Analysis of housing prices in Petaling district, Malaysia using functional relationship model

2019 ◽  
Vol 12 (5) ◽  
pp. 884-905
Author(s):  
Yun Fah Chang ◽  
Wei Cheng Choong ◽  
Sing Yan Looi ◽  
Wei Yeing Pan ◽  
Hong Lip Goh
Keyword(s):  
Housing Market ◽  
Functional Relationship ◽  
Housing Prices ◽  
Hedonic Model ◽  
Analysis Tool ◽  
Content Type ◽  
Proposed Model ◽  
Relationship Model ◽  
Housing Attributes ◽  
House Buyers

Purpose The purpose of this paper is to analyse and predict the housing prices in Petaling district, Malaysia and its six sub-regions with a set of housing attributes using functional relationship model. Design/methodology/approach A new multiple unreplicated linear functional relationship model with both the response and explanatory variables are subject to errors is proposed. A total of 41,750 housing transacted records from November 2008 to February 2016 were used in this study. These data were divided into 70% training and 30% testing sets for each of the selected sub-regions. Individual housing price was regressed on nine housing attributes. Findings The results showed the proposed model has better fitting ability and prediction accuracy as compared to the hedonic model or multiple linear regression. The proposed model achieved at least 20% and 40% of predictions that have less than 5% and 10% deviations from the actual transacted housing prices, respectively. House buyers in these sub-regions showed similar preferences on most of the housing attributes, except for residents in Shah Alam who preferred to stay far away from shopping malls, and leasehold houses in Sri Kembangan are more valuable. From the h-nearest houses indicator, it is concluded that the housing market in Sungai Buloh is the most volatile in Petaling District. Research limitations/implications As the data used are the actual housing transaction records in Petaling District, it represents only a segment of Malaysian urban population. The result will not be generalized to the entire Malaysian population. Practical implications This study is expected to provide insights to policymakers, property developers and investors to understand the volatility of the housing market and the influence of determinants in different sub-regions. The potential house buyers could also use the model to determine if a house is overpriced. Originality/value This study introduces measurement errors into the housing attributes to provide a more reliable analysis tool for the housing market. This study is the first housing research in Malaysia that used a large number of actual housing transaction records. Previous studies relied on small survey samples.

Property investor decisions using income and rental ratio signals

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Billie Ann Brotman
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
Discount Rate ◽  
Price Index ◽  
Housing Prices ◽  
Housing Price ◽  
Consumer Sentiment ◽  
Content Type ◽  
Income Ratio ◽  
Real Estate Prices

PurposeThis paper, a case study, aims to consider whether the income ratio and rental ratio tracks the formation of residential housing price spikes and their collapse. The ratios are measuring the risk associated with house price stability. They may signal whether a real estate investor should consider purchasing real property, continue holding it or consider selling it. The Federal Reserve Bank of Dallas (Dallas Fed) calculates and publishes income ratios for Organization for Economic Cooperation and Development countries to measure “irrational exuberance,” which is a measure of housing price risk for a given country's housing market. The USA is a member of the organization. The income ratio idea is being repurposed to act as a buy/sell signal for real estate investors.Design/methodology/approachThe income ratio calculated by the Dallas Fed and this case study's ratio were date-stamped and graphed to determine whether the 2006–2008 housing “bubble and burst” could be visually detected. An ordinary least squares regression with the data transformed into logs and a regression with structural data breaks for the years 1990 through 2019 were modeled using the independent variables income ratio, rent ratio and the University of Michigan Consumer Sentiment Index. The descriptive statistics show a gradual increase in the ratios prior to exposure to an unexpected, exogenous financial shock, which took several months to grow and collapse. The regression analysis with breaks indicates that the income ratio can predict changes in housing prices using a lead of 2 months.FindingsThe gradual increases in the ratios with predetermine limits set by the real estate investor may trigger a sell decision when a specified rate is reached for the ratios even when housing prices are still rising. The independent variables were significant, but the rent ratio had the correct sign only with the regression with time breaks model was used. The housing spike using the Dallas Fed's income ratio and this study's income ratio indicated that the housing boom and collapse occurred rapidly. The boom does not appear to be a continuous housing price increase followed by a sudden price drop when ratio analysis is used. The income ratio is significant through time, but the rental ratio and Consumer Sentiment Index are insignificant for multiple-time breaks.Research limitations/implicationsInvestors should consider the relative prices of residential housing in a neighborhood when purchasing a property coupled with income and rental ratio trends that are taking place in the local market. High relative income ratios may signal that when an unexpected adverse event occurs the housing market may enter a state of crisis. The relative housing prices to income ratio indicates there is rising housing price stability risk. Aggregate data for the country are used, whereas real estate prices are also significantly impacted by local conditions.Practical implicationsRatio trends might enable real estate investors and homeowners to determine when to sell real estate investments prior to a price collapse and preserve wealth, which would otherwise result in the loss of equity. Higher exuberance ratios should result in an increase in the discount rate, which results in lower valuations as measured by the formula net operating income dividend by the discount rate. It can also signal when to start reinvesting in real estate, because real estate prices are rising, and the ratios are relative low compared to income.Social implicationsThe graphical descriptive depictions seem to suggest that government intervention into the housing market while a spike is forming may not be possible due to the speed with which a spike forms and collapses. Expected income declines would cause the income ratios to change and signal that housing prices will start declining. Both the income and rental ratios in the US housing market have continued to increase since 2008.Originality/valueA consumer sentiment variable was added to the analysis. Prior researchers have suggested adding a consumer sentiment explanatory variable to the model. The results generated for this variable were counterintuitive. The Federal Housing Finance Agency (FHFA) price index results signaled a change during a different year than when the S&P/Case–Shiller Home Price Index is used. Many prior studies used the FHFA price index. They emphasized regulatory issues associated with changing exuberance ratio levels. This case study applies these ideas to measure relative increases in risk, which should impact the discount rate used to estimate the intrinsic value of a residential property.

