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

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  • Malikov, Emir
  • Zhao, Shunan

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 crosssectional 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-firmspillovers in China’s electric machinery manufacturing, with a particular focus on productivity effects of inbound FDI.

Suggested Citation

  • Malikov, Emir & Zhao, Shunan, 2022. "On the Estimation of Cross-Firm Productivity Spillovers with an Application to FDI," 2022 Allied Social Sciences Association (ASSA) Annual Meeting (Virtual), January 7-9, 2022 316529, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:assa22:316529
    DOI: 10.22004/ag.econ.316529
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    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Barry Eichengreen & Hui Tong, 2007. "Is China’s FDI Coming at the Expense of Other Countries?," Chapters, in: Klaus Liebscher & Josef Christl & Peter Mooslechner & Doris Ritzberger-Grünwald (ed.), Foreign Direct Investment in Europe, chapter 11, Edward Elgar Publishing.
    10. 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.
    11. Jan De Loecker, 2013. "Detecting Learning by Exporting," American Economic Journal: Microeconomics, American Economic Association, vol. 5(3), pages 1-21, August.
    12. 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.
    13. Daniel A. Ackerberg & Kevin Caves & Garth Frazer, 2015. "Identification Properties of Recent Production Function Estimators," Econometrica, Econometric Society, vol. 83, pages 2411-2451, November.
    14. Newey, Whitney K., 1984. "A method of moments interpretation of sequential estimators," Economics Letters, Elsevier, vol. 14(2-3), pages 201-206.
    15. 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.
    16. J.J. Heckman & E.E. Leamer (ed.), 2001. "Handbook of Econometrics," Handbook of Econometrics, Elsevier, edition 1, volume 5, number 5.
    17. 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.
    18. 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.
    19. 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.
    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.
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    Keywords

    Production Economics; Productivity Analysis;

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