Pub Date : 2024-01-09DOI: 10.1108/ijhma-09-2023-0120
Visar Hoxha
Purpose The purpose of this study is to carry out a comparative analysis of four machine learning models such as linear regression, decision trees, k-nearest neighbors and support vector regression in predicting housing prices in Prishtina. Design/methodology/approach Using Python, the models were assessed on a data set of 1,512 property transactions with mean squared error, coefficient of determination, mean absolute error and root mean squared error as metrics. The study also conducts variable importance test. Findings Upon preprocessing and standardization of the data, the models were trained and tested, with the decision tree model producing the best performance. The variable importance test found the distance from central business district and distance to the road leading to central business district as the most relevant drivers of housing prices across all models, with the exception of support vector machine model, which showed minimal importance for all variables. Originality/value To the best of the author’s knowledge, the originality of this research rests in its methodological approach and emphasis on Prishtina's real estate market, which has never been studied in this context, and its findings may be generalizable to comparable transitional economies with booming real estate sector like Kosovo.
{"title":"Comparative analysis of machine learning models in predicting housing prices: a case study of Prishtina's real estate market","authors":"Visar Hoxha","doi":"10.1108/ijhma-09-2023-0120","DOIUrl":"https://doi.org/10.1108/ijhma-09-2023-0120","url":null,"abstract":"\u0000Purpose\u0000The purpose of this study is to carry out a comparative analysis of four machine learning models such as linear regression, decision trees, k-nearest neighbors and support vector regression in predicting housing prices in Prishtina.\u0000\u0000\u0000Design/methodology/approach\u0000Using Python, the models were assessed on a data set of 1,512 property transactions with mean squared error, coefficient of determination, mean absolute error and root mean squared error as metrics. The study also conducts variable importance test.\u0000\u0000\u0000Findings\u0000Upon preprocessing and standardization of the data, the models were trained and tested, with the decision tree model producing the best performance. The variable importance test found the distance from central business district and distance to the road leading to central business district as the most relevant drivers of housing prices across all models, with the exception of support vector machine model, which showed minimal importance for all variables.\u0000\u0000\u0000Originality/value\u0000To the best of the author’s knowledge, the originality of this research rests in its methodological approach and emphasis on Prishtina's real estate market, which has never been studied in this context, and its findings may be generalizable to comparable transitional economies with booming real estate sector like Kosovo.\u0000","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":"48 8","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139380062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-08DOI: 10.1108/ijhma-10-2023-0142
Deevarshan Naidoo, P. Moores-Pitt, J. Akande
Purpose Understanding which market to invest in for a well-diversified portfolio is fundamental in economies that are highly vulnerable to fluctuations in exchange rates. Extant literature that has considered phenomenon hardly juxtapose the markets. The purpose of this study is to examine the effects of exchange rate volatility on the Stock and Real Estate market of South Africa. The essence is to determine whether the fluctuations in the exchange rate influence the markets prices differently. Design/methodology/approach The Generalised Autoregressive Conditional Heteroskedasticity [GARCH (1.1)] model was used in establishing the effect of exchange rate volatility on both markets. This study used monthly South African data between 2000 and 2020. Findings The results of this study showed that increased exchange rate volatility increases stock market volatility but decreases real-estate market volatility, both of which revealed weak influences from the exchange rates volatility. Practical implications This study has implication for policy in using the exchange rate as a policy tool to attract foreign portfolio investment. The weak volatility transmission from the exchange rate market to the stock and real estate market indicates that there is prospect for foreign investors to diversify their investments in these two markets. Originality/value This study investigated which of the assets market, stock or housing market do better in volatile exchange rate conditions in South Africa.
