2023年7月27日发(作者：)

Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jerseyand PennsylvaniaAuthor(s): David Card and Alan B. KruegerSource:

The American Economic Review,

Vol. 84, No. 4, (Sep., 1994), pp. 772-793Published by: American Economic AssociationStable URL: /stable/2118030Accessed: 10/06/2008 21:34Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at/page/info/about/policies/. JSTOR's Terms and Conditions of Use provides, in part, that unlessyou have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and youmay use content in the JSTOR archive only for your personal, non-commercial contact the publisher regarding any further use of this work. Publisher contact information may be obtained at/action/showPublisher?publisherCode= copy of any part of a JSTOR transmission must contain the same copyright notice that appears on the screen or printedpage of such is a not-for-profit organization founded in 1995 to build trusted digital archives for scholarship. We enable thescholarly community to preserve their work and the materials they rely upon, and to build a common research platform thatpromotes the discovery and use of these resources. For more information about JSTOR, please contact support@://imum Wages and Employment:

A Case Study of the Fast-Food Industry

in New Jersey and Pennsylvania

By

DAVID CARD AND ALAN

B.

KRUEGER*

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

to $5.05 per

in

410 fast-food restaurants

hour. To evaluate the impact of the law we surveyed

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 J30, J23)

How do employers

in a low-wage labor

market

respond

to an increase

in the mini-

mum wage? The prediction from conven-

tional economic theory is unambiguous: a

rise in the minimum wage leads perfectly

competitive employers to cut employment

(George J. Stigler, 1946). Although studies

in the 1970's based on aggregate

teenage

employment rates usually confirmed this

prediction,1 earlier studies based on com-

parisons of employment at affected and un-

affected establishments often did not (e.g.,

Richard A. Lester, 1960, 1964). Several re-

Department of Economics, Princeton University,

Princeton, NJ 08544. We are grateful to the Institute

for Research on Poverty, University of Wisconsin, for

partial financial support. Thanks to Orley Ashenfelter,

Charles Brown, Richard Lester, Gary Solon, two

anonymous referees, and seminar participants at

Princeton, Michigan State, Texas A&M, University of

Michigan, University of Pennsylvania, University of

Chicago, and the NBER for comments and sugges-

tions. We also acknowledge the expert research assis-

tance of Susan Belden, Chris Burris, Geraldine Harris,

and Jonathan Orszag.

1See Charles Brown et al. (1982, 1983) for surveys of

this literature. A recent update (Allison J. Wellington,

1991) concludes that the employment effects of the

minimum wage are negative but small: a 10-percent

increase in the minimum is estimated to lower teenage

emplovment rates by 0.06 percentage noints.

772

*

compara-

cent studies

that rely on a similar

tive methodology have failed to detect a

effect of higher

mini-

negative employment

mum wages. Analyses

of the 1990-1991 in-

creases in the federal minimum wage

1992; Card,

and Krueger,

(Lawrence F. Katz

1992a) and of an earlier increase in the

minimum

(Card, 1992b)

wage

in California

A study

employment impact.

find no adverse

in Britain

floors

(Stephen

of minimum-wage

reaches

a

1994)

Machin and Alan Manning,

similar conclusion.

This paper presents

new evidence

on the

effect of minimum wages on establishment-

the

We analyze

level employment outcomes.

in

of 410 fast-food restaurants

experiences

the

New Jersey

and Pennsylvania following

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.

within New Jersey between

Comparisons

(those paying more

initially high-wage stores

than the new minimum rate prior to its

effective date) and other stores provide

an

alternative estimate of the impact of the

new law.

In addition

to the simplicity of our empir-

ical methodology, several other features of VOL. 84 NO. 4

AND EMPLOYMENT

CARD

AND KRUEGER: MINIMUM WAGE

773

the New Jersey law and our

data set are

also significant. First, the rise

in the mini-

a recession. The

mum during

wage

occurred

increase

had been legislated

two years ear-

lier when the state economy

was relatively

By the time of the actual

increase,

healthy.

the unemployment rate

in New Jersey

had

political

risen substantially and last-minute

action almost succeeded in

reducing the

of the relative

mini-

and 1991 to measures

mum

wage in each state.

I. The New Jersey Law

A bill signed into law in November

1989

$3.35

minimum wage

from

raised the federal

per hour to $3.80 effective April 1, 1990,

to $4.25 per hour

on

increase

with a further

minimum-wage increase. It is unlikely

the effects of the higher minimum

wage

that

were obscured by a rising tide of general

economic conditions.

state with an economy

Second,

New Jersey is a relatively

sto nearby

group

sthat is closely linked

mall

vania forms a natural

of fast-food

tates. We believe that a control

stores

in eastern

Pennsyl-

with the experiences

Jersey.

obf restaurants in New

asis for comparison

across stores

Jersey, however,

Wage

variation

allows us to compare

in New

the

experiences

stores within New Jersey

of high-wage and low-wage

and to

validity

control

test

the

Moreover, since

of the Pennsylvania

seasonal patterns

of em-

group.

ployment

are similar in New Jersey

and

eastern Pennsylvania,

high- and low-wage

tively "differences

our comparative methodology

stores within New Jer-

as well as across

sey,

effec-

out" any seasonal

em-

ployment

effects.

percent

Third,

we successfully followed

nearly

100

views conducted

of stores from a first

minimum wage (in February

just before the rise

wave of inter-

and March

in the

1992) to a second wave conducted

months after (in November

and December

7-8

1992).

store closings and take account

We have complete information

on

ment changes at the closed stores

of employ-

analyses.

effect of the minimum

We therefore

mthe overall

in our

employment,

and not

simply

weasure

age on average

its effect on

surviving establishments.

-

Our analysis of employment trends

at

stores that were open for business

the increase in the minimum

any potential

wage ignores

before

the rate of new store openings. To assess

effect of minimum wages on

the likely

state-specific growth

magnitude

of this effect we relate

McDonald's

fast-food

rates in the number

outlets between 1986

of

April 1, 1991.

legislature

parallel

went one step further,

In early 1990 the New Jersey

enacting

for 1990

increases in the state

per hour effective

and 1991 and an increase

minimum wage

uled 1992 increase gave New Jersey the

April 1, 1992.

The sched-

to $5.05

highest

and was strongly

state minimum wage in the country

opposed

by business

of National

lead-

ers in the state (see Bureau

Affairs, Daily Labor Report,

In the two years between passage

5 May 1990).

of the

$5.05 minimum wage

New Jersey's economy slipped

and its effective

date,

sion. Concerned with the potentially ad-

into reces-

verse

state legislature voted in March 1992 to

impact

of a higher

minimum wage,

the

phase

The vote fell just short of the margin

in the 80-cent

increase

over

two

years.

quired

the Governor

to override a gubernatorial

veto, and

re-

into effect on April 1 before vetoing the

allowed the $5.05 rate to go

two-step

of having

legislation. Faced

wage earners, the legislature

to roll back wages for minimum-

with

the prospect

issue. Despite a strong last-minute

dropped

the

lenge, the $5.05 minimum

as originally planned.

rate took effect

chal-

II. Sample Design

and Evaluation

impending increase

Early

in 1992

we decided to evaluate

mum

in the New Jersey

mtini-

he

rants

nia.2 Our choice of the fast-food industry

iwage by surveying

n New Jersey

and eastern

fast-food restau-

Pennsylva-

was driven by several

stores are a leading employer

factors.

First,

fast-food

workers: in 1987,

franchised restaurants em-

of low-wage

2At the time we were uncertain whether

the $5.05

rate would go into effect or be overridden. 774

THE

AMERICAN ECONOMIC REVIEW

TABLE 1-SAMPLE

DESIGN

AND RESPONSE

RATES

SEPTEMBER 1994

Stores in:

All

Wave

1,

February

15-March

4,

1992:

Number of stores in sample frame:a

Number of refusals:

Number interviewed:

Response rate (percentage):

Wave

2, November 5-December 31,

1992:

Number of stores in sample

frame:

Number closed:

Number under rennovation:

Number temporarily closed:b

Number of refusals:

Number interviewed:c

410

6

2

2

1

399

331

5

2

2

1

321

79

1

0

0

0

78

473

63

410

86.7

364

33

331

90.9

109

30

79

72.5

NJ

PA

aStores with working phone

numbers only; 29 stores in

original sample frame had

disconnected phone numbers.

bIncludes

one store closed because of

highway construction and one store closed

because of a fire.