Are regional house prices stationary in Iran? New evidence using Fourier quantile unit root test

2019 ◽  
Vol 12 (5) ◽  
pp. 849-864
Author(s):  
Arash Hadizadeh
Keyword(s):  
Interest Rates ◽  
Housing Market ◽  
Unit Root ◽  
House Prices ◽  
Housing Prices ◽  
Unit Root Test ◽  
Generalized Least Squares ◽  
Main Concern ◽  
Content Type ◽  
Positive Effects

Purpose In the Iranian economy, investing in the housing market has been very important and beneficial for investors and households, because of inflationary environment, low real interest rates, underdeveloped financial and tax systems and economic sanctions. Hence, prediction of house prices is the main concern of housing market agents in the economy. The purpose of this paper is to test the stationary properties of Iran's provinces to improve the prediction of future housing prices. Design/methodology/approach In this paper, the authors have tested the stationary properties of 20 Iran’s province centers over the period from 1993 to 2017 using a novel Fourier quantile unit root test and conventional ordinary/generalized least squares (O/GLS) linear unit root/stationary tests. Findings According to conventional O/GLS linear unit root/stationary tests, most of the house prices series exhibit random walk behavior, whereas by applying the Fourier quantile unit root test, the null hypothesis of unit root is rejected for 15 out of 20 series. Other results indicated that house prices of cities responded differently to positive and negative shocks. Originality/value Previous studies only addressed conventional OLS or GLS linear unit root or stationary tests, but novel Fourier quantile unit root test was not used. New results were obtained based on this unit root test, that, as a priori knowledge, will help benefiting from the positive effects, or avoiding being victimized by the negative effects.

The effects of political, economic and financial components of country risk on housing prices in South Africa

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Paul-Francois Muzindutsi ◽  
Sanelisiwe Jamile ◽  
Nqubeko Zibani ◽  
Adefemi A. Obalade
Keyword(s):  
Risk Factors ◽  
South Africa ◽  
Housing Market ◽  
Time Series Data ◽  
Housing Prices ◽  
Political Risk ◽  
Country Risk ◽  
Series Data ◽  
Content Type ◽  
Short Run

Purpose The housing market in South Africa has the potential to drive economic growth and attract foreign investment, but it can be affected by various risk factors. This paper aims to conduct an empirical analysis of the effect of country risk components on the housing market in South Africa. Design/methodology/approach Linear and nonlinear autoregressive distributed lag (ARDL) models were used to evaluate the effects of the economic, financial and political risk factors of country risk on the prices of different segments of houses based on 276 monthly time-series data from January1995 to December 2015. Findings First, the results established that the three housing indices were more sensitive to political risk in the long run. Second, short run results showed that the three housing indices were largely influenced by their own preceding adjustments in the short run albeit minimal influences from political risk. Third, large housing segments indicated a higher magnitude of the country risk effect in South Africa. Originality/value This paper concluded that the response of housing prices to changes in the country risk components differed across the three segments of the housing market in South Africa. Consequently, this study presented the first comparison of the reactions of different housing segments to different components country risk.

