In this paper, we propose a panel data semiparametric varying-coefficient model in which covariates (variables affecting the coefficients) are purely categorical. This model has two features: first, fixed effects are included to allow for correlation between individual unobserved heterogeneity...

In this paper, we study a varying-coefficient panel data model with nonstationarity, wherein a factor structure is adopted to capture different effects of time invariant variables over time. The methodology employed in this paper fills a gap of dealing with the mixed I(1)/I(0) regressors and...

In this paper, we propose a panel data semiparametric varying-coefficient model in which covariates (variables affecting the coefficients) are purely categorical. This model has two features: first, fixed effects are included to allow for correlation between individual unobserved heterogeneity...

In this paper we propose a categorical time-varying coefficient translog cost function to estimate technical change and productivity. The primary feature of this model is that each of its coefficients is expressed as a nonparametric function of a categorical time variable, thereby allowing each...

We examine how city size affect wage levels of cities (agglomeration externality) and how it influence surrounding cities (spill-over effect) in China for the period between 1995 and 2009. Using spatial fixed-effect panel data models and allowing for endogenous and exogenous spatial dependence,...

In this paper, we consider a partially linear panel data model with cross-sectional dependence and non-stationarity. Meanwhile, we allow fixed effects to be correlated with the regressors to capture unobservable heterogeneity. Under a general spatial error dependence structure, we then...

This paper studies a general class of nonlinear varying coefficient time series models with possible nonstationarity in both the regressors and the varying coffiecient components. The model accommodates a cointegrating structure and allows for endogeneity with contemporaneous correlation among...

In this paper, we consider a semiparametric single index panel data mode with cross-sectional dependence, high-dimensionality and stationarity. Meanwhile, we allow fixed effects to be correlated with the regressors to capture unobservable heterogeneity. Under a general spatial error dependence...

In this paper, we consider a model selection issue in semiparametric panel data models with fixed effects. The modelling framework under investigation can accommodate both nonlinear deterministic trends and cross-sectional dependence. And we consider the so-called "large panels" where both the...

A system of vector semiparametric nonlinear time series models is studied with possible dependence structures and nonstationarities in the parametric and nonparametric components. The parametric regressors may be endogenous while the nonparametric regressors are strictly exogenous and represent...