Pub Date : 2023-07-12DOI: 10.1108/ijhma-03-2023-0037
Masatomo Suzuki, C. Shimizu
Purpose This study aims to investigate the relationship between market share and rent levels to understand the supply structure in the Japanese private rental housing market. Design/methodology/approach The study calculates the municipal-level market share of a dominant rental housing operator in Japan and ascertained the overall market rent and the dominant operator’s rent premium at the municipal level by using a major web portal’s listing data of rental houses. Findings The study shows that, as market share increased, overall market rent tends to decrease, and analyzed by market share, there is no significant difference between the rent of the dominant operator and the overall market rent. Practical implications The results of the study suggest that dominant operators may have lowered the rent of their own property to prioritize filling vacancies, which, in turn, causes the overall level of market rent to decline. This is an outcome of rental housing operators’ strategy to maximize long-term rental income under sublease contracts with individual owners, which ensures stable rental income for owners regardless of the occupation status of the apartments. Originality/value Previous research on regional monopolies in mortgage sales and brokerage businesses in the USA implies that rental housing operators in a position of great influence over the market can control and keep the market rents at high levels, that is, at large costs for consumers. The findings of the study are novel in showing the inverse relationship in the Japanese private rental market.
{"title":"Relationship between market share and rent level: understanding supply structure in the Japanese private rental housing market","authors":"Masatomo Suzuki, C. Shimizu","doi":"10.1108/ijhma-03-2023-0037","DOIUrl":"https://doi.org/10.1108/ijhma-03-2023-0037","url":null,"abstract":"\u0000Purpose\u0000This study aims to investigate the relationship between market share and rent levels to understand the supply structure in the Japanese private rental housing market.\u0000\u0000\u0000Design/methodology/approach\u0000The study calculates the municipal-level market share of a dominant rental housing operator in Japan and ascertained the overall market rent and the dominant operator’s rent premium at the municipal level by using a major web portal’s listing data of rental houses.\u0000\u0000\u0000Findings\u0000The study shows that, as market share increased, overall market rent tends to decrease, and analyzed by market share, there is no significant difference between the rent of the dominant operator and the overall market rent.\u0000\u0000\u0000Practical implications\u0000The results of the study suggest that dominant operators may have lowered the rent of their own property to prioritize filling vacancies, which, in turn, causes the overall level of market rent to decline. This is an outcome of rental housing operators’ strategy to maximize long-term rental income under sublease contracts with individual owners, which ensures stable rental income for owners regardless of the occupation status of the apartments.\u0000\u0000\u0000Originality/value\u0000Previous research on regional monopolies in mortgage sales and brokerage businesses in the USA implies that rental housing operators in a position of great influence over the market can control and keep the market rents at high levels, that is, at large costs for consumers. The findings of the study are novel in showing the inverse relationship in the Japanese private rental market.\u0000","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44322304","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 : 2023-07-05DOI: 10.1108/ijhma-02-2023-0027
Fredrick Otieno Okuta, T. Kivaa, Raphael M. Kieti, J. O. Okaka
Purpose The housing market in Kenya continues to experience an excessive imbalance between supply and demand. This imbalance renders the housing market volatile, and stakeholders lose repeatedly. The purpose of the study was to forecast housing prices (HPs) in Kenya using simple and complex regression models to assess the best model for projecting the HPs in Kenya. Design/methodology/approach The study used time series data from 1975 to 2020 of the selected macroeconomic factors sourced from Kenya National Bureau of Statistics, Central Bank of Kenya and Hass Consult Limited. Linear regression, multiple regression, autoregressive integrated moving average (ARIMA) and autoregressive distributed lag (ARDL) models regression techniques were used to model HPs. Findings The study concludes that the performance of the housing market is very sensitive to changes in the economic indicators, and therefore, the key players in the housing market should consider the performance of the economy during the project feasibility studies and appraisals. From the results, it can be deduced that complex models outperform simple models in forecasting HPs in Kenya. The vector autoregressive (VAR) model performs the best in forecasting HPs considering its lowest root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and bias proportion coefficient. ARIMA models perform dismally in forecasting HPs, and therefore, we conclude that HP is not a self-projecting variable. Practical implications A model for projecting