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Concentration, Diversity, and Manufacturing Performance


  • Joshua Drucker


Regional economist Benjamin Chinitz was one of the most successful proponents of the idea that regional industrial structure is an important determinant of economic performance. His influential article in the American Economic Review in 1961 prompted substantial research measuring industrial structure at the regional scale and examining its relationships to economic outcomes. A considerable portion of this work operationalized the concept of regional industrial structure as sectoral diversity, the degree to which the composition of an economy is spread across heterogeneous activities. Diversity is a relatively simple construct to measure and interpret, but does not capture the implications of Chinitz’s ideas fully. The structure within regional industries may also influence the performance of business enterprises. In particular, regional intra-industry concentration—the extent to which an industry is dominated by a few relatively large firms in a locality—has not appeared in empirical work studying economic performance apart from individual case studies, principally because accurately measuring concentration within a regional industry requires firm-level information. Multiple establishments of varying sizes in a given locality may be part of the same firm. Therefore, secondary data sources on establishment size distributions (such as County Business Patterns or aggregated information from the Census of Manufactures) can yield only deceptive portrayals of the level of regional industrial concentration. This paper uses the Longitudinal Research Database, a confidential establishment-level dataset compiled by the United States Census Bureau, to compare the influences of industrial diversity and intra-industry concentration upon regional and firm-level economic outcomes. Manufacturing establishments are aggregated into firms and several indicators of regional industrial concentration are calculated at multiple levels of industrial aggregation. These concentration indicators, along with a regional sectoral diversity measure, are related to employment change over time and incorporated into plant productivity estimations, in order to examine and distinguish the relationships between the differing aspects of regional industrial structure and economic performance. A better understanding of the particular links between regional industrial structure and economic performance can be used to improve economic development planning efforts. With continuing economic restructuring and associated workforce dislocation in the United States and worldwide, industrial concentration and over-specialization are separate mechanisms by which regions may “lock in” to particular competencies and limit the capacity to adjust quickly and efficiently to changing markets and technologies. The most appropriate and effective policies for improving economic adaptability should reflect the structural characteristics that limit flexibility. This paper gauges the consequences of distinct facets of regional industrial structure, adding new depth to the study of regional industries by economic development planners and researchers.

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  • Joshua Drucker, 2010. "Concentration, Diversity, and Manufacturing Performance," Working Papers 10-14, Center for Economic Studies, U.S. Census Bureau.
  • Handle: RePEc:cen:wpaper:10-14

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    1. Steven J. Davis & John Haltiwanger & Ron Jarmin & Javier Miranda, 2007. "Volatility and Dispersion in Business Growth Rates: Publicly Traded versus Privately Held Firms," NBER Chapters,in: NBER Macroeconomics Annual 2006, Volume 21, pages 107-180 National Bureau of Economic Research, Inc.
    2. Fishman, Arthur & Rob, Rafael, 2003. "Consumer inertia, firm growth and industry dynamics," Journal of Economic Theory, Elsevier, vol. 109(1), pages 24-38, March.
    3. Eckard, E Woodrow, Jr, 1988. "Advertising, Concentration Changes, and Consumer Welfare," The Review of Economics and Statistics, MIT Press, vol. 70(2), pages 340-343, May.
    4. Andrew B. Bernard & Stephen J. Redding & Peter K. Schott, 2010. "Multiple-Product Firms and Product Switching," American Economic Review, American Economic Association, vol. 100(1), pages 70-97, March.
    5. Ulrich Doraszelski & Sarit Markovich, 2007. "Advertising dynamics and competitive advantage," RAND Journal of Economics, RAND Corporation, vol. 38(3), pages 557-592, September.
    6. Richard Ericson & Ariel Pakes, 1995. "Markov-Perfect Industry Dynamics: A Framework for Empirical Work," Review of Economic Studies, Oxford University Press, vol. 62(1), pages 53-82.
    7. Marcus Asplund & Volker Nocke, 2003. "Firm Turnover in Imperfectly Competitive Markets," PIER Working Paper Archive 03-010, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    8. Beggs, Alan W & Klemperer, Paul, 1992. "Multi-period Competition with Switching Costs," Econometrica, Econometric Society, vol. 60(3), pages 651-666, May.
    9. Costas Arkolakis, 2010. "Market Penetration Costs and the New Consumers Margin in International Trade," Journal of Political Economy, University of Chicago Press, vol. 118(6), pages 1151-1199.
    10. Gerard R. Butters, 1977. "Equilibrium Distributions of Sales and Advertising Prices," Review of Economic Studies, Oxford University Press, vol. 44(3), pages 465-491.
    11. Fan, Jianqing & Yao, Qiwei, 1998. "Efficient estimation of conditional variance functions in stochastic regression," LSE Research Online Documents on Economics 6635, London School of Economics and Political Science, LSE Library.
    12. F. Lotti & E. Santarelli & M. Vivarelli, 1999. "Does Gibrat’s Law Hold in the Case of Young, Small Firms?," Working Papers 361, Dipartimento Scienze Economiche, Universita' di Bologna.
    13. Richard T. Carson & Yixiao Sun, 2007. "The Tobit model with a non-zero threshold," Econometrics Journal, Royal Economic Society, vol. 10(3), pages 488-502, November.
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