{"title":"The exchange rates volatilities impact on the stock and real estate markets in South Africa","authors":"Deevarshan Naidoo, P. Moores-Pitt, J. Akande","doi":"10.1108/ijhma-10-2023-0142","DOIUrl":"https://doi.org/10.1108/ijhma-10-2023-0142","url":null,"abstract":"\u0000Purpose\u0000Understanding which market to invest in for a well-diversified portfolio is fundamental in economies that are highly vulnerable to fluctuations in exchange rates. Extant literature that has considered phenomenon hardly juxtapose the markets. The purpose of this study is to examine the effects of exchange rate volatility on the Stock and Real Estate market of South Africa. The essence is to determine whether the fluctuations in the exchange rate influence the markets prices differently.\u0000\u0000\u0000Design/methodology/approach\u0000The Generalised Autoregressive Conditional Heteroskedasticity [GARCH (1.1)] model was used in establishing the effect of exchange rate volatility on both markets. This study used monthly South African data between 2000 and 2020.\u0000\u0000\u0000Findings\u0000The results of this study showed that increased exchange rate volatility increases stock market volatility but decreases real-estate market volatility, both of which revealed weak influences from the exchange rates volatility.\u0000\u0000\u0000Practical implications\u0000This study has implication for policy in using the exchange rate as a policy tool to attract foreign portfolio investment. The weak volatility transmission from the exchange rate market to the stock and real estate market indicates that there is prospect for foreign investors to diversify their investments in these two markets.\u0000\u0000\u0000Originality/value\u0000This study investigated which of the assets market, stock or housing market do better in volatile exchange rate conditions in South Africa.\u0000","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":"12 3","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139380193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-29DOI: 10.1108/ijhma-09-2023-0124
P. Rao, Arindam Biswas
Purpose This study aims to assess housing affordability and estimate demand using a hedonic regression model in the context of Lucknow city, India. This study assesses housing affordability by considering various housing and household-related variables. This study focuses on the impoverished urban population, as they experience the most severe housing scarcity. This study’s primary objective is to understand the demand dynamics within the market comprehensively. An understanding of housing demand can be achieved through an examination of its characteristics and components. Individuals consider the implicit values associated with various components when deciding to purchase or rent a home. The components and characteristics have been obtained from variables relating to housing and households. Design/methodology/approach A socioeconomic survey was conducted for 450 households from slums in Lucknow city. Two-stage regression models were developed for this research paper. A hedonic price index was prepared for the first model to understand the relationship between housing expenditure and various housing characteristics. The housing characteristics considered for the hedonic model are dwelling unit size, typology, condition, amenities and infrastructure. In the second stage, a regression model is created between household characteristics. The household characteristics considered for the demand estimation model are household size, age, education, social category, income, nonhousing expenditure, migration and overcrowding. Findings Based on the findings of regression model results, it is evident that the hedonic model is an effective tool for the estimation of housing affordability and housing demand for urban poor. Various housing and household-related variables affect housing expenditure positively or negatively. The two-stage hedonic regression model can define willingness to pay for a particular set of housing with various attributes of a particular household. The results show the significance of dwelling unit size, quality and amenities (R2 > 0.9, p < 0.05) for rent/imputed rent. The demand function shows that income has a direct effect, whereas other variables have mixed effects. Research limitations/implications This study is case-specific and uses a data set generated from a primary survey. Although household surveys for a large sample size are resource-intensive exercises, they provide an opportunity to exploit microdata for a better understanding of the complex housing situation in slums. Practical implications All the stakeholders can use the findings to create an effective housing policy. The variables that are statistically significant and have a positive relationship with housing costs should be deliberated upon to provide the basic standard of living for the urban poor. The formulation of policies should duly include the housing preferences of the economically disadvantaged population residing in slum areas. Originality/value Th
