We develop a minimum distance estimator for dynamic games of incomplete information. We take a two-step approach, following Hotz and Miller (1993), based on the pseudo-model that does not solve the dynamic equilibrium so as to circumvent the potential indeterminacy issues associated with...

Econometric analyses in the happiness literature typically use subjective well-being (SWB) data to compare the mean of observed or latent happiness across samples. Recent critiques show that comparing the mean of ordinal data is only valid under strong assumptions that are usually rejected by...

We propose a general two-step estimation method for the structural parameters of popular semiparametric Markovian discrete choice models that include a class of Markovian Games and allow for continuous observable state space. The estimation procedure is simple as it directly generalizes the...

We study the uniform convergence rates of a nonparametric estimator for a probability density function and its derivatives when the density has a known pole. Such situation arises in some structural microeconometric models, e.g. in auction, labor, and consumer search. Existing uniform...

We consider nonparametric identification and estimation of pricing kernels, or equivalently of marginal utility functions up to scale, in consumption based asset pricing Euler equations. Ours is the first paper to prove nonparametric identification of Euler equations under low level conditions...

Most empirical and theoretical econometric studies of dynamic discrete choice models assume the discount factor to be known. We show the knowledge of the discount factor is not necessary to identify parts, or even all, of the payoff function. We show the discount factor can be generically...