scholarly journals Untangling the nonlinear “knots” of UK’s housing prices

2019 ◽  
Vol 46 (5) ◽  
pp. 1083-1103
Author(s):  
Constantinos Alexiou ◽  
Sofoklis Vogiazas
Keyword(s):  
Housing Market ◽  
House Prices ◽  
Housing Prices ◽  
Positive Association ◽  
Research Area ◽  
Content Type ◽  
Nonlinear Ardl ◽  
Long Run ◽  
Short Run ◽  
The Uk

Purpose Housing prices in the UK offer an inspiring, yet a complex and under-explored research area. The purpose of this paper is to investigate the critical factors that affect UK’s housing prices. Design/methodology/approach The authors utilize the recently developed nonlinear ARDL approach of Shin et al. (2014) over the period 1969–2016. Findings The authors find that both the long-run and short-run impact of the price-to-rent (PTR) ratio and credit-to-GDP ratio on house prices (HP) is asymmetric whilst ambiguous results are established for mortgage rates, industrial production and equities. Apart from the novel framework of analysis, this study also establishes a positive association between HP and the PTR ratio which suggests a speculative behaviour and could imply the formation of a housing bubble. Originality/value It is the first study for the UK housing market that explores the underlying fundamental relationships by looking at nonlinearities hence, allowing HP to be tied by asymmetric relationships in the long as well as in the short run. Modelling the inherent nonlinearities enhances significantly the understanding of UK housing market which can prove useful for policymaking and forecasting purposes.

Long-run drivers and integration in interprovincial Canadian housing price relations

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Vijay Kumar Vishwakarma
Keyword(s):  
Housing Market ◽  
Granger Causality ◽  
Global Financial Crisis ◽  
Housing Prices ◽  
Housing Price ◽  
Housing Markets ◽  
Content Type ◽  
Stochastic Trend ◽  
Long Run ◽  
Long Run Equilibrium

Purpose This paper aims to examine the integration of housing markets in Canada by examining housing price data (1999–2016) of six metropolitan areas in different provinces, namely, Calgary, Vancouver, Winnipeg, Toronto, Montreal and Halifax. The authors test for cointegration, driver cities of long-run relationships, long-run Granger causality and instantaneous causality in light of the global financial crisis (GFC) (2007–2008). Design/methodology/approach The authors use Johansen’s system cointegration approach with structural breaks. Moving average representation is used for common stochastic trend(s) analysis. Finally, the authors apply vector error correction model-based Granger causality and instantaneous causality. Findings Cities’ housing prices are in long-run equilibrium. Post-crisis Canadian housing markets became more integrated. The Calgary, Vancouver, Toronto and Montreal markets drive the Canadian housing market, leading all cities toward long-run equilibrium. Strong long-run Granger causality exists, but the authors observe no instantaneous causality. Price information takes time to disseminate, and long-run price adjustments play a significant role in causation. Practical implications The findings of cointegration increasing after the GFC and strong lead–lag can be used by investors to arbitrage and optimize portfolios. This can also help national and local policymakers in mitigating risk. Incorporating these findings can lead to better price forecasting. Originality/value This study presents many novelties for the Canadian housing market: it is the first to use repeat-sales regional pricing indices to test long-run behaviors, conduct common stochastic trend analyzes and present causality relations.

New housing supply and price reactions: evidence from Spanish markets

2014 ◽  
Vol 7 (1) ◽  
pp. 4-28 ◽  
Author(s):  
Paloma Taltavull de la Paz
Keyword(s):  
Housing Market ◽  
Explanatory Power ◽  
Housing Prices ◽  
Model Parameters ◽  
Credit Crunch ◽  
Housing Supply ◽  
Recursive Procedure ◽  
Content Type ◽  
Spanish Regions ◽  
The Impact

