Proponents of state and federal minimum wage increases argue that past minimum wage hikes have not adversely affected retail employment. However, the existing empirical evidence is mixed. This study uses monthly data from the 1979–2004 Current Population Survey to provide new estimates of the effect of minimum wage increases on retail employment and hours worked. The findings suggest evidence of modest adverse effects. A 10% increase in the minimum wage is associated with a 1% decline in retail trade employment and usual weekly hours worked. Larger negative employment and hours effects are observed for the least experienced workers in the retail sector. These results are robust across a number of specifications, but are sensitive to controls for state time trends.
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Policy Matters Ohio (2006) released a report suggesting similar conclusions.
Card (1992) also uses data from the Current Population Survey to compare workers’ wages, hours, and earnings in California versus workers in comparison states. He finds that wages and earnings for retail trade workers grew faster in California than in other states and attributes this growth, in part, to the California minimum wage hike.
The California minimum wage hike became law in July 1988.
Two additional sets of results by Kim and Taylor (1995) are presented to bolster this claim. First, they estimate a similar set of models to the ones described above using inter-county changes in wages and employment that also control for changes in county retail sales. The results again suggest adverse retail employment effects from the state minimum wage hike. Second, the authors estimate a set of models for earlier time periods (1985–1988) prior to the passage of the California minimum wage hike. In these models there is no evidence that increase in wages reduced employment, bolstering the claim that it was, in fact, the exogenous minimum wage hike of July 1988 that caused the retail employment decline.
A set of unpublished reports from the pro-minimum wage Fiscal Policies Institute (2004; 2006) follow a similar approach. The FPI reports compare retail employment growth in states that raised their minimum wages to retail employment growth in states that did not using data from the US Commerce Department’s County Business Patterns (CBP) series. The 2006 report uses a simple difference-in-difference approach using the years 1998 and 2006 and finds that retail employment growth was actually faster in states that raised minimum wages, though the authors do not report standard errors for a test of statistical significance. Using a similar approach, the 2004 FPI study concluded that “retail employment grew by 6.1 percent in minimum wage states versus 1.9 percent in other states.” The results of the Fiscal Policies Institute study have been publicized in the mainstream media (see, for example, New York Newsday 2006) and have been cited by numerous advocates of minimum wage increases at both the federal and state levels. In 2004, Dr. Jared Bernstein, a senior economist at the Economic Policy Institute, testified before the US House Subcommittee on Workforce, Empowerment, and Government Programs that a federal minimum wage hike would not have adverse effects on retail employment, citing the FPI study’s results on retail employment as evidence for his position. Several advocates of state minimum wage hikes have also cited the conclusions of the FPI study (see, for example, CSCILR 2004 for a discussion of the California minimum wage hike; Hill 2005 for Maryland; Hertzberg, 2005 for Pennsylvania; and Conti 2004 for Washington, DC). Despite this political attention, there are several important problems with the methodology employed in the FPI studies. First, the analyses fail to control for changes in socioeconomic or demographic characteristics that could confound the relationship between minimum wage increases and changes in retail employment, resulting in biased estimates. In fact, there are no controls and no regression analyses; only point estimates are presented. Second, the FPI studies assume that among states that raise their minimum wages, the magnitudes of these increases are identical and that the timing of their implementation is identical. Because the authors do not distinguish among differences in magnitudes of state minimum wage increases or differences in implementation time (or firm adjustment time), minimum wage effects may be biased. Third, the FPI studies only examine employment effects, which may obscure full labor demand effects such as hours adjustments. And finally, the authors examine a fairly short panel, which may not produce results that are generalizable over periods of both macroeconomic growth and recession.
In a few specifications, the authors also include data from 1990.
Comparable measures of retail employment were created during the period when the CPS switched from the Standard Industrial Classification (SIC) system to the North American Industry Classification System (NAICS). In the MORG data, from 1979 to 2002, consistent SIC information is provided and from 2000 to 2004, consistent NAICS information is provided. The robustness of results to this recoding of industries is discussed in the text below.
Data from November 2004 are not available in the MORG files obtained by the author.
For the first robustness check, states are included in the sample if they provided 300 (or 400) observations in January 1979, January 1980, January 1990, and January 2000. For the second robustness check, it is important to note that models that weight by number of observations in each cell will produce estimates that are representative of workers rather than state populations.
Disaggregating retail employment data using two-digit industry codes introduces a great deal more measurement error in the dependent variable, particularly for smaller states. Using CBP data, Partridge and Partridge (1999) find that minimum wages have the strongest adverse employment effects among non-restaurant employment. See Partridge and Partridge (1999; p. 406) for a discussion of how the tipped-employee credit may explain this result.
Means are weighted by overall state population. These variables are similar to those used by Burkhauser et al. (2000a, b). Approximately 1% of the sample has missing observations on employment. Missing information is coded using one-month lagged state-specific employment ratios. Results are statistically equivalent if these observations are omitted from the analysis.
In the wage regressions (Table 2), the controls operate in the expected theoretical direction. Higher mean wages are associated with higher retail wages; the share of teens in the population is associated with lower wages, and the overall unemployment rate is negatively (but not significantly) associated with retail wages. Employment regressions in Table 3 also yield fairly expected results. Higher unemployment rates are negatively associated with retail employment ratios and the share of teens in the population is positively associated with retail employment. A somewhat surprising finding is that the mean adult wage rate is negatively associated with retail employment. One might expect that higher wages would increase retail employment as lower-skilled workers look comparatively more attractive to employers. However, because the average wage rate variable is measured across industries, this could reflect that when mean wages rise, workers move out of the low-wage retail sector and toward other higher-wage sectors. But further investigation reveals that this is not the full story. In alternate regressions that also include the average retail sector wage, there is still a negative correlation between retail wages and employment, although the effect is smaller in magnitude. This could suggest that firms respond to rising wages by substituting away from labor and toward relatively cheaper capital. For example, an employer at a grocery store might substitute away from hiring cashiers and toward technologies that permit self check-out by consumers.
Note that the inclusion of year effects in the specification controls for national inflationary effects.
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The author thanks Rich Burkhauser, David Macpherson, and David Neumark for their comments on earlier version of this paper. Thanks also to Jean Roth at the National Bureau of Economic Research for assistance with the Current Population Survey (CPS) Merged Outgoing Rotation Group (MORG) data and to Deb Templeton for excellent editorial assistance. This study was funded in part by the Employment Policies Institute. The views expressed in this paper do not necessarily reflect their views. All errors are the author’s.
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Sabia, J.J. The Effects of Minimum Wage Increases on Retail Employment and Hours: New Evidence from Monthly CPS Data. J Labor Res 30, 75–97 (2009). https://doi.org/10.1007/s12122-008-9054-1
- Minimum wage
- Retail trade