{"title":"Housing affordability and housing demand assessment for urban poor in India using the hedonic model","authors":"P. Rao, Arindam Biswas","doi":"10.1108/ijhma-09-2023-0124","DOIUrl":"https://doi.org/10.1108/ijhma-09-2023-0124","url":null,"abstract":"Purpose This study aims to assess housing affordability and estimate demand using a hedonic regression model in the context of Lucknow city, India. This study assesses housing affordability by considering various housing and household-related variables. This study focuses on the impoverished urban population, as they experience the most severe housing scarcity. This study’s primary objective is to understand the demand dynamics within the market comprehensively. An understanding of housing demand can be achieved through an examination of its characteristics and components. Individuals consider the implicit values associated with various components when deciding to purchase or rent a home. The components and characteristics have been obtained from variables relating to housing and households. Design/methodology/approach A socioeconomic survey was conducted for 450 households from slums in Lucknow city. Two-stage regression models were developed for this research paper. A hedonic price index was prepared for the first model to understand the relationship between housing expenditure and various housing characteristics. The housing characteristics considered for the hedonic model are dwelling unit size, typology, condition, amenities and infrastructure. In the second stage, a regression model is created between household characteristics. The household characteristics considered for the demand estimation model are household size, age, education, social category, income, nonhousing expenditure, migration and overcrowding. Findings Based on the findings of regression model results, it is evident that the hedonic model is an effective tool for the estimation of housing affordability and housing demand for urban poor. Various housing and household-related variables affect housing expenditure positively or negatively. The two-stage hedonic regression model can define willingness to pay for a particular set of housing with various attributes of a particular household. The results show the significance of dwelling unit size, quality and amenities (R2 > 0.9, p < 0.05) for rent/imputed rent. The demand function shows that income has a direct effect, whereas other variables have mixed effects. Research limitations/implications This study is case-specific and uses a data set generated from a primary survey. Although household surveys for a large sample size are resource-intensive exercises, they provide an opportunity to exploit microdata for a better understanding of the complex housing situation in slums. Practical implications All the stakeholders can use the findings to create an effective housing policy. The variables that are statistically significant and have a positive relationship with housing costs should be deliberated upon to provide the basic standard of living for the urban poor. The formulation of policies should duly include the housing preferences of the economically disadvantaged population residing in slum areas. Originality/value Th","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":"30 4","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139147659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-12DOI: 10.1108/ijhma-09-2023-0126
R. Mwanyepedza, Syden Mishi
Purpose The study aims to estimate the short- and long-run effects of monetary policy on residential property prices in South Africa. Over the past decades, there has been a monetary policy shift, from targeting money supply and exchange rate to inflation. The shifts have affected residential property market dynamics. Design/methodology/approach The Johansen cointegration approach was used to estimate the effects of changes in monetary policy proxies on residential property prices using quarterly data from 1980 to 2022. Findings Mortgage finance and economic growth have a significant positive long-run effect on residential property prices. The consumer price index, the inflation targeting framework, interest rates and exchange rates have a significant negative long-run effect on residential property prices. The Granger causality test has depicted that exchange rate significantly influences residential property prices in the short run, and interest rates, inflation targeting framework, gross domestic product, money supply consumer price index and exchange rate can quickly return to equilibrium when they are in disequilibrium. Originality/value There are limited arguments whether the inflation targeting monetary policy framework in South Africa has prevented residential property market boom and bust scenarios. The study has found that the implementation of inflation targeting framework has successfully reduced booms in residential property prices in South Africa.
{"title":"Short-run dynamics and long-run effects of monetary policy on residential property prices in South Africa","authors":"R. Mwanyepedza, Syden Mishi","doi":"10.1108/ijhma-09-2023-0126","DOIUrl":"https://doi.org/10.1108/ijhma-09-2023-0126","url":null,"abstract":"\u0000Purpose\u0000The study aims to estimate the short- and long-run effects of monetary policy on residential property prices in South Africa. Over the past decades, there has been a monetary policy shift, from targeting money supply and exchange rate to inflation. The shifts have affected residential property market dynamics.\u0000\u0000\u0000Design/methodology/approach\u0000The Johansen cointegration approach was used to estimate the effects of changes in monetary policy proxies on residential property prices using quarterly data from 1980 to 2022.\u0000\u0000\u0000Findings\u0000Mortgage finance and economic growth have a significant positive long-run effect on residential property prices. The consumer price index, the inflation targeting framework, interest rates and exchange rates have a significant negative long-run effect on residential property prices. The Granger causality test has depicted that exchange rate significantly influences residential property prices in the short run, and interest rates, inflation targeting framework, gross domestic product, money supply consumer price index and exchange rate can quickly return to equilibrium when they are in disequilibrium.\u0000\u0000\u0000Originality/value\u0000There are limited arguments whether the inflation targeting monetary policy framework in South Africa has prevented residential property market boom and bust scenarios. The study has found that the implementation of inflation targeting framework has successfully reduced booms in residential property prices in South Africa.\u0000","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":"52 11","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139007062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-06DOI: 10.1108/ijhma-09-2023-0125
