Add to ORKGNonparametric regression is developed for data with both a temporal and a cross-sectional dimension. The model includes additive, unknown, individual-speci\u85c components and allows also for cross-sectional and temporal dependence and conditional heteroscedasticity. A simple nonparametric estimate is shown to be dominated by a GLS-type one. Asymptotically optimal bandwidth choices are justi\u85ed for both estimates. Feasible optimal bandwidths, and feasi-ble optimal regression estimates, are asymptotically justi\u85ed, with \u85nite sample performance examined in a Monte Carlo study. JEL classi\u85cations: C13; C14; C2
In the analysis of longitudinal data it is of main interest to investigate the existence of group an...
This paper addresses inference in large panel data models in the presence of both cross-sectional an...
An asymptotic theory is developed for nonparametric and semiparametric series estimation under gener...
AbstractNonparametric regression is developed for data with both a temporal and a cross-sectional di...
Nonparametric regression is developed for data with both a temporal and a cross-sectional dimension....
Panel data, whose series length T is large but whose cross-section size N need not be, are assumed t...
In this paper, we consider efficiency improvement in a nonparametric panel data model with cross-sec...
Härdle W, Marron JS. Optimal Bandwidth Selection in Nonparametric Regression Function Estimation. Th...
In this paper we consider the problem of estimating semiparametric \u85xed-e¤ects panel data models ...
In the present paper we combine the issues of bandwidth choice and construction of confidence interv...
In this paper we consider nonparametric estimation in panel data under cross-sectional dependence. B...
AbstractAn asymptotic theory is developed for series estimation of nonparametric and semiparametric ...
In time series regressions with nonparametrically autocorrelated errors, it is now standard empirica...
In the context of nonparametric regression estimation, the behaviour of kernel methods such as the N...
Automated bandwidth selection methods for nonparametric regression break down in the presence of cor...
In the analysis of longitudinal data it is of main interest to investigate the existence of group an...
This paper addresses inference in large panel data models in the presence of both cross-sectional an...
An asymptotic theory is developed for nonparametric and semiparametric series estimation under gener...
AbstractNonparametric regression is developed for data with both a temporal and a cross-sectional di...
Nonparametric regression is developed for data with both a temporal and a cross-sectional dimension....
Panel data, whose series length T is large but whose cross-section size N need not be, are assumed t...
In this paper, we consider efficiency improvement in a nonparametric panel data model with cross-sec...
Härdle W, Marron JS. Optimal Bandwidth Selection in Nonparametric Regression Function Estimation. Th...
In this paper we consider the problem of estimating semiparametric \u85xed-e¤ects panel data models ...
In the present paper we combine the issues of bandwidth choice and construction of confidence interv...
In this paper we consider nonparametric estimation in panel data under cross-sectional dependence. B...
AbstractAn asymptotic theory is developed for series estimation of nonparametric and semiparametric ...
In time series regressions with nonparametrically autocorrelated errors, it is now standard empirica...
In the context of nonparametric regression estimation, the behaviour of kernel methods such as the N...
Automated bandwidth selection methods for nonparametric regression break down in the presence of cor...
In the analysis of longitudinal data it is of main interest to investigate the existence of group an...
This paper addresses inference in large panel data models in the presence of both cross-sectional an...
An asymptotic theory is developed for nonparametric and semiparametric series estimation under gener...