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Home , Alan Manning, David Card, KFC, Minimum wage, New Jersey, Pennsylvania

Minimum and : A Case Study of the Fast-Food Industry in New and

On , 1992, 's minimum from $4.25 to $5.05 per . To evaluate the impact of the we surveyed 410 fast-food in New Jersey and eastern Pennsylvania before and after the rise. Comparisons of employment growth at stores in New Jersey and Pennsylvania (where the was constant) provide simple estimates of the effect of the higher minimum wage. We also compare employment changes at stores in New Jersey that were initially paying high wages (above $5) to the changes at lower-wage stores. We find no indication that the rise in the minimum wage reduced employment. (JEL 530, 523)

How do employers in a low-wage labor cent studies that rely on a similar compara- respond to an increase in the mini- tive methodology have failed to detect a mum wage? The prediction from conven- negative employment effect of higher mini- tional economic theory is unambiguous: a mum wages. Analyses of the 1990-1991 in- rise in the minimum wage leads perfectly creases in the federal minimum wage competitive employers to cut employment (Lawrence F. Katz and Krueger, 1992; Card, (George J. Stigler, 1946). Although studies 1992a) and of an earlier increase in the in the 1970's based on aggregate teenage minimum wage in (Card, 1992b) employment rates usually confirmed this find no adverse employment impact. A study prediction,' earlier studies based on com- of minimum-wage floors in Britain (Stephen parisons of employment at affected and un- Machin and , 1994) reaches a affected establishments often did not (e.g., similar conclusion. Richard A. Lester, 1960, 1964). Several re- This paper presents new evidence on the effect of minimum wages on establishment- level employment outcomes. We analyze the experiences of 410 fast-food restaurants in *Department of , , New Jersey and Pennsylvania following the Princeton, NJ 08544. We are grateful to the Institute increase in New Jersey's minimum wage for Research on , University of , for from $4.25 to $5.05 per hour. Comparisons partial financial support. Thanks to , Charles Brown, Richard Lester, Gary Solon, two of employment, wages, and at stores anonymous referees, and seminar participants at in New Jersey and Pennsylvania before and Princeton, State, A&M, University of after the rise offer a simple method for Michigan, university of Pennsylvania, ~niversitJ of evaluating the effects of the-minimum wage. , and the NBER for comments and sugges- ~~~~~~i~~~~ within N~~ jerseybetween tions. We also acknowledge the expert research assis- tance of Susan Belden, Chris Burris, Geraldine Harris, high-wage paying and Jonathan Orszag. than the new minimum rate prior to its 'see Charles Brown et al. (1982,1983) for surveys of effective date) and other stores provide an this literature. A recent update (Allison J. Wellington, alternative estimate of the impact of the 1991) concludes that the employment effects of the minimum wage are negative but small: a 10-percent new lawe increase in the minimum is estimated to lower teenage In addition to the simplicity of our empir- employment rates by 0.06 percentage points. ical methodology, several other features of 772 VOL. 84 NO. 4 CARD AND KRUEGER: MINIMUM WAGE AND EMPLOYMENT 773 the New Jersey law and our data set are and 1991 to measures of the relative mini- also significant. First, the rise in the mini- mum wage in each state. mum wage occurred during a . The increase had been legislated two years ear- I. The New Jersey Law lier when the state economy was relatively healthy. By the time of the actual increase, A bill signed into law in November 1989 the rate in New Jersey had raised the federal minimum wage from $3.35 risen substantially and last-minute political per hour to $3.80 effective April 1, 1990, action almost succeeded in reducing the with a further increase to $4.25 per hour on minimum-wage increase. is unlikely that April 1, 1991. In early 1990 the New Jersey the effects of the higher minimum wage went one step further, enacting were obscured by a rising tide of parallel increases in the state minimum wage economic conditions. for 1990 and 1991 and an increase to $5.05 Second, New Jersey is a relatively small per hour effective April 1, 1992. The sched- state with an economy that is closely linked uled 1992 increase gave New Jersey the to nearby states. We believe that a control highest state minimum wage in the country group of fast-food stores in eastern Pennsyl- and was strongly opposed by lead- vania forms a natural basis for comparison ers in the state (see Bureau of National with the experiences of restaurants in New Affairs, Daily Labor Report, 5 May 1990). Jersey. Wage variation across stores in New In the two years between passage of the Jersey, however, allows us to compare the $5.05 minimum wage and its effective date, experiences of high-wage and low-wage New Jersey's economy slipped into reces- stores within New Jersey and to test the sion. Concerned with the potentially ad- validity of the Pennsylvania control group. verse impact of a higher minimum wage, the Moreover, since seasonal patterns of em- state legislature voted in 1992 to ployment are similar in New Jersey and phase in the 80-cent increase over two years. eastern Pennsylvania, as well as across The vote fell just short of the margin re- high- and low-wage stores within New Jer- quired to override a gubernatorial veto, and sey, our comparative methodology effec- the Governor allowed the $5.05 rate to go tively "differences out" any. seasonal em- into effect on April 1 before vetoing the ployment effects. two-step legislation. Faced with the prospect Third, we successfully followed nearly 100 of having to roll back wages for minimum- percent of stores from a first wave of inter- wage earners, the legislature dropped the views conducted just before the rise in the issue. Despite a strong last-minute chal- minimum wage (in February and March lenge, the $5.05 minimum rate took effect 1992) to a second wave conducted 7-8 as originally planned. months after (in November and December 1992). We have complete information on 11. Sample Design and store closings and take account of employ- ment changes at the closed stores in our Early in 1992 we decided to evaluate the analyses. We therefore measure the overall impending increase in the New Jersey mini- effect of the minimum wage on average mum wage by surveying fast-food restau- employment, and not simply its effect on rants in New Jersey and eastern Pennsylva- surviving establishments. niae2 Our choice of the fast-food industry -Our analysis of employment trends at was driven by several factors. First, fast-food stores that were open for business before stores are a leading employer of low-wage the increase in the minimum wage ignores workers: in 1987, franchised restaurants em- any potential effect of minimum wages on the rate of new store openings. To assess the likely magnitude of this effect we relate state-specific growth rates in the number of 2At the time we were uncertain whether the $5.05 McDonald's fast-food outlets between 1986 rate would go into effect or be overridden. THE SEPTEMBER 1994

Stores in: A1 l NJ PA Waue I, February 15-, 1992:

Number of stores in sample frame:a 473 364 109 Number of refusals: 63 33 30 Number interviewed: 410 33 1 79 Response rate (percentage): 86.7 90.9 72.5

Wace 2, Nocember 5- December 31, 1992:

Number of stores in sample frame: 410 331 79 Number closed: 6 5 1 Number under rennovation: 2 2 0 Number temporarily closed:' 2 2 0 Number of refusals: 1 1 0 Number intervie~ed:~ 399 321 78 aStores with working phone numbers only; 29 stores in original sample frame had disconnected phone numbers. '~ncludes one store closed because of highway construction and one store closed because of a fire. 'Includes 371 phone interviews and 28 personal interviews of stores that refused an initial request for a phone interview. ployed 25 percent of all workers in the rants in New Jersey and eastern Pennsylva- industry (see U.S. Department of nia from the , KFC, Wendy's, Commerce, 1990 table 13). Second, fast-food and Roy Rogers chain^.^ The first wave of restaurants comply with minimum-wage reg- the survey was conducted by telephone in ulations and would be expected to raise late February and early March 1992, a little wages in response to a rise in the minimum over a month before the scheduled increase wage. Third, the requirements and in New Jersey's minimum wage. The survey products of fast-food restaurants are rela- included questions on employment, starting tively homogeneous, making it easier to ob- wages, prices, and other store characteris- tain reliable measures of employment, tic~.~ wages, and product prices. The absence of Table 1shows that 473 stores in our sam- tips greatly simplifies the measurement of ple frame had working telephone numbers wages in the industry. Fourth, it is relatively when we tried to reach them in February- easy to construct a sample frame of fran- March 1992. Restaurants were called as chised restaurants. Finally, past experience many as nine times to elicit a response. We (Katz and Krueger, 1992) suggested that obtained completed interviews (with some fast-food restaurants have high response item nonresponse) from 410 of the restau- rates to telephone survey^.^ rants, for an overall response rate of 87 Based on these considerations we con- percent. The response rate was higher in structed a sample frame of fast-food restau- New Jersey (91 percent) than in Pennsylva-