HPs could be a game changer if applied during the project appraisal stage by the developers and project managers. The study thoroughly compared the various regression models to ascertain the best model for forecasting the prices and revealed that complex models perform better than simple models in forecasting HPs. The study recommends a VAR model in forecasting HPs considering its lowest RMSE, MAE, MAPE and bias proportion coefficient compared to other models. The model, if used in collaboration with the already existing hedonic models, will ensure that the investments in the housing markets are well-informed, and hence, a reduction in economic losses arising from poor market forecasting techniques. However, these study findings are only applicable to the commercial housing market i.e. houses for sale and rent. Originality/value While more research has been done on HP projections, this study was based on a comparison of simple and complex regression models of projecting HPs. A total of five models were compared in the study: the simple regression model, multiple regression model, ARIMA model, ARDL model and VAR model. The findings reveal that complex models outperform simple models in projecting HPs. Nonetheless, the study also used nine macroeconomic indicators in the model-building process. Granger causality test reveals that only household income (HHI), gross domestic product, interest rate, exchange rates (EXC
{"title":"Comparing simple and complex regression models in forecasting housing price: case study from Kenya","authors":"Fredrick Otieno Okuta, T. Kivaa, Raphael M. Kieti, J. O. Okaka","doi":"10.1108/ijhma-02-2023-0027","DOIUrl":"https://doi.org/10.1108/ijhma-02-2023-0027","url":null,"abstract":"\u0000Purpose\u0000The housing market in Kenya continues to experience an excessive imbalance between supply and demand. This imbalance renders the housing market volatile, and stakeholders lose repeatedly. The purpose of the study was to forecast housing prices (HPs) in Kenya using simple and complex regression models to assess the best model for projecting the HPs in Kenya.\u0000\u0000\u0000Design/methodology/approach\u0000The study used time series data from 1975 to 2020 of the selected macroeconomic factors sourced from Kenya National Bureau of Statistics, Central Bank of Kenya and Hass Consult Limited. Linear regression, multiple regression, autoregressive integrated moving average (ARIMA) and autoregressive distributed lag (ARDL) models regression techniques were used to model HPs.\u0000\u0000\u0000Findings\u0000The study concludes that the performance of the housing market is very sensitive to changes in the economic indicators, and therefore, the key players in the housing market should consider the performance of the economy during the project feasibility studies and appraisals. From the results, it can be deduced that complex models outperform simple models in forecasting HPs in Kenya. The vector autoregressive (VAR) model performs the best in forecasting HPs considering its lowest root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and bias proportion coefficient. ARIMA models perform dismally in forecasting HPs, and therefore, we conclude that HP is not a self-projecting variable.\u0000\u0000\u0000Practical implications\u0000A model for projecting HPs could be a game changer if applied during the project appraisal stage by the developers and project managers. The study thoroughly compared the various regression models to ascertain the best model for forecasting the prices and revealed that complex models perform better than simple models in forecasting HPs. The study recommends a VAR model in forecasting HPs considering its lowest RMSE, MAE, MAPE and bias proportion coefficient compared to other models. The model, if used in collaboration with the already existing hedonic models, will ensure that the investments in the housing markets are well-informed, and hence, a reduction in economic losses arising from poor market forecasting techniques. However, these study findings are only applicable to the commercial housing market i.e. houses for sale and rent.\u0000\u0000\u0000Originality/value\u0000While more research has been done on HP projections, this study was based on a comparison of simple and complex regression models of projecting HPs. A total of five models were compared in the study: the simple regression model, multiple regression model, ARIMA model, ARDL model and VAR model. The findings reveal that complex models outperform simple models in projecting HPs. Nonetheless, the study also used nine macroeconomic indicators in the model-building process. Granger causality test reveals that only household income (HHI), gross domestic product, interest rate, exchange rates (EXC","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49172431","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 : 2023-06-26DOI: 10.1108/ijhma-03-2023-0042
Yi Wu, Alan Tidwell, Vivek Sah
