We propose a method of modeling panel time series data with both inter- and intra-individual correlation, and of fitting an autoregressive model to such data. Estimates are obtained by a conditional likelihood argument. If there are few observations in each series, the estimates can be...

Bootstrap confidence intervals for impulse responses computed from autoregressive processes are considered. A detailed analysis of the methods in current use shows that they are not very reliable in some cases. In particular, there are theoretical reasons for them to have actual coverage...

This paper develops a new econometric tool for evolutionary autoregressive models where the AR coefficients change smoothly over time. To estimate the unknown functional form of time-varying coefficients, we propose a mdified local linear smoother. The asymptotic normality and variance of the...

This paper suggests a general functional-coefficient regression model in a form of ARX time series model. Contrast to the common threshold variable in the previous works, our model allows each coefficient to possess a different threshold variable and can cover a wide range of nonlinear dynamic...

For over a decade, nonparametric modelling has been successfully applied to study nonlinear structures in financial time series. It is well known that the usual nonparametric models often have less than satisfactory performance when dealing with more than one lag. When the mean has an additive...

In this paper we introduce a bootstrap procedure to test parameter restrictions in vector autoregressive models which is robust in cases of conditionally heteroskedastic error terms. The adopted wild bootstrap method does not require any parametric specification of the volatility process and...

We consider an additive model with second order interaction terms. It is shown how the components of this model can be estimated using marginal integration, and the asymptotic distribution of the estimators is derived. Moreover, two test statistics for testing the presence of interactions are...

In this paper we study nonparametric estimation and hypothesis testing procedures for the functional coefficient AR (FAR) models of the form Xt = f1(Xt-d)Xt-1 +…+ fp(Xt-d)Xt-p +εt, first proposed by Chen and Tsay (1993). As a direct generalization of the linear AR model, the FAR model is a...

When analyzing the productivity of firms, one may want to compare how the firms transform a set of inputs x (typically labor, energy or capital) into an output y (typically a quantity of goods produced). The economic efficiency of a firm is then defined in terms of its ability of operating close...