CIncludes

371 phone interviews and 28

personal interviews of stores that refused an

initial request for a phone

interview.

ployed 25 percent of all workers in the

restaurant industry (see U.S. Department of

table 13). fast-food

Commerce, 1990 Second,

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

of

tips greatly simplifies the measurement

it is relatively

wages in the industry. Fourth,

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 surveys.3

Based on these considerations we con-

structed a sample frame of fast-food restau-

rants

in New Jersey

and eastern

Pennsylva-

nia from the Burger

King, KFC, Wendy's,

and Roy Rogers

chains.4

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-

tics.5

Table 1 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-

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.

3In

a pilot survey Katz

and

Krueger (1992)

obtained

4The sample was derived from

white-pages

tele-

phone listings

for New Jersey

and Pennsylvania as of

February 1992.

5Copies

of the questionnaires used in both

waves of

the survey are available from

the authors upon

request. VOL. 84 NO. 4 CARD

AND KRUEGER: MINIMUM WAGE AND EMPLOYMENT

775

nia (72.5 percent) because our interviewer

made fewer call-backs to nonrespondents in

Pennsylvania.6 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

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.)8 Means are

presented

separately for stores in New Jer-

sey and Pennsylvania, along

with t statistics

for the null hypothesis that the means are

increase. Only the 410 stores that re-

sponded

the second round

in the first wave were contacted in

fully interviewed

ostores

of a concern

by phone in November

3f interviews. We success-

71 (90 percent) of these

might have closed, we hired an interviewer

that

nonresponding restaurants

1992. Because

to drive to each of the 39 nonrespondents

and determine

open, and to conduct

whether the store was still

possible.

a personal

interview if

restaurants

The interviewer discovered that

were temporarily closed (one because of a

were permanently

closed, two

six

fire, one because of road

two

open for business, all but one granted a

were under

renovation.7

construction), and

Of the 29 stores

request for a personal interview.

sult, we

for 99.8 percent of the restaurants that re-

have second-wave

interview data

As a re-

sponded

information

in the first

wave of the survey,

and

cent of the sample.

on closure status for 100 per-

key variables

Table 2 presents the means for several

the subset

in our data set, averaged

variable.

ment in wave 2 is set to 0 for the perma-

In constructing the

of nonmissing

responses

means,

feor each

over

mploy-

in the two states. Among New Jersey stores, 44.5

6Response rates per call-back were almost

identical

percent

responded

responded

sylvania stores

after at most two call-backs. Among

on the first call, and 72.0 percent

and 71.6 percent responded

42.2

percent responded on the first

Penn-

backs.

after at most two call-

call,

construction and one of the stores closed for renova-

7As of April 1993

the store closed because

of road

tion had reopened.

when our telephone interviewer called in November

The store closed by fire was open

1992 but refused the interview.

follow-up personal

store.

interview a mall

By the time of the

fire had closed

the

equal in the two states.

by chain and ownership status (company-

Rows la-e show

the distribution of stores

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

open for fewer hours. They also offer a

and are

more expensive

the other chains

m(chicken

ain course than stores in

vs. hamburgers).

full-time equivalent workers per store in

In wave 1, average

employment was 23.3

Pennsylvania, compared

20.4 in New Jersey. Starting wages were

with an average

of

very similar

although

among s(medium soda,

the average

tores in the two states,

was

were no significant cross-state

significantly

small

phigher

fries,

rice of a "full meal"

in New

and an

Jersey.

entree)

There

average

full-time workers, or the prevalence of bonus

hours of operation, the fraction

differences in

of

programs to recruit

restaurants

The average starting wage at fast-food

new workers.9

percent following

in New Jersey increased

by 10

wage. Further insight into this change is

the rise in the minimum

provided

tributions of starting wages

in Figure

1, which shows the dis-

before and after the rise. In wave 1, the

in the two states

distributions in New Jersey and Pennsylva-

nia were

very

similar.

By wave

2

virtually

all

tive assumptions on the measurement of employment

8We discuss the sensitivity of our results

to alterna-

in Section

I"bounty"

9These programs

II-C.

on the job for a minimum

for recruiting any new employee

offer current employees a cash

wbounties

the recruiter with an "employee

are $50-$75. Recruiting programs that

period of time. Typical

ho stays

anation

tabulations.

or other

noncash bonuses

aore

f the month"

excluded from

dward

esig-

our 776

THE AMERICAN ECONOMIC REVIEW

SEPTEMBER 1994

TABLE 2-MEANS OF KEY

VARIABLES

Stores in:

Variable NJ

PA

ta

1. Distribution

of Store Types (percentages):

a. Burger King

41.1 44.3 -0.5

b. KFC

20.5 15.2 1.2

c. Roy Rogers

24.8 21.5 0.6

d. Wendy's 13.6 19.0 - 1.1

e. Company-owned 34.1

35.4 -0.2

2. Means in Wave 1:

a. FTE employment 20.4 23.3

-2.0

(0.51) (1.35)

b. Percentage full-time employees 32.8 35.0

-0.7

(1.3) (2.7)

c. Starting wage

4.61 4.63 -0.4

(0.02) (0.04)

d. Wage

=

$4.25 (percentage)

30.5 32.9 -0.4

(2.5) (5.3)

e. Price of full meal 3.35

3.04 4.0

(0.04) (0.07)

f. Hours open (weekday)

14.4 14.5 -0.3

(0.2) (0.3)

g. Recruiting bonus 23.6

29.1 - 1.0

(2.3)

(5.1)

3. Means in Wave

2:

a. FTE employment 21.0 21.2

-0.2

(0.52) (0.94)

b. Percentage full-time employees 35.9 30.4 1.8

(1.4) (2.8)

c. Starting wage

5.08 4.62 10.8

(0.01) (0.04)

d. Wage

=

$4.25 (percentage)

0.0 25.3

(4.9)

e. Wage

=

$5.05 (percentage)

85.2 1.3 36.1

(2.0) (1.3)

f. Price of full meal 3.41 3.03 5.0

(0.04) (0.07)

g. Hours open (weekday)

14.4 14.7 -0.8

(0.2) (0.3)

h. Recruiting bonus

20.3

23.4

-0.6

(2.3)

(4.9)

Notes: See text for definitions. Standard errors are given in

parentheses.

aTest of equality of means in New Jersey and Pennsylvania.

restaurants

paying

starting

less than $5.05 per hour reported

in New Jersey that had been

a

equivalent employment increased in New

Despite the increase in wages, full-time-

estingly,

wJersey relative to Pennsylvania.

apparent

the minimum-wage

age equal to the new rate. Inter-

"spillover" on higher-wage restau-

increase

had no New Jersey stores were initially smaller,

Whereas

rants

employment

change

in the state:

for these stores

the mean

was -3.1 percent.

percentage wage

with losses in Pennsylvania led to a small

gains in New Jersey coupled

and statistically insignificant interstate VOL. 84 NO. 4

CARD AND KRUEGER: MINIMUM WAGE

AND EMPLOYMENT

February 1992

35-

30-

25

-

0

0

15-

0.

10

5-

0

4.25 4.35

.

4.45 4.55

6L.

4.65 4.75 4.85 4.95 5.05

5.15 5.25

5.35 5.45 5.55

Wage Range

November

1

9

P9y2

90 80-

-

70

0

30-

0-

10

4.2 5

4.3 5

4.4 5 4.5 5

4.6 5

4.7 5 4.8 5

4.9

5

5.0 5 5.1 5 5.2 5

5.3 5 5.4 5 5.5 5

Wage Range

New

Jersey

-

Pennsylvania

FIGURE

1. DISTRIBUTION OF STARTING WAGE

RATES

777 778

THE AMERICAN ECONOMIC REVIEW

SEPTEMBER 1994

difference

ables show a relative

in wave 2. Only two other vari-

1 and 2: the fraction

change

between waves

and the price of a meal. Both variables

of full-time

employees

increased

in New Jersey relative

to Pennsyl-

vania.

questionnaire

We can assess

the reliability of our survey

of 11 stores that were inadvertently inter-

by comparing

the responses

viewed

Assuming that measurement

twice

in the first wave

of the survey.10

two interviews are independent of each

errors in the

other and independent

the correlation

estimate of the "reliability ratio"

between responses

of the true variable,

of the variance of the signal to the com-

(the ratio

gives an

bined

estimated reliability

variance of the signal

and noise). The

ranging

employment to 0.98

from 0.70 for full-time equivalent

ratios are fairly high,

for the price of a meal.1"

missing data for any key variables

We have also checked

whether stores with

ferent from restaurants

sponses. We find that stores with missing

with complete re-

are dif-

data on employment,

similar

plete data. There is a significant size differ-

in other respects

wages, or prices are

to stores with com-

ential associated

store closing after wave 1. The six stores

with the likelihood of the

that closed were smaller

(with an average employment

than other stores

full-time-equivalent employees

oin wave

f only 12.4

1).12

III. Employment Effects of the

Minimum-Wage

Increase

A. Differences

in

Differences

changes

Table 3 summarizes

in average

the levels and

employment per

store in

10These

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).