Purpose This study aims to examine living preference and tenure among millennials, with a particular focus on the impact of ethnic and cultural diversity on housing outcomes including observed homeownership inequalities. Design/methodology/approach Using the individual panel data from three waves in American Housing Survey, 2015–2019, this study compares the likelihood of co-residing among Asian and Hispanic millennials with non-Hispanic white millennial peers. Furthermore, this study estimates the effect of co-residence on homeownership across generational and ethnic backgrounds. Findings This study finds a preference for coresident adult familial households among foreign-born Asian and Hispanic millennials, and US-born Hispanic millennials when compared to their non-Hispanic white millennial peers. The results are robust after considering neighborhood selection bias, affordability and education. The effect of co-residence on ownership is significant and positive, suggesting this living arrangement contributes to homeownership across all generational and ethnic groups. Practical implications Housebuilders should be aware of Asian and Hispanic millennials’ increased appetite for extended family living arrangements and consider increasing the physical size of affordable or workforce-oriented rental housing and new single family construction to accommodate more adult co-living arrangements. Originality/value This study provides a more comprehensive understanding of the role ethnic and cultural diversity has on millennial adult living preferences and its generational differences, which is not just “boomeranging” as identified by previous literature, contributing to the growing interest in the housing research on the effect of ethnic diversity and culture on millennials’ homeownership rates.
{"title":"Impact of ethnic and cultural diversity on millennial living preferences and homeownership","authors":"Yi Wu, Alan Tidwell, Vivek Sah","doi":"10.1108/ijhma-03-2023-0042","DOIUrl":"https://doi.org/10.1108/ijhma-03-2023-0042","url":null,"abstract":"\u0000Purpose\u0000This study aims to examine living preference and tenure among millennials, with a particular focus on the impact of ethnic and cultural diversity on housing outcomes including observed homeownership inequalities.\u0000\u0000\u0000Design/methodology/approach\u0000Using the individual panel data from three waves in American Housing Survey, 2015–2019, this study compares the likelihood of co-residing among Asian and Hispanic millennials with non-Hispanic white millennial peers. Furthermore, this study estimates the effect of co-residence on homeownership across generational and ethnic backgrounds.\u0000\u0000\u0000Findings\u0000This study finds a preference for coresident adult familial households among foreign-born Asian and Hispanic millennials, and US-born Hispanic millennials when compared to their non-Hispanic white millennial peers. The results are robust after considering neighborhood selection bias, affordability and education. The effect of co-residence on ownership is significant and positive, suggesting this living arrangement contributes to homeownership across all generational and ethnic groups.\u0000\u0000\u0000Practical implications\u0000Housebuilders should be aware of Asian and Hispanic millennials’ increased appetite for extended family living arrangements and consider increasing the physical size of affordable or workforce-oriented rental housing and new single family construction to accommodate more adult co-living arrangements.\u0000\u0000\u0000Originality/value\u0000This study provides a more comprehensive understanding of the role ethnic and cultural diversity has on millennial adult living preferences and its generational differences, which is not just “boomeranging” as identified by previous literature, contributing to the growing interest in the housing research on the effect of ethnic diversity and culture on millennials’ homeownership rates.\u0000","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42696474","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 : 2023-06-20DOI: 10.1108/ijhma-02-2023-0030
J. Abhang, V. V. Ravi Kumar
Purpose This study aims to develop a database of existing academic information in house purchase decision (HPD) using systematic literature review (SLR), to facilitate worldwide advancement of research under HPD domain. Design/methodology/approach This research examined papers from two reputable databases – Scopus and Google Scholar – from 1992 to 2022 using a scoping review technique (Arksey and O’Malley, 2005) and a theme analysis method. Out of 374, 181 articles fit the inclusion parameters and were evaluated using the theme analysis approach. Findings Data from 181 articles was evaluated thematically to create a thematic map of HPD research. Five main themes and their sub-themes were identified: consumer behaviour, housing attributes, factors influencing purchasing decisions, investment analysis and demographics, which proved essential in understanding HPD and customer preferences for house purchase. Practical implications Data from 181 articles were evaluated thematically to create a thematic map of HPD research. This SLR intends to provide useful new insights on consumer concerns about home purchases in the rapidly developing residential real estate market and the issues that marketers, housing sector stakeholders, real estate industry and existing and future researchers should prioritize. Originality/value This research is unique such that it is the only 30-year-long SLR on the subject matter of HPD. This paper makes a significant contribution to residential real estate domain signifying the present state of research in HPD.
