The homeownership rate was relatively stable for the few decades preceding 1995, followed by a large increase between 1995-2005 and a subsequent decline over the next ten years. We document the evolution of homeownership rate across various age groups for the period 19952015. Two interesting empirical fndings emerge. First, there are uneven variations in the homeownership rates across age: it is large for the young but small for the old. Second, the total variation is mostly driven by renter-to-owner transitions of the young. We next consider a life-cycle model featuring housing tenure decisions to explain these empirical facts. Housing is modeled as an indivisible and lumpy investment subject to both loan-to-value (LTV) and debt-to-income (DTI) credit constraints and transaction fees. Our quantitative model reasonably replicates the key distributions and transitions between housing tenures over the life cycle. Our analysis suggests that variations in the DTI limit play a crucial role in accounting for the overall rise in homeownership and the uneven behavior across age groups.
{"title":"Homeownership and Housing Transitions: Explaining the Demographic Composition","authors":"Eunseong Ma, Sarah Zubairy","doi":"10.2139/ssrn.3568953","DOIUrl":"https://doi.org/10.2139/ssrn.3568953","url":null,"abstract":"The homeownership rate was relatively stable for the few decades preceding 1995, followed by a large increase between 1995-2005 and a subsequent decline over the next ten years. We document the evolution of homeownership rate across various age groups for the period 19952015. Two interesting empirical fndings emerge. First, there are uneven variations in the homeownership rates across age: it is large for the young but small for the old. Second, the total variation is mostly driven by renter-to-owner transitions of the young. We next consider a life-cycle model featuring housing tenure decisions to explain these empirical facts. Housing is modeled as an indivisible and lumpy investment subject to both loan-to-value (LTV) and debt-to-income (DTI) credit constraints and transaction fees. Our quantitative model reasonably replicates the key distributions and transitions between housing tenures over the life cycle. Our analysis suggests that variations in the DTI limit play a crucial role in accounting for the overall rise in homeownership and the uneven behavior across age groups.","PeriodicalId":12014,"journal":{"name":"ERN: Microeconometric Studies of Housing Markets (Topic)","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84982678","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}
The study analysed the effect of neighbourhood characteristics and structural characteristics on residential rental prices in the Accra metropolis of Ghana. This is in response to the absence of scientific approach to determining rental prices and as a way to influence policies to deal with the arbitrarily fixing of rental prices. Multiple regression analysis was employed in analysing data sourced primarily from tenants of residential houses. The study specified four regression equations, linear, linear-log, log-linear and log-log. The different regression models were found to have different effect on the relationship between house rental prices and its influencing factors. However, the log-log mode and linear-log model revealed similar results, both models revealed that distance from church or mosque to a residential property were significant and positively related to house rental prices whilst all other variables were insignificant. The linear model and log-linear model also showed some similarities. In both models distance to central business district, distance to market, electricity supply, refuse dump, wooded area and urban effect were significant with the same signs in both models. However, single household was significant only in the linear model but not in the log-linear model whereas in the case of the log-linear model variables such as distance to church or mosque, park within fifty metres and uncovered drains were significant but insignificant in the linear model. The study concluded that there is a significant relation between house rental prices and neighbourhood characteristics as well as structural characteristics of a residential property.
{"title":"Determinants of Residential House Rental Prices in Accra Metropolis","authors":"Raymond Darfo-Oduro","doi":"10.2139/ssrn.3514560","DOIUrl":"https://doi.org/10.2139/ssrn.3514560","url":null,"abstract":"The study analysed the effect of neighbourhood characteristics and structural characteristics on residential rental prices in the Accra metropolis of Ghana. This is in response to the absence of scientific approach to determining rental prices and as a way to influence policies to deal with the arbitrarily fixing of rental prices. Multiple regression analysis was employed in analysing data sourced primarily from tenants of residential houses. The study specified four regression equations, linear, linear-log, log-linear and log-log. The different regression models were found to have different effect on the relationship between house rental prices and its influencing factors. However, the log-log mode and linear-log model revealed similar results, both models revealed that distance from church or mosque to a residential property were significant and positively related to house rental prices whilst all other variables were insignificant. The linear model and log-linear model also showed some similarities. In both models distance to central business district, distance to market, electricity supply, refuse dump, wooded area and urban effect were significant with the same signs in both models. However, single household was significant only in the linear model but not in the log-linear model whereas in the case of the log-linear model variables such as distance to church or mosque, park within fifty metres and uncovered drains were significant but insignificant in the linear model. The study concluded that there is a significant relation between house rental prices and neighbourhood characteristics as well as structural characteristics of a residential property.","PeriodicalId":12014,"journal":{"name":"ERN: Microeconometric Studies of Housing Markets (Topic)","volume":"37 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89598011","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}
A major part of the literature on land use regulations focuses on the residential land market. In this paper, we examine the impact of the minimum price policy on the large, but understudied, industrial land market in China. The minimum price policy aims to reduce wasteful land use in the industrial market that results from low transaction prices; it varies across counties or districts. We show that this policy increases the overall land-use intensity in the industrial market: for each additional 100 yuan increase in imposed minimum prices, the unit transaction prices range from 31.4 to 59.7 yuan higher, and the output and total factor productivity of new entrants range from 11.8% to 16.1% higher, respectively. Furthermore, we provide suggestive evidence that higher minimum prices reduce the likelihood of land lying unused post transactions, which has the effect of increasing the industrial output per unit of land.
