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Estimating Wal-Mart's Impacts in Maryland: A Test of Identification Strategies and Endogeneity Tests

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Abstract

In this paper, I estimate the impact of Wal-Mart on labor markets in Maryland. My goal is to compare estimation techniques that incorporate corrections for endogeneity of Wal-Mart's entrance and those that test for and fail to reject exogeneity in Wal-Mart's entrance decision. The instrumental variable approaches I test include those offered by Basker and Neumark et al., and a new test introduced in this paper. I also explain why differences in choice of sample time and location may lead to different findings as to the impact of Wal-Mart. I find that there is weak evidence of endogeneity in Wal-Mart's entrance decision, but that the bias is opposite of that anticipated by most researchers. Most interestingly, there are no significant differences across instrumental variable techniques employed in the literature. As for Wal-Mart in Maryland, that exposure to Wal-Mart leads to lower retail employment (from zero to 414 retail jobs), but significantly higher retail wages (as much as $1.95 per hour) at the county level. I also find that exposure to Wal-Mart has no effect on aggregate labor markets, though aggregate wages are positively affected, although the impact is very small (roughly $160 per year). I recommend that Maryland adopt a policy neutral approach to Wal-Mart.

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Notes

  1. For non-econometric studies see Artz [1999], Artz and McConnon [2001], Barnes and Connell [1996], Franz and Robb [1989], Hornbeck [1994], Ketchum and Hughes [1997], McGee and Gresham [1995], Stone [1988, 1995, 1997], and Stone et al. [1992].

  2. The real estate research literature describes this as demand externalities. See Eppli and Benjamin [1994]. This is also highly consistent with the findings of Hicks and Wilburn [2001] and Basker [2005a, 2005b].

  3. Basker painstakingly reproduced data on Wal-Mart from commercial maps that suffered unanticipated errors; these errors were not identified until Neumark, Zhang, and Cicarella (NZC) [2005]. Dube and Jacobs [2005] employed NZC's instrument on Basker's data and found similar results to those of NZC. Hicks [2005, 2007a] employed an instrument similar to Basker's on Ohio counties and found similar (though not directly comparable) results to Basker. Hicks’ paper could be viewed as suffering the same identification critique as those leveled at Basker by, among others, Neumark et al. [2005].

  4. Generalizability of these results to large regions may also not be possible given the heterogeneity in local fiscal structure as noted by Wassmer [2002].

  5. In a December 6, 2005, radio broadcast on WUNC, the North Carolina Public Broadcasting show, ‘The State of Things,’ Glen Wilkins, community affairs manager for the southeast region of Wal-Mart, identified market size as a location choice consideration. Graff [1998] suggests that location decisions for Supercenters are expressly linked to mid-sized towns in less densely populated areas proximal to other Wal-Mart stores (where the firm is already known).

  6. The November 4, 2005 conference, hosted by Global Insight, was memorable for the opportunity several of the paper presenters had to explain endogeneity to the national media representatives.

  7. Several discussions with local developers over the past few years lad me to believe that two important facets of Wal-Mart entrance bear into the choice of instrumentation. First, Wal-Mart is not choosing locations, but rather choosing developers to choose locations. There are many different developers, even within the same geographic regions. Second, the intra-county location choices seem to matter more to the developers than the inter-county choices.

  8. These results are available from the author.

  9. Interestingly, this corresponds to my observations when first speaking publicly about my Wal-Mart at a Richmond FRB conference in rural West Virginia, I was told that a new Wal-Mart hired workers in town by offering Kmart workers $1 more an hour in the parking lot during shift change. This range is somewhat larger than my estimates of new hire wages in selected Pennsylvania counties 2001–2004 [see Hicks 2007b].

  10. The rather high adjusted goodness of fit in these models is most likely due to the very high intertemporal correlation captured by the autoregressive component.

  11. Many studies, particularly those provided to local governments, estimate local fiscal effects of a new Wal-Mart (or other similar retail outlet) focusing on a very small region. These studies are designed to answer very specific questions and so any criticism of them should be viewed within this light.

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Acknowledgements

I thank three anonymous referees and the editor of this journal. I also thank Wal-Mart for making these data available. Any errors are, of course, my own. I also want to make clear that I have no financial relationship with Wal-Mart other than as an occasional consumer (primarily of diapers).

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  1. Ball State University,

    Michael J Hicks

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Appendix A

Appendix A

Table A1, Table A2

Table a1 Coefficient values in models with time-state dummy (Coefficients for Wal-Mart exposure only, t-statistics in parentheses)
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Table a2 Coefficient values in retail employment urban/rural models (Coefficients for Wal-Mart exposure only, t-statistics in parentheses)
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Hicks, M. Estimating Wal-Mart's Impacts in Maryland: A Test of Identification Strategies and Endogeneity Tests. Eastern Econ J 34, 56–73 (2008). https://doi.org/10.1057/palgrave.eej.9050002

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