12A

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

Jersey classified by whether the starting

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

wage in wave 1 was exactly

[column

hour

[column

[column

(iv)] between $4.26 and $4.99 per

$4.25 per hour

(v)]

or $5.00

or more per hour

in average

(vi)].

and Pennsylvania

employment between

We also show the differences

between stores in the various

stores [column

New Jersey

(iii)] and

in New Jersey

wage ranges

in average employment

Row 3 of the table presents

[columns (vii)-(viii)].

and 2. These entries are simply

between waves 1

the changes

ences between the averages for the two

the differ-

waves

tive estimate of the change is presented in

(i.e., row

2 minus row 1). An alterna-

row 4: here we have computed

in employment over

that

tthe change

waves. We refer to this group of stores as

reported valid

employment data

he subsample of stores

in both

the balanced

sents the average

subsample. Finally,

row 5 pre-

the balanced subsample, treating wave-2

change

in employment in

employment

stores as zero, rather

at the four temporarily closed

than as missing.

were initially

As noted in Table 2, New Jersey stores

nia counterparts but grew

smaller

than their Pennsylva-

sylvania

relative tmum wage. The relative gain (the "dif-

stores after the rise in the mini-

o Penn-

ference in differences"

employment)

opercent),

tion of the averages

with a t statistic

is 2.76 FTE employees

f the changes in

of 2.03. Inspec-

(or 13

that the relative

sey and

tical when the analysis

Pennsylvania stores

change between New Jer-

in rows 4 and 5 shows

balanced subsample,

iis virtually iden-

smaller when wave-2 employment at the

and it is only slightly

s restricted to the

temporarily closed stores is treated as

panded

Within New Jersey, employment ex-

zero.

$4.25

the high-wage stores (those paying

per hour

at the low-wage

in wave 1) and contracted

stores

(those paying

at

more

in employment at the high-wage stores

per hour).

Indeed,

the average

$5.00 or

change

(- 2.16 FTE employees)

to the change among Pennsylvania

is almost identical

(- 2.28 FTE employees). Since high-wage

stores

stores in New Jersey should have been VOL. 84 NO. 4

CARD

AND KRUEGER:

MINIMUM WAGE

AND EMPLOYMENT

779

largely unaffected by the new

minimum

wage, this comparison provides

a specifica-

tion test of the validity

of the Pennsylvania

els of the form:

(la)

AEi

=a+bXj+cNJi+

e

control group. The test is

Regardless of whether the affected

clearly passed.

are compared

high-wage stores in New Jersey, the

to stores in

Pennsylvania or

stores

mated employment

effect of the minimum

esti-

wage is similar.

ployment

The results in Table 3 suggest

that em-

November

contracted

were unaffected

of 1992 at fast-food stores

between February and

that

wage (stores in Pennsylvania and

by the rise in the minimum

New Jersey

in wave 1). We suspect

paying $5.00 per hour or more

stores in

this contraction was the continued

that the reason for

ing of the economies

states during 1992.13

oworsen-

in New Jersey,

Pennsylvania, and New York

Uf the middle-Atlantic

nemployment rates

with a larger increase in

all trended

upward between 1991

Pennsylvania

New Jersey than

and

1993,

franchised fast-food restaurants are pro-

during 1992. Since sales of

cyclical,

expected to lower fast-food

the rise in

unemployment would

be

the absence

of other factors.14

employment

in

B.

Regression-Adjusted

Models

allowance

The comparisons in Table 3 make

employment growth, such as differences

for other sources of

variation

no

in

across

estimates in Table 4. The entries in

chains.

These are incorporated in the

table are regression

coefficients

from mod-

this

'3An 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.

14To

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 t statistic of 3.0.

or

(lb)

AEj=a'+b'Xj+c'GAP1+ej

where A

from

of characteristics of store i, and

wave 1 to wave 2 at store i,

Ei

is the change in employment

Xi

is a set

dummy

New Jersey.

variable

that equals 1 for stores in

NJi

is a

of the impact

GAPi

is an alternative measure

i based on the initial wage at that store

of the minimum wage at store

GAPi

=

0 for stores

in

Pennsylvania

=

0

for stores in New Jersey

with

Wli

2 $5.05

=

(5.05

-

W1E)/

W1i

for other

stores

in New Jersey.

GAPi

at store i necessary

is the proportional

increase

in

mum rate. Variation

to meet the new

wages

in GAPE reflects

mini-

both

the New Jersey-Pennsylvania

differences

within New Jersey

contrast and

based on re-

ported

starting wages

in wave 1.

Indeed,

the

value of

of the

actual proportional

GAPi

is a strong

waves 1 and 2

wage change

predictor

between

on

(R2

=

0.75),

and conditional

behavior

GAPj

bthere is no difference

in New

in

etween stores

Jersey

wage

and

Pennsylvania.15

The estimate

in column (i) of Table

4

is directly comparable

difference-in-differences

of

to the simple

changes in column (iv),

employment

The

row 4 of Table 3.

discrepancy

between

the

two

estimates

Table 4. In Table

is due to the restricted

4 and the

sample

tin

a-

bles in this section

remaining

our

to the set of stores

we restrict

ment and wage data

with available

in both waves of the

eanalysis

mploy-

15A regression of the proportional

wage change be-

tween waves 1 and 2 on

GAPi

has a coefficient of 1.03. 780 THE

AMERICAN ECONOMIC REVIEW

SEPTEMBER 1994

TABLE 3-AVERAGE

EMPLOYMENT PER STORE

BEFORE AND AFTER THE RISE

IN NEW JERSEY

MINIMUM

WAGE

Variable

Stores

by state

Stores in New Jerseya Differences within

NJb

Difference, Wage

=

Wage

=

Wage 2

Low- Midrange-

PA NJ

-

PA

NJ $4.25

$4.26-$4.99 $5.00

high high

(i) (ii)

(iii) (vi)

(iv) (v) (vii) (viii)

-2.89

(1.44)

-0.14

(1.07)

2.76

(1.36)

2.75

(1.34)

2.51

(1.35)

19.56

(0.77)

20.88

(1.01)

1.32

(0.95)

1.21

(0.82)

0.90

(0.87)

20.08

(0.84)

20.96

(0.76)

0.87

(0.84)

0.71

(0.69)

0.49

(0.69)

22.25

(1.14)

20.21

(1.03)

-2.04

(1.14)

-2.16

(1.01)

- 2.39

(1.02)

- 2.69

(1.37)

0.67

(1.44)

3.36

(1.48)

3.36

(1.30)

3.29

(1.34)

-2.17

(1.41)

0.75

(1.27)

2.91

(1.41)

2.87

(1.22)

2.88

(1.23)

1. FTE employment

before, 23.33

20.44

all available observations

(1.35)

(0.51)

2. FTE employment

after, 21.17

21.03

all available observations

(0.94)

(0.52)

3. Change in mean FTE

employment

4. Change in mean FTE

balanced

employment,

sample

of storesc

5. Change

in mean FTE

employment, setting

FTE at temporarily

closed stores

to

od

-2.16 0.59

(1.25)

(0.54)

-2.28 0.47

(1.25)

(0.48)

- 2.28 0.23

(1.25)

(0.49)

Notes: Standard

errors are shown in parentheses. The sample consists of all stores with available

data on employment. FTE

counts each part-time worker

(full-time-equivalent) employment

as half a full-time worker. at

six

closed stores

Employment

is set to zero. Employment

at four temporarily

closed stores is treated as missing.

aStores in New Jersey were classified by whether starting

wage in wave 1 equals $4.25 per hour (N

=

101), is between

$4.26 and $4.99 per hour (N

=

140), or is $5.00 per hour or higher

(N

=

73).

bDifference in employment

between low-wage

($4.25 per hour) and high-wage

( 2 $5.00 per hour) stores; and difference

in employment

between midrange stores.

