Fermat's Library | Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania annotated/explained version.

David Card is a labour economist and professor at UC Berkeley. A...

Tl;dr: This is a research summary of the paper from the Nobel pr...

The classic model of employment differs with the reality found from...

"This paper presents new evidence on the effect of minimum wages on...

There could be many explanations for the jump in employment followi...

State history of the minimum wage in New Jersey: ![Imgur](https://...

The authors will discuss more on the differences-in-differences met...

This would be an instance of survivorship bias, if they did not fol...

Choosing to study the fast-food industry was an important decision ...

Sample design and response rates. Key summary data.

More compelling reasons to choose this industry for their natural e...

Economics field research is interesting....: "we hired an interview...

"The average starting wage at fast-food restaurants in New Jersey i...

Key result: "The relative gain (the "difference in differences" of ...

"Difference in differences is a statistical technique used in econo...

"The results in Tables 3 and 4 seem to contradict the standard pred...

"As in the earlier study by Katz and Krueger (1992), our empirical ...

Important conclusion with non-intuitive findings that have real pol...

Minimum Wages and Employment:

Case Study of the Fast-Food Industry

in New Jersey and Pennsylvania

On April 1, 1992, New Jersey's minimum wage rose from $4.25 to $5.05 per

hour. To evaluate the impact of the law we surveyed 410 fast-food restaurants in

New Jersey and eastern Pennsylvania before and after the rise. Comparisons of

employment growth at stores in New Jersey and Pennsylvania (where the

minimum wage 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-

market 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

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 California (Card, 1992b)

employment rates usually confirmed this

find no adverse employment impact.

study

prediction,' earlier studies based on com- of minimum-wage floors in Britain (Stephen

parisons of employment at affected and un- Machin and Alan Manning, 1994) reaches a

affected establishments often did not (e.g.,

similar conclusion.

Richard

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 Economics, Princeton University,

New Jersey and Pennsylvania following the

Princeton,

08544. We are grateful to the Institute

increase in New Jersey's minimum wage

for Research on Poverty, University of Wisconsin, for

from $4.25 to $5.05 per hour. Comparisons

partial financial support. Thanks to Orley Ashenfelter,

of employment, wages, and prices at stores

Charles Brown, Richard Lester, Gary Solon, two

anonymous referees, and seminar participants at

in New Jersey and Pennsylvania before and

Princeton, Michigan State, Texas

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.