Purpose – The paper develops a housing model equation for Spain and selected regions to estimate new supply elasticity. The aim of the paper is to assess the role of housing supply on price evolution and explain the fall in housing starts since the start of the credit crunch. Design/methodology/approach – The paper uses a pooled EGLS specification controlling for the presence of cross-section heteroskedasticity. Fixed effect estimators are calculated to capture regional heterogeneity. The model uses secondary data (quarterly) for 17 Spanish regions over the period 1990-2012. A recursive procedure is applied to estimate model parameters starting with a baseline model (1990-1999) and successively adding one-year time information. Elasticities, as well as explanatory power from models, are reported and jointly analyzed. Elasticity is interpreted as the extent to which market mechanisms drive developer responses. Findings – Elasticities of new supply are shown to be very stable during all periods but characterized by differences in response at a regional level. Elasticity ranges from 0.8 to 1.3 across regions. The model reports a non-market-oriented mechanism that guides building decisions. The credit crunch and debt crisis have had a double negative effect capturing the cumulative effect of exogenous shocks. Research limitations/implications – Elastic responses restrained the effects of over-pricing in the period of strong demand pressures in the early 2000s. Changes in elasticity parameters over time suggest that long-term elasticity in housing supply depends on the specific region analyzed. The results show that the credit crunch shock had varying degrees of severity in Spanish regions, dramatically reducing house-building because of the high sensitivity to changes in prices. Practical implications – Estimated elasticity may be used to forecast responses to changes in housing prices. The results add to the understanding of the equilibrium mechanism in the housing market across regions. Originality/value – This is the first article that analyses housing supply, calculates supply elasticities and measures the impact of the credit crunch on the housing market from the supply side in Spain. The paper adds evidence to the debate concerning the equilibrium mechanism in the housing market.

Housing prices and expectations: a study of Auckland

2020 ◽  
Vol 13 (4) ◽  
pp. 601-616
Author(s):  
Yang Yang ◽  
Mingquan Zhou ◽  
Michael Rehm
Keyword(s):  
Housing Market ◽  
Housing Prices ◽  
Content Type ◽  
Vector Error Correction ◽  
Model Based ◽  
Feedback Cycle ◽  
Vector Error ◽  
Causality Tests ◽  
Vector Error Correction Models ◽  
The Relationship

Purpose The purpose of this paper is twofold. First, the study aims to test whether expectations are adaptive in the Auckland housing market. The second purpose is to examine the interplay between expectations and Auckland housing prices. Design/methodology/approach In this study, two vector error correction models (VECM) are built: one VECM includes survey-based expectations and another one encompasses model-based expectations with the assumption that property investors’ expectations are adaptive. The paper goes on by comparing and examining the results of Granger causality tests and impulse response analyses. Findings The findings reveal that Auckland property buyers’ expectations are adaptive. In addition, this study provides some evidence of a feedback cycle between Auckland housing prices and expectations. Research limitations/implications This study posits that Auckland property buyers’ expectations in the next 12 months are based on three-year price movements with more emphasis being placed on recent price history. This assumption may not be an accurate reflection of true expectations. Practical implications This paper helps policymakers to deepen their understanding of Auckland property buyers by showing that their expectations form through the extrapolation of the past price trend. Originality/value The study possibly marks the first attempt to test and compare the relationship between housing prices and two forms of expectations: survey-based and model-based. Additionally, this study is probably the first one that empirically examines whether there is a feedback cycle between expectations and property prices in the Auckland housing market.

Comparison of the property practitioners and consumer preferences on housing prices in the Jakarta metropolitan region

2015 ◽  
Vol 8 (3) ◽  
pp. 335-358 ◽  
Author(s):  
Raden Aswin Rahadi ◽  
Sudarso Kaderi Wiryono ◽  
Deddy Priatmodjo Koesrindartoto ◽  
Indra Budiman Syamwil
Keyword(s):  
Design Methodology ◽  
Consumer Preferences ◽  
Descriptive Analysis ◽  
Housing Prices ◽  
Principal Component ◽  
Correlation Study ◽  
Metropolitan Region ◽  
Content Type ◽  
Housing Attributes ◽  
Residential Consumers

Purpose – The purpose of this paper is to compare the different preferences between property practitioners and residential consumers on housing prices in the Jakarta Metropolitan Region. Design/methodology/approach – The Jakarta Metropolitan Region as the largest metropolitan city in Indonesia was selected as the main sample city for this study. This study comprises 134 respondents from property practitioners and 277 respondents from residential consumers. Data were collected from all regions in Jakarta Metropolitan Region and their respective satellite cities. Descriptive analysis, the correlation study, Wilcoxon t-test and principal component analysis were used to compare the findings between each group’s preferences on housing attributes. Findings – The results of this research provide an analysis on the different decisive attributes for each group, disparities on the correlation between attributes in housing consumers and property practitioners and disagreements among each group on the attribute preferences influencing housing prices in the Jakarta Metropolitan Region. Research limitations/implications – In conclusion, the study provides valid and dependable evidence on different consumers and property practitioners attribute preferences for housing products in the Jakarta Metropolitan Region. Originality/value – This research is the first to compare the attribute preferences for housing products between housing consumers and property practitioners in Indonesia. In addition, this study is one of the first to reaffirm preference attributes influencing housing product prices in Indonesia.

