We consider a situation where a distribution is being estimated by the empirical distribution of noisy measurements.

We study the asymptotic properties of a class of estimators of the structural parameters in dynamic discrete choice games.

The interaction of economic agents is one of the most important elements in economic analyses.

This paper studies dynamic discrete choices by relaxing the assumption of rational expectations.

We consider identification and estimation of nonseparable sample selection models with censored selection rules.

This paper develops the identification and estimation of nonlinear semi-parametric panel data models with mismeasured variables and their corresponding average partial effects using only three periods of data.

We study a longitudinal data model with nonparametric regression functions that may vary across the observed subjects.

We propose an estimation methodology for a semiparametric quantile factor panel model.

High frequency trading (HFT) has grown substantially in recent years, due to fast-paced technological developments and their rapid uptake, particularly in equity markets.

This paper studies a model with both a parametric global trend and a nonparametric local trend.

Moment restriction semiparametric models, where both the dimension of parameter and the number of restrictions are divergent and an unknown function is involved, are studied using the generalized method of moments (GMM) and sieve method dealing with the nonparametric parameter.

In this paper, we propose three new predictive models: the multi-step nonparametric predictive regression model and the multi-step additive predictive regression model, in which the predictive variables are locally stationary time series; and the multi-step time-varying coefficient predictive regression model, in which the predictive variables are stochastically nonstationary.