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Using Firm Optimization to Evaluate and Estimate Returns to Scale

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  • Gorodnichenko, Yuriy

    () (University of California, Berkeley)

Abstract

At the firm level, revenue and costs are well measured but prices and quantities are not. This paper shows that because of these data limitations estimates of returns to scale at the firm level are for the revenue function, not production function. Given this observation, the paper argues that, under weak assumptions, micro-level estimates of returns to scale are often inconsistent with profit maximization or imply implausibly large profits. The puzzle arises because popular estimators ignore heterogeneity and endogeneity in factor/product prices, assume perfect elasticity of factor supply curves or neglect the restrictions imposed by profit maximization (cost minimization) so that estimators are inconsistent or poorly identified. The paper argues that simple structural estimators can address these problems. Specifically, the paper proposes a full-information estimator that models the cost and the revenue functions simultaneously and accounts for unobserved heterogeneity in productivity and factor prices symmetrically. The strength of the proposed estimator is illustrated by Monte Carlo simulations and an empirical application. Finally, the paper discusses a number of implications of estimating revenue functions rather than production functions and demonstrates that the profit share in revenue is a robust non-parametric economic diagnostic for estimates of returns to scale.

Suggested Citation

  • Gorodnichenko, Yuriy, 2008. "Using Firm Optimization to Evaluate and Estimate Returns to Scale," IZA Discussion Papers 3368, Institute for the Study of Labor (IZA).
  • Handle: RePEc:iza:izadps:dp3368
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    1. Benoit Dostie & Pierre Thomas Léger, 2014. "Firm-Sponsored Classroom Training: Is It Worth It for Older Workers?," Canadian Public Policy, University of Toronto Press, vol. 40(4), pages 377-390, December.
    2. Enghin Atalay, 2014. "Materials Prices And Productivity," Journal of the European Economic Association, European Economic Association, vol. 12(3), pages 575-611, June.
    3. Benoit Dostie, 2011. "Wages, Productivity and Aging," De Economist, Springer, vol. 159(2), pages 139-158, June.
    4. Yuriy Gorodnichenko & Monika Schnitzer, 2013. "Financial Constraints And Innovation: Why Poor Countries Don'T Catch Up," Journal of the European Economic Association, European Economic Association, vol. 11(5), pages 1115-1152, October.
    5. Alvaro Garcia Marin & Nico Voigtländer, 2013. "Exporting and Plant-Level Efficiency Gains: It's in the Measure," NBER Working Papers 19033, National Bureau of Economic Research, Inc.
    6. Daniel Berkowitz, 2016. "Recasting the Iron Rice Bowl: The Reform of China's State Owned Enterprises," Working Paper 5858, Department of Economics, University of Pittsburgh.
    7. Eifert, Benn & Gelb, Alan & Ramachandran, Vijaya, 2008. "The Cost of Doing Business in Africa: Evidence from Enterprise Survey Data," World Development, Elsevier, vol. 36(9), pages 1531-1546, September.
    8. Daniel Berkowitz, 2016. "Capital-Labor Substitution, Institutions and Labor Shares," Working Paper 5981, Department of Economics, University of Pittsburgh.
    9. Kazuhiko Yokota & Kyosuke Kurita & Shujiro Urata, 2016. "In Search of the Learning-by-Exporting Effect: Role of Economies of Scale and Technology," China Economic Policy Review (CEPR), World Scientific Publishing Co. Pte. Ltd., vol. 5(01), pages 1-27, June.
    10. Gorodnichenko, Yuriy & Grygorenko, Yegor, 2008. "Are oligarchs productive? Theory and evidence," Journal of Comparative Economics, Elsevier, vol. 36(1), pages 17-42, March.

    More about this item

    Keywords

    production function; identification; returns to scale; covariance structures;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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