Z. G. Büyükkara, İsmail Cem Özgüler, Ali Hepşen
Purpose The purpose of this study is to explore the intricate relationship between oil prices, house prices in the UK and Norway, and the mediating role of gold and stock prices in both the short- and long-term, unraveling these complex linkages by employing an empirical approach. Design/methodology/approach This study benefits from a comprehensive set of econometric tools, including a multiequation vector autoregressive (VAR) system, Granger causality test, impulse response function, variance decomposition and a single-equation autoregressive distributed lag (ARDL) system. This rigorous approach enables to identify both short- and long-run dynamics to unravel the intricate linkages between Brent oil prices, housing prices, gold prices and stock prices in the UK and Norway over the period from 2005:Q1 to 2022:Q2. Findings The findings indicate that rising oil prices negatively impact house prices, whereas the positive influence of stock market performance on housing is more pronounced. A two-way causal relationship exists between stock market indices and house prices, whereas a one-way causal relationship exists from crude oil prices to house prices in both countries. The VAR model reveals that past housing prices, stock market indices in each country and Brent oil prices are the primary determinants of current housing prices. The single-equation ARDL results for housing prices demonstrate the existence of a long-run cointegrating relationship between real estate and stock prices. The variance decomposition analysis indicates that oil prices have a more pronounced impact on housing prices compared with stock prices. The findings reveal that shocks in stock markets have a greater influence on housing market prices than those in oil or gold prices. Consequently, house prices exhibit a stronger reaction to general financial market indicators than to commodity prices. Research limitations/implications This study may have several limitations. First, the model does not include all relevant macroeconomic variables, such as interest rates, unemployment rates and gross domestic product growth. This omission may affect the accuracy of the model’s predictions and lead to inefficiencies in the real estate market. Second, this study does not consider alternative explanations for market inefficiencies, such as behavioral finance factors, information asymmetry or market microstructure effects. Third, the models have limitations in revealing how predictors react to positive and negative shocks. Therefore, the results of this study should be interpreted with caution. Practical implications These findings hold significant implications for formulating dynamic policies aimed at stabilizing the housing markets of these two oil-producing nations. The practical implications of this study extend to academics, investors and policymakers, particularly in light of the volatility characterizing both housing and commodity markets. The findings reveal that shocks in
{"title":"Relationship between housing, oil, gold and stock markets: evidence from UK and Norway","authors":"Z. G. Büyükkara, İsmail Cem Özgüler, Ali Hepşen","doi":"10.1108/ijhma-09-2023-0125","DOIUrl":"https://doi.org/10.1108/ijhma-09-2023-0125","url":null,"abstract":"\u0000Purpose\u0000The purpose of this study is to explore the intricate relationship between oil prices, house prices in the UK and Norway, and the mediating role of gold and stock prices in both the short- and long-term, unraveling these complex linkages by employing an empirical approach.\u0000\u0000\u0000Design/methodology/approach\u0000This study benefits from a comprehensive set of econometric tools, including a multiequation vector autoregressive (VAR) system, Granger causality test, impulse response function, variance decomposition and a single-equation autoregressive distributed lag (ARDL) system. This rigorous approach enables to identify both short- and long-run dynamics to unravel the intricate linkages between Brent oil prices, housing prices, gold prices and stock prices in the UK and Norway over the period from 2005:Q1 to 2022:Q2.\u0000\u0000\u0000Findings\u0000The findings indicate that rising oil prices negatively impact house prices, whereas the positive influence of stock market performance on housing is more pronounced. A two-way causal relationship exists between stock market indices and house prices, whereas a one-way causal relationship exists from crude oil prices to house prices in both countries. The VAR model reveals that past housing prices, stock market indices in each country and Brent oil prices are the primary determinants of current housing prices. The single-equation ARDL results for housing prices demonstrate the existence of a long-run cointegrating relationship between real estate and stock prices. The variance decomposition analysis indicates that oil prices have a more pronounced impact on housing prices compared with stock prices. The findings reveal that shocks in stock markets have a greater influence on housing market prices than those in oil or gold prices. Consequently, house prices exhibit a stronger reaction to general financial market indicators than to commodity prices.