Purpose The purpose of the paper is twofold: first, to observe the relationship between sale to list ratio (SLR)/ for-sale inventory (FSI)/ sale count nowcast (SCN) and real/nominal housing value, and second, to produce a handbook of empirical evidence that can serve as a foundation for future research on this topic. Design/methodology/approach This paper broadly compiles empirical evidence, using three of the most common causality tests in the field of housing economics. The analysis methods include lagged Pearson correlation test, Granger causality test and cointegration test. Findings Causal relationships were observed between SLR/FSI/SCN and both nominal and real housing values. SLR and SCN showed positive long-term correlations with housing value, whereas FSI had a negative correlation. Adjusting the housing value with the Consumer Price Index (CPI) to derive real housing values could potentially alter the direction of the causal relationships. It is crucial to distinguish the long-term relationship from temporal dynamics, as FSI displayed a positive immediate impulse–response relationship with nominal housing price despite the negative long-term correlation. Originality/value SLR/FSI/SCN are housing market parameters that have only recently begun to be documented and have seen little use in research. So far, housing market research has revolved around traditional macroeconomic indicators such as unemployment rate. To the best of the authors’ knowledge, this study is one of the first studies that introduce these three parameters into housing market research.
{"title":"Sale to list ratio, for-sale inventory, sale count, and housing value","authors":"Xingrui Zhang, Yunpeng Wang, Eunhwa Yang, Shuai Xu, Yihang Yu","doi":"10.1108/ijhma-08-2023-0113","DOIUrl":"https://doi.org/10.1108/ijhma-08-2023-0113","url":null,"abstract":"Purpose The purpose of the paper is twofold: first, to observe the relationship between sale to list ratio (SLR)/ for-sale inventory (FSI)/ sale count nowcast (SCN) and real/nominal housing value, and second, to produce a handbook of empirical evidence that can serve as a foundation for future research on this topic. Design/methodology/approach This paper broadly compiles empirical evidence, using three of the most common causality tests in the field of housing economics. The analysis methods include lagged Pearson correlation test, Granger causality test and cointegration test. Findings Causal relationships were observed between SLR/FSI/SCN and both nominal and real housing values. SLR and SCN showed positive long-term correlations with housing value, whereas FSI had a negative correlation. Adjusting the housing value with the Consumer Price Index (CPI) to derive real housing values could potentially alter the direction of the causal relationships. It is crucial to distinguish the long-term relationship from temporal dynamics, as FSI displayed a positive immediate impulse–response relationship with nominal housing price despite the negative long-term correlation. Originality/value SLR/FSI/SCN are housing market parameters that have only recently begun to be documented and have seen little use in research. So far, housing market research has revolved around traditional macroeconomic indicators such as unemployment rate. To the best of the authors’ knowledge, this study is one of the first studies that introduce these three parameters into housing market research.","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135666618","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}
Purpose Achieving tenure security is a global challenge impacting cities of the global south. The purpose of this paper is to evaluate the role of technology-enabled solutions as an enabler for the tenure rights of slum dwellers. Design/methodology/approach In this paper, we adopted a case study approach to analyze the use cases for technologies aiding India’s securitization of land tenure. The flagship state mission of Odisha, named the Jaga Mission, and that of Punjab, named BASERA – the Chief Minister’s Slum Development Program – were used as cases for this paper. Findings It was found that technologies like drone imagery and digital surveys fast-tracked the data collection and helped in mapping the slums with accuracy, mitigating human errors arising during measurement – a necessary condition for ensuring de jure tenure security. The adoption of a technology-based solution, along with a suitable policy and legal framework, has helped in the distribution of secure land titles to the slum dwellers in these states. Originality/value Odisha’s and Punjab’s journey in using technology to enable tenure security for its urban poor residents can serve as a model for the cities of the global south, dealing with the challenges of providing secure tenure and property rights.
