EconPapers    
Economics at your fingertips  
 

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
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed

Downloads: (external link)
http://www.unive.it/pag/fileadmin/user_upload/dipa ... to_magrini_20_09.pdf

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

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

Access Statistics for this paper

More papers in Working Papers from Department of Economics, University of Venice "Ca' Foscari" Contact information at EDIRC.
Bibliographic data for series maintained by Geraldine Ludbrook ().

 
Page updated 2022-01-23
Handle: RePEc:ven:wpaper:2009_20