4~hesample was derived from white-pages tele- 3~na pilot survey Katz and Krueger (1992) obtained phone listings for New Jersey and Pennsylvania as of very low response rates from McDonald's restaurants. February 1992. For this reason, McDonald's restaurants were excluded 'copies of the questionnaires used in both of from Katz and Krueger's and our sample frames. the survey are available from the authors upon request. VOL.84 NO. 4 CAmAND KRUEGER: MINIiiMUM WAGE AND EMPLOYMENT 775 nia (72.5 percent) because our interviewer nently closed stores but is treated as missing made fewer call-backs to nonrespondents in for the temporarily closed stores. (Full- Penn~ylvania.~In the analysis below we in- time-equivalent [FTE] employment was cal- vestigate possible biases associated with the culated as the number of full-time workers degree of difficulty in obtaining the first- [including managers] plus 0.5 times the wave interview. number of part-time workers.)' Means are The second wave of the survey was con- presented separately for stores in New Jer- ducted in November and December 1992, sey and Pennsylvania, along with t statistics about eight months after the minimum-wage for the null hypothesis that the means are increase. Only the 410 stores that re- equal in the two states. sponded in the first wave were contacted in Rows la-e show the of stores the second round of interviews. We success- by chain and ownership status (company- fully interviewed 371 (90 percent) of these owned versus franchisee-owned). The stores by phone in November 1992. Because Burger King, Roy Rogers, and Wendy's of a concern that nonresponding restaurants stores in our sample have similar average might have closed, we hired an interviewer food prices, store , and employment to drive to each of the 39 nonrespondents levels. The KFC stores are smaller and are and determine whether the store was still open for fewer hours. They also offer a open, and to conduct a personal interview if more expensive main course than stores in possible. The interviewer discovered that six the other chains (chicken vs, ). restaurants were permanently closed, two In wave 1, average employment was 23.3 were temporarily closed (one because of a full-time equivalent workers per store in fire, one because of road construction), and Pennsylvania, compared with an average of two were under renovation.' Of the 29 stores 20.4 in New Jersey. Starting wages were open for business, all but one granted a very similar among stores in the two states, request for a personal interview. As a re- although the average of a "full meal" sult, we have second-wave interview data (medium soda, small fries, and an entree) for 99.8 percent of the restaurants that re- was significantly higher in New Jersey. There sponded in the first wave of the survey, and were no significant cross-state differences in information on closure status for 100 per- average hours of operation, the fraction of cent of the sample. full-time workers, or the prevalence of bonus Table 2 presents the means for several programs to recruit new worker^.^ key variables in our data set, averaged over The average starting wage at fast-food the subset of nonmissing responses for each restaurants in New Jersey increased by 10 variable. In constructing the means, employ- percent following the rise in the minimum ment in wave 2 is set to 0 for the perma- wage. Further insight into this change is provided in Figure 1, which shows the dis- tributions of starting wages in the two states before and after the rise. In wave 1, the distributions in New Jersey and Pennsylva- 6~esponserates per call-back were almost identical nia were very similar. By wave 2 virtually all in the two states. Among New Jersey stores, 44.5 percent responded on the first call, and 72.0 percent responded after at most two call-backs. Among Penn- sylvania stores 42.2 percent responded on the first call, 'we discuss the sensitivity of our results to alterna- and 71.6 percent responded after at most two call- tive assumptions on the measurement of employment backs. in Section 111-C. 7~sof April 1993 the store closed because of road '~hese programs offer current employees a construction and one of the stores closed for renova- "bounty" for recruiting any new employee who stays tion had reopened. The store closed by fire was open on the job for a minimum period of time. Typical when our telephone interviewer called in November bounties are $50-$75. Recruiting programs that award 1992 but refused the interview. By the time of the the recruiter with an "employee of the month" desig- follow-up personal interview a mall fire had closed the nation or other noncash bonuses are excluded from our store. tabulations. THE AMERICAN ECONOMIC REVIEW SEPTEMBER 1994

Stores in: Variable NJ PA ta 1. Distribution of Store Types (percentages):

a. Burger King b. KFC c. Roy Rogers d. Wendy's e. Company-owned

2. Means in Wave I:

a. FTE employment 20.4 (0.51) b. Percentage full-time employees 32.8 (1.3) c. Starting wage 4.61 (0.02) d. Wage = $4.25 (percentage) 30.5 (2.5) e. Price of full meal

f. Hours open (weekday)

g. Recruiting bonus

3. Means in Ware 2:

a. FTE employment 21.0 21.2 -0.2 (0.52) (0.94) b. Percentage full-time employees 35.9 30.4 1.8 (1.4) (2.8) c. Starting wage 5.08 4.62 10.8 (0.01) (0.04) d. Wage = $4.25 (percentage) 0.0 25.3 - (4.9) e. Wage = $5.05 (percentage) 85.2 1.3 36.1 (2.0) (1.3) f. Price of full meal 3.41 3.03 5.0 (0.04) (0.07) g. Hours open (weekday) 14.4 14.7 -0.8 (0.2) (0.3) h. Recruiting bonus 20.3 23.4 - 0.6 (2.3) (4.9) Notes: See text for definitions. Standard errors are given in parentheses. aTest of equality of means in New Jersey and Pennsylvania.

restaurants in New Jersey that had been Despite the increase in wages, full-time- paying less than $5.05 per hour reported a equivalent employment increased in New starting wage equal to the new rate. Inter- Jersey relative to Pennsylvania. Whereas estingly, the minimum-wage increase had no New Jersey stores were initially smaller, apparent "" on higher-wage restau- employment gains in New Jersey coupled rants in the state: the mean percentage wage with losses in Pennsylvania led to a small change for these stores was -3.1 percent. and statistically insignificant interstate VOL. 84 NO. 4 CARD AND KRUEGER: MINIMUM WAGE AND EMPLOYMENT

February 1992

Wage Range

November 1 9 9 2

Wage Range

New Jersey Pennsylvania

FIGURE1. DISTRIBUTIONOF STARTING WAGE RATES 778 THE AMERICAN ECONOMIC REVIEW SEPTEMBER I994 difference in wave 2. Only two other vari- our survey. We present data by state in ables show a relative change between waves columns (i) and (ii), and for stores in New 1 and 2: the fraction of full-time employees Jersey classified by whether the starting and the price of a meal. Both variables wage in wave 1 was exactly $4.25 per hour increased in New Jersey relative to Pennsyl- [column (iv)] between $4.26 and $4.99 per vania. hour [column (v)] or $5.00 or more per hour We can assess the reliability of our survey [column (vi)]. We also show the differences questionnaire by comparing the responses in average employment between New Jersey of 11 stores that were inadvertently inter- and Pennsylvania stores [column (iii)] and viewed twice in the first wave of the survey.10 between stores in the various wage ranges Assuming that measurement errors in the in New Jersey [columns (viil-(viii)]. two interviews are independent of each Row 3 of the table presents the changes other and independent of the true variable, in average employment between waves 1 the correlation between responses gives an and 2. These entries are simply the differ- estimate of the "reliability ratio" (the ratio ences between the averages for the two of the variance of the signal to the com- waves (i.e., row 2 minus row 1). An alterna- bined variance of the signal and noise). The tive estimate of the change is presented in estimated reliability ratios are fairly high, row 4: here we have computed the change ranging from 0.70 for full-time equivalent in employment over the subsample of stores employment to 0.98 for the price of a meal." that reported valid employment data in both We have also checked whether stores with waves. We refer to this group of stores as missing data for any key variables are dif- the balanced subsample. Finally, row 5 pre- ferent from restaurants with complete re- sents the average change in employment in sponses. We find that stores with missing the balanced subsample, treating wave-2 data on employment, wages, or prices are employment at the four temporarily closed similar in other respects to stores with com- stores as zero, rather than as missing. plete data. There is a significant size differ- As noted in Table 2, New Jersey stores ential associated with the likelihood of the were initially smaller than their Pennsylva- store closing after wave 1. The six stores nia counterparts but grew relative to Penn- that closed were smaller than other stores sylvania stores after the rise in the mini- (with an average employment of only 12.4 mum wage. The relative gain (the "dif- full-time-equivalent employees in wave 1).12 ference in differences" of the changes in employment) is 2.76 FTE employees (or 13 111. Employment Effects of the percent), with a t statistic of 2.03. Inspec- Minimum-Wage Increase tion of the averages in rows 4 and 5 shows that the relative change between New Jer- A. Differences in Differences sey and Pennsylvania stores is virtually iden- tical when the analysis is restricted to the Table 3 summarizes the levels and balanced subsample, and it is only slightly changes in average employment per store in smaller when wave-2 employment at the temporarily closed stores is treated as zero. Within New Jersey, employment ex- 10These restaurants were interviewed twice because panded at the low-wage stores (those paying their phone numbers appeared in more than one phone $4.25 per hour in wave 1) and contracted at book, and neither the interviewer nor the respondent noticed that they were previously interviewed. the high-wage stores (those paying $5.00 or 11Similar reliability ratios for very similar questions more per hour). Indeed, the average change were obtained by Katz and Krueger (1992). in employment at the high-wage stores ''A probit analysis of the probability of closure (- 2.16 FTE employees) is almost identical shows that the initial size of the store is a significant predictor of closure. The level of starting wages has a to the change among Pennsylvania stores numerically small and statistically insignificant coeffi- ( -2.28 FTE employees). Since high-wage cient in the probit model. stores in New Jersey should have been VOL. 84 NO. 4 CARD AND KRUEGER: MINIMUM WAGE AND EMPLOYMENT largely unaffected by the new minimum els of the form: wage, this comparison provides a specifica- tion test of the validity of the Pennsylvania (la) AE,=a+bXi+cNJi+~, control group. The test is clearly passed. Regardless of whether the affected stores are compared to stores in Pennsylvania or AE, = a' blXi clGAPi E{ high-wage stores in New Jersey, the esti- (lb) + + + mated employment effect of the minimum where AE, is the change in employment wage is similar. from wave 1to wave 2 at store i, Xi is a set The results in Table 3 suggest that em- of characteristics of store i, and NJ, is a ployment contracted between February and dummy variable that equals 1 for stores in November of 1992 at fast-food stores that New Jersey. GAP, is an alternative measure were unaffected by the rise in the minimum of the impact of the minimum wage at store wage (stores in Pennsylvania and stores in i based on the initial wage at that store New Jersey paying $5.00 per hour or more (W,,): in wave 1). We suspect that the reason for this contraction was the continued worsen- GAP, = 0 for stores in Pennsylvania ing of the economies of the middle-Atlantic states during 1992.13 Unemployment rates = 0 for stores in New Jersey with in New Jersey, Pennsylvania, and all trended upward between 1991 and 1993, with a larger increase in New Jersey than Pennsylvania during 1992. Since sales of franchised fast-food restaurants are pro- for other stores in New Jersey. cyclical, the rise in unemployment would be expected to lower fast-food employment in GAP, is the proportional increase in wages the absence of other factors.14 at store i necessary to meet the new mini- mum rate. Variation in GAP, reflects both B. Regression-Adjusted Models the New Jersey-Pennsylvania contrast and differences within New Jersey based on re- The comparisons in Table 3 make no ported starting wages in wave 1. Indeed, the allowance for other sources of variation in of GAP, is a strong predictor of the employment growth, such as differences actual proportional wage change between across chains. These are incorporated in the waves 1 and 2 (R* = 0.75), and conditional estimates in Table 4. The entries in this on GAP, there is no difference in wage table are regression coefficients from mod- behavior between stores in New Jersey and Pennsylvania.l5 The estimate in column (i) of Table 4 is directly comparable to the simple 13 difference-in-differences of employment An alternative possibility is that seasonal factors produce higher employment at fast-food restaurants in changes in column (iv), row 4 of Table 3. February and March than in November and December. The discrepancy between the two An analysis of national employment data for food estimates is due to the restricted sample in preparation and workers, however, shows higher Table 4. In Table 4 and the remaining ta- average employment in the fourth quarter than in the first quarter. bles in this section we restrict our analysis 14To investigate the cyclicality of fast-food restau- to the set of stores with available employ- rant sales we regressed the year-to-year change in U.S. ment and wage data in both waves of the sales of the McDonald's restaurant chain from 1976-1991 on the corresponding change in the unem- ployment rate. The regression results show that a 1-percentage-point increase in the unemployment rate 15~regression of the proportional wage change be- reduces sales by $257 million, with a t statistic of 3.0. tween waves 1 and 2 on GAP, has a coefficient of 1.03. THE AMERICAN ECONOMIC REVlEW SEPTEMBER 1994

