We suggest using a class of semiparametric dynamic panel data models to capture individual variations in panel data. The model assumes linearity in some continu ous/discrete variables which can be exogenous/endogenous, and allows for nonlinearity in other weakly exogenous variables. We propose a...

We study a new class of semiparametric instrumental variables models with the structural function represented by a partially varying coefficient functional form. Under this representation, the models are linear in the endogenous/exogenous components with unknown constant or functional...

In this paper we study time-varying coefficient models with time trend function and serially correlated errors to characterize nonlinear, nonstationary and trending phenomenon in time series. Compared with the Nadaraya-Watson method, the local linear approach is developed to estimate the time...

In this paper we study time-varying coefficient models with time trend function and serially correlated errors to characterize nonlinear, nonstationary and trending phenomenon in time series. Compared with the Nadaraya-Watson method, the local linear approach is developed to estimate the time...