($4.26-$4.99 per hour) and high-wage

CSubset of stores with available

employment data in wave 1 and wave 2.

dIn

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

data in wave 1 and wave 2.

employment

TABLE 4-REDUCED-FORM

MODELS FOR CHANGE IN EMPLOYMENT

Model

Independent variable

1. New Jersey dummy

2. Initial wage gapa

3. Controls for chain and

ownershipb

(i)

2.33

(1.19)

no

no

8.79

(ii)

2.30

(1.20)

-

(iii)

(iv)

(v)

yes

no

8.78

0.34

15.65

(6.08)

no

no

8.76

-

14.92

(6.21)

yes

no

8.76

0.44

11.91

(7.39)

yes

yes

8.75

0.40

4. Controls for

regionc

5. Standard error of

regression

6. Probability value for controlsd

Notes: Standard errors are given in parentheses. The sample consists of 357 stores

with available data on employment and starting wages in waves 1 and 2. The

dependent variable

in all models is

change

in FTE

employment.

The mean and

standard deviation of the dependent variable are -0.237

and 8.825, respectively. All

models include an unrestricted constant

(not reported).

aProportional increase in starting wage necessary to raise starting wage to new

minimum rate. For stores in

Pennsylvania

the

wage gap is 0.

bThree dummy variables for chain type and whether or not the store is

company-

owned are included.

CDummy variables for two regions of New Jersey and two regions of eastern

Pennsylvania are included.

dProbability value

of

joint

F test for exclusion of all control variables. VOL. 84 NO. 4

AND EMPLOYMENT

CARD

AND KRUEGER: MINIMUM WAGE

781

survey.

smaller

This restriction

results in a slightly

employment in New Jersey.

estimate of the relative

increase in

set of four control variables:

The model in column

(ii) introduces a

three of the chains

dummies

fcompany-owned

probability values in row 6, these covariates

stores. As shown by

and another

dummy

the

for

or

add little to the model and have no effect

on the size of the estimated New Jersey

dummy.

the GAP variable

The specifications in columns

the minimum

to measure

the effect of

(iii)-(v) use

slightly

sey dummy, although

better fit than the simple New Jer-

wage. This variable gives

a

New Jersey-Pennsylvania

its implications for the

similar. The mean value of

comparison are

New Jersey

in column (iii) implies a 1.72 increase

stores is 0.11. Thus

GAPi

the estimate

among

in

FTE employment

Pennsylvania.

in New Jersey

relative to

New

possible to add

Since GAP

varies

Jersey,

it is

employment

cient of the New Jersey dummy

model. The estimated coeffi-

both

within

GAPi

and

NJi

to the

vides a test of the Pennsylvania

then pro-

group.

coefficient

When

we estimate these models,

control

the

significant (with

of the New Jersey

dummy

is in-

ing that inferences about the

t ratios of 0.3-0.7), imply-

minimum wage are similar whether

effect of the

the

comparison is made

stores

across states or across

initial

with

higher

and lower

win New

Jersey

umn (v), where we have added dummies

An even stronger

ages.

test is provided

in col-

representing

(North,

three regions of New Jersey

of eastern Pennsylvania (Allentown-Easton

Central,

and

South)

and two regions

and the northern

These dummies control for any region-

suburbs of Philadelphia).

specific

tfect of the minimum

demand

shocks

and identify

he ef-

employment

Jersey.

stores

changes at higher- and

wage by comparing

no evidence

The

probability

within the same region

lower-

wage

value

in row

6o shows

f New

The addition of the re-

iployment growth.

of regional

components

n em-

gion dummies attenuates

cient and raises

the GAP coeffi-

it no

its standard error, however,

making

longer possible

to reject the

null hypothesis

of the minimum wage. One explanation

of a zero employment effect

this attenuation

ment error in the starting

is the presence

employment growth

wage. Even if

of measure-

for

nent, the addition of region dummies

has no regional

compo-

lead to some attenuation

wGAP coefficient

tion in GAP is explained

if some of the true varia-

of the estimated

ill

calculations based

ity of the GAP variable

on the estimated

by region.

double interviews)

(from

trIndeed,

eliabil-

the estimated

suggest that the fall

he set of 11

(iv) to column (v) is just equal to

GAP coefficient

from

column

in

ttributable to measurement

the ex-

pected change

aerror.'6

Table 4 using as a dependent

We have also estimated the models

in

proportional change

store.'7 The estimated coefficients

in employment at each

variable the

New Jersey dummy

of the

are uniformly

insignificantly different from 0

positive in these models

and the GAP variable

tional levels. The implied employment

at conven-

but

fects of the minimum wage

ef-

when the dependent

proportional terms.

coefficient

For example,

variable

are also smaller

is expressed

the GAP

in

that the increase

in column

(iii) of Table

4 implies

employment at New Jersey

in minimum wages raised

stores

that were

initially paying $4.25 per hour by

14 per-

cent. The estimated

from acorresponding

an effect

proportional

GAP coefficient

model implies

attributable to heterogeneity in the effect of

of only

7 percent.

The difference is

the minimum

wage at larger

and smaller

stores. Weighted versions of

tional-change

ment as a weight)

models (using initial employ-

the propor-

give

rise to wage elastici-

16In

texpected attenuation

a regression model

measurement error

of the GAP coefficient

without

other controls

he

which

of GAP

due to

factor

wwhen

e estimate at 0.70. The expected

is the reliability ratio

(yo),

region

dummies are added

to the model

attenuation

is

statistic of a regression of GAP

lYi =

(yo

-

R2)/(1-

R2),

where

R2

to 0.30). Thus, we expect the

ois the R-square

effects

(equal

cient to fall by a factor of

estimated

n region

GAP coeffi-

dummies are added

to a regression model.

y1

/yo

=

0.8 when region

17These

Card

and Krueger (1993).

specifications

are reported in table 4 of 782 THE

AMERICAN ECONOMIC REVIEW SEPTEMBER 1994

ties similar to the elasticities

implied by the

little effect on the models for the level of

estimates

in Table 4 (see below).

C.

Specification

Tests

contradict the standard prediction that a

The results in Tables 3 and 4 seem to

rise in the minimum

ployment.

wage will reduce em-

specifications

Table 5 presents

some alternative

this conclusion. For completeness, we re-

that probe the robustness

of

port estimates

employment

of models for the change in

mates

in employment [columns (iii) and

of models

[columns

for the proportional change

(i) and (ii)] and esti-

first row of the table reproduces

(iv)].'8 The

specification" from columns

tTable 4. (Note that these models include

(ii) and (iv) of

he "base

chain dummies

owned stores). Row 2 presents an alterna-

and a dummy for company-

tive set of estimates when we set wave-2

employment at the temporarily closed

to 0 (expanding our sample

stores

change

coefficient

has a small

size by 4). This

all four stores are in New Jersey)

of the New Jersey

attenuating effect

dummy

o(n the

since

effect on the GAP coefficient

of GAP is uncorrelated with the probability

(since

bthe size

ut less

of a temporary closure

within

ing alternative

Rows 3-5 present estimation

New Jersey).

results us-

alent employment.

measures

redefined to exclude management

In row 3, employment is

of full-time-equiv-

ees. This change has no effect relative to

employ-

the base specification.

include managers

reweight

in FTE

In rows 4 and

employment

5, we

cent or 60 percent of full-time

part-time workers as either

but

stead of 50 percent).'9

These changes

workers

40 per-

h(ave

in-

18The

fined as the change in employment

proportional

change in employment is de-

average

results

level of employment in waves 1 and 2. This

divided by the

errors

ployment.

tin very

han the alternative of dividing

similar coefficients but smaller

bstandard

change

in employment to -1.

For closed stores we set the proportional

y wave-1

em-

1Analysis

reveals

of the 1991 Current

Ptry

workers. Katz

work

that part-time workers in the restaurant indus-

opulation

Survey

about 46 percent as many

of part-time workers' hours

and Krueger (1992)

report

hours

tas full-time

in the fast-food

industry is 0.57.

to full-time workers' hours

hat the ratio

employment but yield slightly

estimates in the proportional-employment-

smaller point

change models.

from

In row 6 we present estimates obtained

towns along the New Jersey

a subsample that excludes

35 stores iclusion of these stores, which may have a

shore. The ex-

n

different

in our sample,

seasonal

mum-wage effects.

leads to slightly

pattern

than other stores

larger

in row 7 when we add a set of dummy

A similar finding emerges

mini-

variables that indicate the week of the

wave-2

to obtain responses

As noted earlier,

interview.20

win the first

from

e made an extra

New Jersey setores

ffort

of stores called three or more times to ob-

wave of our survey.

The fraction

tain an interview

than in Pennsylvania. To check

was higher in New Jersey

ity of our results to this sampling

the sensitiv-

we reestimated

feature,

that excludes any stores that were called

our models on a subsample

back

are very

more than

similar

ttwice.