Chicago, and the NBER for comments and sugges-

~~~~~~i~~~~ within

N~~

jersey

between

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

the impact of the

1991) concludes that the employment effects of the

new

lawe

minimum wage are negative but small: a 10-percent

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

773

VOL.

NO.

CARD AND KRUEGER: MINIMUM WAGE AND EMPLOYMENT

the New Jersey law and our data set are

also significant. First, the rise in the mini-

mum wage occurred during a recession. The

increase had been legislated two years ear-

lier when the state economy was relatively

healthy. By the time of the actual increase,

the unemployment rate in New Jersey had

risen substantially and last-minute political

action almost succeeded in reducing the

minimum-wage increase. It is unlikely that

the effects of the higher minimum wage

were obscured by a rising tide of general

economic conditions.

Second, New Jersey is a relatively small

state with an economy that is closely linked

to nearby states. We believe that a control

group of fast-food stores in eastern Pennsyl-

vania forms a natural basis for comparison

with the experiences of restaurants in New

Jersey. Wage variation across stores in New

Jersey, however, allows us to compare the

experiences of high-wage and low-wage

stores within New Jersey and to

test

the

validity of the Pennsylvania control group.

Moreover, since seasonal patterns of em-

ployment are similar in New Jersey and

eastern Pennsylvania, as well as across

high- and low-wage stores within New Jer-

sey, our comparative methodology effec-

tively "differences out" any. seasonal em-

ployment effects.

Third, we successfully followed nearly 100

percent of stores from a first wave of inter-

views conducted just before the rise in the

minimum wage (in February and March

1992) to a second wave conducted 7-8

months after (in November and December

1992). We have complete information on

store closings and take account of employ-

ment changes at the closed stores in our

analyses. We therefore measure the overall

effect of the minimum wage on average

employment, and not simply its effect on

surviving establishments.

-Our analysis of employment trends at

stores that were open for business before

the increase in the minimum wage ignores

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

McDonald's fast-food outlets between 1986

and 1991 to measures of the relative mini-

mum wage in each state.

The New Jersey Law

A bill signed into law in November 1989

raised the federal minimum wage from $3.35

per hour to $3.80 effective April 1, 1990,

with a further increase to $4.25 per hour on

April 1, 1991. In early 1990 the New Jersey

legislature went one step further, enacting

parallel increases in the state minimum wage

for 1990 and 1991 and an increase to $5.05

per hour effective April 1, 1992. The sched-

uled 1992 increase gave New Jersey the

highest state minimum wage in the country

and was strongly opposed by business lead-

ers in the state (see Bureau of National

Affairs,

Daily Labor Report,

5 May 1990).

In the two years between passage of the

$5.05 minimum wage and its effective date,

New Jersey's economy slipped into reces-

sion. Concerned with the potentially ad-

verse impact of a higher minimum wage, the

state legislature voted in March 1992 to

phase in the 80-cent increase over two years.

The vote fell just short of the margin re-

quired to override a gubernatorial veto, and

the Governor allowed the $5.05 rate to go

into effect on April 1 before vetoing the

two-step legislation. Faced with the prospect

of having to roll back wages for

minimum-

wage earners, the legislature dropped the

issue. Despite a strong last-minute chal-

lenge, the $5.05 minimum rate took effect

as originally planned.

11.

Sample Design and Evaluation

Early in 1992 we decided to evaluate the

impending increase in the New Jersey mini-

mum wage by surveying fast-food restau-

rants in New Jersey and eastern Pennsylva-

niae2 Our choice of the fast-food industry

was driven by several factors. First, fast-food

stores are a leading employer of low-wage

workers: in 1987, franchised restaurants

em-

2At the time we were uncertain whether the

$5.05

rate would go into effect or be overridden.

THE AMERICAN ECONOMIC REVIEW

Waue

February 15-March

1992:

Number of stores in sample frame:a

Number of refusals:

Number interviewed:

Response rate (percentage):

Wace 2, Nocember 5- December

31,

1992:

Number of stores in sample frame:

Number closed:

Number under rennovation:

Number temporarily closed:'

Number of refusals:

Number intervie~ed:~

473

410

86.7

410

399

SEPTEMBER 1994

Stores in:

364 109

33 30

33 1 79

90.9 72.5

331 79

2 0

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

percent of all workers in the

restaurant industry (see

U.S.

Department of

Commerce, 1990 table 13). Second, fast-food

restaurants comply with minimum-wage reg-

ulations and would be expected to raise

wages in response to a rise in the minimum

wage. Third, the job requirements and

products of fast-food restaurants are rela-

tively homogeneous, making it easier to ob-

tain reliable measures of employment,

wages, and product prices. The absence of

tips greatly simplifies the measurement of

wages in the industry. Fourth, it is relatively

easy to construct a sample frame of fran-

chised restaurants. Finally, past experience

(Katz and Krueger, 1992) suggested that

fast-food restaurants have high response

rates to telephone

survey^.^

Based on these considerations we con-

structed a sample frame of fast-food restau-

3~na pilot survey Katz and Krueger (1992) obtained

very low response rates from McDonald's restaurants.

For this reason, McDonald's restaurants were excluded

from Katz and Krueger's and our sample frames.

rants in New Jersey and eastern Pennsylva-

nia from the Burger King, KFC, Wendy's,

and Roy Rogers

chain^.^

The first wave of

the survey was conducted by telephone in

late February and early March 1992, a little

over a month before the scheduled increase

in New Jersey's minimum wage. The survey

included questions on employment, starting

wages, prices, and other store characteris-

tic~.~

Table

shows that 473 stores in our sam-

ple frame had working telephone numbers

when we tried to reach them in

February-

March 1992. Restaurants were called as

many as nine times to elicit a response. We

obtained completed interviews (with some

item nonresponse) from 410 of the restau-

rants, for an overall response rate of 87

percent. The response rate was higher in

New Jersey (91 percent) than in Pennsylva-

4~hesample was derived from white-pages tele-

phone listings for New Jersey and Pennsylvania as of

February 1992.

'copies of the questionnaires used in both waves of

the survey are available from the authors upon request.

775

VOL.

NO.

CAm AND KRUEGER: MINIiiMUM WAGE AND EMPLOYMENT

nia (72.5 percent) because our interviewer

made fewer call-backs to nonrespondents in

Penn~ylvania.~

In the analysis below we in-

vestigate possible biases associated with the

degree of difficulty in obtaining the

first-

wave interview.

The second wave of the survey was con-

ducted in November and December 1992,

about eight months after the minimum-wage

increase. Only the 410 stores that re-

sponded in the first wave were contacted in

the second round of interviews. We success-

fully interviewed 371 (90 percent) of these

stores by phone in November 1992. Because

of a concern that nonresponding restaurants

might have closed, we hired an interviewer

to drive to each of the 39 nonrespondents

and determine whether the store was still

open, and to conduct a personal interview

possible. The interviewer discovered that six

restaurants were permanently closed, two

were temporarily closed (one because of a

fire, one because of road construction), and

two were under renovation.' Of the 29 stores

open for business, all but one granted a

request for a personal interview. As a re-

sult, we have second-wave interview data

for 99.8 percent of the restaurants that re-

sponded in the first wave of the survey, and

information on closure status for 100 per-

cent of the sample.

Table 2 presents the means for several

key variables in our data set, averaged over

the subset of nonmissing responses for each

variable. In constructing the means, employ-

ment in wave 2 is set to

0 for the perma-

6~esponserates per call-back were almost identical

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,

and 71.6 percent responded after at most two call-

backs.

7~sof April 1993 the store closed because of road

construction and one of the stores closed for renova-

tion had reopened. The store closed by fire was open

when our telephone interviewer called in November

1992 but refused the interview. By the time of the

follow-up personal interview a mall fire had closed the

store.

nently closed stores but is treated as missing

for the temporarily closed stores. (Full-

time-equivalent [FTE] employment was cal-

culated as the number of full-time workers

[including managers] plus 0.5 times the

number of part-time workers.)' Means are

presented separately for stores in New Jer-

sey and Pennsylvania, along with

statistics

for the null hypothesis that the means are

equal in the two states.

Rows la-e show the distribution of stores

by chain and ownership status

(company-

owned versus franchisee-owned). The

Burger King, Roy Rogers, and Wendy's

stores in our sample have similar average

food prices, store hours, and employment

levels. The

KFC

stores are smaller and are

open for fewer hours. They also offer a

more expensive main course than stores in

the other chains (chicken vs, hamburgers).

In wave 1, average employment was 23.3

full-time equivalent workers per store in

Pennsylvania, compared with an average of

20.4 in New Jersey. Starting wages were

very similar among stores in the two states,

although the average price of a "full meal"

(medium soda, small fries, and an entree)

was significantly higher in New Jersey. There