scholarly journals The sources of house price change: identifying liquidity shocks to the housing market

2016 ◽  
Vol 9 (1) ◽  
pp. 98-120 ◽  
Author(s):  
Paloma Taltavull de La Paz ◽  
Michael White
Keyword(s):  
Monetary Policy ◽  
Housing Market ◽  
Error Correction ◽  
House Prices ◽  
Price Change ◽  
Housing Prices ◽  
House Price ◽  
Content Type ◽  
The Uk

Purpose The purpose of this paper is to examine the role of monetary liquidity in house price evolution through examining the Asset (housing) Inflation channel. It identifies the main channels of transmission affecting house prices from monetary supply channels to house price change, examining how the Asset Price channel transmits changes in M1 to housing prices in Spain and the UK. Design/methodology/approach The paper uses Vector Auto Regression (VAR) and Error Correction models to test the Asset Inflation channel in the UK and Spain from 1991 to 2013 in two steps. In the first step, the supply elasticity is estimated through the long-term relationship between house prices and stock supply. The second step estimates a Vector Error Correction (VEC) to explain house price dynamics conditioned on supply reactions. The latter is defined as a long-term inverse demand model where housing prices are controlled by fundamentals in each market. Models allow forecast testing using Choleski impulse responses methodology. Findings Several results are found. In the supply model, both countries show rapid convergence to equilibrium with a larger elasticity of supply in Spain than in the UK but with a short run effect of new supply on prices in the UK. Regarding the Asset Inflation Channel model, the paper finds evidence of the existence of a housing accelerator effect in Spain, but not in the UK where changes in liquidity fully impact house prices in one direction. Research limitations/implications Implications of findings are mainly to forecast the effects of Monetary Policy measures in different economies. Practical implications The model supports the evaluation of different impacts of monetary policy in territories. It shows that the same policy will have different impacts in different housing markets and therefore highlights the importance of examining each market separately to identify the appropriate policy interventions. Originality/value This is the first paper that estimates the impact of the Asset Inflation Channel on house prices that endogenises housing market conditions and compares effects and interrelationships in two different economies.

scholarly journals A hedonic model of the association between grocery brand provision and residential rental prices in England

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Stephen Clark ◽  
Nick Hood ◽  
Mark Birkin
Keyword(s):  
Housing Market ◽  
Consumer Choice ◽  
Service Provision ◽  
Hedonic Model ◽  
Property Market ◽  
Content Type ◽  
Highly Sensitive ◽  
Data Source ◽  
Retail Grocery ◽  
Web Platform

Purpose This study aims to measure the association between local retail grocery provision and private residential rental prices in England. Renting is an important sector of the housing market in England and local grocery provision is an important aspect of service provision and consumers are known to be highly sensitive to the branding of this type of retailing. Design/methodology/approach This research uses a novel data source from a property rental Web platform to estimate a hedonic model for the rental market. These models incorporate information on the nature of the properties and their neighbourhoods, with an emphasis on how different retail brands are associated with rental prices. This retail brand is captured on two scales: the provision of local branded convenience stores and the provision of larger stores. Findings The study finds clear differentials in how the local grocery brand is associated with rental prices. When controlling for commonly explored confounding factors, “Luxury” retailers such as Waitrose and Marks and Spencer are associated with higher rental prices, while “Discounter” retailers are associated with lower rental prices. This finding has many implications, particularly in relation to potential price changes in an already challenging housing market for many people. Research limitations/implications This is an observational study and as such only associations (not causation) can be implied by these findings. Originality/value The focus of this research is on the private residential property market, an important market in England but one that has enjoyed less scrutiny than the sales or socially rented markets. Rather than using general accessibility to retail, this research has differentiated the association by the retail brand and store size, two very important aspects of consumer choice.

Sign in / Sign up

Export Citation Format

Share Document