IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2302.14602.html
   My bibliography  Save this paper

On the Estimation of Cross-Firm Productivity Spillovers with an Application to FDI

Author

Listed:
  • Emir Malikov
  • Shunan Zhao

Abstract

We develop a novel methodology for the proxy variable identification of firm productivity in the presence of productivity-modifying learning and spillovers which facilitates a unified "internally consistent" analysis of the spillover effects between firms. Contrary to the popular two-step empirical approach, ours does not postulate contradictory assumptions about firm productivity across the estimation steps. Instead, we explicitly accommodate cross-sectional dependence in productivity induced by spillovers which facilitates identification of both the productivity and spillover effects therein simultaneously. We apply our model to study cross-firm spillovers in China's electric machinery manufacturing, with a particular focus on productivity effects of inbound FDI.

Suggested Citation

  • Emir Malikov & Shunan Zhao, 2023. "On the Estimation of Cross-Firm Productivity Spillovers with an Application to FDI," Papers 2302.14602, arXiv.org.
  • Handle: RePEc:arx:papers:2302.14602
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2302.14602
    File Function: Latest version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Jan De Loecker & Pinelopi K. Goldberg & Amit K. Khandelwal & Nina Pavcnik, 2016. "Prices, Markups, and Trade Reform," Econometrica, Econometric Society, vol. 84, pages 445-510, March.
    2. Guido M. Kuersteiner & Ingmar R. Prucha, 2020. "Dynamic Spatial Panel Models: Networks, Common Shocks, and Sequential Exogeneity," Econometrica, Econometric Society, vol. 88(5), pages 2109-2146, September.
    3. Jan De Loecker, 2013. "Detecting Learning by Exporting," American Economic Journal: Microeconomics, American Economic Association, vol. 5(3), pages 1-21, August.
    4. Ulrich Doraszelski & Jordi Jaumandreu, 2018. "Measuring the Bias of Technological Change," Journal of Political Economy, University of Chicago Press, vol. 126(3), pages 1027-1084.
    5. Bramoullé, Yann & Djebbari, Habiba & Fortin, Bernard, 2009. "Identification of peer effects through social networks," Journal of Econometrics, Elsevier, vol. 150(1), pages 41-55, May.
    6. Wolfgang Keller & Stephen R. Yeaple, 2009. "Multinational Enterprises, International Trade, and Productivity Growth: Firm-Level Evidence from the United States," The Review of Economics and Statistics, MIT Press, vol. 91(4), pages 821-831, November.
    7. Eichengreen, Barry & Tong, Hui, 2007. "Is China's FDI coming at the expense of other countries?," Journal of the Japanese and International Economies, Elsevier, vol. 21(2), pages 153-172, June.
    8. Jan De Loecker & Frederic Warzynski, 2012. "Markups and Firm-Level Export Status," American Economic Review, American Economic Association, vol. 102(6), pages 2437-2471, October.
    9. Zvi Griliches, 1998. "Issues in Assessing the Contribution of Research and Development to Productivity Growth," NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 17-45, National Bureau of Economic Research, Inc.
    10. Daniel A. Ackerberg & Kevin Caves & Garth Frazer, 2015. "Identification Properties of Recent Production Function Estimators," Econometrica, Econometric Society, vol. 83, pages 2411-2451, November.
    11. Amit Gandhi & Salvador Navarro & David A. Rivers, 2020. "On the Identification of Gross Output Production Functions," Journal of Political Economy, University of Chicago Press, vol. 128(8), pages 2973-3016.
    12. Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(3), pages 531-542.
    13. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    14. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-533, May.
    15. Arthur Lewbel, 2012. "Using Heteroscedasticity to Identify and Estimate Mismeasured and Endogenous Regressor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 67-80.
    16. Newey, Whitney K., 1984. "A method of moments interpretation of sequential estimators," Economics Letters, Elsevier, vol. 14(2-3), pages 201-206.
    17. J.J. Heckman & E.E. Leamer (ed.), 2001. "Handbook of Econometrics," Handbook of Econometrics, Elsevier, edition 1, volume 5, number 5.
