[R-sig-Geo] Instrumental variable quantile estimation of spatial autoregressive models

[Marie-Line Glaesener]

Dear all,

I would like to implement a spatial quantile regression using instrumental variable estimation (according to Su and Yang (2007), Instrumental variable quantile estimation of spatial autoregressive models, SMU economics & statistis working paper series, 2007, 05-2007, p.35 ).

I am applying the hedonic pricing method on land transactions in Luxembourg.  My original data set contains 4335 observations.
I'm quite new to R and would like to ask if someone has implemented the method proposed by Su and Yang in R or if anyone could give me a hint on the different codes and steps?
Please find attached a small sample of my data and matrix.
R codes:

library(foreign)
library(lmtest)
library(spdep)
library(quantreg)

data<-read.table("DataSample.txt",header=TRUE, sep="")
attach(data)

matrix<-read.gwt2nb("matrixsample.gwt" ,region.id=no_Trans)
matrix.listw<-nb2listw(matrix)

OLS model
OLS<-lm(lnprice~surface+d2007+LUX+tsect_ci, data=data)
summary(OLS)

SAR model
SAR<-lagsarlm(lnprice~surface+d2007+LUX+tsect_ci, data=data, listw = matrix.listw)
summary(SAR)

I hope that this information is sufficient and will help you to help me :)

Many thanks in advance,

Marie-Line Glaesener

PhD student
Unité de Recherche IPSE (Identités. Politiques, Sociétés, Espaces)
Laboratoire de Géographie et Aménagement du Territoire

UNIVERSITÉ DU LUXEMBOURG
CAMPUS WALFERDANGE
Route de Diekirch / BP 2
L-7201 Walferdange
Luxembourg
www.geo.ipse.uni.lu<http://www.geo.ipse.uni.lu/>

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