The results,

in row

8,

sults for the proportional-employment-

Row 9 presents weighted estimation

o the base specification.

re-

change models, using as weights the initial

levels of employment

the proportional change

in each store. Since

ment is an employment-weighted

in

average employ-

the proportional

weighted

changes at each store, a

average

of

model should give rise to elasticities that

version of the proportional-change

are similar

from

to the implied elasticities

expectation, the weighted estimates are

the levels models. Consistent with this

arising

larger than the unweighted

significantly different

levels. The weighted estimate of the New

from 0 at conventional

estimates, and

Jersey dummy

relative

(0.13) implies a 13-percent

-the

in New Jersey

implied by the simple difference-in-dif-

same proportional employment effect

increase

employment

ferences

in Table 3.

estimate of the GAP coefficient in the

Similarly,

the

weighted

proportional-change

model (0.81) is close to

for the wave-1

20We also added dummies for the interview

did not change

sturvey, but these were insignificant

dates

he estimated

minimum-wage effects.

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

TABLE 5-SPECIFICATION TESTS OF REDUCED-FORM EMPLOYMENT MODELS

783

Specification

1. Base specification

2. Treat four temporarily closed stores

as permanently closeda

3. Exclude managers in employment

countb

4.

Weight part-time as

0.4

x

full-timec

5. Weight part-time as 0.6

x

full-timed

6. Exclude stores in NJ shore areae

7. Add controls for wave-2 interview

datef

8. Exclude stores called more than twice

in wave 19

9. Weight by initial employmenth

10. Stores in towns around Newark'

11. Stores in towns around Camdeni

12. Pennsylvania stores onlyk

Change

in

employment

NJ dummy Gap measure

(i) (ii)

2.30

(1.19)

2.20

(1.21)

2.34

(1.17)

2.34

(1.20)

2.27

(1.21)

2.58

(1.19)

2.27

(1.20)

2.41

(1.28)

14.92

(6.21)

14.42

(6.31)

14.69

(6.05)

15.23

(6.23)

14.60

(6.26)

16.88

(6.36)

15.79

(6.24)

14.08

(7.11)

Proportional change

in

employment

NJ dummy Gap measure

(iv)

(iii)

0.05

(0.05)

0.04

(0.05)

0.05

(0.07)

0.06

(0.06)

0.04

(0.06)

0.06

(0.05)

0.05

(0.05)

0.05

(0.05)

0.13

(0.05)

0.34

(0.26)

0.34

(0.27)

0.28

(0.34)

0.30

(0.33)

0.17

(0.29)

0.42

(0.27)

0.40

(0.26)

0.31

(0.29)

0.81

(0.26)

0.90

(0.74)

0.21

(0.70)

-0.33

(0.74)

33.75

(16.75)

10.91

(14.09)

-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).

bFull-time equivalent 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.

dFull-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.

fModels 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.

hRegression model is estimated by weighted least squares, using employment in wave

1 as a

weight.

'Subsample

of 51 stores in towns around Newark.

J

Subsample of

54 stores in town around Camden.

k

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

respect

fication

to wages from the basic levels speci-

with

ings suggest that the proportional

in row 1, column

(u).21

These find-

the rise in the minimum wage was concen-

effect of

trated among

lrise in the minimum

One explanation

arger sfor our finding that a

tores.

employment effect is that unobserved

wage has a positive

mand

de-

the negative

shocks

mum

ewmployment effect of the

ithin New Jersey outweighed

10 and 11 present estimation

wage. To address this possibility, rows

mini-

on subsamples of stores in two narrowly

results

based

defined areas: towns around Newark (row

10) and towns around

each case the sample area is identified

Camden

(row 11). In

the first

Within both areas the change in employ-

three digits of the store's zip code.22

by

ment is positively

variable, although in neither case is the

correlated with the GAP

effect statistically

that

constant within local areas, these results

fast-food product

significant. To the extent

market conditions are

suggest that our findings

unobserved demand

price changes (reported below) also sup-

shocks.

are not driven

Our analysis

boy

f

ports

row 12 of Table 5. In this row we exclude

A final

this conclusion.

specification check is presented

in

stores in New Jersey and (incorrectly) de-

fine the GAP variable for Pennsylvania

stores as the proportional increase

necessary to raise the wage to $5.05 per

in wages

hour. In principle

for stores in Pennsylvania should have no

the size of the wage gap

systematic relation

In practice, this is the case. There is no

with

employment growth.

indication that the wage gap is spuriously

related

to employment growth.

Jersey,

2'Assuming average employment

implies

tahe 14.92

n employment elasticity of 0.73.

GAP coefficient in row 1, column

of 20.4 in New

(ii)

2The

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

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

(around

stores

Camden)

have by far the largest numbers of

and

among three-digit zip-code

areas in New Jersey,

stores

together

in our sample.

they

account for 36 percent

of New

Jersey

first-differenced

We have also investigated

employment models is appropriate. A

specification used in our

whether the

first-differenced

of employment in period t is related

model implies that the level

lagged level of employment

cient of 1. If short-run employment fluctua-

with a coeffi-

to the

tions are smoothed, however,

efficient

tthan 1. Imposing

of lagged employment

he true co-

may

coefficient

of a unit

be less

the first-differenced specification we reesti-

may then lead to biases. To test

the assumption

mated models for the change in employ-

ment including

additional explanatory

wave-1 employment

come any mechanical

base-period

cvorrelation

ariable. To over-

as an

between

employment

employment

and the change in

error)

with the number of cash registers in the

we instrumented wave-1

(attributable

to measurement

employment

store in wave 1 and the number

in the store that

of registers

A.M.

all of the specifications

were open at 11:00

wave-1 employment

the coefficient of

In

example, in a specification including the

is close to zero. For

GAP variable and ownership and chain

dummies,

ment is 0.04, with a standard

the coefficient

of wave-1

We conclude

error

employ-

ification is appropriate.

that the first-differenced

of 0.24.

spec-

D. Full-Time and Part-Time Substitution

full-time-equivalent employment

Our analysis

so far has concentrated

on

nored possible changes in the distribution

and ig-

of full- and part-time

in the minimum

An increase

crease in full-time employment

wage could lead to an in-

workers.

part-time

sons. First, in a conventional model one

employment

for at least two rea-

relative to

would expect a minimum-wage increase to

induce

ers and capital

employers to substitute

skilled work-

Full-time workers in fast-food restaurants

for

minimum-wage

workers.

are typically older and may well possess

higher

conventional model predicts

skills than

part-time workers. Thus,

respond to an increase

in the minimum

that stores

may

a

wage by increasing

time workers. Nevertheless, 81 percent of

the proportion

of full-

restaurants paid full-time and part-time VOL. 84 NO. 4

CARD AND KRUEGER:

MINIMUM WAGE

AND EMPLOYMENT 785

TABLE 6-EFFECTS

OF MINIMUM-WAGE

INCREASE ON OTHER OUTCOMES

Regression of change in

Mean change in outcome

outcome variable on:

NJ

PA NJ - PA NJ dummy

Wage gapa Wage gapb

Outcome measure (i)

(ii)

(iii)

(iv)

(v)

(vi)

Store Characteristics:

1. Fraction full-time workersc (percentage) 2.64

-4.65 7.29

7.30 33.64

20.28

(1.71)

(3.80) (4.17)

(3.96) (20.95)

(24.34)

2. Number of hours open per weekday

-0.00

0.11

-0.11 -0.11 -0.24

0.04

(0.06)

(0.08) (0.10)

(0.12) (0.65)

(0.76)

3. Number of cash registers

- 0.04

0.13

-0.17 -0.18 -0.31

0.29

(0.04)

(0.10) (0.11)

(0.10) (0.53)

(0.62)

4. Number of cash registers open

-0.03

-0.20

0.17

0.17

0.15 -0.47

at 11:00

A.M.

