This paper discusses nonparametric kernel regression with the regressor being a d-dimensional ß-null recurrent process in presence of conditional heteroscedasticity. We show that the mean function estimator is consistent with convergence rate p n(T)hd, where n(T) is the number of regenerations...

This study proposes a nonlinear cointegrating regression model based on the well-known energy balance climate model. Specifically, I investigate the nonlinear cointegrating regression of the mean of temperature anomaly distributions on total radiative forcing using estimated spatial...

Although nonlinearity is the rule in economic theory, nonlinearity tends to make life difficult for econometricians. While there have been many advances in nonlinear econometrics in recent years, some problems produced by nonlinearity remain 'skeletons in the closet' in empirical economic...

In this paper we develop a regression and a kernel density based model for finding fixed points and attractors of dynamical systems to explore attractors of structural change for NICs. The results show that countries consume longer time in some structures than the others. This can be interpreted...

In this paper we develop a regression and a kernel density based model for finding fixed points and attractors of dynamical systems to explore attractors of structural change for NICs. The results show that countries consume longer time in some structures than the others. This can be interpreted...