TABLE3-AVERAGE EMPLOYMENTPER STOREBEFORE AND I~ERTHE RISE IN NEW JERSEYMINIMUM WAGE

Stores by state Stores in New Jersey a Differences within NJ~ Difference, Wage = Wage = Wage r Low- Midrange- PA NJ NJ-PA $4.25 $4.26-$4.99 $5.00 high high Variable (i) (ii) (iii) (iv) (v) (vi) (vii) (viii) 1. FTE employment before, all available observations 2. FTE employment after, all available observations 3. Change in mean FTE employment 4. Change in mean FTE employment, balanced sample of storesC 5. Change in mean FTE employment, setting FTE at temporarily closed stores to Od Notes: Standard errors are shown in parentheses. The sample consists of all stores with available data on employment. FTE (full-time-equivalent) employment counts each part-time worker as half a full-time worker. Employment at six closed stores is set to zero. Employment at four temporarily closed stores is treated as missing. astares in New Jersey were classified by whether starting wage in wave 1 equals $4.25 per hour (N = 101), is between $4.26 and $4.99 per hour (N = 140), or is $5.00 per hour or higher (N = 73). b~ifferencein employment between low-wage ($4.25 per hour) and high-wage (2$5.00 per hour) stores; and difference in employment between midrange ($4.26-$4.99 per hour) and high-wage stores. 'Subset of stores with available employment data in wave 1 and wave 2. this row only, wave-2 employment at four temporarily closed stores is set to 0. Employment changes are based on the subset of stores with available employment data in wave 1 and wave 2.

TABLE4-REDUCED-FORM MODELSFOR CHANGEIN EMPLOYMENT

Model Independent variable (i) (ii) (iii) (iv) (v) 1. New Jersey dummy 2.33 2.30 - - - (1.19) (1.20) 2. Initial wage gapa - - 15.65 14.92 11.91 (6.08) (6.21) (7.39) 3. Controls for chain and no yes no yes yes ownershipb 4. Controls for regionC 5. Standard error of regression 6. Probability value for controlsd

