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Identification and counterfactuals in dynamic models of market entry and exit

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  • Victor Aguirregabiria
  • Junichi Suzuki

Abstract

This paper addresses a fundamental identification problem in the structural estimation of dynamic oligopoly models of market entry and exit. Using the standard datasets in existing empirical applications, three components of a firm’s profit function are not separately identified: the fixed cost of an incumbent firm, the entry cost of a new entrant, and the scrap value of an exiting firm. We study the implications of this result on the power of this class of models to identify the effects of different comparative static exercises and counterfactual public policies. First, we derive a closed-form relationship between the three unknown structural functions and the two functions that are identified from the data. We use this relationship to provide the correct interpretation of the estimated objects that are obtained under the ‘normalization assumptions’ considered in most applications. Second, we characterize a class of counterfactual experiments that are identified using the estimated model, despite the non-separate identification of the three primitives. Third, we show that there is a general class of counterfactual experiments of economic relevance that are not identified. We present a numerical example that illustrates how ignoring the non-identification of these counterfactuals (i.e., making a ‘normalization assumption’ on some of the three primitives) generates sizable biases that can modify even the sign of the estimated effects. Finally, we discuss possible solutions to address these identification problems. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Victor Aguirregabiria & Junichi Suzuki, 2014. "Identification and counterfactuals in dynamic models of market entry and exit," Quantitative Marketing and Economics (QME), Springer, vol. 12(3), pages 267-304, September.
  • Handle: RePEc:kap:qmktec:v:12:y:2014:i:3:p:267-304
    DOI: 10.1007/s11129-014-9147-5
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    Cited by:

    1. Kalouptsidi, Myrto & Scott, Paul & Souza-Rodrigues, Edouardo, 2015. "Identification of Counterfactuals and Payoffs in Dynamic Discrete Choice with an Application to Land Use," TSE Working Papers 15-596, Toulouse School of Economics (TSE).
    2. Kalouptsidi, Myrto & Scott, Paul T. & Souza-Rodrigues, Eduardo, 2017. "On the non-identification of counterfactuals in dynamic discrete games," International Journal of Industrial Organization, Elsevier, vol. 50(C), pages 362-371.
    3. Jean-Pierre Dubé & Günter Hitsch & Pranav Jindal, 2014. "The Joint identification of utility and discount functions from stated choice data: An application to durable goods adoption," Quantitative Marketing and Economics (QME), Springer, vol. 12(4), pages 331-377, December.
    4. V Kumar & Amalesh Sharma & Shaphali Gupta, 2017. "Accessing the influence of strategic marketing research on generating impact: moderating roles of models, journals, and estimation approaches," Journal of the Academy of Marketing Science, Springer, vol. 45(2), pages 164-185, March.
    5. Patrick Bajari & Chenghuan Sean Chu & Denis Nekipelov & Minjung Park, 2016. "Identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action," Quantitative Marketing and Economics (QME), Springer, vol. 14(4), pages 271-323, December.
    6. Mitsuru Igami, 2015. "Offshoring under Oligopoly," Working Papers BFI-2015-04, Becker Friedman Institute for Research In Economics.
    7. Fabio A. Miessi Sanches & Daniel Silva Junior, Sorawoot Srisuma, 2014. "Ordinary Least Squares Estimation for a Dynamic Game," Working Papers, Department of Economics 2014_19, University of São Paulo (FEA-USP), revised 23 Feb 2015.
    8. An-Hsiang Liu & Ralph Siebert, 2020. "The Competitive Effects of Declining Entry Costs over Time: Evidence from the Static Random Access Memory Market," CESifo Working Paper Series 8552, CESifo.
    9. Kalouptsidi, Myrto & Scott, Paul & Souza-Rodrigues, Eduardo, 2017. "Identification of Counterfactuals in Dynamic Discrete Choice Models," CEPR Discussion Papers 12470, C.E.P.R. Discussion Papers.
    10. Myrto Kalouptsidi & Paul T. Scott & Eduardo Souza-Rodrigues, 2015. "Identification of Counterfactuals in Dynamic Discrete Choice Models," NBER Working Papers 21527, National Bureau of Economic Research, Inc.
    11. Joachim Freyberger, 2021. "Normalizations and misspecification in skill formation models," Papers 2104.00473, arXiv.org.
    12. Marmer, Vadim & Slade, Margaret E., 2018. "Investment and uncertainty with time to build: Evidence from entry into U.S. copper mining," Journal of Economic Dynamics and Control, Elsevier, vol. 95(C), pages 233-254.
    13. Jason R. Blevins & Wei Shi & Donald R. Haurin & Stephanie Moulton, 2020. "A Dynamic Discrete Choice Model Of Reverse Mortgage Borrower Behavior," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 61(4), pages 1437-1477, November.
    14. Komarova, Tatiana & Sanches, Fábio Adriano & Silva Junior, Daniel & Srisuma, Sorawoot, 2018. "Joint analysis of the discount factor and payoff parameters in dynamic discrete choice games," LSE Research Online Documents on Economics 86858, London School of Economics and Political Science, LSE Library.
    15. Victor Aguirregabiria & Junichi Suzuki, 2015. "Empirical Games of Market Entry and Spatial Competition in Retail Industries," Working Papers tecipa-534, University of Toronto, Department of Economics.
    16. Nikhil Agarwal & Itai Ashlagi & Michael A. Rees & Paulo Somaini & Daniel Waldinger, 2021. "Equilibrium Allocations Under Alternative Waitlist Designs: Evidence From Deceased Donor Kidneys," Econometrica, Econometric Society, vol. 89(1), pages 37-76, January.
    17. Mitsuru Igami, 2015. "Offshoring under Oligopoly," 2015 Meeting Papers 713, Society for Economic Dynamics.
    18. Golombek, Rolf & Raknerud, Arvid, 2018. "Exit dynamics of start-up firms: Structural estimation using indirect inference," Journal of Econometrics, Elsevier, vol. 205(1), pages 204-225.
    19. Mitsuru Igami, 2018. "Industry Dynamics of Offshoring: The Case of Hard Disk Drives," American Economic Journal: Microeconomics, American Economic Association, vol. 10(1), pages 67-101, February.
    20. Nikhil Agarwal & Itai Ashlagi & Michael A. Rees & Paulo J. Somaini & Daniel C. Waldinger, 2019. "Equilibrium Allocations under Alternative Waitlist Designs: Evidence from Deceased Donor Kidneys," NBER Working Papers 25607, National Bureau of Economic Research, Inc.
    21. Arcidiacono, Peter & Miller, Robert A., 2020. "Identifying dynamic discrete choice models off short panels," Journal of Econometrics, Elsevier, vol. 215(2), pages 473-485.

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    More about this item

    Keywords

    Dynamic structural models; Market entry and exit; Identification; Fixed cost; Entry cost; Exit value; Counterfactual experiment; Land price; L10; C01; C51; C54; C73;
    All these keywords.

    JEL classification:

    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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