(0.05) (0.08) (0.10)

(0.12) (0.62)

(0.74)

Employee Meal Programs:

5. Low-price meal program (percentage)

-

4.67

- 1.28 - 3.39 - 2.01

-30.31

- 33.15

(2.65)

(3.86) (4.68)

(5.63) (29.80)

(35.04)

6. Free meal program (percentage) 8.41 6.41

2.00

0.49 29.90 36.91

(2.17)

(3.33) (3.97)

(4.50) (23.75)

(27.90)

7. Combination of low-price and free -4.04 -5.13 1.09

1.20 -11.87 -19.19

meals (percentage)

(1.98)

(3.11) (3.69)

(4.32) (22.87)

(26.81)

Wage

Profile:

8. Time to first raise (weeks)

3.77 1.26 2.51

2.21

4.02

-5.10

(0.89)

(1.97) (2.16)

(2.03) (10.81)

(12.74)

9. Usual amount of first raise (cents)

-0.01

-0.02 0.01 0.01

0.03

0.03

(0.01)

(0.02) (0.02)

(0.02) (0.11)

(0.11)

10. Slope of wage profile (percent

-0.10

-0.11 0.01 0.01 -0.09 -0.08

per week)

(0.04) (0.09) (0.10)

(0.10) (0.56)

(0.57)

Notes: Entries in columns (i) and

(ii)

represent mean changes in the outcome variable indicated by

the row heading

for stores with available data on the outcome in waves 1 and 2. Entries in columns (iv)-(vi) represent estimated

regression coefficients of indicated

variable (NJ dummy or initial wage gap) in models for the change in the

outcome variable. Regression models include chain dummies and an indicator for company-owned stores.

aThe wage gap is the proportional increase in starting wage necessary to raise

the wage to the new minimum

rate. For stores in Pennsylvania, the wage gap is zero.

bModels in column (vi) include dummies for two regions of New Jersey and two regions

of eastern Pennsylvania.

CFraction

of part-time employees in total full-time-equivalent employment.

workers

wave 1 of our survey.23

exactly the same starting

wage in

workers are more productive

that full-time

paid), there may be a second reason for

(but equally

as part-time workers or that equity

workers

hThis suggests

ave the same skills

either

stores to substitute full-time workers for

lead restaurants to pay equal

concerns

part-time workers; namely,

equally productive workers. If full-time

wages for un-

increase

a minimum-wage

full-time workers, and stores would natu-

enables the industry to attract

more

rally want to hire a greater proportion

full-time

tive.

workers

if they are more produc-

of

231n

the other 19 percent of stores, full-time workers

are paid more, typically 10 percent more.

changes

Row 1 of Table 6 presents the mean

in the proportion of full-time work- 786

THE

AMERICAN ECONOMIC REVIEW

SEPTEMBER 1994

ers in New Jersey and Pennsylvania

coefficient

1 and 2 of our survey, and

be-

tween waves

change in the proportion

estimates

from

regressions of the

ers on the wage-gap

mies, a company-ownership

variable, chain dum-

of full-time

work-

gion dummies

dummy, and re-

are ambiguous. The fraction of full-time

[in column (vi)]. The results

workers

Pennsylvania by 7.3 percent

increased

in New Jersey

relative

= 1.84),

to

but regressions on the wage-gap variable

(t ratio

show no significant

full-time workers.24

shift in the fraction

of

E. Other

Employment-Related

Measures

other outcome variables

Rows 2-4 of Table 6 present results for

be related

that we expect to

ment. In particular,

to the level of restaurant employ-

the rise in the minimum wage is associated

we examine whether

with a change in the number of hours a

restaurant is open on a weekday,

ber of cash registers

tthe number of cash registers typically

in the restaurant,

he num-

and

at 11:00

in

operation in the restaurant

A.M.

Consistent with our employment results,

none of these variables

significant decline

shows a statistically

Pennsylvania. Similarly,

in New Jersey relative

ing the gap variable provide no evidence

regressions

includ-

to

that the minimum-wage increase led to a

systematic

[see

columns

change

in any of these variables

(v) and (vi)].

IV. Nonwage Offsets

in the minimum

One explanation of our finding

ployment

effect of the minimum

is that restaurants

wage does not lower em-

that a rise

can offset the

nonwage compensation.

wage by reducing

workers value fringe benefits and wages

For example, if

equally, employers can simply reduce

level of fringe

the

minimum-wage increase, leaving

benefits

by the amount

their em-

of the

ployees

24Within New Jersey, the fraction

of full-time

eand lower

increased about

wages in wave 1.

as quickly at stores

with higher

m-

ployment

benefits for fast-food employees are free

costs unchanged. The main

fringe

and reduced-price meals.

of our survey

restaurants

about 19 percent

In the first wave

opercent offered reduced-price meals,

offered workers

free meals, 72

f fast-food

percent offered a combination

and reduced-price

of both free

and 9

are an obvious fringe benefit to cut if the

meals. Low-price

meals

minimum-wage increase forces restaurants

to pay higher wages.

mates of the effect of the minimum-wage

Rows 5 and 6 of Table 6 present esti-

increase

reduced-price meals.

on the incidence

taurants offering reduced-price

The proportion of res-

of free meals and

in both New Jersey and Pennsylvania after

meals fell

the minimum wage increased,

what greater decline in New Jersey. Con-

with a some-

trary

tion in reduced-price

to an offset story, however, the reduc-

accompanied by an

meal programs

was

of stores offering free meals. Relative to

increase

in the fraction

stores in Pennsylvania, New Jersey

ers actually

employ-

fringe benefits (i.e., free meals rather

shifted toward more generous

reduced-price meals).

shift is not statistically significant.

However, the relative

than

We continue to find a statistically

isignificant

crease

effect of the minimum-wage

in-

n-

reduced-price meals

on the likelihood

where

in columns

of receiving free or

(v) and (vi),

GAP variable from regression models

we report coefficient

estimates

of the

the change in the incidence of these pro-

for

grams.

temployers offset

The results

pthe minimum-wage

rovide

no evidence

hat

in-

crease by reducing free or reduced-price

meals.

is that employers

re-

sponded to

Another possibility

wage by reducing on-the-job training

the increase in the minimum

and

flattening

Jacob Mincer and Linda Leighton, 1981).

the

tenure-wage profile (see

Indeed,

in

wave 1 that her workers were forgoing

one manager told our interviewer

ordi-

nary

wage was about

scheduled

raises

provide

to

because the minimum

termine

arise,

and this would

more generally, we analyzed store man-

w raise for all her workers.

hether this phenomenon

occurred

To de-

agers' responses

to

questions

on the amount VOL. 84 NO. 4

AND EMPLOYMENT

CARD AND KRUEGER: MINIMUM WAGE

787

of time before a normal

the usual amount

of such raises. In rows

wage increase and

8

and 9 we report the average

tween

as well as regression

waves

1 and 2 for these two

changes be-

els that include

coefficients

from

variables,

mod-

though the average time to the

the wage-gap

variable.25

Al-

raise increased

relative

statistically

to Pennsylvania, the increase

by 2.5 weeks in New Jersey

first pay

is not

is only a trivial difference

significant.

Furthermore,

there

change

ment between

in the amount of the first

in the relative

pay incre-

stores.

New Jersey

and Pennsylvania

Finally,

we examined a related

variable:

the "slope" of the wage profile,

measure

to the amount

by the ratio

which we

given.

oof the typical

first raise

wage profile flattened in both

As shown

f time until the first

in row 10, the slope of the

raise is

New Jersey

and Pennsylvania, with no significant

tive difference

rin the slope is also uncorrelated

between states. The change

ela-

GAP variable.

indication that New Jersey

In summary, we can find no

with the

changed

wage profiles

either their fringe

mum

wage.26

to offset the rise

benefits

employers

in the mini-

or their

V. Price

Effects of the Minimum-Wage

Increase

the minimum wage

A final issue we examine

fast-food restaurants.

on the prices

is the effect of

of meals

mat

of the fast-food industry implies

A competitive

that an

odel

increase

an increase

in the minimum

wage

will lead to

constant

increase

returns

in product

to scale in the industry, the

prices.

If we assume

the share of minimum-wage

in price should be proportional to

labor in total

25In

wave 1, 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.

