Identification in Models with Discrete Variables

Identification and Estimation in Discrete Choice Demand Models when Endogenous Variables Interact with the Error

We develop an estimator for the parameters of a utility function that has interactions between the unobserved demand error and observed factors including price. We show that the Berry (1994)/Berry, Levinsohn, and Pakes (1995) inversion and contraction can still be used to recover the mean utility term that now contains both the demand error and the interactions with the error. However, the inst...

Discrete Endogenous Variables in Weakly Separable Models

This paper contains an extension of the identification method proposed in Jun, Pinkse, and Xu (2009, JPX), which is based on a generated collection of sets, i.e. a Dynkin system. We demonstrate the usefulness of this extension in the context of the model proposed by Vytlacil and Yıldız (2007, VY). VY formulate a fully nonparametric model featuring a nested weakly separable structure in which an...

Closed-Form Identification of Dynamic Discrete Choice Models with Proxies for Unobserved State Variables

For dynamic discrete choice models of forward-looking agents where a continuous state variable is unobserved but its proxy is available, we derive closed-form identification of the structure by explicitly solving integral equations. For an empirical illustration, we analyze industry dynamics in Chile.

on some bayesian statistical models in actuarial science with emphasis on claim count

چکیده ندارد.

What do instrumental variable models deliver with discrete dependent variables?