{"title":"Three decades of house purchase decisions: a scoping review and thematic classification","authors":"J. Abhang, V. V. Ravi Kumar","doi":"10.1108/ijhma-02-2023-0030","DOIUrl":"https://doi.org/10.1108/ijhma-02-2023-0030","url":null,"abstract":"\u0000Purpose\u0000This study aims to develop a database of existing academic information in house purchase decision (HPD) using systematic literature review (SLR), to facilitate worldwide advancement of research under HPD domain.\u0000\u0000\u0000Design/methodology/approach\u0000This research examined papers from two reputable databases – Scopus and Google Scholar – from 1992 to 2022 using a scoping review technique (Arksey and O’Malley, 2005) and a theme analysis method. Out of 374, 181 articles fit the inclusion parameters and were evaluated using the theme analysis approach.\u0000\u0000\u0000Findings\u0000Data from 181 articles was evaluated thematically to create a thematic map of HPD research. Five main themes and their sub-themes were identified: consumer behaviour, housing attributes, factors influencing purchasing decisions, investment analysis and demographics, which proved essential in understanding HPD and customer preferences for house purchase.\u0000\u0000\u0000Practical implications\u0000Data from 181 articles were evaluated thematically to create a thematic map of HPD research. This SLR intends to provide useful new insights on consumer concerns about home purchases in the rapidly developing residential real estate market and the issues that marketers, housing sector stakeholders, real estate industry and existing and future researchers should prioritize.\u0000\u0000\u0000Originality/value\u0000This research is unique such that it is the only 30-year-long SLR on the subject matter of HPD. This paper makes a significant contribution to residential real estate domain signifying the present state of research in HPD.\u0000","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44542037","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 : 2023-06-19DOI: 10.1108/ijhma-04-2023-0054
Shufeng Cong, Lee Chin, A. Abdul Samad
Purpose The purpose of this study is to investigate the relationship between tourism development and urban housing prices in Chinese cities. Specifically, the study aimed to explore whether there is a relationship between the two variables in tourist and non-tourist cities and whether there is a non-linear relationship between them. Design/methodology/approach In this study, the entropy method was used to construct the China City Tourism Development Index, which provides a more comprehensive measure of the level of tourism development in different cities. In total, 45 major cities in China were studied using the panel data approach for the period of 2011 to 2019. Findings The empirical analysis conducted for this study found that tourism development affects urban house prices, and that there is an inverted U-shaped relationship. However, this varies across cities, with house prices in tourist cities tending to be more influenced by tourism development than non-tourist cities. Also, foreign direct investment, population size, fixed asset investment and disposable income per capita were found to have an impact on house prices in both tourism and non-tourism cities. Originality/value There are significant differences in tourism development and urban house prices in different cities in China. This study considers these differences when examining the impact of tourism on house prices in 45 major cities in China by dividing the sample cities into tourist and non-tourist cities.
