The Evolution of Retail Markets in Metropolitan, Micropolitan and Rural Regions October 18, 2005 Ron Jarmin, Shawn Klimek, and Javier Miranda Center for Economic Studies, U.S. Census Bureau

Disclaimer This paper was written by Census Bureau staff. It has undergone a more limited review than official Census Bureau publications. Any views, findings or opinions expressed in this paper are those of the authors and do not necessarily reflect those of the Census Bureau.

Trends in the U.S. Retail Sector Overall sector growth Significant increase in employment Modest changes in the number of firms and, especially, establishments Retail activity shifting from mom-and-pop stores to large retail chains

Significant Employment Growth

Modest Growth of Establishments

Growing Dominance of Chains

Long run trend in composition of retail sales

What are the factors behind these trends? Technology (especially IT) Suburbanization Transportation Costs Changes in consumer preferences Small but growing literature examining retail market structure and evolution Recent models try to explain observed market structure (e.g., coexistence of chains and mom-and-pops) Empirical work limited to publicly available or narrowly focused datasets.

A first look… Data development Analysis of “local” markets Distinguish between different types of retail firms Detailed retail industries

Features of the Longitudinal Business Database Requirements for measuring market structure and firm entry and exit at the county level Longitudinal establishment level data Firm ownership information Industry classification Employment (measure of level of activity) Geography (state and county – or better?)

Types of Counties We use counties to delineate retail markets Core Based Statistical Areas CBSA-Metropolitan Areas based on urbanized areas of 50,000 or more population CBSA-Micropolitan Areas based on urban clusters of at least 10,000 but less than 50,000 population Non-CBSA “Rural” Areas

Characteristics of County Types

Types of Retail Firms Single Units – “Mom-and-Pops” Local Chains Firms that operate in one location only Local Chains Firms that operate two or more retail establishments within one state Regional Chains Firms the operate retail establishments in 2 to 10 states National Chains Firms that operate retail establishments in more than 10 states

County level measures Market Structure (in per capita terms) Number of firms Number of establishments Employment Summarizing Results By type of firm By type of county Long-run changes (1976 to 2000) Retail sector Selected two-digit SIC industries Eating and Drinking Places Food Stores

Measures of Firm Dynamics Entry Rate : ERfct = Efct/Nct-1 Exit Rate : XRfct = Xfct/Nct-1 Continuer Rate : CRfct = Xfct/Nct-1 Turnover : TRfct = ERfct + XRfct Net Entry : NEfct = ERfct – XRfct where f={single, local, regional, national} c=county t=time

Summarizing the results Average rates within county types Metropolitan Micropolitan “Rural” Average rates for various periods All years The 1980’s The 1990’s

Results for Retail Sector Negative net entry for single units except metropolitan in the 1990’s Positive net entry for all types of chains except local chains in the 1990’s On average, turnover rates are higher in larger markets Strong decline in turnover rates between the 80’s and 90’s except national chains

Turnover Differences Across Market Types

Turnover differences over time

Employment Weighted Results Net entry contributes to substantial job losses for single units, and substantial job gains in chains ESH-XSH = -.021 for single units (metro) ESH-XSH = .005 for national chains (metro) Employment weighted share of continuing national chains is growing over time across all market types

Conclusions Provided more basic facts on the evolution of retail markets LBD is the first longitudinal establishment level covering all of retail in the U.S. over a long time period Noted differences between market types and between firm types in both the cross section and dynamics

Future work Refine definitions of chain types to take distance into account Change focus from per capita numbers to entry and exit rates Construct detailed industry measures of entry and exit and use summary regressions Analysis by cohort Revised paper forthcoming in October