Notes: Standard errors are given in parentheses. The sample consists of 357 stores with available data on employment and starting wages in waves 1 and 2. The dependent variable in all models is change in FTE employment. The mean and standard deviation of the dependent variable are -0.237 and 8.825, respectively. All models include an unrestricted constant (not reported). aProportional increase in starting wage necessary to raise starting wage to new minimum rate. For stores in Pennsylvania the wage gap is 0. b~hreedummy variables for chain type and whether or not the store is company- owned are included. 'Dummy variables for two regions of New Jersey and two regions of eastern Pennsylvania are included. d~robabilityvalue of joint F test for exclusion of all control variables. VOL. 84 NO. 4 CARD AND KRUEGER: MINIMUM WAGE AND EMPLOYMENT 781 survey. This restriction results in a slightly null hypothesis of a zero employment effect smaller estimate of the relative increase in of the minimum wage. One explanation for employment in New Jersey. this attenuation is the presence of measure- The model in column (ii) introduces a ment error in the starting wage. Even if set of four control variables: dummies for employment growth has no regional compo- three of the chains and another dummy for nent, the addition of region dummies will company-owned stores. As shown by the lead to some attenuation of the estimated probability values in row 6, these covariates GAP coefficient if some of the true varia- add little to the model and have no effect tion in GAP is explained by region. Indeed, on the size of the estimated New Jersey calculations based on the estimated reliabil- dummy. ity of the GAP variable (from the set of 11 The specifications in columns (iiil-(v) use double interviews) suggest that the fall in the GAP variable to measure the effect of the estimated GAP coefficient from column the minimum wage. This variable gives a (iv) to column (v) is just equal to the ex- slightly better fit than the simple New Jer- pected change attributable to measurement sey dummy, although its implications for the error.16 New Jersey-Pennsylvania comparison are We have also estimated the models in similar. The mean value of GAPi among Table 4 using as a dependent variable the New Jersey stores is 0.11. Thus the estimate proportional change in employment at each in column (iii) implies a 1.72 increase in store.17 The estimated coefficients of the FTE employment in New Jersey relative to New Jersey dummy and the GAP variable Pennsylvania. are uniformly positive in these models but Since GAP, varies within New Jersey, it is insignificantly different from 0 at conven- possible to add both GAP, and NJ, to the tional levels. The implied employment ef- employment model. The estimated coeffi- fects of the minimum wage are also smaller cient of the New Jersey dummy then pro- when the dependent variable is expressed in vides a test of the Pennsylvania control proportional terms. For example, the GAP group. When we estimate these models, the coefficient in column (iii) of Table 4 implies coefficient of the New Jersey dummy is in- that the increase in minimum wages raised significant (with t ratios of 0.3-0.7), imply- employment at New Jersey stores that were ing that inferences about the effect of the initially paying $4.25 per hour by 14 per- minimum wage are similar whether the cent. The estimated GAP coefficient from a comparison is made across states or across corresponding proportional model implies stores in New Jersey with higher and lower an effect of only 7 percent. The difference is initial wages. attributable to heterogeneity in the effect of An even stronger test is provided in col- the minimum wage at larger and smaller umn (v), where we have added dummies stores. Weighted versions of the propor- representing three regions of New Jersey tional-change models (using initial employ- (North, Central, and South) and two regions ment as a weight) give rise to wage elastici- of eastern Pennsylvania (Allentown-Easton and the northern of ). These dummies control for any region- s~ecificdemand shocks and identifv the ef- 16In a regression model without other controls the feet of the minimum wage by expected attenuation of the GAP coefficient due to employment changes at higher- and lower- measurement error is the reliability ratio of GAP (yo), which we estimate at 0.70. The expected attenuation wage within the same region of New factor when region dummies are added to the model is Jersey. The probability value in row 6 shows yl = (Yo- ~2)/(1- ~2),where ~2 is the R-square no evidence of regional components in em- statistic of a regression of GAP on region effects (equal ployment growth. The addition of the re- to 0.30). Thus, we expect the estimated GAP coeffi- cient to fall by a factor of YI /YO = 0.8 when region gion dummies attenuates the GAP coeffi- dummies are added to a regression model. cient and raises its standard error, however, "~hese specifications are reported in table 4 of making it no longer possible to reject the Card and Krueger (1993). 782 THE AMERICAN ECONOMIC REVIEW SEPTEMBER I994 ties similar to the elasticities implied by the little effect on the models for the level of estimates in Table 4 (see below). employment but yield slightly smaller point estimates in the proportional-employment- C. Specification Tests change models. In row 6 we present estimates obtained The results in Tables 3 and 4 seem to from a subsample that excludes 35 stores in contradict the standard prediction that a along the New . The ex- rise in the minimum wage will reduce em- clusion of these stores, which may have a ployment. Table 5 presents some alternative different seasonal pattern than other stores specifications that probe the robustness of in our sample, leads to slightly larger mini- this conclusion. For completeness, we re- mum-wage effects. A similar finding emerges port estimates of models for the change in in row 7 when we add a set of dummy employment [columns (i) and (ii)] and esti- variables that indicate the week of the mates of models for the proportional change wave-2 inter vie^.^' in employment [columns (iii) and (iv)].18 The As noted earlier, we made an extra effort first row of the table reproduces the "base to obtain responses from New Jersey stores specification" from columns (ii) and (iv) of in the first wave of our survey. The fraction Table 4. (Note that these models include of stores called three or more times to ob- chain dummies and a dummy for company- tain an interview was higher in New Jersey owned stores). Row 2 presents an alterna- than in Pennsylvania. To check the sensitiv- tive set of estimates when we set wave-2 ity of our results to this sampling feature, employment at the temporarily closed stores we reestimated our models on a subsample to 0 (expanding our sample size by 4). This that excludes any stores that were called change has a small attenuating effect on the back more than twice. The results, in row 8, coefficient of the New Jersey dummy (since are very similar to the base specification. all four stores are in New Jersey) but less Row 9 presents weighted estimation re- effect on the GAP coefficient (since the size sults for the proportional-employment- of GAP is uncorrelated with the probability change models, using as weights the initial of a temporary closure within New Jersey). levels of employment in each store. Since Rows 3-5 present estimation results us- the proportional change in average employ- ing alternative measures of full-time-equiv- ment is an employment-weighted average of alent employment. In row 3, employment is the proportional changes at each store, a redefined to exclude management employ- weighted version of the proportional-change ees. This change has no effect relative to model should give rise to elasticities that the base specification. In rows 4 and 5, we are similar to the implied elasticities arising include managers in FTE employment but from the levels models. Consistent with this reweight part-time workers as either 40 per- expectation, the weighted estimates are cent or 60 percent of full-time workers (in- larger than the unweighted estimates, and stead of 50 percent).19 These changes have significantly different from 0 at conventional levels. The weighted estimate of the New Jersey dummy (0.13) implies a 13-percent relative increase in New Jersey employment 18 The proportional change in employment is de- -the same proportional employment effect fined as the change in employment divided by the implied by the simple difference-in-dif- average level of employment in waves 1 and 2. This ferences in Table 3. Similarly, the weighted results in very similar coefficients but smaller standard errors than the alternative of dividing by wave-1 em- estimate of the GAP coefficient in the ployment. For closed stores we set the proportional proportional-change model (0.81) is close to change in employment to - 1. 19Analysis of the 1991 Current Population Survey reveals that part-time workers in the restaurant indus- try about 46 percent as many hours as full-time workers. Katz and Krueger (1992) report that the ratio 20We also added dummies for the interview dates of part-time workers' hours to full-time workers' hours for the wave-1 survey, but these were insignificant and in the fast-food industry is 0.57. did not change the estimated minimum-wage effects. VOL. 84 NO. 4 CARD AND KRUEGER: MINIMUM WAGE AND EMPLOYMENT 783

Proportional change Change in employment in employment NJ dummy Gap measure NJ dummy Gap measure Specification (i) (ii) (iii) (iv) 1. Base specification 2.30 14.92 (1.19) (6.21) 2. Treat four temporarily closed stores as permanently closeda 3. Exclude managers in employment countb 4. Weight part-time as 0.4 x full-timec

5. Weight part-time as 0.6 X full-timed

6. Exclude stores in NJ shore areae

7. Add controls for wave-2 interview dateE 8. Exclude stores called more than twice in wave lg 9. Weight by initial employmenth

10. Stores in towns around Newark' - 33.75 (16.75) 11. Stores in towns around CamdenJ - 10.91 (14.09)

12. Pennsylvania stores only - -0.30 (22.00)

Notes: Standard errors are given in parentheses. Entries represent estimated coefficient of New Jersey dummy [columns (i) and (iii)] or initial wage gap [columns (ii) and (iv)] in regression models for the change in employment or the percentage change in employment. All models also include chain dummies and an indicator for company- owned stores. aWave-2 employment at four temporarily closed stores is set to 0 (rather than missing). b~ull-timeequivalent employment excludes managers and assistant managers. CFull-time equivalent employment equals number of managers, assistant managers, and full-time nonmanage- ment workers, plus 0.4 times the number of part-time nonmanagement workers. d~ull-timeequivalent employment equals number of managers, assistant managers, and full-time nonmanage- ment workers, plus 0.6 times the number of part-time nonmanagement workers. eSample excludes 35 stores located in towns along the New Jersey shore. '~odelsinclude three dummy variables identifying week of wave-2 interview in November-December 1992. gSample excludes 70 stores (69 in New Jersey) that were contacted three or more times before obtaining the wave-1 interview. h~egressionmodel is estimated by weighted least squares, using employment in wave 1 as a weight. i . Subsample of 51 stores in towns around Newark. Subsample of 54 stores in around Camden. Subsample of Pennsylvania stores only. Wage gap is defined as percentage increase in starting wage necessary to raise starting wage to $5.05. 784 THE AMERICAN ECONOMIC REVIEW SEPTEMBER 1994 the implied of employment with We have also investigated whether the respect to wages from the basic levels speci- first-differenced specification used in our fication in row 1, column (iiI2l These find- employment models is appropriate. A ings suggest that the proportional effect of first-differenced model implies that the level the rise in the minimum wage was concen- of employment in period t is related to the trated among larger stores. lagged level of employment with a coeffi- One explanation for our finding that a cient of 1. If short-run employment fluctua- rise in the minimum wage has a positive tions are smoothed, however, the true co- employment effect is that unobserved de- efficient of lagged employment may be less mand shocks within New Jersey outweighed than 1. Imposing the assumption of a unit the negative employment effect of the mini- coefficient may then lead to biases. To test mum wage. To address this possibility, rows the first-differenced specification we reesti- 10 and 11 present estimation results based mated models for the change in employ- on subsamples of stores in two narrowly ment including wave-1 employment as an defined areas: towns around Newark (row additional explanatory variable. To over- 10) and towns around Camden (row 11). In come any mechanical correlation between each case the sample is identified by base-period employment and the change in the first three digits of the store's .22 employment (attributable to measurement Within both areas the change in employ- error) we instrumented wave-1 employment ment is positively correlated with the GAP with the number of cash registers in the variable, although in neither case is the store in wave 1 and the number of registers effect statistically significant. To the extent in the store that were open at 11:OO A.M. In that fast-food product market conditions are all of the specifications the coefficient of constant within local areas, these results wave-1 employment is close to zero. For suggest that our findings are not driven by example, in a specification including the unobserved demand shocks. Our analysis of GAP variable and ownership and chain price changes (reported below) also sup- dummies, the coefficient of wave-1 employ- ports this conclusion. ment is 0.04, with a standard error of 0.24. A final specification check is presented in We conclude that the first-differenced spec- row 12 of Table 5. In this row we exclude ification is appropriate. stores in New Jersey and (incorrectly) de- fine the GAP variable for Pennsylvania D. Full-Time and Part-Time Substitution stores as the proportional increase in wages necessary to raise the wage to $5.05 per Our analysis so far has concentrated on hour. In principle the size of the wage gap full-time-equivalent employment and ig- for stores in Pennsylvania should have no nored possible changes in the distribution systematic relation with employment growth. of full- and part-time workers. An increase In practice, this is the case. There is no in the minimum wage could lead to an in- indication that the wage gap is spuriously crease in full-time employment relative to related to employment growth. part-time employment for at least two rea- sons. First, in a conventional model one would expect a minimum-wage increase to induce employers to substitute skilled work- ers and capital for minimum-wage workers. Full-time workers in fast-food restaurants 21~ssumingaverage employment of 20.4 in New Jersey, the 14.92 GAP coefficient in row 1, column (ii) are typically older and may well possess im lies an employment elasticity of 0.73. higher skills than part-time workers. Thus, a "The "070" three-digit zip-code area (around conventional model predicts that stores may Newark) and the "080" three-digit zip-code area respond to an increase in the minimum (around Camden) have by far the largest numbers of stores among three-digit zip-code areas in New Jersey, wage by increasing the proportion of full- and together they account for 36 percent of New Jersey time workers. Nevertheless, 81 percent of stores in our sample. restaurants paid full-time and part-time VOL. 84 NO. 4 CARD AND KRUEGER: MINIMUM WAGE AND EMPLOYMENT 785