26Katz and 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

Jersey initially

restaurant

in New

less than the new minimum

paid about half its workers

rose by roughly

ers, and if labor's

15 percent for these work-

wage. If wages

percent, we would expect

share of total costs is 30

prices to rise by

the minimum-wage rise.27

about 2.2 percent

(= 0.15 x 0.5 x 0.3) due to

managers

In each wave of our survey

we asked

items: a medium soda,

for the prices of three standard

french fries, and a main course.

a small order of

The main

course was a basic hamburger

at Burger

King,

and two pieces of chicken at KFC

Roy Rogers,

and Wendy's restaurants,

We define "full

price of a medium soda,

meal" price as the after-tax

stores.

french

fries, and a main course.

a small order of

of the effect of the minimum-wage

Table 7 presents reduced-form

estimates

on prices. The dependent

models

in the

vincrease

in these

price of a full

is the change

logarithm

ariable

of the

independent

dicating whether

variable

meal at each store. The key

Jersey or the proportional

the store

is either a dummy

is located

in New

in-

required

GAP variable

to meet the minimum

wage increase

wage (the

umn (i) shows that after-tax

The estimated

defined

New Jersey

above).

dummy

in col-

rose 3.2-percent

in Pennsylvania between February

faster in New Jersey

meal prices

than

and

November

larger controlling

1992.28 The effect is slightly

ownership [see

New Jersey

sales tax rate fell by

column (ii)]. Since

for chain and company-

1

the

age point between

these estimates suggest

the waves of our survey,

percent-

that

rose 4-percent faster as

a result of the

pretax prices

27According

to the McDonald's

operating costs at company-owned

and

aCre 31.3

orporation

percent

1991

Annual Report,

payroll

benefits

This

cof

tion is only

ers make

approximate

because

mstores.

inimum-wage

alcula-

ework-

they

are about half of

up less than

half of payroll

ven though

minimum wage causes

workers,

and because a rise in the

the

pay

relative

of other

some employers to increase

pay differentials.

higher-wage workers in order

to maintain

in prices

28The effect

is attributable to a 2.0-percent

increase

prices

in Pennsylvania.

in New Jersey

and a 1.0-percent decrease

in 788

THE

AMERICAN ECONOMIC REVIEW

TABLE 7-REDUCED-FORM

SEPTEMBER 1994

MODELS FOR CHANGE IN THE PRICE OF A FULL MEAL

Dependent variable: change in the log price

of a full meal

Independent variable

1. New Jersey dummy

2. Initial wage

gapa

3. Controls for chain andb

ownership

4. Controls for regionc

5. Standard error of regression

no

no

0.101

(i)

0.033

(0.014)

(ii)

0.037

(0.014)

-

(iii)

(iv)

(v)

0.077

(0.075)

no

no

0.102

0.146

(0.074)

yes

no

0.098

0.063

(0.089)

yes

yes

0.097

yes

no

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 (entree, medium

soda, small fries). The sample contains 315 stores with valid data on prices, wages, and

employment for waves 1 and 2. The mean and standard deviation of the dependent

variable are 0.0173 and 0.1017, respectively.

aProportional increase in starting wage necessary to raise the wage to

the new

minimum-wage rate. For stores in Pennsylvania the wage gap is 0.

bThree dummy variables for chain type and whether or not the store is company-

owned are included.

CDummy variables for two regions of New Jersey and two regions of eastern

Pennsylvania are included.

minimum-wage increase in New Jersey-

slightly more than the increase needed to

pass through the cost increase caused by the

minimum-wage hike.

The pattern of price changes within New

Jersey is less consistent with a simple

"pass-through" view of minimum-wage cost

increases. In fact, meal prices rose at

approximately the same rate at stores in

New Jersey with differing

levels of initial

wages. Inspection of the estimated GAP

coefficients

in column (v) of Table 7 con-

firms that within regions of New Jersey, the

GAP variable

is statistically insignificant.

In sum, these results provide

mixed evi-

dence that higher minimum wages result in

higher fast-food prices. The strongest evi-

of New

dence emerges from a comparison

Jersey

and Pennsylvania stores. The magni-

is consistent with

tude of the price increase

from a conventional model of a

predictions

we

competitive industry. On the other hand,

find no evidence that prices rose faster

among stores in New Jersey that were most

affected by the rise in the minimum wage.

for the latter

One potential explanation

compete

finding is that stores

in New Jersey

in the same product market.

As a result,

restaurants that are most affected by the

minimum wage are unable

to increase

their

faster than their

competitors.

product prices

and Penn-

In contrast, stores in New Jersey

sylvania

are in separate product markets,

enabling prices to rise

in New Jersey rela-

tive to Pennsylvania when overall

costs rise

in New Jersey. Note that this explanation

that store-

seems to rule out the possibility

for the

demand shocks can account

specific

at stores in

anomalous rise in employment

with lower initial wages.

New Jersey

VI. Store Openings

An important

potential effect of higher

the open-

minimum

wages is to discourage

our sample

Although

ing of new businesses.

the effect

of the

us to estimate

design allows

in

minimum

wage on

existing

restaurants

the effect

of

we cannot address

New Jersey,

the higher minimum wage on potential VOL. 84 NO. 4

CARD AND KRUEGER: MINIMUM WAGE AND EMPLOYMENT

789

entrants.29 To assess the likely size of such

an effect,

tories for the McDonald's

we used national

rto compare the numbers of operating

restaurant direc-

estaurant chain

restaurants and the numbers of newly

opened restaurants

the 1986-1991 period. Many states raised

in different

states over

their minimum wages during

addition, the federal minimum wage in-

this period. In

creased in the early 1990's from $3.35 to

$4.25,

depending on the level of wages in the

with differing effects

in different states

state. These policies create an opportunity

to measure the impact of minimum-wage

laws on store opening rin Table 8. We regressed

The results of our analysis

ates across

are presented

states.

the number of McDonald's

the growth

rate in

state on two alternative

minimum

measures of the

stores in each

other control variables

wage in the state and a set of

and the change in the state unemployment

(population growth

rate). The first minimum-wage measure is

the fraction

trade industry in 1986

of workers

in the state's retail

tween the existing

whose wages fell be-

1986

imum

($3.35 per hour)

federal

and the effective

minimum wage in

min-

maximum of the federal

wage in the state in April 1990 (the

the state

minimum wage and

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

minimum wages

as of April

1990).30

tive minimum

hourly

wage

in 1990 to the

average

state in 1986. Both of these measures are

wage of retail trade workers in the

designed to gauge the degree of upward

wage pressure exerted by state or federal

minimum-wage changes between 1986 and

1990.

higher

The results provide no evidence that

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

minimum-wage rates (relative

to the

vealed that Wendy's opened two stores

29Direct inquiries to the chains in our sample re-

in 1992 and one store in Pennsylvania. The other

in New Jersey

chains were unwilling to provide

information on new

openings.

(merged

30We used the 1986 Current Population Survey

variables. State minimum-wage

monthly file) to construct the minimum-wage

tained from the Bureau of National Affairs Labor

rates in 1990 were ob-

Relations Reporter Wages and Hours Manual (undated).

tive effect on either the net number of

restaurants or the rate of new openings.

the contrary, all the estimates

To

effects of higher minimum

number of operating or newly

wshow

positive

although many of the point estimates are

opened

ages on the

stores,

insignificantly

evidence is limited, we conclude that the

different from zero. While this

effects

opening

of minimum wages

rates are probably small.

on fast-food store

VII. Broader Evidence on Employment

Changes

in New

Jersey

that the rise in the minimum

Our establishment-level analysis suggests

Jersey may have increased employment

wage in New

the fast-food

iassociated

phenomenon

with our particular sample, or a

industry. Is this just

an anomaly

n

try? Data from the monthly

unique to the fast-food

lation Survey (CPS) allow us to compare

Current

iPndus-

opu-

state-wide

sey and the surrounding states, providing

employment trends in New Jer-

check on the interpretation of our findings.

a

Using monthly

we computed

CPS

files for 1991

and

1992,

for teenagers

efor New Jersey, Pennsylvania,

amployment-population rates

nd adults

(age 25 and older)

and the entire

Jersey

United States. Since the New

New York,

we computed the employment rates for

minimum wage rose on April 1, 1992,

April-December of both 1991

The relative

and 1992.

Jersey

changes

in employment in New

an indication

and the

ployment rates show that the New Jersey

A

comparison

of the effect of the new law.

surrounding states then give

of

changes

in adult em-

labor market

fared slightly

market as a whole or labor markets in

1991-1992 period

than either

wtorse over the

he U.S. labor

Pennsylvania or New York (see Card

Krueger,

however, the situation

1993 table

and

9).31

Among teenagers,

Jersey,

was reversed.

In New

percent

teenage employment rates

from 1991 to 1992. In New

fell by 0.7

York,

older fell by 2.6 percent

31The employment rate of individuals age 25 and

and 1992,

in New Jersey

and fell by 0.2 percent

while it rose by 0.3 percent

in the United Sitates

n Pennsylvania,

between 1991

as a whole. 790

TABLE 8-ESTIMATED

THE AMERICAN ECONOMIC REVIEW

EFFECT OF MINIMUM WAGES ON NUMBERS

OF MCDONALD'S

SEPTEMBER 1994

RESTAURANTS,

1986-1991

Independent variable

Variable:

Minimum-Wage

1. Fraction of retail workers

Dependent variable: proportional

increase in number of stores

(ii) (iv)

(i)

(iii)

Dependent variable:

+

(number of newly

opened stores)

(number in 1986)

(v) (vi)

(vii) (viii)

in affected wage 1986a

range

2. (State minimum wage in 1991)

Other Control Variables:

3. Proportional growth in

(0.20)

-

0.33

(0.19)

(0.22)

0.38

0.13

-

(0.22)

(0.22)

0.47

0.37

-

(0.21)

(0.23)

0.47

-

0.16

in

1986)b

(average retail wage

(0.24)

0.56

-

-

4.

