The first hypothesis in my study predicts that the Round II Urban EZs had an impact on the percentage change of business establishments or employees in a given zip code. However, the results of the linear regression models indicate that the zone presence did not have a statistically significant effect on local business and job growth. The
predicted effects of the EZ program presented in Table 10 include the coefficients and standard errors from Model A and Model B, as well as the number of observations, F-test, R2, and Adjusted R2 values. In Model A, in which the change in the number of businesses is the dependent variable, the statistically significant independent variables are the
percentages of people residing in the same home since 1995 and families in poverty, and median household income.
Of the two models, Model A (change in number of business establishments) performed better than Model B (change in number of employees). Model A produced a higher F-test value than that obtained by Model B, higher R2, and more statistically significant independent variables than the competing model. As shown in Table 10, the adjusted R2 is 0.2722 for Model A, meaning that approximately 27% of the variance in the dependent variable can be explained by this model. Both of the models were tested for multicollinearity, heteroskedasticity, skewness, and kurtosis and were within the acceptable ranges to maintain the validity of the regression models (see Appendix for detailed results.
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Table 10: Predicting the Effects of the Round II Urban EZs Variable Model A CHGBIZ 3 Model B CHGEMP 4 Empowerment Zone 0.044 (2.689) 1.164 (5.064)
Percent Non-Minority Residents -0.068 (0.074) -0.753 (0.138)
Median Age 0.591 (0.292) -0.029 (0.549)
Percent Rental Housing -0.102 (0.129) 0.086 (0.243) Percent Vacant Housing -0.428 (0.256) -0.947 (0.482) Retail per 1K Residents 0.24 (0.207) 0.167 (0.389) Percent Living Same House,
1995 -0.532 (0.189) ** -0.161 (0.357)
Percent High School Graduate 0.000 (0.209) -0.013 (0.393) Percent Bachelor Degree -0.179 (0.153) -0.094 (0.287)
Language Other than English 0.060 (0.733) -0.211 (0.138) Percent of Labor Unemployed 0.059 (0.275) 0.342 (0.517) Percent of Labor Employed 0.149 (0.193) -0.688 (0.363) Median Travel Time to Work 0.313 (0.356) 0.185 (0.669) Median Household Income 0.623 (0.184) ** 0.694 (0.346) * Families in Poverty 0.571 (0.245) * 0.226 (0.461) Individuals in Poverty -0.486 (0.264) -0.499 (0.497) N 176 176 F-Statistic 4.85 1.49 R² 0.3429 0.1054 Adjusted R² 0.2722 0.138 *p < 0.05, ** p < 0.01
Standard errors are given in parentheses next to coefficients.
In regards to the F-test, Model A is statistically significant at the 0.001 probability level with a F-statistic of 4.85. Therefore, at least one independent variable in this model has a linear relationship with the dependent variable. A Ramsey RESET test found that the models have no omitted variables. In regards to heteroskedasticity, the null hypothesis that the distribution is normal, failed to be rejected on the basis of the result of the Breusch-
3The dependent variable in Model A is the change in the number of businesses per
Zip Code from 1998 to 2007.
4 The dependent variable in Model B is the change in the number of employees per Zip Code from 1998 to 2007.
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Pagan/ Cook-Weisberg test. Therefore, there is heteroskedasticity in Model A.
Multicollinearity does not appear to be an issue with a relatively low Variance Inflation Factor of 4.42. Further testing suggests that there are no omitted variables. The joint Skewness/Kurtosis test for normality produced a small probability level in which case, the null hypothesis that there is no skewness can be rejected.
The independent variables found to be statistically significant at α=0.05 in Model A are Tenure, Median Household Income, and Families in Poverty. The variable TENURE was significant at alpha level α=0.01, as was the Median Household Income. The variable
TENURE had a surprising negative influence on the rate of business growth. For every
unit increase in TENURE, the percentage change in the number of businesses or CHGBIZ, decreased by -0.532, holding all other variables constant.
For instance, if the number of residents residing in the same house five years ago increases by one percentage point, than the change in the number of businesses in that zip code from 1998 to 2007 is expected to decrease by a little more than half a percentage point. Communities with higher levels of housing tenure or relatively stable resident population would therefore experience lower rates of business growth. The variable
TENURE has a negative impact on CHGBIZ, thus it strengthens the argument made by
government auditors and scholars (e.g. GAO, 2006 and Busso and Kline, 2008) that employment gains may actually be attributed to gentrification and neighborhood turnover.
4.5 Conclusion
This chapter evaluated the statistical impact of the Empowerment Zones on local business growth, as measured by the percentage change in the number of business establishments and employees from 1998 to 2007. The presence of an EZ designated census tract within a given zip code was not found to be statistically significant in either model, at the 5% significance level. The variables found to be significant in Model A
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(CHGBIZ) are the percentage living in the same house in 1995 (TENURE), the average household annual income (AVGINC), and the percentage of families living in poverty (FAMPOV). Only the variable AVGINC was found to be significant in Model B (CHGEMP). On the basis of these findings, it appears that a one-unit increase in the average household income will have a slight positive impact on the percentage change in the number of businesses and employees, holding all other variables constant.
Despite media reports, academic papers, and government audits that raised serious issues of accountability and responsiveness regarding the initiative, the United States’ Renewal Communities, Empowerment Zones, and Enterprise Communities Initiative (RC/EZ/EC) program continued to expand. A timeline on HUD’s website highlighted a $19 billion package of EZ/EC and Gulf Opportunity Zones tax incentives in 2006 and another $11 billion in tax credits and deductions that were made available to businesses. In December 2010, President Obama retroactively extended the EZ tax incentives until December 31, 2011, two years beyond their original deadline.
In the current economic and political climate, it remains unclear whether or not the program will be reestablished at some point. However, until the agencies responsible for its implementation, like HUD and IRS, are able to successfully collaborate and develop a system for tracking and verifying the use of tax incentives by corporations, the true value and effectiveness of the Community Renewal Initiative will remain elusive. Even if the regression analyses had shown that the EZ presence had a statistically significant impact on the change in the number of business establishments or employees, it would not be possible to discern what aspect of the program had the greatest influence using empirical methods. However, regression is useful for testing the significance of the expected relationship between the dependent and independent variables.
The only independent variable that had a statistically significant impact on the change in the number of businesses and employees (Model A and Model B, respectively)
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was the average household income. As the average household income increases in a given community, the number of businesses and employees is also expected to rise. Based on these findings, it appears that the best way to promote business and employment growth in these communities is to reduce the level of poverty, however it is difficult to ascertain whether the increase in household income is a result of business and employment growth and not vice versa.
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