This paper proposes a semiparametric estimator for spatial autoregressive (SAR) binary choice models in the context of panel data with fixed effects. The estimation procedure is based on the observational equivalence between distribution free models with a conditional median restriction and...

This paper proposes a semiparametric estimator for spatial autoregressive (SAR) binary choice models in the context of panel data with fixed effects. The estimation procedure is based on the observational equivalence between distribution free models with a conditional median restriction and...

This paper considers spatial autoregressive (SAR) binary choice models in the context of panel data with fixed effects, where the latent dependent variables are spatially correlated. Without imposing any parametric structure of the error terms, this paper proposes a smoothed spatial maximum...

In this paper, we study the spatial dynamic panel data models with high-order time-varying endogenous weights matrices. The quasi-maximum likelihood (QML) estimator is inconsistent under heteroskedastic errors and would be computationally complicated due to the evaluation of the Jacobian...

In this paper, we study the spatial dynamic panel data models with high-order time-varying endogenous weights matrices. To estimate the model, we propose a generalized method of moments (GMM) estimator. Compared to the traditional quasi-maximum likelihood (QML) estimator, GMM estimators can...

In this paper we investigate a class of semiparametric models for panel datasets where the cross-section and time dimensions are large. Our model contains a latent time series that is to be estimated and perhaps forecasted along with a nonparametric covariate effect. Our model is motivated by...

This paper considers kernel-based nonparametric estimation of panel models using local linear least squares, when both the fixed individual effects and the time effects present. The marginal effect is of the main interest. A within-group type nonparametric estimator is developed, where the...