\u0000\u0000\u0000Research limitations/implications\u0000This study may have several limitations. First, the model does not include all relevant macroeconomic variables, such as interest rates, unemployment rates and gross domestic product growth. This omission may affect the accuracy of the model’s predictions and lead to inefficiencies in the real estate market. Second, this study does not consider alternative explanations for market inefficiencies, such as behavioral finance factors, information asymmetry or market microstructure effects. Third, the models have limitations in revealing how predictors react to positive and negative shocks. Therefore, the results of this study should be interpreted with caution.\u0000\u0000\u0000Practical implications\u0000These findings hold significant implications for formulating dynamic policies aimed at stabilizing the housing markets of these two oil-producing nations. The practical implications of this study extend to academics, investors and policymakers, particularly in light of the volatility characterizing both housing and commodity markets. The findings reveal that shocks in ","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":"41 6","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138596390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-04DOI: 10.1108/ijhma-07-2023-0100
S. Low, Li-Ting Neo, W. Choong, Razlin Mansor, Siaw-Chui Wee, Jing-Ying Woon
Purpose The world population over the age of 60 is expected to increase from 900 million in 2015 to two billion by 2050. Retirement homes have emerged as a prominent housing alternative and become a trend for the older adults; however, older population in Malaysia could have a negative view of retirement homes. Different generations could have different perceptions of the value of retirement homes. This study aims to explore the value of retirement homes across diverse age cohorts in Malaysia. Design/methodology/approach A qualitative approach is adopted for this study. Thematic analysis is used to analyse the interview transcripts obtained from semi-structured interviews. Findings The results indicated that baby boomers tend to have more negative values towards retirement homes, whereas Generations X and Y demonstrated more favourable and positive values for retirement homes. Originality/value This study serves as a useful reference for housing developers, policymakers and the management of retirement homes to better understand how different age cohorts value retirement homes, thereby encouraging relevant housing strategies to enhance the quality and support systems of retirement homes in society.
{"title":"Am I being abandoned? The value of retirement homes in Malaysian society","authors":"S. Low, Li-Ting Neo, W. Choong, Razlin Mansor, Siaw-Chui Wee, Jing-Ying Woon","doi":"10.1108/ijhma-07-2023-0100","DOIUrl":"https://doi.org/10.1108/ijhma-07-2023-0100","url":null,"abstract":"\u0000Purpose\u0000The world population over the age of 60 is expected to increase from 900 million in 2015 to two billion by 2050. Retirement homes have emerged as a prominent housing alternative and become a trend for the older adults; however, older population in Malaysia could have a negative view of retirement homes. Different generations could have different perceptions of the value of retirement homes. This study aims to explore the value of retirement homes across diverse age cohorts in Malaysia.\u0000\u0000\u0000Design/methodology/approach\u0000A qualitative approach is adopted for this study. Thematic analysis is used to analyse the interview transcripts obtained from semi-structured interviews.\u0000\u0000\u0000Findings\u0000The results indicated that baby boomers tend to have more negative values towards retirement homes, whereas Generations X and Y demonstrated more favourable and positive values for retirement homes.\u0000\u0000\u0000Originality/value\u0000This study serves as a useful reference for housing developers, policymakers and the management of retirement homes to better understand how different age cohorts value retirement homes, thereby encouraging relevant housing strategies to enhance the quality and support systems of retirement homes in society.\u0000","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":"10 4","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138604390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-21DOI: 10.1108/ijhma-10-2023-0130
Haobo Zou, Mansoora Ahmed, Syed Ali Raza, Rija Anwar
Purpose Monetary policy has major impacts on macroeconomic indicators of the country. Accordingly, uncertainty regarding monetary policy shifts can cause challenges and risks for businesses, financial markets and investors. Thus, the purpose of this study is to investigate how real estate market volatility responds to monetary policy uncertainty. Design/methodology/approach The GARCH-MIDAS model is applied in this study to investigate the nexus between monetary policy uncertainty and real estate market volatility. This model was fundamentally instituted to accommodate low-frequency variables. Findings The results of this study reveal that increased monetary policy uncertainty highly affects the volatility in real estate market during the peak period of COVID-19 as compared to full sample period and COVID-19 recovery period; hence, a significant decline is evident in real estate market volatility during crisis. Originality/value This study is particularly focused on peak and recovery period of COVID-19 considering the geographical region of Greece, Japan and the USA. This study provides a complete perspective on the nexus between monetary policy uncertainty and real estate markets volatility in three distinct economic views.