{"title":"Does urban tourism development impact urban housing prices?","authors":"Shufeng Cong, Lee Chin, A. Abdul Samad","doi":"10.1108/ijhma-04-2023-0054","DOIUrl":"https://doi.org/10.1108/ijhma-04-2023-0054","url":null,"abstract":"\u0000Purpose\u0000The purpose of this study is to investigate the relationship between tourism development and urban housing prices in Chinese cities. Specifically, the study aimed to explore whether there is a relationship between the two variables in tourist and non-tourist cities and whether there is a non-linear relationship between them.\u0000\u0000\u0000Design/methodology/approach\u0000In this study, the entropy method was used to construct the China City Tourism Development Index, which provides a more comprehensive measure of the level of tourism development in different cities. In total, 45 major cities in China were studied using the panel data approach for the period of 2011 to 2019.\u0000\u0000\u0000Findings\u0000The empirical analysis conducted for this study found that tourism development affects urban house prices, and that there is an inverted U-shaped relationship. However, this varies across cities, with house prices in tourist cities tending to be more influenced by tourism development than non-tourist cities. Also, foreign direct investment, population size, fixed asset investment and disposable income per capita were found to have an impact on house prices in both tourism and non-tourism cities.\u0000\u0000\u0000Originality/value\u0000There are significant differences in tourism development and urban house prices in different cities in China. This study considers these differences when examining the impact of tourism on house prices in 45 major cities in China by dividing the sample cities into tourist and non-tourist cities.\u0000","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45006249","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 : 2023-06-16DOI: 10.1108/ijhma-04-2023-0047
F. Chege, Hassan F. Gholipour, Sharon Yam
Purpose Given the coincidental and sustained rise in house prices and foreign capital flows in Kenya, this study aims to understand whether a long-run relationship exists between real diaspora remittances and real house prices. Design/methodology/approach This study uses data from 2004-Q1 to 2020-Q4 and applies an autoregressive distributed lag model for estimation. Findings The results indicate that a positive and significant relationship exists between real remittances and real house prices in Kenya in the long run. Originality/value To the best of the authors’ knowledge, there is no study exploring the relationship between real remittance inflows and house prices in Kenya, after controlling for other key macroeconomic determinants of house prices. This study addresses this research gap.
{"title":"The long-run impact of remittances on house prices in Kenya","authors":"F. Chege, Hassan F. Gholipour, Sharon Yam","doi":"10.1108/ijhma-04-2023-0047","DOIUrl":"https://doi.org/10.1108/ijhma-04-2023-0047","url":null,"abstract":"\u0000Purpose\u0000Given the coincidental and sustained rise in house prices and foreign capital flows in Kenya, this study aims to understand whether a long-run relationship exists between real diaspora remittances and real house prices.\u0000\u0000\u0000Design/methodology/approach\u0000This study uses data from 2004-Q1 to 2020-Q4 and applies an autoregressive distributed lag model for estimation.\u0000\u0000\u0000Findings\u0000The results indicate that a positive and significant relationship exists between real remittances and real house prices in Kenya in the long run.\u0000\u0000\u0000Originality/value\u0000To the best of the authors’ knowledge, there is no study exploring the relationship between real remittance inflows and house prices in Kenya, after controlling for other key macroeconomic determinants of house prices. This study addresses this research gap.\u0000","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46242506","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 : 2023-06-16DOI: 10.1108/ijhma-03-2023-0040
Mingchen Duan, Yi Duan
Purpose Previous studies on housing affordability in China were concentrated in China’s coastal and central regions. The purpose of this paper is to investigate housing affordability of urban residents in Northwest China. Moreover, this paper attempts to understand the consistency and influencing factors of various indicators on the evaluation of housing affordability. Design/methodology/approach This paper uses multiyear data on house sales, residents’ incomes and living expenses from 2011 to 2022. House price-to-income ratio, housing affordability index and residual income approach were calculated by using these data and used as the measure of housing affordability. Findings The results show that there are obvious differences in the housing affordability among the Xi’an, Lanzhou and Yinchuan during 2011–2022, and the housing affordability of residents in cities with small population and economic scale is better. The ability of most urban residents to afford suitable housing is still poor, and the ability to afford small-sized housing is better. Most families with below-middle income have poor housing affordability. It is also observed that although various indicators had similarities in the evaluation of residents’ housing affordability, the comprehensive evaluation results of multiple indicators were more reliable. Social implications The research results provide a basis for the decision-making of the government’s urban housing policy and improvement of residents’ housing conditions. Originality/value The results have a clear understanding of the housing affordability of urban residents in Northwest China. The study found that the geographical location and topography of the city is also a factor affecting the housing affordability.
