Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/79534 
Year of Publication: 
2013
Series/Report no.: 
cemmap working paper No. CWP12/13
Publisher: 
Centre for Microdata Methods and Practice (cemmap), London
Abstract: 
Individual players in a simultaneous equation binary choice model act differently in different environments in ways that are frequently not captured by observables and a simple additive random error. This paper proposes a random coefficient specification to capture this type of heterogeneity in behaviour, and discusses nonparametric identification and estimation of the distribution of random coefficients. We establish nonparametric point identification of the joint distribution of all random coefficients, except those on the interaction effects, provided the players behave competitively in all markets. Moreover, we establish set identification of the density of the coefficients on the interaction effects, and provide additional conditions that allow to point identify this density. Since our identification strategy is constructive throughout, it allows us to construct sample counterpart estimators. We analyse their asymptotic behaviour, and illustrate their finite sample behaviour in a numerical study. Finally, we discuss several extensions, like the semiparametric case, or correlated random coefficients.
Subjects: 
Games
Heterogeneity
Nonparametric Identification
Random Coefficients
Inverse Problems
JEL: 
C13
C14
C22
G12
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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