Change

in

unemployment

population, 1986-1991

rates,

1986-1991

of regression

5. Standard error

- -1.78

(0.23)

(0.62)

0.071

0.88

- 1.40

(0.23)

(0.61)

0.068

0.088

1.03

-

-

- 1.85

(0.25)

(0.68)

0.077

0.86

- 1.40

(0.25)

(0.65)

0.073

1.04

0.083 0.083

0.088

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

(i)-(iv) is the

proportional increase

columns

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

between

1986

opened

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).

bMaximum of state and federal minimum wage as of April 1, 1990, divided

hourly wage of

by the average

workers in retail trade

in the state in 1986.

and the United States as a

Pennsylvania,

rates dropped

whole, teenage employment

faster. Relative to teenagers

in Pennsylva-

nia, for example, the teenage

employment

rate in New Jersey rose by 2.0 percentage

points. While this point estimate

is consis-

for the fast-food in-

tent with our findings

error is too large (3.2

dustry, the standard

assessment.

percent)

to allow any confident

of the standard

the predictions

summarize

model and

some simple

alternatives, and

we

posed by our find-

the difficulties

highlight

ings.

Model

A. Standard Competitive

A standard competitive model

predicts

employment will

fall

that establishment-level

raised. For an

if the wage is exogenously

entire industry, total employment

is pre-

VIII. Interpretation

price

is predicted

dicted

to fall, and

product

in a bind-

to an increase

As in the earlier study by Katz

and

to rise in response

Krueger (1992),

our empirical findings on

ing minimum wage. Estimates

from the

on minimum-wage ef-

literature

minimum wage

time-series

of the New Jersey

the effects

are inconsistent

with the predictions

of a

fects can be used to get

a rough

idea of the

model of the fast-

elasticity of low-wage employment

to the

competitive

conventional

et al.

results are

minimum wage.

The surveys by Brown

Our employment

food industry.

in-

models,

(1982, 1983)

conclude that a 10-percent

consistent with several alternative

minimum

although none of these models

can also

crease in the coverage-adjusted

rise in fast-food

prices

wage will reduce teenage

employment rates

the apparent

explain

in New Jersey. In this section we briefly

by 1-3 percent. Since this

effect is for all VOL. 84 NO. 4 CARD AND KRUEGER: MINIMUM WAGE

AND EMPLOYMENT

791

teenagers, and not just those employed in

low-wage industries, it is surely a lower

bound on the magnitude

fast-food workers.

in the New Jersey

The 18-percent

of the effect for

increase

fore predicted to reduce employment at

minimum wage is there-

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.

model is that unobserved

A possible defense of the competitive

affected certain stores in New Jersey-

demand shocks

specifically,

paying wages

those stores that were initially

ever, such localized demand shocks should

less than $5.00

per hour.

How-

also affect product prices. (In fact, in a

competitive

work through a rise in prices.) Although

model, product

demand

shocks

lower-wage

tive employment

stores in New Jersey had rela-

relative price increases. Furthermore,

gains, they did not have

jor suburban areas (around Newark and

analysis

of employment changes in two ma-

our

Camden) reveals that, even within local

areas, employment rose faster at the stores

that had to increase

of the new minimum wage.

wages

the most

because

B. Altemative Models

petitive model is one

An alternative

to the conventional

price-takers in the product

in which firms are

com-

some degree of market

market.

power

market

in the labor

but have

sloping labor-supply schedule, a rise in the

If fast-food

stores face an upward-

minimum

ployment

wage can potentially

increase etry

at affected firms

and in the indus-

m-

equilibrium

This same basic insight

as a whole.32

emerges

from an

post wages and employees search among

search model in which firms

posted offers

Kenneth Burdett

(see Dale T. Mortensen,

and Mortensen

(1989)

1988).

de-

(1993)

32Daniel G. Sullivan (1989)

and

Msity teachers

present

empirical results for nurses

ichael

R Ransom

employers.

that suggest

monopsony-like behavior

and univer-

of

rive the equilibrium wage distribution for a

noncooperative wage-search/wage-posting

model and show that the imposition of a

binding minimum

wages

equilibrium. Furthermore, their model pre-

and

employment relative

wage can increase both

to the initial

dicts that the minimum

employment

wage will increase

paid the lowest

the most at firms

that initially

models provide

Although monopsonistic and job-search

wages.

the observed employment effects

a potential explanation

for

Jersey

of the New

the observed

minimum

industry

Jersey

prices should have fallen in New

price effects. In these models,

wage, they cannot explain

wage stores in New Jersey

relative to Pennsylvania, and at low-

wage stores in New Jersey.

rtion is confirmed: indeed, prices

Nelative

either predic-

to high-

in New Jersey than in Pennsylvania,

rose faster

though

al-

low-wage stores in New Jersey. Another

at about the same rate at high- and

puzzle for equilibrium search

absence

initially

of wage

increases

at firms

models is the

that

The strict link between the employment

paying $5.05

or more per hour.

were

wage may

and price effects of a rise in the minimum

vary

the queue at peak hours,

the quality

be broken

of service

if fast-food

(stores can

of stores).

altered the

Another possibility

<, the length

r the cleanliness

of

is that stores

menu items. Comparisons of price changes

relative

prices of their various

for the three items in our

declines (- 1.5 percent) in the price of

survey

show

slight

french

to Pennsylvania,

fries and soda in New Jersey

crease (8 percent) in entree prices. These

coupled

with a relative

relative

in-

limited

tive price changes within the fast-food in-

data suggest a possible

role for rela-

dustry following the rise in the minimum

wage.

identify stores that were initially "supply-

One way to test a

monopsony model

is to

constrained"

for

in the labor market and test

tive to other stores.

employment gains

at these stores rela-

market power is the use of recruitment

A

potential

indicator

of

bonuses.

As we noted in Table

percent

2, about 25

cash bonuses

of stores in wave 1 were

a new worker. We

to employees

offering

compared

who helped find

employment 792 THE AMERICAN ECONOMIC REVIEW SEPTEMBER 1994

changes at New Jersey

fering recruitment

also interacted the GAP variable with a

bonuses in wave 1, and

stores that were of-

dummy

employment-change

for recruitment

faster

New Jersey stores that were initially

(or slower) employment growth

models.

bonuses in several

We do not find

arecruitment

ut the

sing

the GAP variable had a larger effect for

bonuses, or any evidence that

stores that were using bonuses.

IX. Conclusions

textbook

Contrary to the central

consistent

model of the minimum wage, but

prediction

of the

based on cross-sectional

with a number of recent studies

parisons

or employers,

of affected and unaffected

time-series com-

markets

rise in New Jersey's

we find no evidence that the

employment

minimum wage reduced

state. Regardless of whether we compare

at fast-food restaurants in the

stores in New Jersey that were affected

the $5.05 minimum to stores in eastern

by

Pennsylvania (where

constant at $4.25 per hour) or to stores in

the minimum wage

was

New Jersey

per

that were initially

paying $5.00

fected by the new law), we find that the

hour or more

(and were largely

unaf-

increase in the minimum

employment.

alternative

We present a wide

wage increased

variety

of

bustness of this conclusion. None of the

specifications to probe the ro-

alternatives

effect. We also check our

shows a negative employment

fast-food industry

teenage employment

by comparing changes in

findings

for the

Pennsylvania,

following

Again, these results

the increase

and New York in the year

rates in New

Jersey,

pioint toward

n the minimum

a relative

wage.

increase

ers in New Jersey.

in employment

othat minimum-wage increases negatively

We also find

f low-wage

no evidence

work-

affect the number of McDonald's outlets

opened

meals increased in New Jersey relative to

Finally, we find that prices of fast-food

in a state.

Pennsylvania, suggesting

burden of the minimum-wage rise was

that much of the

passed on to consumers.

sey,

Within New Jer-

increased more in stores that were most

however, we find

no

evidence that

prices

affected by the minimum-wage rise. Taken

as a whole, these findings are difficult

explain

or with models in which employers face

with

the standard competitive model

to

supply

librium

csonstraints (e.g., monopsony or equi-

earch models).

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