{"title":"Technology as an enabler for securing tenure rights for the slum dwellers","authors":"Anindita Mukherjee, Ashish Gupta, Piyush Tiwari, Baisakhi Sarkar Dhar","doi":"10.1108/ijhma-06-2023-0083","DOIUrl":"https://doi.org/10.1108/ijhma-06-2023-0083","url":null,"abstract":"Purpose Achieving tenure security is a global challenge impacting cities of the global south. The purpose of this paper is to evaluate the role of technology-enabled solutions as an enabler for the tenure rights of slum dwellers. Design/methodology/approach In this paper, we adopted a case study approach to analyze the use cases for technologies aiding India’s securitization of land tenure. The flagship state mission of Odisha, named the Jaga Mission, and that of Punjab, named BASERA – the Chief Minister’s Slum Development Program – were used as cases for this paper. Findings It was found that technologies like drone imagery and digital surveys fast-tracked the data collection and helped in mapping the slums with accuracy, mitigating human errors arising during measurement – a necessary condition for ensuring de jure tenure security. The adoption of a technology-based solution, along with a suitable policy and legal framework, has helped in the distribution of secure land titles to the slum dwellers in these states. Originality/value Odisha’s and Punjab’s journey in using technology to enable tenure security for its urban poor residents can serve as a model for the cities of the global south, dealing with the challenges of providing secure tenure and property rights.","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":"201 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135823734","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 : 2023-10-05DOI: 10.1108/ijhma-06-2023-0079
XiaoJun Yuan, Aslihan Gizem Korkmaz, Haigang Zhou
Purpose In China, having a home before getting married is viewed as being a crucial indicator of the sincerity of romance. Despite recent increases in housing costs, men who have their homes ready for marriage stand out in the marriage market. This study aims to explore the association between readiness to marry, marriage age and the home that men purchase prior to marriage using the China Labor-force Dynamics Survey, the first countrywide follow-up survey with the theme of labor force. Design/methodology/approach The authors suggest new standards for determining the marital residence. In addition, contrary to the existing literature, which focuses on “Sheng Nu” (women who do not marry by the traditional marriage age in China), the authors focus on “Sheng Nan” (men who do not marry by the traditional marriage age in China). Findings The results show that men who own a house before marriage are reluctant to get married. The authors document robust evidence that the preexistence of the marital house decreases the willingness to marry and postpones the marriage date, regardless of location and time. Originality/value The authors document robust evidence that the preexistence of the marital house decreases the willingness to marry and postpones the marriage date, regardless of location and time.
{"title":"Marital house and marriage: evidence from micro-level data","authors":"XiaoJun Yuan, Aslihan Gizem Korkmaz, Haigang Zhou","doi":"10.1108/ijhma-06-2023-0079","DOIUrl":"https://doi.org/10.1108/ijhma-06-2023-0079","url":null,"abstract":"Purpose In China, having a home before getting married is viewed as being a crucial indicator of the sincerity of romance. Despite recent increases in housing costs, men who have their homes ready for marriage stand out in the marriage market. This study aims to explore the association between readiness to marry, marriage age and the home that men purchase prior to marriage using the China Labor-force Dynamics Survey, the first countrywide follow-up survey with the theme of labor force. Design/methodology/approach The authors suggest new standards for determining the marital residence. In addition, contrary to the existing literature, which focuses on “Sheng Nu” (women who do not marry by the traditional marriage age in China), the authors focus on “Sheng Nan” (men who do not marry by the traditional marriage age in China). Findings The results show that men who own a house before marriage are reluctant to get married. The authors document robust evidence that the preexistence of the marital house decreases the willingness to marry and postpones the marriage date, regardless of location and time. Originality/value The authors document robust evidence that the preexistence of the marital house decreases the willingness to marry and postpones the marriage date, regardless of location and time.","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134976080","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 : 2023-10-03DOI: 10.1108/ijhma-07-2023-0090
Nestor Garza, Michael Goldman
Purpose This study aims to test the effect of Seattle’s discontinuous sidewalk requirement, on the number of housing units per construction permit. Design/methodology/approach This study uses discontinuity linear regression (DLR) on a database of Seattle’s housing construction permits during January-2015 to January-2018, controlled by 51 socioeconomic, planning and geographic variables. The sidewalk requirement is continuous inside the designated urban villages; however, it is spatially and quantitatively discontinuous in the rest of the city: certain blocks at certain locations require sidewalks’ design and construction in permits with six or more housing units. DLR detects the effect of the discontinuity while controlling for a vast array of confounding variables. Findings The primary finding is that the discontinuous requirement reduces the number of housing units in about 75% of a housing unit per permit, which at the aggregate level amounts to around 335 fewer housing units during the period of analysis. Research limitations/implications The database is relatively small, which has limited a more thorough specification process and robustness tests. Originality/value Besides directly testing the effect of a discontinuous in-kind development contribution, the research setup allows to discuss a wider, more structural problem: the possibility of contributions avoidance due to spatial substitution. In contrast, spatially continuous (i.e. city-level) contributions cannot be avoided by performing spatial substitution, and they are internalized by the housing supply side (market-neutral).