were no significant cross-state differences in

average hours of operation, the fraction of

full-time workers, or the prevalence of bonus

programs to recruit new

worker^.^

The average starting wage at fast-food

restaurants in New Jersey increased by 10

percent following the rise in the minimum

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-

nia were very similar. By wave 2 virtually all

'we discuss the sensitivity of our results to alterna-

tive assumptions on the measurement of employment

in Section

111-C.

'~hese programs offer current employees a cash

"bounty" for recruiting any new employee who stays

on the job for a minimum period of time. Typical

bounties are $50-$75. Recruiting programs that award

the recruiter with an "employee of the month" desig-

nation or other noncash bonuses are excluded from our

tabulations.

THE AMERICAN ECONOMIC REVIEW SEPTEMBER 1994

Variable

Distribution of Store Types (percentages):

a. Burger King

KFC

c. Roy Rogers

d. Wendy's

e. Company-owned

Means in Wave I:

a. FTE employment

b. Percentage full-time employees

c. Starting wage

d. Wage

$4.25 (percentage)

e. Price of full meal

f. Hours open (weekday)

g. Recruiting bonus

Means in Ware

a. FTE employment

b. Percentage full-time employees

c. Starting wage

d. Wage

$4.25 (percentage)

e. Wage

$5.05 (percentage)

f. Price of full meal

g. Hours open (weekday)

h. Recruiting bonus

Stores in:

NJ PA

20.4

(0.51)

32.8

(1.3)

4.61

(0.02)

30.5

(2.5)

21.0 21.2

0.2

(0.52) (0.94)

35.9 30.4 1.8

(1.4) (2.8)

5.08 4.62 10.8

(0.01) (0.04)

0.0 25.3

(4.9)

85.2 1.3 36.1

(2.0) (1.3)

3.41 3.03 5.0

(0.04) (0.07)

14.4 14.7

0.8

(0.2) (0.3)

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

paying less than

$5.05

per hour reported a

starting wage equal to the new rate. Inter-

estingly, the minimum-wage increase had no

apparent "spillover" on higher-wage restau-

rants in the state: the mean percentage wage

change for these stores was

3.1

percent.

Despite the increase in wages, full-time-

equivalent employment

increased

in New

Jersey relative to Pennsylvania. Whereas

New Jersey stores were initially smaller,

employment gains in New Jersey coupled

with losses in Pennsylvania led to a small

and statistically insignificant interstate

VOL.

NO.

CARD AND KRUEGER: MINIMUM WAGE AND EMPLOYMENT

February

1992

Wage Range

November

9 9

Wage Range

New Jersey Pennsylvania

FIGURE

DISTRIBUTION WAGE RATES

STARTING

778

THE AMERICAN ECONOMIC REVIEW SEPTEMBER

I994

difference in wave 2. Only two other vari-

ables show a relative change between waves

1 and 2: the fraction of full-time employees

and the price of a meal. Both variables

increased in New Jersey relative to Pennsyl-

vania.

We can assess the reliability of our survey

questionnaire by comparing the responses

of 11 stores that were inadvertently inter-

viewed twice in the first wave of the survey.10

Assuming that measurement errors in the

two interviews are independent of each

other and independent of the true variable,

the correlation between responses gives an

estimate of the "reliability ratio" (the ratio

of the variance of the signal to the com-

bined variance of the signal and noise). The

estimated reliability ratios are fairly high,

ranging from 0.70 for full-time equivalent

employment to 0.98 for the price of a meal."

We have also checked whether stores with

missing data for any key variables are dif-

ferent from restaurants with complete re-

sponses. We find that stores with missing

data on employment, wages, or prices are

similar in other respects to stores with com-

plete data. There is a significant size differ-

ential associated with the likelihood of the

store closing after wave 1. The six stores

that closed were smaller than other stores

(with an average employment of only 12.4

full-time-equivalent employees in wave

1).12

111. Employment Effects of the

Minimum-Wage Increase

Differences in Differences

Table 3 summarizes the levels and

changes in average employment per store in

These restaurants were interviewed twice because

their phone numbers appeared in more than one phone

book, and neither the interviewer nor the respondent

noticed that they were previously interviewed.

Similar reliability ratios for very similar questions

were obtained by Katz and Krueger

(1992).

''A

probit analysis of the probability of closure

shows that the initial size of the store is a significant

predictor of closure. The level of starting wages has a

numerically small and statistically insignificant coeffi-

cient in the

probit model.

our survey. We present data by state in

columns (i) and (ii), and for stores in New

Jersey classified by whether the starting

wage in wave

was exactly $4.25 per hour

[column (iv)] between $4.26 and $4.99 per

hour [column (v)] or $5.00 or more per hour

[column (vi)]. We also show the differences

in average employment between New Jersey

and Pennsylvania stores [column (iii)] and

between stores in the various wage ranges

in New Jersey [columns (viil-(viii)].

Row 3 of the table presents the changes

in average employment between waves

and 2. These entries are simply the differ-

ences between the averages for the two

waves

(i.e., row 2 minus row 1). An alterna-

tive estimate of the change is presented in

row

here we have computed the change

in employment over the subsample of stores

that reported valid employment data in both

waves. We refer to this group of stores as

the balanced subsample. Finally, row 5 pre-

sents the average change in employment in

the balanced subsample, treating wave-2

employment at the four temporarily closed

stores as zero, rather than as missing.

As noted in Table 2, New Jersey stores

were initially smaller than their Pennsylva-

nia counterparts but grew relative to Penn-

sylvania stores after the rise in the mini-

mum wage. The relative gain (the "dif-

ference in differences" of the changes in

employment) is 2.76 FTE employees (or 13

percent), with a

statistic of 2.03. Inspec-

tion of the averages in rows 4 and 5 shows

that the relative change between New Jer-

sey and Pennsylvania stores is virtually iden-

tical when the analysis is restricted to the

balanced subsample, and it is only slightly

smaller when wave-2 employment at the

temporarily closed stores is treated as zero.

Within New Jersey, employment ex-

panded at the low-wage stores (those paying

$4.25 per hour in wave 1) and contracted at

the high-wage stores (those paying $5.00 or

more per hour). Indeed, the average change

in employment at the high-wage stores

2.16 FTE employees) is almost identical

to the change among Pennsylvania stores

(

2.28 FTE employees). Since high-wage

stores in New Jersey should have been

VOL.

NO.

CARD AND KRUEGER: MINIMUM WAGE AND EMPLOYMENT

largely unaffected by the new minimum

wage, this comparison provides a specifica-

tion test of the validity of the Pennsylvania

control group. The test is clearly passed.

Regardless of whether the affected stores

are compared to stores in Pennsylvania or

high-wage stores in New Jersey, the esti-

mated employment effect of the minimum

wage is similar.

The results in Table 3 suggest that em-

ployment contracted between February and

November of 1992 at fast-food stores that

were unaffected by the rise in the minimum

wage (stores in Pennsylvania and stores in

New Jersey paying $5.00 per hour or more

in wave 1). We suspect that the reason for

this contraction was the continued worsen-

ing of the economies of the middle-Atlantic

states during 1992.13 Unemployment rates

in New Jersey, Pennsylvania, and New York

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-

cyclical, the rise in unemployment would be

expected to lower fast-food employment in

the absence of other

factors.14

Regression-Adjusted Models

The comparisons in Table 3 make no

allowance for other sources of variation in

employment growth, such as differences

across chains. These are incorporated in the

estimates in Table

The entries in this

table are regression coefficients from mod-

An alternative possibility is that seasonal factors

produce higher employment at fast-food restaurants in

February and March than in November and December.

An analysis of national employment data for food

preparation and service workers, however, shows higher

average employment in the fourth quarter than in the

first quarter.

To investigate the cyclicality of fast-food restau-

rant sales we regressed the year-to-year change in

U.S.

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

reduces sales by $257 million, with a

statistic of 3.0.

els of the form:

(la) AE,=a+bXi+cNJi+~,

(lb)

AE,

blXi

clGAPi

where

AE,

is the change in employment

from wave

to wave

at store i, Xi is a set

of characteristics of store i, and NJ, is a

dummy variable that equals 1 for stores in

New Jersey. GAP, is an alternative measure

of the impact of the minimum wage at store

based on the initial wage at that store

(W,,):

GAP,

for stores in Pennsylvania

for stores in New Jersey with

for other stores in New Jersey.

GAP, is the proportional increase in wages

at store

necessary to meet the new mini-

mum rate. Variation in GAP, reflects both

the New Jersey-Pennsylvania contrast and

differences within New Jersey based on re-

ported starting wages in wave 1. Indeed, the

value of GAP, is a strong predictor of the

actual proportional wage change between

waves 1 and

(R*

0.75), and conditional

on GAP, there is no difference in wage

behavior between stores in New Jersey and

Pennsylvania.

The estimate in column (i) of Table

is directly comparable to the simple

difference-in-differences of employment

changes in column

(iv), row

of Table 3.

The discrepancy between the two

estimates is due to the restricted sample in

Table

In Table

and the remaining ta-

bles in this section we restrict our analysis

to the set of stores with available employ-

ment and wage data in both waves of the

15~

regression of the proportional wage change be-

tween waves 1 and 2 on

GAP,

has a coefficient of 1.03.

THE AMERICAN ECONOMIC REVlEW SEPTEMBER