Regression of change in Mean change in outcome outcome variable on: NJ PA NJ -PA NJ dummy Wage gapa Wage gapb Outcome measure (i) (ii) (iii) (iv) (v) (vi) Store Characteristics:

1. Fraction full-time workersc (percentage)

2. Number of hours open per weekday

3. Number of cash registers

4. Number of cash registers open at 11:OO A.M.

Employee Meal Programs:

5. Low-price meal program (percentage)

6. Free meal program (percentage)

7. Combination of low-price and free meals (percentage)

Wage Profile:

8. Time to first raise (weeks)

9. Usual amount of first raise (cents)

10. Slope of wage profile (percent per week)

Notes: Entries in columns (i) and (ii) represent mean changes in the outcome variable indicated by the row heading for stores with available data on the outcome in waves 1 and 2. Entries in columns (iv)-(vi) represent estimated regression coefficients of indicated variable (NJ dummy or initial wage gap) in models for the change in the outcome variable. Regression models include chain dummies and an indicator for company-owned stores. aThe wage gap is the proportional increase in starting wage necessary to raise the wage to the new minimum rate. For stores in Pennsylvania, the wage gap is zero. b~odelsin column (vi) include dummies for two regions of New Jersey and two regions of eastern Pennsylvania. 'Fraction of part-time employees in total full-time-equivalent employment.

workers exactly the same starting wage in workers are more productive (but equally wave 1 of our survey.23 This suggests either paid), there may be a second reason for that full-time workers have the same skills stores to substitute full-time workers for as part-time workers or that concerns part-time workers; namely, a minimum-wage lead restaurants to pay equal wages for un- increase enables the industry to attract more equally productive workers. If full-time full-time workers, and stores would natu- rally want to hire a greater proportion of full-time workers if they are more produc- tive. 231n the other 19 percent of stores, full-time workers Row 1 of Table 6 presents the mean are paid more, typically 10 percent more. changes in the proportion of full-time work- 786 THE AMERICAN ECONOMIC REVIEW SEPTEMBER 1994 ers in New Jersey and Pennsylvania be- ployment costs unchanged. The main fringe tween waves 1 and 2 of our survey, and benefits for fast-food employees are free coefficient estimates from regressions of the and reduced-price meals. In the first wave change in the proportion of full-time work- of our survey about 19 percent of fast-food ers on the wage-gap variable, chain dum- restaurants offered workers free meals. 72 mies, a company-ownership dummy, and re- percent offered reduced-price meals, aid 9 gion dummies [in column (41. The results percent offered a combination of both free are ambiguous. The fraction of full-time and reduced-price meals. Low-price meals workers increased in New Jersey relative to are an obvious fringe benefit to cut if the Pennsylvania by 7.3 percent (t ratio = 1.841, minimum-wage increase forces restaurants but regressions on the wage-gap variable to pay higher wages. show no significant shift in the fraction of Rows 5 and 6 of Table 6 present esti- full-time workers.24 mates of the effect of the minimum-wage increase on the incidence of free meals and E. Other Employment-Related Measures reduced-price meals. The proportion of res- taurants offering reduced-price meals fell Rows 2-4 of Table 6 present results for in both New Jersey and Pennsylvania after other outcome variables that we expect to the minimum wage increased, with a some- be related to the level of restaurant employ- what greater decline in New Jersey. Con- ment. In particular, we examine whether trary to an story, however, the reduc- the rise in the minimum wage is associated tion in reduced-price meal programs was with a change in the number of hours a accompanied by an increase in the fraction restaurant is open on a weekday, the num- of stores offering free meals. Relative to ber of cash registers in the restaurant, and stores in Pennsylvania, New Jersey employ- the number of cash registers typically in ers actually shifted toward more generous operation in the restaurant at 11:OO A.M. fringe benefits (i.e., free meals rather than Consistent with our employment results, reduced-price meals). However, the relative none of these variables shows a statistically shift is not statistically significant. significant decline in New Jersey relative to We continue to find a statistically in- Pennsylvania. Similarly, regressions includ- significant effect of the minimum-wage in- ing the gap variable provide no evidence crease on the likelihood of receiving free or that the minimum-wage increase led to a reduced-price meals in columns (v) and (vi), systematic change in any of these variables where we report coefficient estimates of the [see columns (v) and (vi)]. GAP variable from regression models for the change in the incidence of these pro- IV. Nonwage Offsets grams. The results provide no evidence that employers offset the minimum-wage in- One explanation of our finding that a rise crease by reducing free or reduced-price in the minimum wage does not lower em- meals. ployment is that restaurants can offset the Another possibility is that employers re- effect of the minimum wage by reducing sponded to the increase in the minimum nonwage compensation. For example, if wage by reducing on-the-job and workers value fringe benefits and wages flattening the tenure-wage profile (see equally, employers can simply reduce the and Linda Leighton, 1981). level of fringe benefits by the amount of the Indeed, one manager told our interviewer in minimum-wage increase, leaving their em- wave 1that her workers were forgoing ordi- nary scheduled raises because the minimum wage was about to rise, and this would provide a raise for all her workers. To de- 24~ithinNew Jersey, the fraction of full-time em- termine whether this phenomenon occurred ployees increased about as at stores with higher more generally, we analyzed store man- and lower wages in wave 1. agers' responses to questions on the amount VOL. 84 NO. 4 CARD AND KRUEGER: MINIMUM WAGE AND EMPLOYMENT 787 of time before a normal wage increase and . The average restaurant in New the usual amount of such raises. In rows 8 Jersey initially paid about half its workers and 9 we report the average changes be- less than the new minimum wage. If wages tween waves 1 and 2 for these two variables, rose by roughly 15 percent for these work- as well as regression coefficients from mod- ers, and if labor's share of total costs is 30 els that include the wage-gap variable.25Al- percent, we would expect prices to rise by though the average time to the first pay about 2.2 percent ( = 0.15 X 0.5 X 0.3) due to raise increased by 2.5 weeks in New Jersey the minimum-wage rise.27 relative to Pennsylvania, the increase is not In each wave of our survey we asked statistically significant. Furthermore, there managers for the prices of three standard is only a trivial difference in the relative items: a medium soda, a small order of change in the amount of the first pay incre- , and a main course. The main ment between New Jersey and Pennsylvania course was a basic at Burger stores. King, Roy Rogers, and Wendy's restaurants, Finally, we examined a related variable: and two pieces of chicken at KFC stores. the "slope" of the wage profile, which we We define "full meal" price as the after- measure by the ratio of the typical first raise price of a medium soda, a small order of to the amount of time until the first raise is french fries, and a main course. given. As shown in row 10, the slope of the Table 7 presents reduced-form estimates wage profile flattened in both New Jersey of the effect of the minimum-wage increase and Pennsylvania, with no significant rela- on prices. The dependent variable in these tive difference between states. The change models is the change in the logarithm of the in the slope is also uncorrelated with the price of a full meal at each store. The key GAP variable. In summary, we can find no independent variable is either a dummy in- indication that New Jersey employers dicating whether the store is located in New changed either their fringe benefits or their Jersey or the proportional wage increase wage profiles to offset the rise in the mini- required to meet the minimum wage (the mum wage.26 GAP variable defined above). The estimated New Jersey dummy in col- V. Price Effects of the Minimum-Wage umn (i) shows that after-tax meal prices Increase rose 3.2-percent faster in New Jersey than in Pennsylvania between February and A final issue we examine is the effect of November 1992.~~The effect is slightly the minimum wage on the prices of meals at larger controlling for chain and company- fast-food restaurants. A competitive model ownership [see column ($1. Since the of the fast-food industry implies that an New Jersey rate fell by 1 percent- increase in the minimum wage will lead to age point between the waves of our survey, an increase in product prices. If we assume these estimates suggest that pretax prices constant in the industry, the rose 4-percent faster as a result of the increase in price should be proportional to the share of minimum-wage labor in total

"~ccordin~to the McDonald's 1991 Annual Report. and benefits are 31.3 percent of operating costs at company-owned stores. This calcula- 25~nwave 1, the average time to a first wage in- tion is only approximate because minimum-wage work- crease was 18.9 weeks, and the average amount of the ers make up less than half of payroll even though they first increase was $0.21 per hour. are about half of workers, and because a rise in the 26~atzand Krueger (1992) report that a significant minimum wage causes some employers to increase the fraction of fast-food stores in Texas responded to an pay of other higher-wage workers in order to maintain increase in the minimum wage by raising wages for relative pay differentials. workers who were initially earning more than the new he effect is attributable to a 2.0-percent increase minimum rate. Our results on the slope of the tenure in prices in New Jersey and a 1.0-percent decrease in profile are consistent with their findings. prices in Pennsylvania. THE AMERICAN ECONOMIC REVIEW SEPTEMBER 1994

