Nonparametric Regression with Spatially Dependent Data

39 Pages Posted: 2 Oct 2009 Last revised: 1 May 2012

See all articles by Stefano Magrini

Stefano Magrini

Ca Foscari University of Venice - Dipartimento di Economia

Margherita Gerolimetto

Ca Foscari University of Venice

Date Written: March 30, 2010

Abstract

In this paper we present a new procedure for nonparametric regression in case of spatially dependent data. In particular, we extend usual local linear regression (along the lines of Martins-Filho and Yao, 2009) and propose a two-step method where information on spatial dependence is incorporated in the error covariance matrix, estimated nonparametrically. The finite sample performance of our proposed procedure is then shown via Monte Carlo simulations for various data generating processes.

Keywords: nonparametric smoothing, spatial dependence

JEL Classification: C14, C21

Suggested Citation

Magrini, Stefano and Gerolimetto, Margherita, Nonparametric Regression with Spatially Dependent Data (March 30, 2010). University Ca' Foscari of Venice, Dept. of Economics Research Paper Series, Available at SSRN: https://ssrn.com/abstract=1480626 or http://dx.doi.org/10.2139/ssrn.1480626

Stefano Magrini (Contact Author)

Ca Foscari University of Venice - Dipartimento di Economia ( email )

Cannaregio 873
Venice, 30121
Italy

Margherita Gerolimetto

Ca Foscari University of Venice ( email )

Dorsoduro 3246
Venice, Veneto 30123
Italy

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