eprintid: 4009
rev_number: 4
eprint_status: archive
userid: 1
dir: disk0/00/00/40/09
datestamp: 2022-08-31 10:32:13
lastmod: 2022-08-31 10:32:13
status_changed: 2022-08-31 10:32:13
type: thesis
metadata_visibility: show
sword_depositor: 1
creators_name: Weenink, Philibert Lorenz, MSc
creators_id: S3246620
creators_email: p.l.weenink@outlook.com
title: Local spatio-temporal regression kriging for property price predictions
ispublished: unpub
full_text_status: public
abstract: This thesis proposes a hedonic regression model that accounts for spatio-temporal dependence
and heterogeneity in property transaction prices.
The considered methodology extends upon
purely spatial geostatistical methods and applies local spatio-temporal regression kriging (LSTRK).
We account for spatio-temporal dependence by specifying dual structure variograms. Since such
variograms consider distances between properties in space and time simultaneously, they allow
for the estimation of a single covariance structure that controls for spatio-, temporal- and joint
dependence. We account for heterogeneity of both attribute prices and dependence structures by
performing the analysis per individual submarket. To empirically examine the prediction accuracy
of our model, out-of-sample forecasts are made on residential housing prices. We consider a housing
transaction dataset of 57,154 properties in Mecklenburg County, North Carolina. Our data is split
into 7 spatial zones and 5 temporal zones, providing us with a total of 35 submarkets. For each
submarket, in-sample- and out-of-sample subsets are obtained. These allow for model training and
prediction assessment respectively. In terms of mean absolute error, median absolute error, mean
squared error and root mean squared error, the proposed methodology outperforms traditional
hedonic models consistently. Hence, empirical results suggest that LSTRK indeed provides more
accurate predictions than traditional OLS models.
date: 2022
pages: 78
thesis_type: master
degree_programme: VG
tutors_name: Liu, X.
tutors_name: Vlist, A.J. van der
tutors_organization: Fac. Ruimtelijke wetenschappen, Basiseenheid Economische Geografie
tutors_organization: Fac. Ruimtelijke wetenschappen, Basiseenheid Economische Geografie
tutors_email: Xiaolong.Liu@rug.nl
tutors_email: A.J.van.der.Vlist@rug.nl
security: public
keywords_local: Spatio-temporal dependence
keywords_local: Spatio-temporal heterogeneity
keywords_local: House price prediction
language_iso: en
date_issued: 2022-08-31
citation:   Weenink, Philibert Lorenz, MSc  (2022) Local spatio-temporal regression kriging for property price predictions.  Master thesis.   
document_url: https://frw.studenttheses.ub.rug.nl/4009/1/Thesis_Real_Estate_Studies.pdf