1994

TABLE 3-AVERAGE EMPLOYMENT THE RISE PER STORE BEFORE

AND

I~ER

NEW JERSEY MINIMUM WAGE

Stores by state Stores in New Jersey

Differences within

NJ~

Variable

(i)

(ii)

Difference,

NJ-PA

(iii)

Wage

$4.25

(iv)

Wage

$4.26-$4.99

(v)

Wage

$5.00

(vi)

Low-

high

(vii)

Midrange-

high

(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

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

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

$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.

TABLE 4-REDUCED-FORM MODELS FOR CHANGE

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

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

test for exclusion of all control variables.

781

VOL.

NO.

CARD AND KRUEGER: MINIMUM WAGE AND EMPLOYMENT

survey. This restriction results in a slightly

smaller estimate of the relative increase in

employment in New Jersey.

The model in column (ii) introduces a

set of four control variables: dummies for

three of the chains and another dummy for

company-owned stores. As shown by the

probability values in row

these covariates

add little to the model and have no effect

on the size of the estimated New Jersey

dummy.

The specifications in columns

(iiil-(v) use

the GAP variable to measure the effect of

the minimum wage. This variable gives a

slightly better fit than the simple New Jer-

sey dummy, although its implications for the

New Jersey-Pennsylvania comparison are

similar. The mean value of

GAPi among

New Jersey stores is 0.11. Thus the estimate

in column (iii) implies a 1.72 increase in

FTE employment in New Jersey relative to

Pennsylvania.

Since GAP, varies within New Jersey, it is

possible to add both GAP, and NJ, to the

employment model. The estimated coeffi-

cient of the New Jersey dummy then pro-

vides a test of the Pennsylvania control

group. When we estimate these models, the

coefficient of the New Jersey dummy is in-

significant (with

ratios of 0.3-0.7), imply-

ing that inferences about the effect of the

minimum wage are similar whether the

comparison is made across states or across

stores in New Jersey with higher and lower

initial wages.

even stronger test is provided in col-

umn (v), where we have added dummies

representing three regions of New Jersey

(North, Central, and South) and two regions

of eastern Pennsylvania (Allentown-Easton

and the northern suburbs of Philadelphia).

These dummies control for any region-

s~ecific demand shocks and identifv the ef-

feet

of the minimum wage by

employment changes at higher- and lower-

wage

within

the

same

region

New

Jersey. The probability value in row

shows

no evidence of regional components in em-

ployment growth. The addition

the re-

gion dummies

attenuates

the

GAP

coeffi-

cient and raises its standard error, however,

making it no longer possible to reject the

null hypothesis of a zero employment effect

of the minimum wage. One explanation for

this attenuation is the presence of measure-

ment error in the starting wage. Even if

employment growth has no regional compo-

nent, the addition of region dummies will

lead to some attenuation of the estimated

GAP coefficient if some of the true varia-

tion in GAP is explained by region. Indeed,

calculations based on the estimated reliabil-

ity of the GAP variable (from the set of 11

double interviews) suggest that the fall in

the estimated GAP coefficient from column

(iv) to column

(v)

is just equal to the ex-

pected change attributable to measurement

error.16

We have also estimated the models in

Table 4 using as a dependent variable the

proportional change in employment at each

store.17 The estimated coefficients of the

New Jersey dummy and the GAP variable

are uniformly positive in these models but

insignificantly different from 0 at conven-

tional levels. The implied employment ef-

fects of the minimum wage are also smaller

when the dependent variable is expressed in

proportional terms. For example, the GAP

coefficient in column

(iii) of Table 4 implies

that the increase in minimum wages raised

employment at New Jersey stores that were

initially paying $4.25 per hour by 14 per-

cent. The estimated GAP coefficient from a

corresponding proportional model implies

an effect of only 7 percent. The difference is

attributable to heterogeneity in the effect of

the minimum wage at larger and smaller

stores. Weighted versions of the propor-

tional-change models (using initial employ-

ment as a weight) give rise to wage

elastici-

In a regression model without other controls the

expected attenuation of the GAP coefficient due to

measurement error is the reliability ratio of

GAP (yo),

which we estimate at 0.70. The expected attenuation

factor when region dummies are added to the model is

(Yo

~2)/(1- ~2), where

is the R-square

statistic of a regression of GAP on region effects (equal

to 0.30). Thus, we expect the estimated GAP coeffi-

cient to fall by a factor of

/YO

0.8 when region

dummies are added to a regression model.

"~hese specifications are reported in table

Card and Krueger (1993).

782

THE AMERICAN ECONOMIC REVIEW SEPTEMBER

I994

ties similar to the elasticities implied by the

estimates in Table 4 (see below).

Specification Tests

The results in Tables 3 and 4 seem to

contradict the standard prediction that a

rise in the minimum wage will reduce em-

ployment. Table 5 presents some alternative

specifications that probe the robustness of

this conclusion. For completeness, we re-

port estimates of models for the change in

employment [columns

(i) and (ii)] and esti-

mates of models for the proportional change

in employment [columns

(iii) and (iv)].18 The

first row of the table reproduces the "base

specification" from columns (ii) and (iv) of

Table 4. (Note that these models include

chain dummies and a dummy for company-

owned stores). Row 2 presents an alterna-

tive set of estimates when we set wave-2

employment at the temporarily closed stores

to 0 (expanding our sample size by 4). This

change has a small attenuating effect on the

coefficient of the New Jersey dummy (since

all four stores are in New Jersey) but less

effect on the GAP coefficient (since the size

of GAP is uncorrelated with the probability

of a temporary closure within New Jersey).

Rows 3-5 present estimation results us-

ing alternative measures of

full-time-equiv-

alent employment. In row 3, employment is

redefined to exclude management employ-

ees. This change has no effect relative to

the base specification. In rows 4 and 5, we

include managers in FTE employment but

reweight part-time workers as either 40 per-

cent or 60 percent of full-time workers (in-

stead of 50 percent).19 These changes have

The proportional change in employment is de-

fined as the change in employment divided by the

average level of employment in waves 1 and

This

results in very similar coefficients but smaller standard

errors than the alternative of dividing by wave-1 em-

ployment. For closed stores we set the proportional

change in employment to

Analysis of the 1991 Current Population Survey

reveals that part-time workers in the restaurant indus-

try work about

percent as many hours as full-time

workers. Katz and Krueger (1992) report that the ratio

of part-time workers' hours to full-time workers' hours

in the fast-food industry is

0.57.

little effect on the models for the level of

employment but yield slightly smaller point

estimates in the proportional-employment-

change models.

In row 6 we present estimates obtained

from a subsample that excludes 35 stores in

towns along the New Jersey shore. The ex-

clusion of these stores, which may have a

different seasonal pattern than other stores

in our sample, leads to slightly larger mini-

mum-wage effects. A similar finding emerges

in row

when we add a set of dummy

variables that indicate the week of the

wave-2

inter vie^.^'

As noted earlier, we made an extra effort

to obtain responses from New Jersey stores

in the first wave of our survey. The fraction

of stores called three or more times to ob-

tain an interview was higher in New Jersey

than in Pennsylvania. To check the sensitiv-

ity of our results to this sampling feature,

we reestimated our models on a subsample

that excludes any stores that were called

back more than twice. The results, in row 8,

are very similar to the base specification.

Row

presents weighted estimation re-

sults for the proportional-employment-

change models, using as weights the initial

levels of employment in each store. Since

the proportional change in average employ-

ment is an employment-weighted average of

the proportional changes at each store, a

weighted version of the proportional-change

model should give rise to elasticities that

are similar to the implied elasticities arising

from the levels models. Consistent with this

expectation, the weighted estimates are

larger than the unweighted estimates, and

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

-the same proportional employment effect

implied by the simple

difference-in-dif-

ferences in Table 3. Similarly, the weighted

estimate of the GAP coefficient in the

proportional-change model (0.81) is close to

We also added dummies for the interview dates

for the wave-1 survey, but these were insignificant and

did not change the estimated minimum-wage effects.

783

VOL. 84 NO. 4

CARD AND KRUEGER: MINIMUM WAGE AND EMPLOYMENT

Proportional change

Change in employment

in employment

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

full-timec

5. Weight part-time as 0.6

full-timed

6. Exclude stores in NJ shore areae

7. Add controls for wave-2 interview

dateE

Exclude stores called more than twice

in wave

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-time equivalent 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.

'~odels include 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.

Subsample of 51 stores in towns around Newark.

Subsample of 54 stores in town 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 elasticity of employment with

respect to wages from the basic levels speci-