{"title":"Housing affordability in the capital cities of three Northwestern China provinces","authors":"Mingchen Duan, Yi Duan","doi":"10.1108/ijhma-03-2023-0040","DOIUrl":"https://doi.org/10.1108/ijhma-03-2023-0040","url":null,"abstract":"\u0000Purpose\u0000Previous studies on housing affordability in China were concentrated in China’s coastal and central regions. The purpose of this paper is to investigate housing affordability of urban residents in Northwest China. Moreover, this paper attempts to understand the consistency and influencing factors of various indicators on the evaluation of housing affordability.\u0000\u0000\u0000Design/methodology/approach\u0000This paper uses multiyear data on house sales, residents’ incomes and living expenses from 2011 to 2022. House price-to-income ratio, housing affordability index and residual income approach were calculated by using these data and used as the measure of housing affordability.\u0000\u0000\u0000Findings\u0000The results show that there are obvious differences in the housing affordability among the Xi’an, Lanzhou and Yinchuan during 2011–2022, and the housing affordability of residents in cities with small population and economic scale is better. The ability of most urban residents to afford suitable housing is still poor, and the ability to afford small-sized housing is better. Most families with below-middle income have poor housing affordability. It is also observed that although various indicators had similarities in the evaluation of residents’ housing affordability, the comprehensive evaluation results of multiple indicators were more reliable.\u0000\u0000\u0000Social implications\u0000The research results provide a basis for the decision-making of the government’s urban housing policy and improvement of residents’ housing conditions.\u0000\u0000\u0000Originality/value\u0000The results have a clear understanding of the housing affordability of urban residents in Northwest China. The study found that the geographical location and topography of the city is also a factor affecting the housing affordability.\u0000","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47377134","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 : 2023-06-15DOI: 10.1108/ijhma-04-2023-0045
W. Wong, K. Mintah, P. Wong, K. Baako
Purpose This study aims to examine the impact of lending liquidity on house prices especially during black swan events such as the Global Financial Crisis of 2007–08 and COVID-19. Homeownership is an important goal for many, and house prices are a significant driver of household wealth and the wider economy. This study argues that excessive liquidity from central banks may be driving house price increases, despite negative changes to fundamental drivers. This study contributes to the literature by examining lending liquidity as a driver of house prices and evaluating the efficacy of fiscal policies aimed at boosting liquidity during black swan events. Design/methodology/approach This study aims to examine the impact of quantitative easing on Australian house prices during back swan events using data from 2004 to 2021. All macroeconomic and financial data are freely available from official sources such as the Australian Bureau of Statistics and the nation's Central Bank. Methodology wise, given the problematic nature of the data such as a mixed order of integration and the possibility of cointegration among some of the I(1) variables, the auto-regressive distributed lag model was selected given its flexibility and relative lack of assumptions. Findings The Australian housing market continued to perform well during the COVID-19 pandemic, with the house price index reaching an unprecedented high towards the end of 2021. Research using data from 2004 to 2021 found a consistent positive relationship between house prices and housing finance, as well as population growth and the value of work commenced on residential properties. Other traditional drivers such as the unemployment rate, economic activity, stock prices and income levels were found to be less significant. This study suggests that quantitative easing implemented during the pandemic played a significant role in the housing market's performance. Originality/value Given the severity of COVID-19, policymakers have responded with fiscal and monetary measures that are unprecedented in scale and scope. The full implications of these responses are yet to be completely understood. In Australia, the policy interest rate was reduced to a historic low of 0.1%. In the following periods house prices appreciated by over 20%. The efficacy of quantitative easing and associated fiscal policies aimed at boosting liquidity to mitigate the impact of black swan events such as the pandemic has yet to be tested empirically. This study aims to address that paucity in literature by providing such evidence.