TABLE7-REDUCED-FORM MODELS FOR CHANGEIN THE PRICEOF A FULLMEAL

------Dependent variable: change in the log price of a full meal Independent variable (i) (ii) (iii) (iv) (v)

1. New Jersey dummy 0.033 0.037 - - - (0.014) (0.014) 2. Initial wage gapa - - 0.077 0.146 0.063 (0.075) (0.074) (0.089) 3. Controls for chain andb no yes no yes Yes ownership 4. Controls for regionC no no no no yes 5. Standard error of regression 0.101 0.097 0.102 0.098 0.097 Notes: Standard errors are given in parentheses. Entries are estimated regression coefficients for models fit to the change in the log price of a full meal (entrCe, medium soda, small fries). The sample contains 315 stores with valid data on prices, wages, and employment for waves 1 and 2. The mean and standard deviation of the dependent variable are 0.0173 and 0.1017, respectively. aProportional increase in starting wage necessary to raise the wage to the new minimum-wage rate. For stores in Pennsylvania the wage gap is 0. bThree dummy variables for chain type and whether or not the store is company- owned are included. 'Dummy variables for two regions of New Jersey and two regions of eastern Pennsylvania are included.

minimum-wage increase in New Jersey- One potential explanation for the latter slightly more than the increase needed to finding is that stores in New Jersey compete pass through the cost increase caused by the in the same product market. As a result, minimum-wage hike. restaurants that are most affected by the The pattern of price changes within New minimum wage are unable to increase their Jersey is less consistent with a simple product prices faster than their competitors. "pass-through" view of minimum-wage cost In contrast, stores in New Jersey and Penn- increases. In fact, meal prices rose at sylvania are in separate product markets, approximately the same rate at stores in enabling prices to rise in New Jersey rela- New Jersey with differing levels of initial tive to Pennsylvania when overall costs rise wages. Inspection of the estimated GAP in New Jersey. Note that this explanation coefficients in column (v) of Table 7 con- seems to rule out the possibility that store- firms that within regions of New Jersey, the specific demand shocks can account for the GAP variable is statistically insignificant. anomalous rise in employment at stores in In sum, these results provide mixed evi- New Jersey with lower initial wages. dence that higher minimum wages result in higher fast-food prices. The strongest evi- VI. Store Openings dence emerges from a comparison of New Jersey and Pennsylvania stores. The magni- An important potential effect of higher tude of the price increase is consistent with minimum wages is to discourage the open- predictions from a conventional model of a ing of new . Although our sample competitive industry. On the other hand, we design allows us to estimate the effect of the find no evidence that prices rose faster minimum wage on existing restaurants in among stores in New Jersey that were most New Jersey, we cannot address the effect of affected by the rise in the minimum wage. the higher minimum wage on potential VOL. 84 NO. 4 CARD AND KRUEGER: MINIMUM WAGE AND EMPLOYMENT 789 entrants.29 To assess the likely size of such tive effect on either the number of an effect, we used national restaurant direc- restaurants or the rate of new openings. To tories for the McDonald's restaurant chain the contrary, all the estimates show positice to compare the numbers of operating effects of higher minimum wages on the restaurants and the numbers of newly number of operating or newly opened stores, opened restaurants in different states over although many of the point estimates are the 1986-1991 period. Many states raised insignificantly different from zero. While this their minimum wages during this period. In evidence is limited, we conclude that the addition, the federal minimum wage in- effects of minimum wages on fast-food store creased in the early 1990's from $3.35 to opening rates are probably small. $4.25, with differing effects in different states depending on the level of wages in the VII. Broader Evidence on Employment state. These policies create an opportunity Changes in New Jersey to measure the impact of minimum-wage on store opening rates across states. Our establishment-level analysis suggests The results of our analysis are presented that the rise in the minimum wage in New in Table 8. We regressed the growth rate in Jersey may have increased employment in the number of McDonald's stores in each the fast-food industry. Is this just an anomaly state on two alternative measures of the associated with our particular sample, or a minimum wage in the state and a set of phenomenon unique to the fast-food indus- other control variables (population growth try? Data from the monthly Current Popu- and the change in the state unemployment lation Survey (CPS) allow us to compare rate). The first minimum-wage measure is state-wide employment trends in New Jer- the fraction of workers in the state's sey and the surrounding states, providing a industry in 1986 whose wages fell be- check on the interpretation of our findings. tween the existing federal minimum wage in Using monthly CPS files for 1991 and 1992, 1986 ($3.35 per hour) and the effective min- we computed employment-population rates imum wage in the state in April 1990 (the for teenagers and adults (age 25 and older) maximum of the federal minimum wage and for New Jersey, Pennsylvania, New York, the state minimum wages as of April 1990)." and the entire . Since the New The second is the ratio of the state's effec- Jersey minimum wage rose on April 1, 1992, tive minimum wage in 1990 to the average we computed the employment rates for hourly wage of retail trade workers in the April-December of both 1991 and 1992. state in 1986. Both of these measures are The relative changes in employment in New designed to gauge the degree of upward Jersey and the surrounding states then give wage pressure exerted by state or federal an indication of the effect of the new law. minimum-wage changes between 1986 and A comparison of changes in adult em- 1990. ployment rates show that the New Jersey The results provide no evidence that labor market fared slightly worse over the higher minimum-wage rates (relative to the 1991-1992 period than either the U.S. labor retail-trade wages in a state) exert a nega- market as a whole or labor markets in Pennsylvania or New York (see Card and Krueger, 1993 table 9l3' Among teenagers,

29 however, the situation was reversed. In New Direct inquiries to the chains in our sample re- Jersey, teenage employment rates fell by 0.7 vealed that Wendy's opened two stores in New Jersey in 1992 and one store in Pennsylvania. The other percent from 1991 to 1992. In New York, chains were unwilling to provide information on new openings. 30We used the 1986 Current Population Survey (merged monthly file) to construct the minimum-wage 31 The employment rate of individuals age 25 and variables. State minimum-wage rates in 1990 were ob- older fell by 2.6 percent in New Jersey between 1991 tained from the Bureau of National Affairs Labor and 1992, while it rose by 0.3 percent in Pennsylvania, Relations Reporter Wages and Hours Manual (undated). and fell by 0.2 percent in the United States as a whole. 790 THE AMERICAN ECONOMIC REVIEW SEPTEMBER 1994

Dependent variable: Dependent variable: proportional (number of newly opened stores)+ increase in number of stores (number in 1986) Independent variable (i) (ii) (iii) (iv) (v) (vi) (vii) (viii) Minimum- Wage Variable:

1. Fraction of retail workers 0.33 - 0.13 - 0.37 - 0.16 - in affected wage range 1986" (0.20) (0.19) (0.22) (0.21) 2. (State minimum wage in 1991)+ - 0.38 - 0.47 - 0.47 - 0.56 (average retail wage in 1986Ib (0.22) (0.22) (0.23) (0.24)

Other Control Variables:

3. Proportional growth in - - 0.88 1.03 - - 0.86 1.04 population, 1986-1991 (0.23) (0.23) (0.25) (0.25) 4. Change in unemployment - - -1.78 -1.40 - - - 1.85 - 1.40 rates, 1986-1991 (0.62) (0.61) (0.68) (0.65) 5. Standard error of regression 0.083 0.083 0.071 0.068 0.088 0.088 0.077 0.073 Notes: Standard errors are shown in parentheses. The sample contains 51 state-level observations (including the District of Columbia) on the number of McDonald's restaurants open in 1986 and 1991. The dependent variable in columns (i)-(iv) is the proportional increase in the number of restaurants open. The mean and standard deviation are 0.246 and 0.085, respectively. The dependent variable in columns (v)-(viii) is the ratio of the number of new stores opened between 1986 and 1991 to the number open in 1986. The mean and standard deviation are 0.293 and 0.091, respectively. All regressions are weighted by the state population in 1986. aFraction of all workers in retail trade in the state in 1986 earning an hourly wage between $3.35 per hour and the "effective" state minimum wage in 1990 (i.e., the maximum of the federal minimum wage in 1990 ($3.80) and the state minimum wage as of April 1, 1990). b~aximumof state and federal minimum wage as of April 1, 1990, divided by the average hourly wage of workers in retail trade in the state in 1986.