{"title":"Nexus between monetary policy uncertainty and real estate market volatility in COVID-19 peak and recovery period","authors":"Haobo Zou, Mansoora Ahmed, Syed Ali Raza, Rija Anwar","doi":"10.1108/ijhma-10-2023-0130","DOIUrl":"https://doi.org/10.1108/ijhma-10-2023-0130","url":null,"abstract":"Purpose Monetary policy has major impacts on macroeconomic indicators of the country. Accordingly, uncertainty regarding monetary policy shifts can cause challenges and risks for businesses, financial markets and investors. Thus, the purpose of this study is to investigate how real estate market volatility responds to monetary policy uncertainty. Design/methodology/approach The GARCH-MIDAS model is applied in this study to investigate the nexus between monetary policy uncertainty and real estate market volatility. This model was fundamentally instituted to accommodate low-frequency variables. Findings The results of this study reveal that increased monetary policy uncertainty highly affects the volatility in real estate market during the peak period of COVID-19 as compared to full sample period and COVID-19 recovery period; hence, a significant decline is evident in real estate market volatility during crisis. Originality/value This study is particularly focused on peak and recovery period of COVID-19 considering the geographical region of Greece, Japan and the USA. This study provides a complete perspective on the nexus between monetary policy uncertainty and real estate markets volatility in three distinct economic views.","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":"53 75 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139252733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-16DOI: 10.1108/ijhma-09-2023-0129
Nenavath Sreenu
Purpose This research study aims to delve into the enduring relationship between housing property prices and economic policy uncertainty across eight major Indian cities. Design/methodology/approach Using the panel non-linear autoregressive distributed lag model, this study meticulously investigates the asymmetric impact of economic policy uncertainty on apartment and house (unit) prices in India during the period from 2000 to 2022. Findings The findings of this study indicate that economic policy uncertainty exerts a negative influence on property prices, but noteworthy asymmetry is observed, with positive changes in effect having a more pronounced impact than negative changes. This asymmetrical effect is particularly prominent in the case of unit prices. Originality/value This research reveals that long-run price trends are also influenced by factors such as interest rates, building costs and housing loans. Through a comprehensive analysis of these factors and their interplay with property prices, this research paper contributes valuable insights to the understanding of the real estate market dynamics in Indian cities.
{"title":"Dynamics of property prices and asymmetrical impacts of economic policy uncertainty: new evidence from Indian cities","authors":"Nenavath Sreenu","doi":"10.1108/ijhma-09-2023-0129","DOIUrl":"https://doi.org/10.1108/ijhma-09-2023-0129","url":null,"abstract":"Purpose This research study aims to delve into the enduring relationship between housing property prices and economic policy uncertainty across eight major Indian cities. Design/methodology/approach Using the panel non-linear autoregressive distributed lag model, this study meticulously investigates the asymmetric impact of economic policy uncertainty on apartment and house (unit) prices in India during the period from 2000 to 2022. Findings The findings of this study indicate that economic policy uncertainty exerts a negative influence on property prices, but noteworthy asymmetry is observed, with positive changes in effect having a more pronounced impact than negative changes. This asymmetrical effect is particularly prominent in the case of unit prices. Originality/value This research reveals that long-run price trends are also influenced by factors such as interest rates, building costs and housing loans. Through a comprehensive analysis of these factors and their interplay with property prices, this research paper contributes valuable insights to the understanding of the real estate market dynamics in Indian cities.","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":"3 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136227907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-30DOI: 10.1108/ijhma-07-2023-0095
Junfeng Jiao, Xiaohan Wu, Yefu Chen, Arya Farahi
Purpose By comparing regression models, this study aims to analyze the added home value of green sustainability features and green efficiency characteristics, rather than green certifications, in the city of Austin. Design/methodology/approach The adoption of home green energy efficiency upgrades has emerged as a new trend in the real estate industry, offering several benefits to builders and home buyers. These include tax reductions, health improvements and energy savings. Previous studies have shown that energy-certified single-family homes command a premium in the marketplace. However, the literature is limited in its analysis of the effects of green upgrades and certification on different types of single-family homes. To address this gap, this research collected data from 21,292 multiple listing services (MLS) closed home-selling listings in Austin, Texas, over a period of 35 months. Findings The analysis results showed that green efficiency features could generally increase single-family housing prices by 11.9%, whereas green sustainability upgrades can potentially bring a 11.7% higher selling price. Although green housing certification did not have significant effects on most housing groups, it did increase closing prices by 13.2% for single-family residences sold at the medium price range, which is higher than the impacts from simply listing the green features on MLS. Originality/value The study contributes to the body of knowledge by examining the market value of broadly defined energy efficiency and sustainability features in the residential housing market. The findings can help policymakers, brokerage firms, home builders and owners adjust their policies and strategies related to single-family home sales and mortgage approvals. The research also highlights the potential benefits of capitalizing on green housing features other than certifications.
