Nonparametric regression with spatially dependent data

Stefano Magrini and Margherita Gerolimetto ()

No 2009_20, Working Papers from Department of Economics, University of Venice "Ca' Foscari"

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 (search for similar items in EconPapers)
JEL-codes: C14 C21 (search for similar items in EconPapers)
Pages: 32
Date: 2009
New Economics Papers: this item is included in nep-ecm, nep-geo and nep-ure
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:ven:wpaper:2009_20

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