fication in row 1, column (iiI2l These find-

ings suggest that the proportional effect of

the rise in the minimum wage was concen-

trated among larger stores.

One explanation for our finding that a

rise in the minimum wage has a positive

employment effect is that unobserved de-

mand shocks within New Jersey outweighed

the negative employment effect of the mini-

mum wage. To address this possibility, rows

10 and

present estimation results based

on subsamples of stores in two narrowly

defined areas: towns around Newark (row

10) and towns around

Camden (row 11). In

each case the sample area is identified by

the first three digits of the store's zip

code.22

Within both areas the change in employ-

ment is positively correlated with the GAP

variable, although in neither case is the

effect statistically significant. To the extent

that fast-food product market conditions are

constant within local areas, these results

suggest that our findings are not driven by

unobserved demand shocks. Our analysis of

price changes (reported below) also sup-

ports this conclusion.

A final specification check is presented in

row 12 of Table 5. In this row we exclude

stores in New Jersey and (incorrectly) de-

fine the GAP variable for Pennsylvania

stores as the proportional increase in wages

necessary to raise the wage to $5.05 per

hour. In principle the size of the wage gap

for stores in Pennsylvania should have no

systematic relation with employment growth.

In practice, this is the case. There is no

indication that the wage gap is spuriously

related to employment growth.

21~ssuming average employment of 20.4 in New

Jersey, the

14.92

GAP coefficient in row

column (ii)

im lies an employment elasticity of 0.73.

"The "070" three-digit zip-code area (around

Newark) and the "080" three-digit zip-code area

(around Camden) have by far the largest numbers of

stores among three-digit zip-code areas in New Jersey,

and together they account for 36 percent of New Jersey

stores in our sample.

We have also investigated whether the

first-differenced specification used in our

employment models is appropriate. A

first-differenced model implies that the

level

of employment in period

is related to the

lagged level of employment with a coeffi-

cient of 1. If short-run employment fluctua-

tions are smoothed, however, the true co-

efficient of lagged employment may be less

than 1. Imposing the assumption of a unit

coefficient may then lead to biases. To test

the first-differenced specification we

reesti-

mated models for the change in employ-

ment including wave-1 employment as an

additional explanatory variable. To over-

come any mechanical correlation between

base-period employment and the change in

employment (attributable to measurement

error) we instrumented wave-1 employment

with the number of cash registers in the

store in wave

and the number of registers

in the store that were open at 11:OO

A.M.

all of the specifications the coefficient of

wave-1 employment is close to zero. For

example, in a specification including the

GAP variable and ownership and chain

dummies, the coefficient of wave-1 employ-

ment is 0.04, with a standard error of 0.24.

We conclude that the first-differenced spec-

ification is appropriate.

Full-Time and Part-Time Substitution

Our analysis so far has concentrated on

full-time-equivalent employment and ig-

nored possible changes in the distribution

of full- and part-time workers.

increase

in the minimum wage could lead to an in-

crease in full-time employment relative to

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

are typically older and may well possess

higher skills than part-time workers. Thus, a

conventional model predicts that stores may

respond to an increase in the minimum

wage by increasing the proportion of full-

time workers. Nevertheless, 81 percent of

restaurants paid full-time and part-time

785 VOL. 84 NO. 4

CARD AND KRUEGER: MINIMUM WAGE AND EMPLOYMENT

Outcome measure

Store Characteristics:

Mean c

(i)

hange in

(ii)

outcome

(iii)

Regression of change in

outcome variable on:

NJ dummy Wage gapa Wage gapb

(iv)

(v) (vi)

1. Fraction full-time workersc (percentage)

Number of hours open per weekday

Number of cash registers

Number of cash registers open

at 11:OO

A.M.

Employee Meal Programs:

Low-price meal program (percentage)

Free meal program (percentage)

Combination of low-price and free

meals (percentage)

Wage Profile:

Time to first raise (weeks)

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

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

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 equity 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

of Table

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-

tween waves

and 2 of our survey, and

coefficient estimates from regressions of the

change in the proportion of full-time work-

ers on the wage-gap variable, chain dum-

mies, a company-ownership dummy, and re-

gion dummies [in column (41. The results

are ambiguous. The fraction of full-time

workers increased in New Jersey relative to

Pennsylvania by 7.3 percent

(t ratio

1.841,

but regressions on the wage-gap variable

show no significant shift in the fraction of

full-time

workers.24

Other Employment-Related Measures

Rows 2-4 of Table

present results for

other outcome variables that we expect to

be related to the level of restaurant employ-

ment. In particular, we examine whether

the rise in the minimum wage is associated

with a change in the number of hours a

restaurant is open on a weekday, the num-

ber of cash registers in the restaurant, and

the number of cash registers typically in

operation in the restaurant at

11:OO

A.M.

Consistent with our employment results,

none of these variables shows a statistically

significant decline in New Jersey relative to

Pennsylvania. Similarly, regressions includ-

ing the gap variable provide no evidence

that the minimum-wage increase led to a

systematic change in any of these variables

[see columns

(v) and (vi)].

IV.

Nonwage Offsets

One explanation of our finding that a rise

in the minimum wage does not lower em-

ployment is that restaurants can offset the

effect of the minimum wage by reducing

nonwage compensation. For example, if

workers value fringe benefits and wages

equally, employers can simply reduce the

level of fringe benefits by the amount of the

minimum-wage increase, leaving their

em-

24~ithinNew Jersey, the fraction of full-time em-

ployees increased about as quickly at stores with higher

and lower wages in wave

ployment costs unchanged. The main fringe

benefits for fast-food employees are free

and reduced-price meals. In the first wave

of our survey about 19 percent of fast-food

restaurants offered workers free meals. 72

percent offered reduced-price meals, aid 9

percent offered a combination of both free

and reduced-price meals. Low-price meals

are an obvious fringe benefit to cut if the

minimum-wage increase forces restaurants

to pay higher wages.

Rows

and

of Table

present esti-

mates of the effect of the minimum-wage

increase on the incidence of free meals and

reduced-price meals. The proportion of res-

taurants offering reduced-price meals fell

in both New Jersey and Pennsylvania after

the minimum wage increased, with a some-

what greater decline in New Jersey. Con-

trary to an offset story, however, the reduc-

tion in reduced-price meal programs was

accompanied by an increase in the fraction

of stores offering free meals. Relative to

stores in Pennsylvania, New Jersey employ-

ers actually shifted toward more generous

fringe benefits

(i.e., free meals rather than

reduced-price meals). However, the relative

shift is not statistically significant.

We continue to find a statistically in-

significant effect of the minimum-wage in-

crease on the likelihood of receiving free or

reduced-price meals in columns

(v) and (vi),

where we report coefficient estimates of the

GAP variable from regression models for

the change in the incidence of these pro-

grams. The results provide no evidence that

employers offset the minimum-wage in-

crease by reducing free or reduced-price

meals.

Another possibility is that employers re-

sponded to the increase in the minimum

wage by reducing on-the-job training and

flattening the tenure-wage profile (see

Jacob

Mincer and Linda Leighton, 1981).

Indeed, one manager told our interviewer in

wave

that 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-

termine whether this phenomenon occurred

more generally, we analyzed store man-

agers' responses to questions on the amount

VOL. 84 NO. 4

CARD AND KRUEGER: MINIMUM WAGE AND EMPLOYMENT

of time before a normal wage increase and

the usual amount of such raises. In rows

and 9 we report the average changes be-

tween waves 1 and 2 for these two variables,

as well as regression coefficients from mod-

els that include the wage-gap variable.25

Al-

though the average time to the first pay

raise increased by 2.5 weeks in New Jersey

relative to Pennsylvania, the increase is not

statistically significant. Furthermore, there

is only a trivial difference in the relative

change in the amount of the first pay incre-

ment between New Jersey and Pennsylvania

stores.

Finally, we examined a related variable:

the "slope" of the wage profile, which we

measure by the ratio of the typical first raise

to the amount of time until the first raise is

given. As shown in row 10, the slope of the

wage profile flattened

both New Jersey

and Pennsylvania, with no significant rela-

tive difference between states. The change

in the slope is also uncorrelated with the

GAP variable. In summary, we can find no

indication that New Jersey employers

changed either their fringe benefits or their

wage profiles to offset the rise in the mini-

mum wage.26

Price Effects

the Minimum-Wage

Increase

A final issue we examine is the effect of

the minimum wage on the prices of meals at

fast-food restaurants. A competitive model

of the fast-food industry implies that an

increase in the minimum wage will lead to