{"title":"How the single-family residence housing market capitalizes green property upgraded features: evidence from city of Austin","authors":"Junfeng Jiao, Xiaohan Wu, Yefu Chen, Arya Farahi","doi":"10.1108/ijhma-07-2023-0095","DOIUrl":"https://doi.org/10.1108/ijhma-07-2023-0095","url":null,"abstract":"Purpose By comparing regression models, this study aims to analyze the added home value of green sustainability features and green efficiency characteristics, rather than green certifications, in the city of Austin. Design/methodology/approach The adoption of home green energy efficiency upgrades has emerged as a new trend in the real estate industry, offering several benefits to builders and home buyers. These include tax reductions, health improvements and energy savings. Previous studies have shown that energy-certified single-family homes command a premium in the marketplace. However, the literature is limited in its analysis of the effects of green upgrades and certification on different types of single-family homes. To address this gap, this research collected data from 21,292 multiple listing services (MLS) closed home-selling listings in Austin, Texas, over a period of 35 months. Findings The analysis results showed that green efficiency features could generally increase single-family housing prices by 11.9%, whereas green sustainability upgrades can potentially bring a 11.7% higher selling price. Although green housing certification did not have significant effects on most housing groups, it did increase closing prices by 13.2% for single-family residences sold at the medium price range, which is higher than the impacts from simply listing the green features on MLS. Originality/value The study contributes to the body of knowledge by examining the market value of broadly defined energy efficiency and sustainability features in the residential housing market. The findings can help policymakers, brokerage firms, home builders and owners adjust their policies and strategies related to single-family home sales and mortgage approvals. The research also highlights the potential benefits of capitalizing on green housing features other than certifications.","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":"84 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136019144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-24DOI: 10.1108/ijhma-04-2023-0048
Hanudin Amin, Imran Mehboob Shaikh
Purpose This study aims to examine the zakat al-mustaghallat acceptance index (ZAMAi) through the examination of its predictors identified in this work, including attitude, social influence, self-efficacy, amount of information and Islamic altruism, at best. Design/methodology/approach Drawing from the attitude-social influence-self efficacy model, this study evaluated the effects of these factors on ZAMAi using an empirical investigation surveying 184 respondents who were identified as the owners of residential properties in Malaysia. Findings In the core model, this study found significant outcomes for the effects of attitude, social influence, self-efficacy, amount of information and Islamic altruism, along with the demographic items tested. For post hoc analysis, this study found two significant outcomes drawn from the role of attitude as a mediating variable in this study. Research limitations/implications The results obtained from this study should be used with caution owing to its limited applicability and the constraints of subjects and variables in the framework developed. Practical implications The results obtained can become a yardstick to gauge the success of zakat al-mustaghallat acceptance in Malaysia. Originality/value This study introduced new measures of ZAMAi, where Malaysian landlords are brought into play.
{"title":"<i>Zakat al-mustaghallat</i> for Malaysian landlords of residential properties","authors":"Hanudin Amin, Imran Mehboob Shaikh","doi":"10.1108/ijhma-04-2023-0048","DOIUrl":"https://doi.org/10.1108/ijhma-04-2023-0048","url":null,"abstract":"Purpose This study aims to examine the zakat al-mustaghallat acceptance index (ZAMAi) through the examination of its predictors identified in this work, including attitude, social influence, self-efficacy, amount of information and Islamic altruism, at best. Design/methodology/approach Drawing from the attitude-social influence-self efficacy model, this study evaluated the effects of these factors on ZAMAi using an empirical investigation surveying 184 respondents who were identified as the owners of residential properties in Malaysia. Findings In the core model, this study found significant outcomes for the effects of attitude, social influence, self-efficacy, amount of information and Islamic altruism, along with the demographic items tested. For post hoc analysis, this study found two significant outcomes drawn from the role of attitude as a mediating variable in this study. Research limitations/implications The results obtained from this study should be used with caution owing to its limited applicability and the constraints of subjects and variables in the framework developed. Practical implications The results obtained can become a yardstick to gauge the success of zakat al-mustaghallat acceptance in Malaysia. Originality/value This study introduced new measures of ZAMAi, where Malaysian landlords are brought into play.","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135219393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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