Pennsylvania, and the United States as a summarize the predictions of the standard whole, teenage employment rates dropped model and some simple alternatives, and we faster. Relative to teenagers in Pennsylva- highlight the difficulties posed by our find- nia, for example, the teenage employment ings. rate in New Jersey rose by 2.0 percentage points. While this point estimate is consis- A. Standard Competitive Model tent with our findings for the fast-food in- dustry, the standard error is too large (3.2 A standard competitive model predicts percent) to allow any confident assessment. that establishment-level employment will fall if the wage is exogenously raised. For an VIII. Interpretation entire industry, total employment is pre- dicted to fall, and product price is predicted As in the earlier study by Katz and to rise in response to an increase in a bind- Krueger (1992), our empirical findings on ing minimum wage. Estimates from the the effects of the New Jersey minimum wage time-series literature on minimum-wage ef- are inconsistent with the predictions of a fects can be used to get a rough idea of the conventional competitive model of the fast- elasticity of low-wage employment to the food industry. Our employment results are minimum wage. The surveys by Brown et al. consistent with several alternative models, (1982. 1983) conclude that a 10-~ercentin- although none of these models can also crease in the coverage-adjusted minimum explain the apparent rise in fast-food prices wage will reduce teenage employment rates in New Jersey. In this section we briefly by 1-3 percent. Since this effect is for all VOL. 84 NO. 4 CARD AND KRUEGER: MINIMUM WAGE AND EMPLOYMENT 791 teenagers, and not just those employed in rive the equilibrium wage distribution for a low-wage industries, it is surely a lower noncooperative wage-search/wage-posting bound on the magnitude of the effect for model and show that the imposition of a fast-food workers. The 18-percent increase binding minimum wage can increase both in the New Jersey minimum wage is there- wages and employment relative to the initial fore predicted to reduce employment at equilibrium. Furthermore, their model pre- fast-food stores by 0.4-1.0 employees per dicts that the minimum wage will increase store. Our empirical results clearly reject employment the most at firms that initially the upper range of these estimates, al- paid the lowest wages. though we cannot reject a small negative Although monopsonistic and job-search effect in some of our specifications. models provide a potential explanation for A possible defense of the competitive the observed employment effects of the New model is that unobserved demand shocks Jersey minimum wage, they cannot explain affected certain stores in New Jersey- the observed price effects. In these models, specifically, those stores that were initially industry prices should have fallen in New paying wages less than $5.00 per hour. How- Jersey relative to Pennsylvania, and at low- ever, such localized demand shocks should wage stores in New Jersey relative to high- also affect product prices. (In fact, in a wage stores in New Jersey. Neither predic- competitive model, product demand shocks tion is confirmed: indeed, prices rose faster work through a rise in prices.) Although in New Jersey than in Pennsylvania, al- lower-wage stores in New Jersey had rela- though at about the same rate at high- and tive employment gains, they did not have low-wage stores in New Jersey. Another relative price increases. Furthermore, our puzzle for equilibrium search models is the analysis of employment changes in two ma- absence of wage increases at firms that were jor suburban areas (around Newark and initially paying $5.05 or more per hour. Camden) reveals that, even within local The strict link between the employment areas, employment rose faster at the stores and price effects of a rise in the minimum that had to increase wages the most because wage may be broken if fast-food stores can of the new minimum wage. vary the quality of service (e.g., the length of the queue at peak hours, or the cleanliness B. Alternative Models of stores). Another possibility is that stores altered the relative prices of their various An alternative to the conventional com- menu items. Comparisons of price changes petitive model is one in which firms are for the three items in our survey show slight price-takers in the product market but have declines (-1.5 percent) in the price of some degree of in the labor french fries and soda in New Jersey relative market. If fast-food stores face an upward- to Pennsylvania, coupled with a relative in- sloping labor- , a rise in the crease (8 percent) in entrCe prices. These minimum wage can potentially increase em- limited data suggest a possible role for rela- ployment at affected firms and in the indus- tive price changes within the fast-food in- try as a whole.32 dustry following the rise in the minimum This same basic insight emerges from an wage. equilibrium search model in which firms One way to test a model is to post wages and employees search among identify stores that were initially "supply- posted offers (see Dale T. Mortensen, 1988). constrained" in the labor market and test Kenneth Burdett and Mortensen (1989) de- for employment gains at these stores rela- tive to other stores. A potential indicator of market power is the use of bonuses. As we noted in Table 2, about 25 "~aniel G. Sullivan (1989) and Michael R Ransom (1993) present empirical results for nurses and univer- percent of stores in wave 1 were offering sity teachers that suggest monopsony-like behavior of cash bonuses to employees who helped find employers. a new worker. We compared employment 792 THE AMERICAN ECONOMIC REVIEW SEPTEMBER 1994 changes at New Jersey stores that were of- affected by the minimum-wage rise. Taken fering recruitment bonuses in wave 1, and as a whole, these findings are difficult to also interacted the GAP variable with a explain with the standard competitive model dummy for recruitment bonuses in several or with models in which employers face employment-change models. We do not find supply constraints (e.g., monopsony or equi- faster (or slower) employment growth at the librium search models). New Jersey stores that were initially using recruitment bonuses, or any evidence that the GAP variable had a larger effect for REFERENCES stores that were using bonuses. Brown, Charles; Gilroy, Curtis and Kohen, An- IX. Conclusions drew. "The Effect of the Minimum Wage on Employment and Unemployment." Contrary to the central prediction of the Journal of Economic Literature, June 1982, textbook model of the minimum wage, but 20(2), pp. 487-528. consistent with a number of recent studies . "Time Series Evidence on the Ef- based on cross-sectional time-series com- fect of the Minimum Wage on Youth parisons of affected and unaffected markets Employment and Unemployment." Jour- or employers, we find no evidence that the nal of , Winter 1983, rise in New Jersey's minimum wage reduced 18(1), pp. 3-31. employment at fast-food restaurants in the Burdett, Kenneth and Mortensen, Dale T. state. Regardless of whether we compare "Equilibrium Wage Differentials and stores in New Jersey that were affected by Employer Size." Center for Mathematical the $5.05 minimum to stores in eastern Studies in Economics and Management Pennsylvania (where the minimum wage was Science Discussion Paper No. 860, North- constant at $4.25 per hour) or to stores in western University, October 1989. New Jersey that were initially paying $5.00 Bureau of National Affairs. Daily Labor Re- per hour or more (and were largely unaf- port. , DC: Bureau of Na- fected by the new law), we find that the tional Affairs, 5 May 1990. increase in the minimum wage increased . Labor Relations Reporter Wages and employment. We present a wide variety of Hours Manual. Washington, DC: Bureau alternative specifications to probe the ro- of National Affairs, irregular. bustness of this conclusion. None of the Card, David. "Using Regional Variation in alternatives shows a negative employment Wages To Measure the Effects of the effect. We also check our findings for the Federal Minimum Wage." Industrial and fast-food industry by comparing changes in Labor Relations Reuiew, October 1992a, teenage employment rates in New Jersey, 46(1), pp. 22-37. Pennsylvania, and New York in the year . "Do Minimum Wages Reduce Em- following the increase in the minimum wage. ployment? A Case Study of California, Again, these results point toward a relative 1987-89." Industrial and Labor Relations increase in employment of low-wage work- Reuiew, October 1992b, 46(1), pp. 38-54. ers in New Jersey. We also find no evidence Card, David and Krueger, Alan B. "Minimum that minimum-wage increases negatively Wages and Employment: A Case Study of affect the number of McDonald's outlets the Industry in New Jersey and opened in a state. Pennsylvania." National Bureau of Eco- Finally, we find that prices of fast-food nomic Research (Cambridge, MA) Work- meals increased in New Jersey relative to ing Paper No. 4509, October 1993. Pennsylvania, suggesting that much of the Katz, Lawrence F. and Krueger, Alan B. "The burden of the minimum-wage rise was Effect of the Minimum Wage on the Fast passed on to consumers. Within New Jer- Food Industry." Industrial and Labor Re- sey, however, we find no evidence that prices lations Reuiew, October 1992, 46(1), pp. increased more in stores that were most 6-21. VOL. 84 NO. 4 CARD AND KRUEGER: MINIMUM WAGE AND EMPLOYMENT 793

Lester, Richard A. "Employment Effects of Management Science Discussion Paper Minimum Wages." Industrial and Labor No. 811, Northwestern University, March Relations Reuiew, January 1960, 13, pp. 1988. 254-64. Ransom, Michael R. "Seniority and Monop- . The economics of labor, 2nd Ed. sony in the Academic Labor Market." New York: Macmillan, 1964. American Economic Reuiew, March 1993, Machin, Stephen and Manning, Alan. "The 83(1), pp. 221-33. Effects of Minimum Wages on Wage Dis- Stigler, George J. "The Economics of Mini- persion and Employment: Evidence from mum Wage Legislation." American Eco- the U.K. Wage Councils." Industrial and nomic Reciew, June 1946, 36(3), pp. Labor Relations Reuiew, January 1994, 358-65. 47(2), pp. 319-29. Sullivan, Daniel G. "Monopsony Power in the McDonald's Corporation. 1991 Annual report. Market for Nurses." Journal of Law and Chicago, 1991. Economics, October 1989, Part 2, 32(2), Mincer, Jacob and Leighton, Linda. "The Ef- pp. S135-78. fects of Minimum Wages on Human Cap- U.S. Department of Commerce. 1987 Census of ital Formation," in Simon Rottenberg, retail trade: Miscellaneous subjects. Wash- ed., The economics of legal minimum ington, DC: U.S. Government Printing wages. Washington, DC: American Enter- Office, October 1990. prise Institute, 1981, pp. 155-73. Wellington, Alison J. "Effects of the Mini- Mortensen, Dale T. "Equilibrium Wage Dis- mum Wage on the Employment Status of tributions: A Synthesis." Center for Youths: An Update." Journal of Human Mathematical Studies in Economics and Resources, Winter 1991, 26(1), pp. 27-46. http://www.jstor.org