{"title":"Housing supply and development contributions: a case study of sidewalks in Seattle","authors":"Nestor Garza, Michael Goldman","doi":"10.1108/ijhma-07-2023-0090","DOIUrl":"https://doi.org/10.1108/ijhma-07-2023-0090","url":null,"abstract":"Purpose This study aims to test the effect of Seattle’s discontinuous sidewalk requirement, on the number of housing units per construction permit. Design/methodology/approach This study uses discontinuity linear regression (DLR) on a database of Seattle’s housing construction permits during January-2015 to January-2018, controlled by 51 socioeconomic, planning and geographic variables. The sidewalk requirement is continuous inside the designated urban villages; however, it is spatially and quantitatively discontinuous in the rest of the city: certain blocks at certain locations require sidewalks’ design and construction in permits with six or more housing units. DLR detects the effect of the discontinuity while controlling for a vast array of confounding variables. Findings The primary finding is that the discontinuous requirement reduces the number of housing units in about 75% of a housing unit per permit, which at the aggregate level amounts to around 335 fewer housing units during the period of analysis. Research limitations/implications The database is relatively small, which has limited a more thorough specification process and robustness tests. Originality/value Besides directly testing the effect of a discontinuous in-kind development contribution, the research setup allows to discuss a wider, more structural problem: the possibility of contributions avoidance due to spatial substitution. In contrast, spatially continuous (i.e. city-level) contributions cannot be avoided by performing spatial substitution, and they are internalized by the housing supply side (market-neutral).","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135697477","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 : 2023-10-03DOI: 10.1108/ijhma-07-2023-0101
Umar Lawal Dano
Purpose This study aims to examine the determinants that influence housing prices in Dammam metropolitan area (DMA), Saudi Arabia, by using the analytic hierarchy process (AHP) model. The study considers determinants such as building age (BLD AG), building size (BLD SZ), building condition (BLD CN), access to parking (ACC PK), proximity to transport infrastructure (PRX TRS), proximity to green areas (PRX GA) and proximity to amenities (PRX AM). Design/methodology/approach The AHP decision model was used to assess the determinants of housing prices in DMA, using a pair-wise comparison matrix to determine the influence of the investigated factors on housing prices. Findings The study’s results revealed that building size (BLD SZ) was the most critical determinant affecting housing prices in DMA, with a weight of 0.32, trailed by proximity to transport infrastructure (PRX TRS), with a weight of 0.24 as the second most influential housing price determinant in DMA. The third most important determinant was proximity to amenities (PRX AM), with a weight of 0.18. Originality/value This study addresses a research gap by using the AHP model to assess the spatial determinants of housing prices in DMA, Saudi Arabia. Few studies have used this model in examining housing price factors, particularly in the context of Saudi Arabia. Consequently, the findings of this study provide unique insights for policymakers, housing developers and other stakeholders in understanding the importance of building size, proximity to transport infrastructure and proximity to amenities in influencing housing prices in DMA. By considering these determinants, stakeholders can make informed decisions to improve housing quality and prices in the region.
