Editorial: IJHMA 17.5 editorial

• Date: 13 August 2024
• Pages: 1125-1128
• DOI: https://doi.org/10.1108/IJHMA-09-2024-189
• Published date: 13 August 2024
• Subject Matter: Property management & built environment,Real estate & property,Housing markets
• Author: Richard Reed

Editorial: IJHMA 17.5 editorial

Welcome to the f‌ifth issue in the 17th volume of the International Journal of Housing

Markets and Analysis. Being editor for this publication since the very f‌irst issue it has been

evident that the scope and depthof research into housing markets has continued to evolve in

this journal to a higher standard.This issue supports this view. Housing is consistentlytaking

the centre stage in global economic discussions and is proudly viewed as the largest capital

global investment in the property market. Other critical issues of high relevance continue to

include housing affordabilityand tenure options. These 10 research papers have been double

blind refereed to ensure the highest quality and effective contribution to knowledge. This

journal encourages the publication of research which is new and innovative as well was

though provoking and pushing research boundaries. This issue highlights the inclusion of

both developed and developingcountries as well as diverse research methodologies.

The f‌irst paper from Malaysia uses a lifetime income measure to evaluate the long-run

housing affordability for four housing types across geographic locations and income

distributions. The methodology is based on calculating a long-run housing affordability

index (HAI) using data on house prices and householdincomes. A ratio of predicted lifetime

incomes to house prices, the HAI, is computed for four common housing types insix states.

The HAI is also compared across four income percentiles. The f‌indings identify varying

patterns of housing affordability between different states. Notably the level of housing

affordability has declined since 2010 with most housing types being unaffordable for

millennial-led householdsassociated with the lowest income. Housing is most affordable for

those in the highest incomebracket although there were also pockets of unaffordablehousing

observed.

The second paper from Australia acknowledges that house price f‌luctuations send vital

signals to many parts of the economy where long-term predictions of house prices are of

great interest to stakeholders including governments and property developers. Although

predictive models based on economic fundamentals are widely used, the common

requirement for such studies is that underlying data are stationary. This paper demonstrates

the usefulness of alternative f‌ilteringmethods for forecasting house prices. The methodology

is based on exponential smoothing with trend adjustment and multiplicative decomposition

using median house prices. The model performance is evaluated using out-of-sample

forecasting techniques. The f‌indings conf‌irmthat multiplicative decomposition outperforms

exponential smoothing in relation to forecasting accuracy. The superior decomposition

model suggests that seasonal and cyclical components provide important additional

information for predictinghouse prices. Overall, the paper demonstratedthat f‌iltering models

are simple (univariate models that only require historical house prices), easy to implement

(with no condition of stationarity)and also are used widely in f‌inancial trading, sports betting

and other f‌ields where producing accurate forecasts is more important than explaining the

drivers of change.

The third paper from Mauritius is based on the premise that the residential real estate

sector has received an increase in foreign investment over past decades. This study

investigates if the increasing level of foreign real estate investments (FREI) has increased

land demand and land prices. The study also aims to depict whether the relation between

FREI and land prices prevails at an aggregate and/or a regional level. The methodology

examines data from 26 regions (based on the classif‌ications of urban, rural or coastal) and

analysed via a dynamic panel regression framework, namely, an autoregressive distributed

International

Journal of

Housing Markets

and Analysis

1125

InternationalJournal of Housing

Marketsand Analysis

Vol.17 No. 5, 2024

pp. 1125-1128

© Emerald Publishing Limited

1753-8270

DOI 10.1108/IJHMA-09-2024-189