{"title":"Australian housing markets, the COVID-19 pandemic and black swan events","authors":"W. Wong, K. Mintah, P. Wong, K. Baako","doi":"10.1108/ijhma-04-2023-0045","DOIUrl":"https://doi.org/10.1108/ijhma-04-2023-0045","url":null,"abstract":"\u0000Purpose\u0000This study aims to examine the impact of lending liquidity on house prices especially during black swan events such as the Global Financial Crisis of 2007–08 and COVID-19. Homeownership is an important goal for many, and house prices are a significant driver of household wealth and the wider economy. This study argues that excessive liquidity from central banks may be driving house price increases, despite negative changes to fundamental drivers. This study contributes to the literature by examining lending liquidity as a driver of house prices and evaluating the efficacy of fiscal policies aimed at boosting liquidity during black swan events.\u0000\u0000\u0000Design/methodology/approach\u0000This study aims to examine the impact of quantitative easing on Australian house prices during back swan events using data from 2004 to 2021. All macroeconomic and financial data are freely available from official sources such as the Australian Bureau of Statistics and the nation's Central Bank. Methodology wise, given the problematic nature of the data such as a mixed order of integration and the possibility of cointegration among some of the I(1) variables, the auto-regressive distributed lag model was selected given its flexibility and relative lack of assumptions.\u0000\u0000\u0000Findings\u0000The Australian housing market continued to perform well during the COVID-19 pandemic, with the house price index reaching an unprecedented high towards the end of 2021. Research using data from 2004 to 2021 found a consistent positive relationship between house prices and housing finance, as well as population growth and the value of work commenced on residential properties. Other traditional drivers such as the unemployment rate, economic activity, stock prices and income levels were found to be less significant. This study suggests that quantitative easing implemented during the pandemic played a significant role in the housing market's performance.\u0000\u0000\u0000Originality/value\u0000Given the severity of COVID-19, policymakers have responded with fiscal and monetary measures that are unprecedented in scale and scope. The full implications of these responses are yet to be completely understood. In Australia, the policy interest rate was reduced to a historic low of 0.1%. In the following periods house prices appreciated by over 20%. The efficacy of quantitative easing and associated fiscal policies aimed at boosting liquidity to mitigate the impact of black swan events such as the pandemic has yet to be tested empirically. This study aims to address that paucity in literature by providing such evidence.\u0000","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47433159","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 : 2023-06-14DOI: 10.1108/ijhma-05-2023-0062
Mohammed A. M. Alhefnawi, Umar Lawal Dano, Abdulrahman M. Alshaikh, Gamal Abd Elghany, Abed A. Almusallam, Sivakumar Paraman
Purpose The Saudi 2030 Housing Program Vision aims to increase the population of Riyadh City, the capital of the Kingdom of Saudi Arabia, to between 15 and 20 million people. This paper aims to predict the demand for residential units in Riyadh City by 2030 in line with this vision. Design/methodology/approach This paper adopts a statistical modeling approach to estimate the residential demands for Riyadh City. Several population growth models, including the nonlinear quadratic polynomial spline regression model, the sigmoidal logistic power model and the exponential model, are tested and applied to Riyadh to estimate the expected population in 2030. The growth model closest to the Kingdom’s goal of reaching between 15 and 20 million people in 2030 is selected, and the paper predicts the required number of residential units for the population obtained from the selected model. Desktop database research is conducted to obtain the data required for the modeling and analytical stage. Findings The exponential model predicts a population of 16,476,470 in Riyadh City by 2030, and as a result, 2,636,235 household units are needed. This number of housing units required in Riyadh City exceeds the available residential units by almost 1,370,000, representing 108% of the available residential units in Riyadh in 2020. Originality/value This study provides valuable insights into the demand for residential units in Riyadh City by 2030 in line with the Saudi 2030 Housing Program Vision, filling the gap in prior research. The findings suggest that significant efforts are required to meet the housing demand in Riyadh City by 2030, and policymakers and stakeholders need to take appropriate measures to address this issue.