{"title":"Analyzing the spatial determinants of housing prices in Dammam, Saudi Arabia: an AHP approach","authors":"Umar Lawal Dano","doi":"10.1108/ijhma-07-2023-0101","DOIUrl":"https://doi.org/10.1108/ijhma-07-2023-0101","url":null,"abstract":"Purpose This study aims to examine the determinants that influence housing prices in Dammam metropolitan area (DMA), Saudi Arabia, by using the analytic hierarchy process (AHP) model. The study considers determinants such as building age (BLD AG), building size (BLD SZ), building condition (BLD CN), access to parking (ACC PK), proximity to transport infrastructure (PRX TRS), proximity to green areas (PRX GA) and proximity to amenities (PRX AM). Design/methodology/approach The AHP decision model was used to assess the determinants of housing prices in DMA, using a pair-wise comparison matrix to determine the influence of the investigated factors on housing prices. Findings The study’s results revealed that building size (BLD SZ) was the most critical determinant affecting housing prices in DMA, with a weight of 0.32, trailed by proximity to transport infrastructure (PRX TRS), with a weight of 0.24 as the second most influential housing price determinant in DMA. The third most important determinant was proximity to amenities (PRX AM), with a weight of 0.18. Originality/value This study addresses a research gap by using the AHP model to assess the spatial determinants of housing prices in DMA, Saudi Arabia. Few studies have used this model in examining housing price factors, particularly in the context of Saudi Arabia. Consequently, the findings of this study provide unique insights for policymakers, housing developers and other stakeholders in understanding the importance of building size, proximity to transport infrastructure and proximity to amenities in influencing housing prices in DMA. By considering these determinants, stakeholders can make informed decisions to improve housing quality and prices in the region.","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135696422","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}
Purpose This study aims to examine whether or not residential properties closer to landfill sites have lower offer values by the developers. That is, by analyzing real estate data and landfill site locations, the study seeks to provide insights into whether properties situated closer to landfill sites tend to have a lower offer values than those located farther away. Design/methodology/approach The study is exploratory in nature, and a case study approach is applied. A landfill site named “Uruli Devachi” is selected in the region of Pune district, and data is collected from 102 developers selling residential projects within a radius of 15 km (about 9.32 mi). The gathered data is analyzed by using basic descriptive statistics, one-way ANOVA and ordinary least squares (OLS) regression. The OLS regression helps to determine whether there is a relationship between the distance of a residential property from a landfill site and its offer value. Findings The findings suggest that landfill sites have a detrimental impact on residential property offer values, with the negative impact increasing with proximity to a landfill site. The negative effect seems to vanish after over 10 km (about 6.21 mi). The developers provide extra facilities including a clubhouse, a children’s play area, a gym and a swimming pool in an effort to mitigate the negative effects of the landfill site on residential properties. Practical implications The findings of this study could have implications for property developers, real estate professionals and policymakers in understanding how landfill proximity might impact property offer values. Originality/value This study presents many novelties for the Indian housing market: the landfill sites do have a negative effect on the offer value of residential property; the closer the residential property to a landfill site, the higher the negative effect. Further, the developers try and mitigate the negative effect of landfill sites on residential properties by providing additional amenities such as a clubhouse, children’s play park, gym and swimming pool.
{"title":"Impact of solid waste landfill proximity on residential property offer values: a case study of Pune","authors":"Abhijat Arun Abhyankar, Anand Prakash, Harish Kumar Singla","doi":"10.1108/ijhma-08-2023-0109","DOIUrl":"https://doi.org/10.1108/ijhma-08-2023-0109","url":null,"abstract":"Purpose This study aims to examine whether or not residential properties closer to landfill sites have lower offer values by the developers. That is, by analyzing real estate data and landfill site locations, the study seeks to provide insights into whether properties situated closer to landfill sites tend to have a lower offer values than those located farther away. Design/methodology/approach The study is exploratory in nature, and a case study approach is applied. A landfill site named “Uruli Devachi” is selected in the region of Pune district, and data is collected from 102 developers selling residential projects within a radius of 15 km (about 9.32 mi). The gathered data is analyzed by using basic descriptive statistics, one-way ANOVA and ordinary least squares (OLS) regression. The OLS regression helps to determine whether there is a relationship between the distance of a residential property from a landfill site and its offer value. Findings The findings suggest that landfill sites have a detrimental impact on residential property offer values, with the negative impact increasing with proximity to a landfill site. The negative effect seems to vanish after over 10 km (about 6.21 mi). The developers provide extra facilities including a clubhouse, a children’s play area, a gym and a swimming pool in an effort to mitigate the negative effects of the landfill site on residential properties. Practical implications The findings of this study could have implications for property developers, real estate professionals and policymakers in understanding how landfill proximity might impact property offer values. Originality/value This study presents many novelties for the Indian housing market: the landfill sites do have a negative effect on the offer value of residential property; the closer the residential property to a landfill site, the higher the negative effect. Further, the developers try and mitigate the negative effect of landfill sites on residential properties by providing additional amenities such as a clubhouse, children’s play park, gym and swimming pool.","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135790467","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 : 2023-09-29DOI: 10.1108/ijhma-07-2023-0096
