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Production Function Estimation With Unobserved Input Price Dispersion

Author

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  • Paul L. E. Grieco
  • Shengyu Li
  • Hongsong Zhang
Abstract
We propose a method to consistently estimate production functions in the presence of input price dispersion when intermediate input quantities are not observed. We find that the traditional approach to dealing with unobserved input quantities—using deflated expenditure as a proxy—substantially biases the production estimates. In contrast, our method controls for heterogeneous input prices by exploiting the first‐order conditions of the firm's profit maximization problem and consistently recovers the production function parameters. Using our preferred method, we provide empirical evidence of significant input price dispersion and even wider productivity dispersion than is estimated using proxy methods.

Suggested Citation

  • Paul L. E. Grieco & Shengyu Li & Hongsong Zhang, 2016. "Production Function Estimation With Unobserved Input Price Dispersion," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57(2), pages 665-690, May.
  • Handle: RePEc:wly:iecrev:v:57:y:2016:i:2:p:665-690
    DOI: 10.1111/iere.12172
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    References listed on IDEAS

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    Cited by:

    1. Geoffrey Barrows & Hélène Ollivier & Ariell Reshef, 2023. "Production Function Estimation with Multi-Destination Firms," CESifo Working Paper Series 10716, CESifo.
    2. Sampi Bravo,James Robert Ezequiel & Jooste,Charl & Vostroknutova,Ekaterina, 2021. "Identification Properties for Estimating the Impact of Regulation on Markups and Productivity," Policy Research Working Paper Series 9523, The World Bank.
    3. Emir Malikov & Shunan Zhao & Jingfang Zhang, 2024. "A System Approach to Structural Identification of Production Functions with Multi-Dimensional Productivity," Advances in Econometrics, in: Essays in Honor of Subal Kumbhakar, volume 46, pages 211-263, Emerald Group Publishing Limited.
    4. Kritikos, Alexander S. & Schiersch, Alexander & Stiel, Caroline, 2021. "The Productivity Puzzle in Business Services," IZA Discussion Papers 14610, Institute of Labor Economics (IZA).
    5. James Harrigan & Ariell Reshef & Farid Toubal, 2018. "Techies, Trade, and Skill-Biased Productivity," NBER Working Papers 25295, National Bureau of Economic Research, Inc.
    6. Paul L. E. Grieco & Shengyu Li & Hongsong Zhang, 2022. "Input prices, productivity, and trade dynamics: long‐run effects of liberalization on Chinese paint manufacturers," RAND Journal of Economics, RAND Corporation, vol. 53(3), pages 516-560, September.
    7. Laurens Cherchye & Thomas Demuynck & Bram De Rock & Cédric Duprez & Glenn Magerman & Marijn Verschelde, 2021. "Structural Identification of Productivity under Biased Technological Change∗," Working Papers ECARES 2021-28, ULB -- Universite Libre de Bruxelles.
    8. van Heuvelen, Gerrit Hugo & Bettendorf, Leon & Meijerink, Gerdien, 2021. "Markups in a dual labour market: The case of the Netherlands," International Journal of Industrial Organization, Elsevier, vol. 77(C).
    9. Hashemi, Arshia & Kirov, Ivan & Traina, James, 2022. "The production approach to markup estimation often measures input distortions," Economics Letters, Elsevier, vol. 217(C).
    10. Jonathan Hambur, 2023. "Product Market Competition and its Implications for the Australian Economy," The Economic Record, The Economic Society of Australia, vol. 99(324), pages 32-57, March.
    11. Murray Leclair, Emmanuel, 2024. "Balancing Production and Carbon Emissions with Fuel Substitution," MPRA Paper 121139, University Library of Munich, Germany.
    12. Nelli Valmari, 2023. "Estimating Production Functions of Multiproduct Firms," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(6), pages 3315-3342.
    13. Ackerberg, Daniel A. & Frazer, Garth & Kim, Kyoo il & Luo, Yao & Su, Yingjun, 2023. "Under-identification of structural models based on timing and information set assumptions," Journal of Econometrics, Elsevier, vol. 237(1).
    14. Mauro Caselli & Arpita Chatterjee & Shengyu Li, 2023. "Productivity and Quality of Multi-product Firms," Discussion Papers 2023-10, School of Economics, The University of New South Wales.
    15. Li, Tong & Sasaki, Yuya, 2024. "Identification of heterogeneous elasticities in gross-output production functions," Journal of Econometrics, Elsevier, vol. 238(2).
    16. Jared Hutchins & Yating Gong & Xiaodong Du, 2024. "The role of animal breeding in productivity growth: Evidence from Wisconsin dairy farms," American Journal of Agricultural Economics, John Wiley & Sons, vol. 106(1), pages 286-305, January.
    17. Alexander S. Kritikos & Alexander Schiersch & Caroline Stiel, 2022. "The productivity shock in business services," Small Business Economics, Springer, vol. 59(3), pages 1273-1299, October.
    18. Shunan Zhao & Bing Qian & Subal C. Kumbhakar, 2020. "Estimation of productivity and markups with price dispersion: Evidence from Chinese manufacturing during economic transition," Southern Economic Journal, John Wiley & Sons, vol. 87(2), pages 666-699, October.
    19. Eisenberg, Tom, 2024. "Missing data and the effects of market deregulation: Evidence from Chinese coal power," International Journal of Industrial Organization, Elsevier, vol. 93(C).
    20. Scott E. Atkinson & Rong Luo, 2024. "Estimation Of Production Technologies With Output And Environmental Constraints," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 65(2), pages 755-780, May.
    21. Fei Jia & Minjie Huang & Shunan Zhao, 2024. "Estimation of endogenous firm productivity without instruments: an application to foreign investment," Journal of Productivity Analysis, Springer, vol. 61(2), pages 135-155, April.
    22. Emir Malikov & Jingfang Zhang & Shunan Zhao & Subal C. Kumbhakar, 2023. "Accounting for Cross-Location Technological Heterogeneity in the Measurement of Operations Efficiency and Productivity," Papers 2302.13430, arXiv.org.

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