{"title":"Population modeling and housing demand prediction for the Saudi 2030 Vision: a case study of Riyadh City","authors":"Mohammed A. M. Alhefnawi, Umar Lawal Dano, Abdulrahman M. Alshaikh, Gamal Abd Elghany, Abed A. Almusallam, Sivakumar Paraman","doi":"10.1108/ijhma-05-2023-0062","DOIUrl":"https://doi.org/10.1108/ijhma-05-2023-0062","url":null,"abstract":"\u0000Purpose\u0000The Saudi 2030 Housing Program Vision aims to increase the population of Riyadh City, the capital of the Kingdom of Saudi Arabia, to between 15 and 20 million people. This paper aims to predict the demand for residential units in Riyadh City by 2030 in line with this vision.\u0000\u0000\u0000Design/methodology/approach\u0000This paper adopts a statistical modeling approach to estimate the residential demands for Riyadh City. Several population growth models, including the nonlinear quadratic polynomial spline regression model, the sigmoidal logistic power model and the exponential model, are tested and applied to Riyadh to estimate the expected population in 2030. The growth model closest to the Kingdom’s goal of reaching between 15 and 20 million people in 2030 is selected, and the paper predicts the required number of residential units for the population obtained from the selected model. Desktop database research is conducted to obtain the data required for the modeling and analytical stage.\u0000\u0000\u0000Findings\u0000The exponential model predicts a population of 16,476,470 in Riyadh City by 2030, and as a result, 2,636,235 household units are needed. This number of housing units required in Riyadh City exceeds the available residential units by almost 1,370,000, representing 108% of the available residential units in Riyadh in 2020.\u0000\u0000\u0000Originality/value\u0000This study provides valuable insights into the demand for residential units in Riyadh City by 2030 in line with the Saudi 2030 Housing Program Vision, filling the gap in prior research. The findings suggest that significant efforts are required to meet the housing demand in Riyadh City by 2030, and policymakers and stakeholders need to take appropriate measures to address this issue.\u0000","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45075852","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 : 2023-06-09DOI: 10.1108/ijhma-04-2023-0055
Guangping Liu, Guo Zhang
Purpose This study aims to explore the impact of decentralized long-term rental apartments on the value of in-community housing from two perspectives of housing price and rent. Design/methodology/approach This study uses the hedonic model to identify the factors affecting the housing value, and the influence of distributed long-rented apartments on the housing value in the community is analyzed from two aspects of housing price and rent by using the ordinary least square method and propensity score matching method. Findings The primary finding indicates that decentralized long-term rental apartments increase housing prices while decreasing general rental housing rents in the community, with the average degree of increase ranging from 0.93% to 2.59% and the average degree of decrease ranging from 2.23% to 4.34%. According to additional research, the prices of houses within communities rise by 0.042% for every 1% increase in the share of decentralized long-term rentals, while the rents for other types of rental property fall by 0.162%. Practical implications The government can regulate the housing market by regulating the access and layout of distributed long-rent apartments. Originality/value The findings of this study indicate that the existence and share of distributed long-rent apartments have a heterogeneous impact on the housing price and rent in the community, respectively.
{"title":"Impact of decentralized long-term rental apartments on the value of community housing--taking Tianjin, China, as an example","authors":"Guangping Liu, Guo Zhang","doi":"10.1108/ijhma-04-2023-0055","DOIUrl":"https://doi.org/10.1108/ijhma-04-2023-0055","url":null,"abstract":"\u0000Purpose\u0000This study aims to explore the impact of decentralized long-term rental apartments on the value of in-community housing from two perspectives of housing price and rent.\u0000\u0000\u0000Design/methodology/approach\u0000This study uses the hedonic model to identify the factors affecting the housing value, and the influence of distributed long-rented apartments on the housing value in the community is analyzed from two aspects of housing price and rent by using the ordinary least square method and propensity score matching method.\u0000\u0000\u0000Findings\u0000The primary finding indicates that decentralized long-term rental apartments increase housing prices while decreasing general rental housing rents in the community, with the average degree of increase ranging from 0.93% to 2.59% and the average degree of decrease ranging from 2.23% to 4.34%. According to additional research, the prices of houses within communities rise by 0.042% for every 1% increase in the share of decentralized long-term rentals, while the rents for other types of rental property fall by 0.162%.\u0000\u0000\u0000Practical implications\u0000The government can regulate the housing market by regulating the access and layout of distributed long-rent apartments.\u0000\u0000\u0000Originality/value\u0000The findings of this study indicate that the existence and share of distributed long-rent apartments have a heterogeneous impact on the housing price and rent in the community, respectively.\u0000","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45780517","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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