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New results on the identification of stochastic bargaining models

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  • Merlo, Antonio
  • Tang, Xun

Abstract

We present new identification results for stochastic sequential bargaining models when the data only reports the time of agreement and the evolution of observable states. With no information on the stochastic surplus available for allocation or how it is allocated under agreement, we recover the latent surplus process, the distribution of unobservable states, and the equilibrium outcome in counterfactual contexts. The method we propose, which is constructive and original, can also be adapted to establish identification in general optimal stopping models.

Suggested Citation

  • Merlo, Antonio & Tang, Xun, 2019. "New results on the identification of stochastic bargaining models," Journal of Econometrics, Elsevier, vol. 209(1), pages 79-93.
    • Handle: RePEc:eee:econom:v:209:y:2019:i:1:p:79-93
    DOI: 10.1016/j.jeconom.2018.02.006
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    Cited by:

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    3. Kionka, Marlene & Kuethe, Todd H. & Musshoff, Oliver & Odening, Martin & Ritter, Matthias, 2022. "Bargaining Power in the Agricultural Land Rental Market," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322186, Agricultural and Applied Economics Association.

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    More about this item

    Keywords

    Nonparametric identification; Stochastic sequential bargaining;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • C78 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Bargaining Theory; Matching Theory

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