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California Enterprise Zone Program: A Review and Analysis

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)

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California Enterprise Zone Program: A Review and Analysis

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  1. California Enterprise Zone Program: A Review and Analysis Presentation By: Chuck Swenson Professor and Leventhal Research Fellow, Marshall School of Business, USC

  2. Outline • EZs: The National Landscape • Swenson (2009) and Ham, Imrohoroglu, and Swenson(2009) • Kolko and Neumark (2009) vs. Ham et al • Conclusions

  3. 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.

  4. National Landscape (cont’d)

  5. Swenson (2009) • Hiring credits should: • Increase employment (decrease unemployment rates) • Increase wages • Increase capital expenditures • Increase firm after-tax income • Increase business retention

  6. 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

  7. Ham et al (cont’d)

  8. 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)

  9. 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)

  10. 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)

  11. Kolko vs. Ham (cont’d) • Outcome variables: • Ham et al: unemployment rates, poverty rates, wage and salary incomes • Kolko & Neumark: employment levels only

  12. 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?

  13. Conclusions • EZs seem to work • More analysis on business retention, expansion, increased number of firms, capital outlays, etc. would solidify findings

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