Another Look at 'Coveting Thy Neighbor's Manufacturing'
38 Pages Posted: 16 Mar 2014
Date Written: March 14, 2014
Abstract
Goolsbee and Maydew (2000) reported that lowering the weight on payroll in states’ corporate income tax apportionment formulae had the potential to raise manufacturing employment. Their analyses continue to be cited in academic articles and are still influential in the policy debate. I gather data and attempt to replicate their analyses and findings. I identify an apparent but inconsequential error in G&M’s sample and I replicate the most widely cited result in the original paper. Other results are substantively but not quantitatively replicated. I show that G&M’s results are sensitive to relatively arbitrary choices about the sample that is used.
I argue that the most cited result in the paper does not come from the most preferred econometric specification and that when the most preferred econometric specification is used G&M’s original paper found no statistically significant evidence that lowering the apportionment weight on payroll raises employment. Similarly when I use this specification with data covering the period G&M studied (1978 to 1994) I find no statistically significant evidence for this hypothesis. When I extend the data set forward in time to 2010 and rerun the same specifications I find results similar to those found with the earlier data but I find increased statistical significance when standard errors are not clustered by state. When standard errors are clustered by state, as is now common econometric practice, none of the key estimated coefficients are statistically significant. I get very similar results whether I use manufacturing employment or manufacturing payroll as the dependent variable.
In summary, econometric evidence to support the hypothesis that changes in the payroll weight affected the distribution of manufacturing employment among US states in the 1978 to 1994 period appears less strong than G&M asserted even when using G&M’s data and methods. However, more recent data lends some support to G&M’s conclusion but the econometric evidence is still weak by current standards.
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