Xingrui Zhang, Eunhwa Yang, Yunpeng Wang
Purpose Private residential construction spending (PRRESCON) is an important indicator for assessing housing supply/demand and economic strength. Currently, there are no comprehensive studies on PRRESCON forecasting. This study aims to address the gap in knowledge by conducting a comprehensive exploration of indicators for PRRESCON using time series methods. Design/methodology/approach Granger causality test trials were conducted between PRRESCON and all of its potential indicators before the vector autoregression model was implemented. Extensive effort was exerted toward model interpretation in the form of impulse–response functions. Findings Impulse–response functions indicated that the escalation of labor supply, material/construction costs and issued building permits at any given time consistently had a positive impact on PRRESCON 10–11 months later, with a 95% confidence interval. Conversely, the unemployment rate and housing value escalations at any given time were found to have a negative impact on PRRESCON 10–11 months later in more than 95% of the instances. Furthermore, material/construction cost escalations at any given time were shown to have a negative impact on PRRESCON 7 months later in more than 95% of the instances. Originality/value Current forecasting literature on construction spending focuses exclusively on the parameter’s relationship with gross domestic product and the architectural billing index. This study reveals many additional indicators, many of which are directly related to the implementation of housing development projects. The paper is also the first in the body of forecasting literature, to the best of the authors’ knowledge, to conduct impulse–response analysis on residential construction spending.
{"title":"Time series observation of relationship between United States private residential construction spending and its indicators","authors":"Xingrui Zhang, Eunhwa Yang, Yunpeng Wang","doi":"10.1108/ijhma-07-2023-0096","DOIUrl":"https://doi.org/10.1108/ijhma-07-2023-0096","url":null,"abstract":"Purpose Private residential construction spending (PRRESCON) is an important indicator for assessing housing supply/demand and economic strength. Currently, there are no comprehensive studies on PRRESCON forecasting. This study aims to address the gap in knowledge by conducting a comprehensive exploration of indicators for PRRESCON using time series methods. Design/methodology/approach Granger causality test trials were conducted between PRRESCON and all of its potential indicators before the vector autoregression model was implemented. Extensive effort was exerted toward model interpretation in the form of impulse–response functions. Findings Impulse–response functions indicated that the escalation of labor supply, material/construction costs and issued building permits at any given time consistently had a positive impact on PRRESCON 10–11 months later, with a 95% confidence interval. Conversely, the unemployment rate and housing value escalations at any given time were found to have a negative impact on PRRESCON 10–11 months later in more than 95% of the instances. Furthermore, material/construction cost escalations at any given time were shown to have a negative impact on PRRESCON 7 months later in more than 95% of the instances. Originality/value Current forecasting literature on construction spending focuses exclusively on the parameter’s relationship with gross domestic product and the architectural billing index. This study reveals many additional indicators, many of which are directly related to the implementation of housing development projects. The paper is also the first in the body of forecasting literature, to the best of the authors’ knowledge, to conduct impulse–response analysis on residential construction spending.","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135243488","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 : 2023-09-20DOI: 10.1108/ijhma-07-2023-0094
Ali Raza, Laiba Asif, Turgut Türsoy, Mehdi Seraj, Gül Erkol Bayram
Purpose This study aims to determine how changes in macroeconomic indicators and the housing prices index (HPI) are related. These factors can cause short-term and long-term changes in the housing market in Spain. Design/methodology/approach The study used cointegrating regression, fully modified ordinary least squares and dynamic ordinary least squares methodologies. The models are trained using quarterly time series data for these parameters from 2010 to 2022. A comprehensive examination is conducted to explore the relationship between macroeconomic issues and fluctuations in the HPI. Findings The results indicate statistically significant short-run effects ( p < 0.05) of economic growth, inflation, Spanish stock indices, foreign trade and the interest rate on HPI. The inflation variables, Spain’s stock indices, interest rate and monetary rate, have statistically significant long-run effects ( p < 0.05) on HPI. The exchange rate, unemployment and money supply have no substantial impact on HPI in Spain. Originality/value The study’s findings significantly contribute to increased information concerning the level of investing activity in the Spanish housing sector. After conducting an in-depth study of both the long-run and short-run connections with HPI, the study proved to be highly effective in formulating appropriate policies.
