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/>
no_trans idsect lnprice surface surfsq dVFA d2006 d2007 LUX
73474 13120402 12.408 594 352836 0 1 0 0
73710 12050503 11.878 576 331776 0 0 1 0
73713 12050505 12.429 383 146689 1 1 0 1
73722 13110202 12.782 1078 1162084 0 0 1 0
73764 12070503 11.849 495 245025 0 1 0 0
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