an increase in product prices. If we assume

constant returns to scale in the industry, the

increase in price should be proportional to

the share of minimum-wage labor in total

25~nwave

the average time to a first wage in-

crease was 18.9 weeks, and the average amount of the

first increase was $0.21 per hour.

26~atzand Krueger (1992) report that a significant

fraction of fast-food stores in Texas responded to an

increase in the minimum wage by raising wages for

workers who were initially earning more than the new

minimum rate. Our results on the slope of the tenure

profile are consistent with their findings.

factor cost. The average restaurant in New

Jersey initially paid about half its workers

less than the new minimum wage. If wages

rose by roughly 15 percent for these work-

ers, and if labor's share of total costs is 30

percent, we would expect prices to rise by

about 2.2 percent

(

0.15

0.5

0.3) due to

the minimum-wage rise.27

In each wave of our survey we asked

managers for the prices of three standard

items: a medium soda, a small order of

french fries, and a main course. The main

course was a basic hamburger at Burger

King, Roy Rogers, and Wendy's restaurants,

and two pieces of chicken at

KFC

stores.

We define "full meal" price as the after-tax

price of a medium soda, a small order of

french fries, and a main course.

Table

presents reduced-form estimates

of the effect of the minimum-wage increase

on prices. The dependent variable in these

models is the change in the logarithm of the

price of a full meal at each store. The key

independent variable is either a dummy in-

dicating whether the store is located in New

Jersey or the proportional wage increase

required to meet the minimum wage (the

GAP variable defined above).

The estimated New Jersey dummy in col-

umn

(i) shows that after-tax meal prices

rose 3.2-percent faster in New Jersey than

in Pennsylvania between February and

November 1992.~~The effect is slightly

larger controlling for chain and company-

ownership [see column ($1. Since the

New Jersey sales tax rate fell by 1 percent-

age point between the waves of our survey,

these estimates suggest that pretax prices

rose 4-percent faster as a result of the

"~ccordin~to the McDonald's Corporation 1991

Annual Report.

payroll and benefits are 31.3 percent of

operating costs at company-owned stores. This calcula-

tion is only approximate because minimum-wage work-

ers make up less than half of payroll even though they

are about half of workers, and because a rise in the

minimum wage causes some employers to increase the

pay of other higher-wage workers in order to maintain

relative pay differentials.

effect is attributable to a 2.0-percent increase

in prices in New Jersey and a 1.0-percent decrease in

prices in Pennsylvania.

- -

THE AMERICAN ECONOMIC REVIEW SEPTEMBER

1994

TABLE 7-REDUCED-FORM MODELS

THE

PRICE

FULL MEAL

FOR

CHANGE

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

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

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-

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 businesses. 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

789

VOL. 84 NO. 4 CARD AND KRUEGER: MINIMUM WAGE AND EMPLOYMENT

entrants.29 To assess the likely size of such

an effect, we used national restaurant direc-

tories for the McDonald's restaurant chain

to compare the numbers of operating

restaurants and the numbers of newly

opened restaurants in different states over

the 1986-1991 period. Many states raised

their minimum wages during this period. In

addition, the federal minimum wage in-

creased in the early 1990's from $3.35 to

$4.25, with differing effects in different states

depending on the level of wages in the

state. These policies create an opportunity

to measure the impact of minimum-wage

laws on store opening rates across states.

The results of our analysis are presented

in Table 8. We regressed the growth rate in

the number of McDonald's stores in each

state on two alternative measures of the

minimum wage in the state and a set of

other control variables (population growth

and the change in the state unemployment

rate). The first minimum-wage measure is

the fraction of workers in the state's retail

trade industry in 1986 whose wages fell be-

tween the existing federal minimum wage in

1986 ($3.35 per hour) and the effective min-

imum wage in the state in April 1990 (the

maximum of the federal minimum wage and

the state minimum wages as of April 1990)."

The second is the ratio of the state's effec-

tive minimum wage in 1990 to the average

hourly wage of retail trade workers in the

state in 1986. Both of these measures are

designed to gauge the degree of upward

wage pressure exerted by state or federal

minimum-wage changes between 1986 and

1990.

The results provide no evidence that

higher minimum-wage rates (relative to the

retail-trade wages in a state) exert a nega-

Direct inquiries to the chains in our sample re-

vealed that Wendy's opened two stores in New Jersey

in 1992 and one store in Pennsylvania. The other

chains were unwilling to provide information on new

openings.

We used the 1986 Current Population Survey

(merged monthly file) to construct the minimum-wage

variables. State minimum-wage rates in 1990 were ob-

tained from the Bureau of National Affairs

Labor

Relations Reporter Wages and Hours Manual

(undated).

tive effect on either the net number of

restaurants or the rate of new openings. To

the contrary, all the estimates show

positice

effects of higher minimum wages on the

number of operating or newly opened stores,

although many of the point estimates are

insignificantly different from zero. While this

evidence is limited, we conclude that the

effects of minimum wages on fast-food store

opening rates are probably small.

VII.

Broader Evidence on Employment

Changes in New Jersey

Our establishment-level analysis suggests

that the rise in the minimum wage in New

Jersey may have increased employment in

the fast-food industry. Is this just an anomaly

associated with our particular sample, or a

phenomenon unique to the fast-food indus-

try? Data from the monthly Current Popu-

lation Survey

(CPS) allow us to compare

state-wide employment trends in New Jer-

sey and the surrounding states, providing a

check on the interpretation of our findings.

Using monthly CPS files for 1991 and 1992,

we computed employment-population rates

for teenagers and adults (age 25 and older)

for New Jersey, Pennsylvania, New York,

and the entire United States. Since the New

Jersey minimum wage rose on April 1, 1992,

we computed the employment rates for

April-December of both 1991 and 1992.

The relative changes in employment in New

Jersey and the surrounding states then give

an indication of the effect of the new law.

A comparison of changes in adult em-

ployment rates show that the New Jersey

labor market fared slightly worse over the

1991-1992 period than either the U.S. labor

market as a whole or labor markets in

Pennsylvania or New York (see Card and

Krueger, 1993 table

9l3' Among teenagers,

however, the situation was reversed. In New

Jersey, teenage employment rates fell by 0.7

percent from 1991 to 1992. In New York,

The employment rate of individuals age 25 and

older fell by 2.6 percent in New Jersey between 1991

and 1992, while it rose by 0.3 percent in Pennsylvania,

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

0.56

(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~aximum of 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-

Standard Competitive Model

tent with our findings for the fast-food in-

dustry, the standard error is too large (3.2

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-~ercent in-

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

791

VOL.

NO.

CARD AND KRUEGER: MINIMUM WAGE AND EMPLOYMENT

teenagers, and not just those employed in

low-wage industries, it is surely a lower

bound on the magnitude of the effect for

fast-food workers. The 18-percent increase

in the New Jersey minimum wage is there-

fore predicted to reduce employment at

fast-food stores by 0.4-1.0 employees per

store. Our empirical results clearly reject

the upper range of these estimates, al-

though we cannot reject a small negative

effect in some of our specifications.

A possible defense of the competitive

model is that unobserved demand shocks

affected certain stores in New Jersey-

specifically, those stores that were initially

paying wages less than $5.00 per hour. How-

ever, such localized demand shocks should

also affect product prices. (In fact, in a

competitive model, product demand shocks

work through a rise in prices.) Although

lower-wage stores in New Jersey had rela-

tive employment gains, they did not have

relative price increases. Furthermore, our

analysis of employment changes in two ma-

jor suburban areas (around Newark and

Camden) reveals that, even within local

areas, employment rose faster at the stores

that had to increase wages the most because

of the new minimum wage.

Alternative Models

An alternative to the conventional com-

petitive model is one in which firms are

price-takers in the product market but have

some degree of market power in the labor

market. If fast-food stores face an

upward-

sloping labor-supply schedule, a rise in the

minimum wage can potentially increase em-

ployment at affected firms and in the indus-

try as a whole.32

This same basic insight emerges from an

equilibrium search model in which firms

post wages and employees search among

posted offers (see Dale T. Mortensen, 1988).

Kenneth Burdett and Mortensen (1989)

de-

"~aniel

Sullivan

(1989)

and Michael R Ransom

(1993)

present empirical results for nurses and univer-

sity teachers that suggest monopsony-like behavior of

employers.

rive the equilibrium wage distribution for a

noncooperative

wage-search/wage-posting

model and show that the imposition of a

binding minimum wage can increase both

wages and employment relative to the initial

equilibrium. Furthermore, their model pre-