{"title":"Macro-economic indicators and housing price index in Spain: fresh evidence from FMOLS and DOLS","authors":"Ali Raza, Laiba Asif, Turgut Türsoy, Mehdi Seraj, Gül Erkol Bayram","doi":"10.1108/ijhma-07-2023-0094","DOIUrl":"https://doi.org/10.1108/ijhma-07-2023-0094","url":null,"abstract":"Purpose This study aims to determine how changes in macroeconomic indicators and the housing prices index (HPI) are related. These factors can cause short-term and long-term changes in the housing market in Spain. Design/methodology/approach The study used cointegrating regression, fully modified ordinary least squares and dynamic ordinary least squares methodologies. The models are trained using quarterly time series data for these parameters from 2010 to 2022. A comprehensive examination is conducted to explore the relationship between macroeconomic issues and fluctuations in the HPI. Findings The results indicate statistically significant short-run effects ( p < 0.05) of economic growth, inflation, Spanish stock indices, foreign trade and the interest rate on HPI. The inflation variables, Spain’s stock indices, interest rate and monetary rate, have statistically significant long-run effects ( p < 0.05) on HPI. The exchange rate, unemployment and money supply have no substantial impact on HPI in Spain. Originality/value The study’s findings significantly contribute to increased information concerning the level of investing activity in the Spanish housing sector. After conducting an in-depth study of both the long-run and short-run connections with HPI, the study proved to be highly effective in formulating appropriate policies.","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136313756","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 : 2023-09-19DOI: 10.1108/ijhma-06-2023-0081
Nhung Thi Nguyen, Lan Hoang Mai Nguyen, Quyen Do, Linh Khanh Luu
Purpose This paper aims to explore factors influencing apartment price volatility in the two biggest cities in Vietnam, Hanoi and Ho Chi Minh City. Design/methodology/approach The study uses the supply and demand approach and provides a literature review of previous studies to develop four main hypotheses using four determinants of apartment price volatility in Vietnam: gross domestic product (GDP), inflation rate, lending interest rate and construction cost. Subsequently, the Vector Error Correction Model (VECM) is used to analyze a monthly data sample of 117. Findings The research highlights the important role of construction costs in apartment price volatility in the two largest cities. Moreover, there are significant differences in how all four determinants affect apartment price volatility in the two cities. In addition, there is a long-run relationship between the determinants and apartment price volatility in both Hanoi and Ho Chi Minh City. Research limitations/implications Limitations related to data transparency of the real estate industry in Vietnam lead to three main limitations of this paper, including: this paper only collects a sample of 117 valid monthly observations; apartment price volatility is calculated by changes in the apartment price index instead of apartment price standard deviation; and this paper is limited by only four determinants, those being GDP, inflation rate, lending interest rate and construction cost. Practical implications The study provides evidence of differences in how the above determinants affect apartment price volatility in Hanoi and Ho Chi Minh City, which helps investors and policymakers to make informed decisions relating to the real estate market in the two biggest cities in Vietnam. Social implications This paper makes several recommendations to policymakers and investors in Vietnam to ensure a stable real estate market, contributing to the stability of the national economy. Originality/value This paper provides a new approach using VECM to analyze both long-run and short-run relationships between macroeconomic and sectoral independent variables and apartment price volatility in the two biggest cities in Vietnam.
