Research on Labor Demand Elasticity and the Minimum Wage

Overview of Results Overview of Results Some studies in the 1960s found no relationship between minimum wage (MW) and employment (E). In the 1970s, studies confirmed the negative relationship between MW and teen E. Brown (1999) – Survey of studies Elasticity of teen E with respect to MW= -0.1 to -0.3 i.e., 10% increase in MW  1-3% decrease in teen E Until the 1990s, generally accepted that increases in MW modestly reduced E of teens.

Overview of selected results (cont.) Overview of selected results (cont.) Studies in the 1990s began to find no negative relationship between MW and E. Series of articles by David Card, Alan Kruger, and colleagues showed no effect, or even a positive effect, of MW on teen E. Collective volume edited by Card and Kruger, Myth and Measurement: The New Economics of the Minimum Wage, NJ: Princeton University Press, Most well-known: Card and Kruger (1994).

Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania David Card and Alan B. Krueger American Economic Review 84(4), September 1994:

Question of InterestQuestion of Interest “How do employers in a low-wage labor market respond to an increase in the minimum wage?” ApproachApproach Compare employment of teenagers in New Jersey and eastern Pennsylvania before and after the increase in the minimum wage in NJ from $4.25 to $5.05 on April 1, Methods of Analysis Methods of Analysis Difference-in-Differences Regression Analysis

DataData Phone survey of fast-food restaurants in NJ and eastern Penn (personal interview for 28 stores in wave 2) Wave 1: late Feb. and early Mar Wave 2: Nov. and Dec Restaurants: Burger King, KFC, Wendy’s and Roy Rogers 371 restaurants were interviewed in both waves What if employment increased when the MW in NJ increased? Did the increase in MW cause the increase in employment?

“Correlation does not mean causation.”“Correlation does not mean causation.” Could be that econ conds improved, which caused E to go up. Difference-in-Differences ApproachDifference-in-Differences Approach Premise – Economic conditions in NJ and eastern Penn are the same. Compare E change in NJ before and after the MW change, with the E change in eastern Penn in the same time period. If NJ and eastern Penn E grow at the same rate, MW would have had no effect. If E in Penn grew or stayed the same, and E in NJ fell  evidence that MW decreases E.

Results of Difference-in-Difference AnalysisResults of Difference-in-Difference Analysis Employment in Typical Fast-Food Restaurants (in FTEs) NJE Penn Before change After change Difference Difference-in-Differences = 0.6 – (-2.1) = 2.7 NJ: Employment increased after MW. E Penn: Employment decreased after MW  depressed economy in E Penn and NJ. Despite declining economic conditions, in E Penn (and presumably NJ), employment increased in NJ.

Regression AnalysisRegression Analysis Equation (1a):  E = a + bX + cNJ  E = change in employment from wave 1 to wave 2 at a given restaurant X = set of characteristics of the restaurant NJ = 1 if restaurant is in New Jersey; NJ = 0 if restaurant is in eastern Pennsylvania. If c < 0,  E lower for NJ than for Penn restaurants after the MW If c > 0,  E higher for NJ If c = 0, no difference in the change in E

Equation (1b):  E = a’ + b’X + c’GAP GAP = 0 for stores in Penn GAP = 0 for stores in NJ with W 1  $5.15 GAP = (5.05 – W 1 )/ W 1 for other stores in NJ GAP is the proportional increase in wages needed to meet the new MW. If c’ < 0, an increase in the required wage hike, results in a negative change in employment. If c’ > 0,  E higher as stores have to pay more to meet the MW requirement. If c’ = 0, no difference in the change in E for stores that have to increase wages more.

Regression ResultsRegression Results Equation (1a):  E = a + bX + cNJ c >0 Equation (1b):  E = a’ + b’X + c’GAP c’ >0 Indicates MW is positively associated with  E. Results robust across many specification tests. ConclusionConclusion April, 1992 rise in the MW did not decrease employment of teens in fast-food restaurants in New Jersey.

Why Counter-Intuitive Result?Why Counter-Intuitive Result? Survey data may not accurately measure actual employment. (Neumark and Wachter (2000) use establishment data with same methodology and find a zero or slightly negative effect.) Fast-food restaurants may not be representative of low-wage employers, e.g., there may be fewer opportunities to substitute capital for labor. Employers may need more time to adjust to minimum wage changes than comparing just before and just after a change.

Why Counter-Intuitive Result?Why Counter-Intuitive Result? Economic health of the fast-food market in E Penn may be an imperfect match for NJ. Adjustment may begin before MW takes effect.

BACKLASH

A Reassessment of the New Economics of the Minimum Wage Literature with Monthly Data from the Current Population Survey Burkhauser, Robert V., Kenneth A. Couch and David C. Wittenburg, Journal of Labor Economics, 18(4), October 2000, pp

Purpose of the Paper: Estimate the employment effects of increases in the minimum wage in the 1990s. Re-estimate the empirical specifications used by Card, Krueger and colleagues (1995) showing no adverse effects of the minimum wage.

Suppose that we want to find the impact of an increase in the minimum wage in 1990 on the teen employment ratio. Model 1:E it = B 0 + B 1 T where E it = teen employment/teen population in state i in year t T 90 = 1 in 1990; T 90 = 0 in the other years of the data set B 1 = the change in the teen employment ratio before and after the change in the minimum wage What else does B 1 capture?

Card and Krueger find no or sometimes even a positive effect of minimum wages on the teen employment ratio.

Data: May Current Population Survey, Problem of Card and Krueger’s analysis: Minimum wages rarely change more than once per year. Time dummies are highly correlated with MW. Time dummies are likely capturing part of the effect of minimum wages.

Further: the C & K minimum wage variable, MW, is actually DIFF = State Minimum Wage – Federal Minimum Wage when time dummies are included in the model  the coefficient on the MW variable shows the impact of the difference between the federal and state minimum wage, not the impact of the minimum wage on teen employment ratios.

Burkhauser empirical specifications Use monthly CPS data, rather than annual data, and use more recent time period Add lagged 1 year minimum wage variable Add recession dummy In all cases, deleting the time dummies eliminates positive and zero effects of the minimum wage on employment ratios.

Burkhauser Conclusion Teen employment elasticity ranges from -0.2 to Who is right? Does it matter?