We deal with nonparametric estimation in a nonlinear cointegration model whose regressor and dependent variable can be contemporaneously correlated. The asymptotic properties of the Nadaraya-Watson estimator are already examined in the literature. In this paper, we consider nonparametric least...

The main objective of the paper is to analyse the local determinants of innovation in the Luxembourg metropolitan region. We are particularly interested in the impact of the local milieu and characteristics of firms. Our paper addresses two specific research questions. Firstly, we examine the...

This paper develops a fully modified OLS estimator for cointegrating polynomial regressions, i.e. for regressions including deterministic variables, integrated processes and powers of integrated processes as explanatory variables and stationary errors. The errors are allowed to be serially...

This essay investigates the impacts of primary care giver’s (PCG) time allocation and food expenditure choices on childhood obesity using national panel study of income dynamic (PSID) data. A triangular system of equations is derived and estimated under parametric and semi-parametric model...

Statistische Prognosen basieren auf der Annahme, dass ein funktionaler Zusammenhang zwischen der zu prognostizierenden Variable y und anderen j-dimensional beobachtbaren Variablen x = (x1,...xl) besteht. Kann der funktionale Zusammenhang geschätzt werden, so kann im Prinzip für jedes x der...

Statistische Prognosen basieren auf der Annahme, dass ein funktionaler Zusammenhang zwischen der zu prognostizierenden Variable y und anderen j-dimensional beobachtbaren Variablen x = (x1,...xl) besteht. Kann der funktionale Zusammenhang geschätzt werden, so kann im Prinzip für jedes x der...

The new growth theory establishes, among other things, that government expenditure can manipulate economic growth of a country. This study attempts to explain whether government expenditure increases or decreases economic growth in the context of Sri Lanka. Results obtained applying an...

We consider the nonparametric estimation of the regression functions for dependent data. Suppose that the covariates are observed with additive errors in the data and we employ nonparametric deconvolution kernel techniques to estimate the regression functions in this paper. We investigate how...