{"title":"Determinants of apartment price volatility in Vietnam: a comparison between Hanoi and Ho Chi Minh City","authors":"Nhung Thi Nguyen, Lan Hoang Mai Nguyen, Quyen Do, Linh Khanh Luu","doi":"10.1108/ijhma-06-2023-0081","DOIUrl":"https://doi.org/10.1108/ijhma-06-2023-0081","url":null,"abstract":"Purpose This paper aims to explore factors influencing apartment price volatility in the two biggest cities in Vietnam, Hanoi and Ho Chi Minh City. Design/methodology/approach The study uses the supply and demand approach and provides a literature review of previous studies to develop four main hypotheses using four determinants of apartment price volatility in Vietnam: gross domestic product (GDP), inflation rate, lending interest rate and construction cost. Subsequently, the Vector Error Correction Model (VECM) is used to analyze a monthly data sample of 117. Findings The research highlights the important role of construction costs in apartment price volatility in the two largest cities. Moreover, there are significant differences in how all four determinants affect apartment price volatility in the two cities. In addition, there is a long-run relationship between the determinants and apartment price volatility in both Hanoi and Ho Chi Minh City. Research limitations/implications Limitations related to data transparency of the real estate industry in Vietnam lead to three main limitations of this paper, including: this paper only collects a sample of 117 valid monthly observations; apartment price volatility is calculated by changes in the apartment price index instead of apartment price standard deviation; and this paper is limited by only four determinants, those being GDP, inflation rate, lending interest rate and construction cost. Practical implications The study provides evidence of differences in how the above determinants affect apartment price volatility in Hanoi and Ho Chi Minh City, which helps investors and policymakers to make informed decisions relating to the real estate market in the two biggest cities in Vietnam. Social implications This paper makes several recommendations to policymakers and investors in Vietnam to ensure a stable real estate market, contributing to the stability of the national economy. Originality/value This paper provides a new approach using VECM to analyze both long-run and short-run relationships between macroeconomic and sectoral independent variables and apartment price volatility in the two biggest cities in Vietnam.","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135011451","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 : 2023-09-15DOI: 10.1108/ijhma-07-2023-0093
Paul Chinedu Okey
Purpose The purpose of this paper is to assess the long-run and short-run drivers of real house prices in Nigeria from 1991Q1 to 2020Q4. Design/methodology/approach Vector autoregression and cointegration tests were used to assess the key drivers of Nigeria’s real house prices in the long run and short run. Findings The empirical findings revealed that household disposable income is the most important determinant of house prices in Nigeria. House prices increased by 1.6% and 60.8% in response to a 1% increase in disposable income in the long run and short run, respectively, while real mortgage credits pushed up house prices by 5% and have no long-run effects, suggesting that most Nigerians depend on their money income rather than credits in securing a home. In addition, prices of oil sector products and real interest rates had negative and significant relationship with house prices, while positive correlations were found for real effective exchange rate and real housing investments regardless of the time horizon. The impact of construction costs and cement prices was also documented. Originality/value This is likely a pioneering study of its kind to focus on the determinants of real house prices in Nigeria. It is probably the first study, the best of the author’s knowledge, to empirically examine the impact of the oil sector on house prices in the country.
{"title":"Drivers of Nigeria’s real house prices: long-run analysis and short-run dynamics","authors":"Paul Chinedu Okey","doi":"10.1108/ijhma-07-2023-0093","DOIUrl":"https://doi.org/10.1108/ijhma-07-2023-0093","url":null,"abstract":"Purpose The purpose of this paper is to assess the long-run and short-run drivers of real house prices in Nigeria from 1991Q1 to 2020Q4. Design/methodology/approach Vector autoregression and cointegration tests were used to assess the key drivers of Nigeria’s real house prices in the long run and short run. Findings The empirical findings revealed that household disposable income is the most important determinant of house prices in Nigeria. House prices increased by 1.6% and 60.8% in response to a 1% increase in disposable income in the long run and short run, respectively, while real mortgage credits pushed up house prices by 5% and have no long-run effects, suggesting that most Nigerians depend on their money income rather than credits in securing a home. In addition, prices of oil sector products and real interest rates had negative and significant relationship with house prices, while positive correlations were found for real effective exchange rate and real housing investments regardless of the time horizon. The impact of construction costs and cement prices was also documented. Originality/value This is likely a pioneering study of its kind to focus on the determinants of real house prices in Nigeria. It is probably the first study, the best of the author’s knowledge, to empirically examine the impact of the oil sector on house prices in the country.","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135397296","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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