bruce domazlicky southeast missouri state university

24
Bruce Domazlicky Southeast Missouri State University

Upload: kane-toops

Post on 15-Jan-2016

221 views

Category:

Documents


0 download

TRANSCRIPT

Page 1: Bruce Domazlicky Southeast Missouri State University

Bruce DomazlickySoutheast Missouri State University

Page 2: 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

Page 3: Bruce Domazlicky Southeast Missouri State University

Important Contributor to Standard of Living in an Urban Area

Supplies Goods & Services that Residents Demand

Important Source of Jobs to Urban Residents

Page 4: Bruce Domazlicky Southeast Missouri State University

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

Page 5: Bruce Domazlicky Southeast Missouri State University

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

Page 6: Bruce Domazlicky Southeast Missouri State University

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?

Page 7: Bruce Domazlicky Southeast Missouri State University

Data Envelopment Analysis is used to measure efficiency levels

Productivity Growth is measured using the Malmquist Productivity Index

Page 8: Bruce Domazlicky Southeast Missouri State University

348 Metropolitan Statistical Areas in U.S. 3 Variables: Output, Labor, Capital Output and Labor from the Bureau of

Economic Analysis:Http://www.bea.gov

Capital computed using variation on method by Garofalo and Yamarik (REStat, 2002)

Page 9: Bruce Domazlicky Southeast Missouri State University
Page 10: Bruce Domazlicky Southeast Missouri State University
Page 11: Bruce Domazlicky Southeast Missouri State University

Variable Mean Std. Deviation Maximum Minimum

Output (millions)

1865.217 4497.217 52536.429 107.286

Labor 42892.146 89281.836 977328 4491

Capital (billions)

1.641 4.223 46.069 0.066

Table 1. Variable Statistics

Page 12: Bruce Domazlicky Southeast Missouri State University

Year Mean Std. Deviation Minimum Maximum

2001 0.7137 0.0961 0.4444 1

2002 0.7366 0.0938 0.4878 1

2003 0.7201 0.0900 0.4415 1

2004 0.7006 0.0919 0.4249 1

2005 0.6995 0.0977 0.4103 1

2006 0.6939 0.0984 0.4185 1

2007 0.6781 0.0938 0.4101 1

All 7 Years 0.7061 0.0909 0.4339 1

Table 2. Efficiency Estimates

Page 13: Bruce Domazlicky Southeast Missouri State University

Region Average Efficiency

New England 0.7272

Mid-Atlantic 0.6869

Great Lakes 0.6892

Plains 0.6448

Southeast 0.7280

Southwest 0.6797

Rocky Mountain 0.6784

Far West 0.7556

Table 4. Average Efficiency by Region

Page 14: Bruce Domazlicky Southeast Missouri State University

Size Average Efficiency Score Number

Less than 100,000 0.6626 23

100,001-200,000 0.6695 133

200,001-500,000 0.7081 102

500,001-1,000,000 0.7353 45

1,000,001-2,000,000 0.7789 21

More than 2,000,000 0.8230 24

Table 6. Average Efficiency Scores by Metropolitan Size

Page 15: Bruce Domazlicky Southeast Missouri State University

Productivity Mean Std. Deviation Minimum Maximum

TFP Growth Rate

1.2530 0.0951 1.0173 1.8110

Efficiency Change

0.9524 0.0732 0.7644 1.3878

Technical Change

1.3159 0.0252 1.2187 1.3633

Table 3. Productivity Estimates, 2001-2007

Page 16: Bruce Domazlicky Southeast Missouri State University

Region TFP Efficiency Change Technical Change

New England 1.2220 0.9208 1.3269

Mid-Atlantic 1.2599 0.9556 1.3188

Great Lakes 1.2024 0.9229 1.3038

Plains 1.2055 0.9195 1.3114

Southeast 1.2730 0.9687 1.3146

Southwest 1.2408 0.9312 1.3332

Rocky Mountain 1.3106 0.9910 1.3227

Far West 1.2774 0.9696 1.3174

Table 5. Average Productivity Growth by Region

Page 17: Bruce Domazlicky Southeast Missouri State University

Size TFP Growth Rate Efficiency Change Technical Change

Less than 100,000 1.3272 1.0165 1.3057

100,001-200,000 1.2593 0.9587 1.3136

200,001-500,000 1.2518 0.9523 1.3150

500,001-1,000,000 1.2387 0.9394 1.3187

1,000,001-2,000,000 1.2276 0.9229 1.3301

More than 2,000,000 1.2010 0.9071 1.3243

Table 7. Average Productivity Growth by Metropolitan Size

Page 18: Bruce Domazlicky Southeast Missouri State University

Regression Results

Page 19: Bruce Domazlicky Southeast Missouri State University

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

Page 20: Bruce Domazlicky Southeast Missouri State University

Variable Coefficient Std. Error t-Statistic

Constant 0.0684 0.0769 0.89

URBAN 0.0429 0.0042 10.23

LOCAL 0.0653 0.0216 3.03

EDUC 0.0022 0.0006 3.58

Adj. R-Squared 0.538 F-Statistic 8.77

Table 8. Efficiency RegressionDependent Variable: AVEEFFNo. of Obs.: 348

Page 21: Bruce Domazlicky Southeast Missouri State University

Regression Results

Page 22: Bruce Domazlicky Southeast Missouri State University

PROD: Productivity growth, 2001-2007 TC: Growth rate of technical change, 2001-

2007 EC: Growth rate of efficiency change, 2001-

2007

Page 23: Bruce Domazlicky Southeast Missouri State University

Variable PROD TC ECConstant 1.4714

(13.86)1.2547(62.76)

1.1681(14.71)

URBAN -0.0164(-2.82)

0.0048(3.60)

-0.0162(-3.63)

LOCAL 0.0173(0.66)

0.0094(1.22)

0.0060(0.30)

EDUC 0.0007(0.92)

0.0001(0.75)

0.0003(0.62)

Adj. R-Squared 0.24 0.17 0.21F-Statistic 3.11 2.37 2.80

Table 9. Productivity RegressionsNo. of Obs.: 348(Numbers in parentheses are t-statistics.)

Page 24: Bruce Domazlicky Southeast Missouri State University

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”?