Measuring and decomposing the distance to the Shapley wage function with limited data
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- Victor Aguiar & Roland Pongou & Jean-Baptiste Tondji, 2016. "Measuring and Decomposing the Distance to the Shapley Wage Function with Limited Data," Working Papers 1613e, University of Ottawa, Department of Economics.
References listed on IDEAS
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Cited by:
- Pongou, Roland & Tondji, Jean-Baptiste, 2018.
"Valuing inputs under supply uncertainty: The Bayesian Shapley value,"
Games and Economic Behavior, Elsevier, vol. 108(C), pages 206-224.
- Roland Pongou & Jean-Baptiste Tondji, 2016. "Valuing Inputs Under Supply Uncertainty: The Bayesian Shapley Value," Working Papers 1617E, University of Ottawa, Department of Economics.
- Pongou, Roland & Tondji, Jean-Baptiste, 2016. "Valuing Inputs Under Supply Uncertainty : The Bayesian Shapley Value," MPRA Paper 74747, University Library of Munich, Germany.
- Tido Takeng, Rodrigue, 2022. "Uncertain production environment and communication structure," Journal of Mathematical Economics, Elsevier, vol. 102(C).
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More about this item
Keywords
Shapley wage function; firm; fairness violations; linear contract; bargaining; limited data;All these keywords.
JEL classification:
- C71 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Cooperative Games
- C78 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Bargaining Theory; Matching Theory
- D20 - Microeconomics - - Production and Organizations - - - General
- D30 - Microeconomics - - Distribution - - - General
- J30 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - General
NEP fields
This paper has been announced in the following NEP Reports:- NEP-GTH-2016-09-18 (Game Theory)
- NEP-LMA-2016-09-18 (Labor Markets - Supply, Demand, and Wages)
- NEP-SOG-2016-09-18 (Sociology of Economics)
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