Repeat Sales House Price Index Methodology

Nagaraja, Chaitra H.; Brown, Lawrence D.; Wächter, Susan M.

doi:10.2139/ssrn.2458491

Cited by 19 publications

(13 citation statements)

References 23 publications

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“…This indexation approach is subject to criticism. The main defect of this approach is its inability to cover houses that are only transacted once or newly produced (Nagaraja et al, 2010(Nagaraja et al, , 2011. This has mainly resulted from the pre-requisite of input data that a house needs to have more than one transaction over a period.…”

Section: Ijhmamentioning

confidence: 99%

Spatial–temporal neighbourhood-level house price index

Sipan

Iman

Razali

2018

IJHMA

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Purpose-The purpose of this study is to develop a spatio-temporal neighbourhood-level house price index (STNL-HPI) incorporating a geographic information system (GIS) functionality that can be used to improve the house price indexation system. Design/methodology/approach-By using the Malaysian house price index (MHPI) and application of geographically weighted regression (GWR), GIS-based analysis of STNL-HPI through an application called LHPI Viewer v.1.0.0, the stand-alone GIS-statistical application for STNL-HPI was successfully developed in this study. Findings-The overall results have shown that the modelling and GIS application were able to help users understand the visual variation of house prices across a particular neighbourhood. Research limitations/implications-This research was only able to acquire data from the federal government over the period 1999 to 2006 because of budget limitations. Data purchase was extremely costly. Because of financial constraints, data with lower levels of accuracy have been obtained from other sources. As a consequence, a major portion of data was mismatched because of the absence of a common parcel identifier, which also affected the comparison of this system to other comparable systems. Originality/value-Neighbourhood-level HPI is needed for a better understanding of the local housing market.

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Section: Ijhmamentioning

confidence: 99%

Spatial–temporal neighbourhood-level house price index

Sipan

Iman

Razali

2018

IJHMA

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“…Statistical controls are possibly needed for poorer correlations between earlier and much later sale prices as formulated by Case and Shiller (1987). Another less relevant methodological concern is about the volatility of these predicted prices, and this is empirically investigated in studies with much larger numbers of repeat sales than that herein (Jansen et al 2008;Hill et al 2009;Goh et al 2012;Bourassa et al 2013;Nagaraja et al 2014).…”

Section: Measuring Changes With a Repeat Sales Modelmentioning

confidence: 99%

Use of repeat house sales to measure changes since the early‐ or mid‐1980s in two inner‐city neighbourhoods in Windsor, Ontario

Phipps

2019

Canadian Geographies / Géographies canadiennes

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Changes in the prices of homes and the reasons for those changes may be more accurately predicted from repeat sales of the same homes after controlling for their changed attributes and differences in time between their sales and resales. This paper analyzes 346 of 583 sold houses in the Glengarry neighbourhood in Windsor, Ontario, that were sold more than once between 1981 and mid‐2017, and a corresponding 414 of 737 sold houses in the city's Wellington‐Crawford neighbourhood, sold more than once between 1986 and mid‐2017. After comparing types of resold homes with once‐sold ones, a repeat sales model predicts a first period of increasing annual percentage changes in resale prices compared to sale prices during the 1980s, followed by a second period of stagnation and possible decreases until 2011, and then increases during a third period after that. In addition, changes in resold homes’ attributes of the dwelling unit and neighbourhood are a second type of neighbourhood change in two inner‐city neighbourhoods during the past 30 or more years.

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“…A credible house price index is important in order to find which determinants are actually contributing and are significant to the house price. A lot of studies that are related to the construction of house price index have been conducted in order to improve the modeling of house price index with the purpose to produce an accurate house price index (Bourassa et al 2004;Longford 2009;Nagaraja et al 2010;Selim 2008;Ali & Metin 2011;Lizam et al 2013). House price index has long been implemented in developed countries such as the United States of America (US), United Kingdom (UK), Canada and Germany.…”

Section: Literature Reviewmentioning

confidence: 99%

Constructing an Enhanced House Price Index Model: Empirical Evidence

Sukrri¹,

Wahab²,

Yusof³

2019

JEM

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The objective of this study is to construct an enhanced house price index model in Malaysia. Having reviewed the current model of the Malaysian House Price Index (MHPI), it is currently found that this index is constructed based on the demand-driven variables. Previous studies explained that both macroeconomic factors (income levels, interest rates, and labor market) and supply factors are included in the construction of the house price index. This study begins by examining the determinants of the existing house price index in Malaysia. This study employs the Autoregressive Distributed Lag Model (ARDL) to discover the short and long-run dynamics between the variables. The study considers the quarterly data from the first quarter of 2008 to the fourth quarter of 2017. The findings reveal that construction cost (CC) and housing loan (HLN) are significant in determining HPI while Overnight Policy Rate (OPR) and land supply (LS) are insignificant with HPI. Then, the housing loan was found to be the most significant variable in determining HPI in Malaysia. Hence, we propose a new enhanced house price index that incorporates new demand and supply variables, by using the Laspeyres approach to calculate the new enhanced HPI. The analysis shows that the enhanced house price index has also recorded the same trend but with a lower value of prices as compared to the current MHPI. This enhanced HPI model may reflect the real situation of the housing market in Malaysia and it is expected to increase the affordability of the society in fulfilling their basic needs. This study may provide evidence for the involved parties to have some policy ramifications to further monitor and take appropriate measures to control the prices of property.

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Repeat Sales House Price Index Methodology

Cited by 19 publications

References 23 publications

Spatial–temporal neighbourhood-level house price index

Spatial–temporal neighbourhood-level house price index

Use of repeat house sales to measure changes since the early‐ or mid‐1980s in two inner‐city neighbourhoods in Windsor, Ontario

Constructing an Enhanced House Price Index Model: Empirical Evidence

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