort tracts • Differences in differences design • National as well as state specific effects
Ham et al (cont’d) • National Results: EZs have statistically significant • Decrease in unemployment rate (1.6%; Table 2) • Decrease in poverty rate (5.4%; Table 3) • Increase in fraction of households with wage and salary income (.61%; Table 4)
Ham et al (cont’d) • CA Results: EZs result in statistically significant: • Decrease in unemployment rate (2.2%; Table 2) • Decrease in poverty rate (.5%--Table 3;not significant) • Increase in fraction of households with wage and salary income (2.0%; Table 4)
Kolko and Neumark (2009) vs. Ham et al (2009) • Scope: • Ham et al (national plus specific states; control for national effects) • Kolko and Neumark (CA only; no control for national effects)
Kolko vs. Ham (cont’d) • Outcome variables: • Ham et al: unemployment rates, poverty rates, wage and salary incomes • Kolko & Neumark: employment levels only
Kolko vs. Ham (cont’d) • Source data: • Ham et al: Bureau of Census (available since 1970s) • Kolko & Neumark: relatively new dataset derived from Standard & Poors surveys sent to businesses->noise in data->high standard errors->lowered power of statistical tests?
Conclusions • EZs seem to work • More analysis on business retention, expansion, increased number of firms, capital outlays, etc. would solidify findings