Bruce Domazlicky Southeast Missouri State University

 The Retail Trade Sector in the U.S.  Agglomeration Economies  Efficiency and Productivity Growth  Model  Model Results  Relationship between Agglomeration Economies & Efficiency  Relationship between Agglomeration Economies & Productivity Growth

 Important Contributor to Standard of Living in an Urban Area  Supplies Goods & Services that Residents Demand  Important Source of Jobs to Urban Residents

 Computerization: Bar Scanning Universal in U.S.  Improved Inventory Tracking  Increased Average Size of Retail Establishments  Increased Concentration in Urban Areas at expense of Rural Areas

 Localization Economies: economies that arise when firms in the same industry locate near each other: pooling of labor force, development of industry suppliers, diffusion of ideas (technological spillovers)  Urbanization Economies: economies that arise from locating in an urban area: access to markets, labor supply, financial and other specialized services, low communication costs

 Does efficiency in the retail trade sector increase with urban size?  Does productivity growth in the retail trade sector increase with urban size?  What is relationship between agglomeration economies and efficiency in the retail trade sector?  What is relationship between agglomeration economies and productivity growth in the retail trade sector?

 Data Envelopment Analysis is used to measure efficiency levels  Productivity Growth is measured using the Malmquist Productivity Index

 348 Metropolitan Statistical Areas in U.S.  3 Variables: Output, Labor, Capital  Output and Labor from the Bureau of Economic Analysis:  Capital computed using variation on method by Garofalo and Yamarik (REStat, 2002)

VariableMeanStd. DeviationMaximumMinimum Output (millions) Labor Capital (billions) Table 1. Variable Statistics

YearMeanStd. DeviationMinimumMaximum All 7 Years Table 2. Efficiency Estimates

RegionAverage Efficiency New England Mid-Atlantic Great Lakes Plains Southeast Southwest Rocky Mountain Far West Table 4. Average Efficiency by Region

SizeAverage Efficiency ScoreNumber Less than 100, , , , , ,001-1,000, ,000,001-2,000, More than 2,000, Table 6. Average Efficiency Scores by Metropolitan Size

ProductivityMeanStd. DeviationMinimumMaximum TFP Growth Rate Efficiency Change Technical Change Table 3. Productivity Estimates,

RegionTFPEfficiency ChangeTechnical Change New England Mid-Atlantic Great Lakes Plains Southeast Southwest Rocky Mountain Far West Table 5. Average Productivity Growth by Region

SizeTFP Growth RateEfficiency ChangeTechnical Change Less than 100, , , , , ,001-1,000, ,000,001-2,000, More than 2,000, Table 7. Average Productivity Growth by Metropolitan Size

Regression Results

 AVEEFF: Average Efficiency  URBAN: Urbanization Economies, log of average population  LOCAL: Localization economies, relative share of retail trade output  EDUC: Percentage of population with at least a Bachelor’s Degree

VariableCoefficientStd. Errort-Statistic Constant URBAN LOCAL EDUC Adj. R-Squared0.538F-Statistic8.77 Table 8. Efficiency Regression Dependent Variable: AVEEFF No. of Obs.: 348

Regression Results

 PROD: Productivity growth,  TC: Growth rate of technical change,  EC: Growth rate of efficiency change,

VariablePRODTCEC Constant (13.86) (62.76) (14.71) URBAN (-2.82) (3.60) (-3.63) LOCAL (0.66) (1.22) (0.30) EDUC (0.92) (0.75) (0.62) Adj. R-Squared F-Statistic Table 9. Productivity Regressions No. of Obs.: 348 (Numbers in parentheses are t-statistics.)

 Efficiency in urban areas increase with city size & relative importance of sector  Productivity change is due solely to technical change  Efficiency change declines as urban size increases-indication of “catching-up”?