Review of Industrial Organization 22: 253–273, 2003.
© 2003 Kluwer Academic Publishers. Printed in the Netherlands.
Firm Responses to Income Inequality and
the Cost of Time
B. PETER PASHIGIAN
, SAM PELTZMAN
and JEANNE-MEY SUN
Graduate School of Business, University of Chicago, 110 E 58th Street, Chicago IL 60637-1511,
A.T. Kearney Co.
Abstract. The full cost of shopping includes the cost of the shopper’s time. When that cost in-
creases, stores have incentives to respond in ways that economize on shopper time. One response is
to substitute in-store labor for shopper time. Pooled cross-sectional tests using data from suburban
and city food stores show that various labor intensity measures are higher where the opportunity cost
of shopper time is higher. We distinguish between income and cost of time effects by showing that
store labor intensity depends on the composition of income between male and female members of
the family, and not only on the level of family income. We obtain similar results for two other ways
that food stores can economize on shopper time – locating closer to the customer and offering more
check out stations within a store. We also use a unique shopping time survey to show that shoppers
from higher income households make fewer visits to food stores, spend less time per visit in the
check out line and are more likely to shop at stores with longer hours.
JEL Classiﬁcations: D1,J2,L8,R2
While considerable attention has been paid to the rise in income inequality in the
U.S. and its causes, less effort has been devoted to the responses of ﬁrms to greater
inequality in the cost of time of consumers. One expression of income inequality
is geographic. Suburban income is often greater than city income. In our sample
of American cities and their associated suburbs, family income was on average 18
percent higher in suburbs than in associated cities in 1970 and 31% higher in 1990.
In other words, the cost of time of suburban residents is often (but not always)
higher. Income differences between the suburbs and cities have widened over time
and so have income differences between suburbs. In our sample, the standard devi-
We would like to thank The Lynde and Harry Bradley, and Sarah Scaife Foundations for sup-
port through grants to the George J. Stigler Center for the Study of the Economy and the State,
The University of Chicago. We are also grateful to the Food Marketing Institute (FMI) for making
available their survey data and to Karen Gardner and Mauricio Puerto in particular for assistance
with interpretation of parts of the survey. The Food Marketing Institute has neither reviewed nor
necessarily agrees with our conclusions. We thank Michael Roberts for research assistance. We
received helpful suggestions from Eric Anderson, Keith Bryant, France Leclerc, Casey Mulligan,
Michael Waldman, and Arnold Zellner.