A multiproduct cost function is estimated for German higher education institutions using a panel of data from recent years. The use of panel data allows a random parameter stochastic frontier model to be estimated, and this delivers new insights on the extent to which differences in costs...

A multiproduct cost function is estimated for English higher education institutions using a panel of data from recent years. The panel approach allows estimation by means of a random parameter stochastic frontier model which provides considerable new insights in that it allows the impact on...

In this paper, we propose a single-index panel data model with unobserved multiple interactive fixed effects. This model has the advantages of being flexible and of being able to allow for common shocks and their heterogeneous impacts on cross sections, thus making it suitable for the...

We propose a simple but flexible parametric method for estimating multiple conditional quantiles. By construction, the estimated quantiles will satisfy the monotonicity requirement which must hold for any distribution, so, in contrast to many benchmark methods, they are not susceptible to the...

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 establish...

This paper considers a model with general regressors and unobservable factors. An estimator based on iterated principal components is proposed, which is shown to be not only asymptotically normal and oracle efficient, but under certain conditions also free of the otherwise so common asymptotic...

This paper establishes conditions for nonparametric identification of dynamic optimization models in which agents make both discrete and continuous choices. We consider identification of both the payoff function and the distribution of unobservables. Models of this kind are prevalent in applied...

This paper analyzes the impact of load factor, facility and generator types on the productivity of Korean electric power plants. In order to capture important differences in the effect of load policy on power output, we use a semiparametric smooth coefficient (SPSC) model that allows us to model...

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...

A random parameters stochastic frontier model is applied to Italian data in order to evaluate the cost function and efficiency of higher education institutions. The method yields useful information about inter-institutional variation in cost structure and technical efficiency. Returns to scale...