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Misallocation in the Presence of Multiple Production Technologies

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  • Jack Rossbach

    (Georgetown University Qatar)

  • Jose Asturias

    (Georgetown University)

Abstract

While firms may employ different production technologies for producing the same or similar goods, the production technology used by each firm is typically not available in the data or otherwise known. Due to this limitation, researchers are often forced to assume all firms within an industry share a single production function. We develop a methodology based on cluster analysis that requires only firm level data on revenues and factor input expenditures, and allows us to identify when multiple production technologies are present in an industry and to identify the production technologies that each firm employs. We apply our methodology to Chilean plant level data and find strong evidence of multiple production technologies in most industries. We then evaluate the quantitative impact of this finding as it relates to the misallocation literature. While most studies of misallocation attribute all variation in factor input expenditure shares across firms within an industry to misallocation, we are able to use our framework to separate variation arising due to misallocation from variation resulting from differences in production technologies across firms. After accounting for the presence of multiple production technologies, we find that the estimated gains in manufacturing TFP and output from eliminating misallocation decrease by approximately 60 percent.

Suggested Citation

  • Jack Rossbach & Jose Asturias, 2017. "Misallocation in the Presence of Multiple Production Technologies," 2017 Meeting Papers 1094, Society for Economic Dynamics.
  • Handle: RePEc:red:sed017:1094
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    References listed on IDEAS

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    1. Levinsohn, James, 1999. "Employment responses to international liberalization in Chile," Journal of International Economics, Elsevier, vol. 47(2), pages 321-344, April.
    2. Nina Pavcnik, 2002. "Trade Liberalization, Exit, and Productivity Improvements: Evidence from Chilean Plants," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 69(1), pages 245-276.
    3. Alwyn Young, 1995. "The Tyranny of Numbers: Confronting the Statistical Realities of the East Asian Growth Experience," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(3), pages 641-680.
    4. James Levinsohn & Amil Petrin, 2003. "Estimating Production Functions Using Inputs to Control for Unobservables," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 70(2), pages 317-341.
    5. Raphael Bergoeing & Andrea Repetto, 2006. "Micro Efficiency and Aggregate Growth in Chile," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 43(127), pages 169-192.
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    Cited by:

    1. Michele Battisti & Filippo Belloc & Massimo Del Gatto, 2020. "Labor Productivity and Firm-Level TFP with Technology-Specific Production Function," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 35, pages 283-300, January.
    2. Elías Albagli & Mario Canales & Antonio Martner & Matías Tapia & Juan M. Wlasiuk, 2019. "Misallocation or Misspecification? The Effect of “Average” Distortions on TFP Gains Estimations," Working Papers Central Bank of Chile 835, Central Bank of Chile.
    3. Michele Battisti & Filippo Belloc & Massimo Del Gatto, 2020. "Labor Productivity and Firm-Level TFP with Technology-Specific Production Function," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 35, pages 283-300, January.

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