dicts that the minimum wage will increase

employment the most at firms that initially

paid the lowest wages.

Although monopsonistic and job-search

models provide a potential explanation for

the observed employment effects of the New

Jersey minimum wage, they cannot explain

the observed price effects. In these models,

industry prices should have fallen in New

Jersey relative to Pennsylvania, and at

low-

wage stores in New Jersey relative to high-

wage stores in New Jersey. Neither predic-

tion is confirmed: indeed, prices rose faster

in New Jersey than in Pennsylvania, al-

though at about the same rate at high- and

low-wage stores in New Jersey. Another

puzzle for equilibrium search models is the

absence of wage increases at firms that were

initially paying $5.05 or more per hour.

The strict link between the employment

and price effects of a rise in the minimum

wage may be broken if fast-food stores can

vary the quality of service

(e.g., the length of

the queue at peak hours, or the cleanliness

of stores). Another possibility is that stores

altered the

relative

prices of their various

menu items. Comparisons of price changes

for the three items in our survey show slight

declines (-1.5 percent) in the price of

french fries and soda in New Jersey relative

to Pennsylvania, coupled with a relative in-

crease (8 percent) in entrCe prices. These

limited data suggest a possible role for rela-

tive price changes within the fast-food in-

dustry following the rise in the minimum

wage.

One way to test a monopsony model is to

identify stores that were initially

"supply-

constrained" in the labor market and test

for employment gains at these stores rela-

tive to other stores.

potential indicator of

market power is the use of recruitment

bonuses. As we noted in Table 2, about 25

percent of stores in wave

were offering

cash bonuses to employees who helped find

a new worker. We compared employment

792

THE AMERICAN ECONOMIC REVIEW SEPTEMBER

1994

changes at New Jersey stores that were of-

fering recruitment bonuses in wave 1, and

also interacted the GAP variable with a

dummy for recruitment bonuses in several

employment-change models. We do not find

faster (or slower) employment growth at the

New Jersey stores that were initially using

recruitment bonuses, or any evidence that

the GAP variable had a larger effect for

stores that were using bonuses.

IX.

Conclusions

Contrary to the central prediction of the

textbook model of the minimum wage, but

consistent with a number of recent studies

based on cross-sectional time-series com-

parisons of affected and unaffected markets

or employers, we find no evidence that the

rise in New Jersey's minimum wage reduced

employment at fast-food restaurants in the

state. Regardless of whether we compare

stores in New Jersey that were affected by

the $5.05 minimum to stores in eastern

Pennsylvania (where the minimum wage was

constant at $4.25 per hour) or to stores in

New Jersey that were initially paying $5.00

per hour or more (and were largely unaf-

fected by the new law), we find that the

increase in the minimum wage increased

employment. We present a wide variety of

alternative specifications to probe the ro-

bustness of this conclusion. None of the

alternatives shows a negative employment

effect. We also check our findings for the

fast-food industry by comparing changes in

teenage employment rates in New Jersey,

Pennsylvania, and New York in the year

following the increase in the minimum wage.

Again, these results point toward a relative

increase in employment of low-wage work-

ers in New Jersey. We also find no evidence

that minimum-wage increases negatively

affect the number of McDonald's outlets

opened in a state.

Finally, we find that prices of fast-food

meals increased in New Jersey relative to

Pennsylvania, suggesting that much of the

burden of the minimum-wage rise was

passed on to consumers. Within New Jer-

sey, however, we find no evidence that prices

increased more in stores that were most

affected by the minimum-wage rise. Taken

as a whole, these findings are difficult to

explain with the standard competitive model

or with models in which employers face

supply constraints

(e.g., monopsony or equi-

librium search models).

REFERENCES

Brown, Charles; Gilroy, Curtis and Kohen, An-

drew.

"The Effect of the Minimum Wage

on Employment and Unemployment."

Journal of Economic Literature, June 1982,

20(2), pp. 487-528.

"Time Series Evidence on the Ef-

fect of the Minimum Wage on Youth

Employment and Unemployment." Jour-

nal of Human Resources, Winter 1983,

18(1), pp. 3-31.

Burdett, Kenneth and Mortensen, Dale

"Equilibrium Wage Differentials and

Employer Size." Center for Mathematical

Studies in Economics and Management

Science Discussion Paper No. 860, North-

western University, October 1989.

Bureau of National Affairs.

Daily Labor Re-

port. Washington, DC: Bureau of Na-

tional Affairs, 5 May 1990.

Labor Relations Reporter Wages and

Hours Manual. Washington, DC: Bureau

of National Affairs, irregular.

Card, David.

"Using Regional Variation in

Wages To Measure the Effects of the

Federal Minimum Wage." Industrial and

Labor Relations

Reuiew, October 1992a,

46(1), pp. 22-37.

"Do Minimum Wages Reduce Em-

ployment? A Case Study of California,

1987-89." Industrial and Labor Relations

Reuiew, October 1992b, 46(1), pp. 38-54.

Card, David and Krueger, Alan B.

"Minimum

Wages and Employment: A Case Study of

the Fast Food Industry in New Jersey and

Pennsylvania." National Bureau of Eco-

nomic Research (Cambridge, MA) Work-

ing Paper No. 4509, October 1993.

Katz, Lawrence

and Krueger, Alan B.

"The

Effect of the Minimum Wage on the Fast

Food Industry." Industrial and Labor Re-

lations

Reuiew, October 1992, 46(1), pp.

6-21.

793

VOL.

NO.

CARD AND KRUEGER: MINIMUM WAGE AND EMPLOYMENT

Lester, Richard A.

"Employment Effects of

Minimum Wages." Industrial and Labor

Relations Reuiew, January 1960, 13, pp.

254-64.

The economics of labor, 2nd Ed.

New York: Macmillan, 1964.

Machin, Stephen and Manning, Alan.

"The

Effects of Minimum Wages on Wage Dis-

persion and Employment: Evidence from

the

U.K.

Wage Councils." Industrial and

Labor Relations Reuiew, January 1994,

47(2), pp. 319-29.

McDonald's Corporation.

1991 Annual report.

Chicago, 1991.

Mincer, Jacob and Leighton, Linda.

"The Ef-

fects of Minimum Wages on Human Cap-

ital Formation," in Simon Rottenberg,

ed., The economics of legal minimum

wages. Washington, DC: American Enter-

prise Institute, 1981, pp. 155-73.

Mortensen, Dale

"Equilibrium Wage Dis-

tributions:

Synthesis." Center for

Mathematical Studies in Economics and

Management Science Discussion Paper

No. 811, Northwestern University, March

1988.

Ransom, Michael R.

"Seniority and Monop-

sony in the Academic Labor Market."

American Economic

Reuiew, March 1993,

83(1), pp. 221-33.

Stigler, George J.

"The Economics of Mini-

mum Wage Legislation." American Eco-

nomic Reciew, June 1946,

36(3), pp.

358-65.

Sullivan, Daniel G.

"Monopsony Power in the

Market for Nurses." Journal of Law and

Economics, October 1989, Part 2,

32(2),

pp. S135-78.

U.S. Department of Commerce.

1987 Census of

retail trade: Miscellaneous subjects. Wash-

ington, DC: U.S. Government Printing

Office, October 1990.

Wellington, Alison J.

"Effects of the Mini-

mum Wage on the Employment Status of

Youths: An Update." Journal of Human

Resources, Winter 1991, 26(1), pp. 27-46.

You have printed the following article:

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

and Pennsylvania

David Card; Alan B. Krueger

The American Economic Review, Vol. 84, No. 4. (Sep., 1994), pp. 772-793.

Stable URL:

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[Footnotes]

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

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

http://www.jstor.org

LINKED CITATIONS

- Page 1 of 4 -

NOTE: The reference numbering from the original has been maintained in this citation list.

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

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

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

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

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

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

http://www.jstor.org

LINKED CITATIONS

- Page 2 of 4 -

NOTE: The reference numbering from the original has been maintained in this citation list.

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

http://www.jstor.org

LINKED CITATIONS

- Page 3 of 4 -

NOTE: The reference numbering from the original has been maintained in this citation list.

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

Stephen Machin; 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

http://www.jstor.org

LINKED CITATIONS

- Page 4 of 4 -

NOTE: The reference numbering from the original has been maintained in this citation list.

Discussion