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You have printed the following article: Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania ; Alan B. Krueger The American Economic Review, Vol. 84, No. 4. (Sep., 1994), pp. 772-793. Stable URL: http://links.jstor.org/sici?sici=0002-8282%28199409%2984%3A4%3C772%3AMWAEAC%3E2.0.CO%3B2-O

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[Footnotes]

1 The Effect of The Minimum Wage on Employment and Unemployment Charles Brown; Curtis Gilroy; Andrew Kohen Journal of Economic Literature, Vol. 20, No. 2. (Jun., 1982), pp. 487-528. Stable URL: http://links.jstor.org/sici?sici=0022-0515%28198206%2920%3A2%3C487%3ATEOTMW%3E2.0.CO%3B2-C

1 Time-Series Evidence of the Effect of the Minimum Wage on Youth Employment and Unemployment Charles Brown; Curtis Gilroy; Andrew Kohen The Journal of Human Resources, Vol. 18, No. 1. (Winter, 1983), pp. 3-31. Stable URL: http://links.jstor.org/sici?sici=0022-166X%28198324%2918%3A1%3C3%3ATEOTEO%3E2.0.CO%3B2-Q

1 Effects of the Minimum Wage on the Employment Status of Youths: An Update Alison J. Wellington The Journal of Human Resources, Vol. 26, No. 1. (Winter, 1991), pp. 27-46. Stable URL: http://links.jstor.org/sici?sici=0022-166X%28199124%2926%3A1%3C27%3AEOTMWO%3E2.0.CO%3B2-5

NOTE: The reference numbering from the original has been maintained in this citation list. http://www.jstor.org

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3 The Effect of the Minimum Wage on the Fast-Food Industry Lawrence F. Katz; Alan B. Krueger Industrial and Labor Relations Review, Vol. 46, No. 1. (Oct., 1992), pp. 6-21. Stable URL: http://links.jstor.org/sici?sici=0019-7939%28199210%2946%3A1%3C6%3ATEOTMW%3E2.0.CO%3B2-S

11 The Effect of the Minimum Wage on the Fast-Food Industry Lawrence F. Katz; Alan B. Krueger Industrial and Labor Relations Review, Vol. 46, No. 1. (Oct., 1992), pp. 6-21. Stable URL: http://links.jstor.org/sici?sici=0019-7939%28199210%2946%3A1%3C6%3ATEOTMW%3E2.0.CO%3B2-S

19 The Effect of the Minimum Wage on the Fast-Food Industry Lawrence F. Katz; Alan B. Krueger Industrial and Labor Relations Review, Vol. 46, No. 1. (Oct., 1992), pp. 6-21. Stable URL: http://links.jstor.org/sici?sici=0019-7939%28199210%2946%3A1%3C6%3ATEOTMW%3E2.0.CO%3B2-S

26 The Effect of the Minimum Wage on the Fast-Food Industry Lawrence F. Katz; Alan B. Krueger Industrial and Labor Relations Review, Vol. 46, No. 1. (Oct., 1992), pp. 6-21. Stable URL: http://links.jstor.org/sici?sici=0019-7939%28199210%2946%3A1%3C6%3ATEOTMW%3E2.0.CO%3B2-S

32 Monopsony Power in the Market for Nurses Daniel Sullivan Journal of , Vol. 32, No. 2, Part 2, Empirical Approaches to Market Power: A Conference Sponsored by the University of and the Federal Trade Commission. (Oct., 1989), pp. S135-S178. Stable URL: http://links.jstor.org/sici?sici=0022-2186%28198910%2932%3A2%3CS135%3AMPITMF%3E2.0.CO%3B2-1

32 Seniority and Monopsony in the Academic Labor Market Michael R. Ransom The American Economic Review, Vol. 83, No. 1. (Mar., 1993), pp. 221-233. Stable URL: http://links.jstor.org/sici?sici=0002-8282%28199303%2983%3A1%3C221%3ASAMITA%3E2.0.CO%3B2-J

NOTE: The reference numbering from the original has been maintained in this citation list. http://www.jstor.org

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References

The Effect of The Minimum Wage on Employment and Unemployment Charles Brown; Curtis Gilroy; Andrew Kohen Journal of Economic Literature, Vol. 20, No. 2. (Jun., 1982), pp. 487-528. Stable URL: http://links.jstor.org/sici?sici=0022-0515%28198206%2920%3A2%3C487%3ATEOTMW%3E2.0.CO%3B2-C

Time-Series Evidence of the Effect of the Minimum Wage on Youth Employment and Unemployment Charles Brown; Curtis Gilroy; Andrew Kohen The Journal of Human Resources, Vol. 18, No. 1. (Winter, 1983), pp. 3-31. Stable URL: http://links.jstor.org/sici?sici=0022-166X%28198324%2918%3A1%3C3%3ATEOTEO%3E2.0.CO%3B2-Q

Using Regional Variation in Wages to Measure the Effects of the Federal Minimum Wage David Card Industrial and Labor Relations Review, Vol. 46, No. 1. (Oct., 1992), pp. 22-37. Stable URL: http://links.jstor.org/sici?sici=0019-7939%28199210%2946%3A1%3C22%3AURVIWT%3E2.0.CO%3B2-3

Do Minimum Wages Reduce Employment? A Case Study of California, 1987-89 David Card Industrial and Labor Relations Review, Vol. 46, No. 1. (Oct., 1992), pp. 38-54. Stable URL: http://links.jstor.org/sici?sici=0019-7939%28199210%2946%3A1%3C38%3ADMWREA%3E2.0.CO%3B2-%23

The Effect of the Minimum Wage on the Fast-Food Industry Lawrence F. Katz; Alan B. Krueger Industrial and Labor Relations Review, Vol. 46, No. 1. (Oct., 1992), pp. 6-21. Stable URL: http://links.jstor.org/sici?sici=0019-7939%28199210%2946%3A1%3C6%3ATEOTMW%3E2.0.CO%3B2-S

NOTE: The reference numbering from the original has been maintained in this citation list. http://www.jstor.org

LINKED CITATIONS - Page 4 of 4 -

Employment Effects of Minimum Wages Richard A. Lester Industrial and Labor Relations Review, Vol. 13, No. 2. (Jan., 1960), pp. 254-264. Stable URL: http://links.jstor.org/sici?sici=0019-7939%28196001%2913%3A2%3C254%3AEEOMW%3E2.0.CO%3B2-3

The Effects of Minimum Wages on Wage Dispersion and Employment: Evidence from the U.K. Wages Councils ; Alan Manning Industrial and Labor Relations Review, Vol. 47, No. 2. (Jan., 1994), pp. 319-329. Stable URL: http://links.jstor.org/sici?sici=0019-7939%28199401%2947%3A2%3C319%3ATEOMWO%3E2.0.CO%3B2-7

Seniority and Monopsony in the Academic Labor Market Michael R. Ransom The American Economic Review, Vol. 83, No. 1. (Mar., 1993), pp. 221-233. Stable URL: http://links.jstor.org/sici?sici=0002-8282%28199303%2983%3A1%3C221%3ASAMITA%3E2.0.CO%3B2-J

The Economics of Minimum Wage Legislation George J. Stigler The American Economic Review, Vol. 36, No. 3. (Jun., 1946), pp. 358-365. Stable URL: http://links.jstor.org/sici?sici=0002-8282%28194606%2936%3A3%3C358%3ATEOMWL%3E2.0.CO%3B2-A

Monopsony Power in the Market for Nurses Daniel Sullivan Journal of Law and Economics, Vol. 32, No. 2, Part 2, Empirical Approaches to Market Power: A Conference Sponsored by the University of Illinois and the Federal Trade Commission. (Oct., 1989), pp. S135-S178. Stable URL: http://links.jstor.org/sici?sici=0022-2186%28198910%2932%3A2%3CS135%3AMPITMF%3E2.0.CO%3B2-1

Effects of the Minimum Wage on the Employment Status of Youths: An Update Alison J. Wellington The Journal of Human Resources, Vol. 26, No. 1. (Winter, 1991), pp. 27-46. Stable URL: http://links.jstor.org/sici?sici=0022-166X%28199124%2926%3A1%3C27%3AEOTMWO%3E2.0.CO%3B2-5 NOTE: The reference numbering from the original has been maintained in this citation list.