    18. Lee, Lung-fei, 2007. "The method of elimination and substitution in the GMM estimation of mixed regressive, spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 140(1), pages 155-189, September.
    19. Hahn, Jinyong & Liao, Zhipeng & Ridder, Geert, 2018. "Nonparametric Two-Step Sieve M Estimation And Inference," Econometric Theory, Cambridge University Press, vol. 34(6), pages 1281-1324, December.
    20. Ulrich Doraszelski & Jordi Jaumandreu, 2013. "R&D and Productivity: Estimating Endogenous Productivity," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 80(4), pages 1338-1383.
    21. Lee, Lung-fei, 2007. "GMM and 2SLS estimation of mixed regressive, spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 137(2), pages 489-514, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Jingfang Zhang & Emir Malikov, 2023. "Detecting Learning by Exporting and from Exporters," Journal of Productivity Analysis, Springer, vol. 60(1), pages 1-19, August.
    3. 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.
    4. Geoffrey Barrows & Hélène Ollivier & Ariell Reshef, 2023. "Production Function Estimation with Multi-Destination Firms," CESifo Working Paper Series 10716, CESifo.
    5. Ioannis Bournakis & Mike Tsionas, 2024. "A Non‐parametric Estimation of Productivity with Idiosyncratic and Aggregate Shocks: The Role of Research and Development (R&D) and Corporate Tax," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(3), pages 641-671, June.
    6. Gornig, Martin & Schiersch, Alexander, 2019. "Agglomeration economies and firm TFP: different effects across industries," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203597, Verein für Socialpolitik / German Economic Association.
    7. 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.
    8. Jamil, Nida & Chaudhry, Theresa Thompson & Chaudhry, Azam, 2022. "Trading textiles along the new silk route: The impact on Pakistani firms of gaining market access to China," Journal of Development Economics, Elsevier, vol. 158(C).
    9. Yoonseok Lee & Mary E. Lovely & Hoang Pham, 2023. "Dynamic and non‐neutral productivity effects of foreign ownership: A nonparametric approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(1), pages 24-48, January.
    10. David Van Dijcke, 2022. "On the Non-Identification of Revenue Production Functions," Papers 2212.04620, arXiv.org, revised May 2024.
    11. Guido M. Kuersteiner & Ingmar R. Prucha, 2020. "Dynamic Spatial Panel Models: Networks, Common Shocks, and Sequential Exogeneity," Econometrica, Econometric Society, vol. 88(5), pages 2109-2146, September.
    12. Aguiar, Victor H. & Kashaev, Nail & Allen, Roy, 2023. "Prices, profits, proxies, and production," Journal of Econometrics, Elsevier, vol. 235(2), pages 666-693.
    13. CHANG Pao-Li & MAKIOKA Ryo & NG Bo Lin & YANG Zhenlin, 2023. "Estimating Firm-level Production Functions with Spatial Dependence in Output, Input, and Productivity," Discussion papers 23016, Research Institute of Economy, Trade and Industry (RIETI).
    14. Gibbon, Alexandra J. & Schain, Jan Philip, 2023. "Rising markups, common ownership, and technological capacities," International Journal of Industrial Organization, Elsevier, vol. 89(C).
    15. Xiaodong Liu, 2020. "GMM identification and estimation of peer effects in a system of simultaneous equations," Journal of Spatial Econometrics, Springer, vol. 1(1), pages 1-27, December.
    16. Richter, Philipp M. & Schiersch, Alexander, 2017. "CO2 emission intensity and exporting: Evidence from firm-level data," European Economic Review, Elsevier, vol. 98(C), pages 373-391.
    17. James Harrigan & Ariell Reshef & Farid Toubal, 2018. "Techies, Trade, and Skill-Biased Productivity," NBER Working Papers 25295, National Bureau of Economic Research, Inc.
    18. Nathaniel Lane, 2020. "The New Empirics of Industrial Policy," Journal of Industry, Competition and Trade, Springer, vol. 20(2), pages 209-234, June.
    19. Li, Mingyang & Jin, Man & Kumbhakar, Subal C., 2022. "Do subsidies increase firm productivity? Evidence from Chinese manufacturing enterprises," European Journal of Operational Research, Elsevier, vol. 303(1), pages 388-400.
    20. Li, Tong & Sasaki, Yuya, 2024. "Identification of heterogeneous elasticities in gross-output production functions," Journal of Econometrics, Elsevier, vol. 238(2).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2302.14602. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.