"As in the earlier study by Katz and Krueger (1992), our empirical findings on the effects of the New Jersey minimum wage are inconsistent with the predictions of a conventional competitive model of the fast- food industry. Our employment results are consistent with several alternative models, although none of these models can also explain the apparent rise in fast-food prices in New Jersey." Key result: "The relative gain (the "difference in differences" of the changes in employment) is 2.76 FTE employees (or 13 percent), with a t statistic of 2.03." "The average starting wage at fast-food restaurants in New Jersey increased by 10 percent following the rise in the minimum wage." "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 New Jersey and Pennsylvania following the increase in New Jersey's minimum wage from 4.25 to 5.05 per hour. Comparisons of employment, wages, and prices at stores in New Jersey and Pennsylvania before and after the rise offer a simple method for evaluating the effects of the-minimum wage. Comparisons within New Jersey between initially high-wage stores (those paying more than the new minimum rate prior to its effective date) and other stores provide an alternative estimate of the impact of the new law." Economics field research is interesting....: "we hired an interviewer to drive to each of the 39 nonrespondents and determine whether the store was still open, and to conduct a personal interview if possible." "The results in Tables 3 and 4 seem to contradict the standard prediction that a rise in the minimum wage will reduce employment." Choosing to study the fast-food industry was an important decision and meaningful part of this study, as it lent itself perfectly to a natural experiment. State history of the minimum wage in New Jersey: ![Imgur](https://imgur.com/NWEpFeO.png) Source: https://fred.stlouisfed.org/series/STTMINWGNJ This would be an instance of survivorship bias, if they did not follow up with all of the stores (but only the ones that stayed open following the introduction of the minimum wage). "Third, we successfully followed nearly 100 percent of stores from a first wave of inter- views conducted just before the rise in the minimum wage (in February and March 1992) to a second wave conducted 7-8 months after (in November and December 1992). We have complete information on store closings and take account of employment changes at the closed stores in our analyses. We therefore measure the overall effect of the minimum wage on average employment, and not simply its effect on surviving establishments." Sample design and response rates. Key summary data. More compelling reasons to choose this industry for their natural experiment. "Second, fast-food restaurants comply with minimum-wage regulations and would be expected to raise wages in response to a rise in the minimum wage. Third, the job requirements and products of fast-food restaurants are relatively homogeneous, making it easier to obtain reliable measures of employment, wages, and product prices. The absence of tips greatly simplifies the measurement of wages in the industry. Fourth, it is relatively easy to construct a sample frame of franchised restaurants. Finally, past experience (Katz and Krueger, 1992) suggested that fast-food restaurants have high response rates to telephone survey." The authors will discuss more on the differences-in-differences method that they use to model the effect of this minimum wage on employment. One key to the differences-in-differences approach is having a control group that is very similar to the treatment group. The control group in this case is the adjacent state Pennsylvania which did not implement a minimum wage, but should otherwise behave very similar (I️.e. when it comes to seasonal employment). "Second, New Jersey is a relatively small state with an economy that is closely linked to nearby states. We believe that a control group of fast-food stores in eastern Pennsylvania forms a natural basis for comparison with the experiences of restaurants in New Jersey. Wage variation across stores in New Jersey, however, allows us to compare the experiences of high-wage and low-wage stores within New Jersey and to test the validity of the Pennsylvania control group. Moreover, since seasonal patterns of employment are similar in New Jersey and eastern Pennsylvania, as well as across high- and low-wage stores within New Jersey, our comparative methodology effectively "differences out" any. seasonal employment effects." The classic model of employment differs with the reality found from most natural experiments: that increasing wages leads to increasing employment. Under the classic model, which has the textbook supply and demand curves, lifting the minimum wage would lead to less employment. Here are the curves, and the outcome there is that employment moves from the N_eq to N_min. ![Imgur](https://imgur.com/j8oFvaO.png) Source and discussion of the basic model: https://jaredbernsteinblog.com/models-of-the-minimum-wage-for-what-theyre-worth/ David Card is a labour economist and professor at UC Berkeley. Alan Krueger was an economist and former Assistant Secretary of the Treasury for Economic Policy. Their bios: David Card: https://en.wikipedia.org/wiki/David_Card Alan Krueger: https://en.wikipedia.org/wiki/Alan_Krueger Important conclusion with non-intuitive findings that have real policy implications. "Contrary to the central prediction of the textbook model of the minimum wage, but consistent with a number of recent studies based on cross-sectional time-series com- parisons of affected and unaffected markets or employers, we find no evidence that the rise in New Jersey's minimum wage reduced employment at fast-food restaurants in the state. Regardless of whether we compare stores in New Jersey that were affected by the $5.05 minimum to stores in eastern Pennsylvania (where the minimum wage was constant at 4.25 per hour) or to stores in New Jersey that were initially paying 5.00 per hour or more (and were largely unaffected by the new law), we find that the increase in the minimum wage increased employment. We present a wide variety of alternative specifications to probe the robustness of this conclusion. None of the alternatives shows a negative employment effect. We also check our findings for the fast-food industry by comparing changes in teenage employment rates in New Jersey, Pennsylvania, and New York in the year following the increase in the minimum wage. Again, these results point toward a relative increase in employment of low-wage workers in New Jersey. We also find no evidence that minimum-wage increases negatively affect the number of McDonald's outlets opened in a state." "Difference in differences is a statistical technique used in econometrics and quantitative research in the social sciences that attempts to mimic an experimental research design using observational study data, by studying the differential effect of a treatment on a 'treatment group' versus a 'control group' in a natural experiment. It calculates the effect of a treatment (i.e., an explanatory variable or an independent variable) on an outcome (i.e., a response variable or dependent variable) by comparing the average change over time in the outcome variable for the treatment group to the average change over time for the control group. Although it is intended to mitigate the effects of extraneous factors and selection bias, depending on how the treatment group is chosen, this method may still be subject to certain biases (e.g., mean regression, reverse causality and omitted variable bias)." Source: https://en.wikipedia.org/wiki/Difference_in_differences Tl;dr: This is a research summary of the paper from the Nobel prize website, explaining the paper that contributed to the 2021 Nobel prize in Economics being awarded to David Card. "In the early 1990s, the conventional wisdom among economists was that higher minimum wages lead to lower employment because they increase wage costs for businesses. However, the evidence supporting this conclusion was not fully convincing; there were indeed many studies that indicated a negative correlation between minimum wages and employment, but did this really mean that higher minimum wages led to higher unemployment? Reverse causation could even be the issue: when unemployment rises, employers can set lower wages which, in turn, may lead to demands to increase the minimum wage. To investigate how increased minimum wages affect employment, Card and Krueger used a natural experiment. In the early 1990s, the minimum hourly wage in New Jersey was raised from 4.25 dollars to 5.05 dollars. Just studying what happened in New Jersey after this increase does not give a reliable answer to the question, as numerous other factors can influence how employment levels change over time. As with randomised experiments, a control group was needed, i.e., a group where wages didn’t change but all the other factors were the same. Card and Krueger noted that there was no increase in neighbouring Pennsylvania. Of course, there were differences between the two states, but it is likely that the labour markets would evolve similarly close to the border. So, they studied the effects on employment in two neighbouring areas – New Jersey and eastern Pennsylvania – which have a similar labour market, but where the minimum wage was increased on one side of the border but not the other. There was no apparent reason to believe that any factor (such as the economic situation) apart from the increase in the minimum wage would affect employment trends differently on either side of the border. Thus, if a change in the number of employees was observed in New Jersey, and this differed from any change on the other side of the border, there was good reason to interpret this as an effect of the increase in the minimum wage. Card and Krueger focused on employment in fast-food restaurants, an industry where pay is low and minimum wages matter. Contrary to previous research, they found that an increase in the minimum wage had no effect on the number of employees. David Card arrived at the same conclusion in a couple of studies in the early 1990s. This pioneering research has led to a large number of follow-up studies. The overall conclusion is that the negative effects of increasing the minimum wage are small, and significantly smaller than was believed 30 years ago." Source: https://www.nobelprize.org/prizes/economic-sciences/2021/popular-information/ ![Imgur](https://imgur.com/DTqka0P.png) There could be many explanations for the jump in employment following the introduction of the minimum wage, and the authors here counter argue a few of the main arguments skeptics might have. The first argument might be that employment everywhere jumped around the same time (not true). "First, the rise in the minimum wage occurred during a recession. The increase had been legislated two years earlier when the state economy was relatively healthy. By the time of the actual increase, the unemployment rate in New Jersey had risen substantially and last-minute political action almost succeeded in reducing the minimum-wage increase. It is unlikely that the effects of the higher minimum wage were obscured by a rising tide of general economic conditions."

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