{"title":"Can Price Regulation Increase Land-Use Intensity? Evidence from China’s Industrial Land Market","authors":"Yatang Lin, Yu Qin, Zoe Yang, Hongjia Zhu","doi":"10.2139/ssrn.3505834","DOIUrl":"https://doi.org/10.2139/ssrn.3505834","url":null,"abstract":"A major part of the literature on land use regulations focuses on the residential land market. In this paper, we examine the impact of the minimum price policy on the large, but understudied, industrial land market in China. The minimum price policy aims to reduce wasteful land use in the industrial market that results from low transaction prices; it varies across counties or districts. We show that this policy increases the overall land-use intensity in the industrial market: for each additional 100 yuan increase in imposed minimum prices, the unit transaction prices range from 31.4 to 59.7 yuan higher, and the output and total factor productivity of new entrants range from 11.8% to 16.1% higher, respectively. Furthermore, we provide suggestive evidence that higher minimum prices reduce the likelihood of land lying unused post transactions, which has the effect of increasing the industrial output per unit of land.","PeriodicalId":12014,"journal":{"name":"ERN: Microeconometric Studies of Housing Markets (Topic)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79848820","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}
E. Eiling, Erasmo Giambona, Ricardo Lopez Aliouchkin, Patrick Tuijp
While homeownership provides consumption benefits, housing is risky. Using zip code housing returns, we document that homeowners are compensated for bearing housing risk. Our sample covers more than 9,000 zip codes across 135 metropolitan statistical areas (MSAs), representing almost 70% of the U.S. population. We find that in 71% of the MSAs housing displays investment good properties with significant heterogeneity across MSAs in terms of which risk factors are priced. Local and idiosyncratic housing risks are the most important risks for homeowners, with the latter more likely priced in MSAs with lower loan--to--value and rent--to--price ratios.
{"title":"Homeowners' Risk Premia: Evidence from Zip Code Housing Returns","authors":"E. Eiling, Erasmo Giambona, Ricardo Lopez Aliouchkin, Patrick Tuijp","doi":"10.2139/ssrn.3312391","DOIUrl":"https://doi.org/10.2139/ssrn.3312391","url":null,"abstract":"While homeownership provides consumption benefits, housing is risky. Using zip code housing returns, we document that homeowners are compensated for bearing housing risk. Our sample covers more than 9,000 zip codes across 135 metropolitan statistical areas (MSAs), representing almost 70% of the U.S. population. We find that in 71% of the MSAs housing displays investment good properties with significant heterogeneity across MSAs in terms of which risk factors are priced. Local and idiosyncratic housing risks are the most important risks for homeowners, with the latter more likely priced in MSAs with lower loan--to--value and rent--to--price ratios.","PeriodicalId":12014,"journal":{"name":"ERN: Microeconometric Studies of Housing Markets (Topic)","volume":"152 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77621361","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}
A. Biswas, C. Cunningham, Kristopher Gerardi, Daniel Sexton
This paper tests the effectiveness of vacant property registration ordinances (VPROs) in reducing negative externalities from foreclosures. VPROs were widely adopted by local governments across the United States during the foreclosure crisis and facilitated the monitoring and enforcement of existing property maintenance laws. We implement a border discontinuity design combined with a triple-difference speci�cation to overcome policy endogeneity concerns, and we �nd that the enactment of VPROs in Florida more than halved the negative externality from foreclosure. This �nding is robust to a rich set of time-by-location �xed effects, limiting the sample to properties within 0.1 miles of a VPRO/non-VPRO border and to a number of other sample restrictions and falsi�cation exercises. The results suggest that an important driver of the negative price effect of nearby foreclosures is a non-pecuniary externality where the failure to maintain or secure a property affects one's neighbors.
{"title":"Foreclosure Externalities and Vacant Property Registration Ordinances","authors":"A. Biswas, C. Cunningham, Kristopher Gerardi, Daniel Sexton","doi":"10.29338/wp2019-20","DOIUrl":"https://doi.org/10.29338/wp2019-20","url":null,"abstract":"This paper tests the effectiveness of vacant property registration ordinances (VPROs) in reducing negative externalities from foreclosures. VPROs were widely adopted by local governments across the United States during the foreclosure crisis and facilitated the monitoring and enforcement of existing property maintenance laws. We implement a border discontinuity design combined with a triple-difference speci�cation to overcome policy endogeneity concerns, and we �nd that the enactment of VPROs in Florida more than halved the negative externality from foreclosure. This �nding is robust to a rich set of time-by-location �xed effects, limiting the sample to properties within 0.1 miles of a VPRO/non-VPRO border and to a number of other sample restrictions and falsi�cation exercises. The results suggest that an important driver of the negative price effect of nearby foreclosures is a non-pecuniary externality where the failure to maintain or secure a property affects one's neighbors.","PeriodicalId":12014,"journal":{"name":"ERN: Microeconometric Studies of Housing Markets (Topic)","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87507844","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}
A comprehensive literature tests the effects of land use regulation on housing supply. Most empirical studies find that regulation increases prices and decreases construction levels. Several papers also find a negative relation between regulation intensity and price elasticity of supply. However, we show the share of land available for development is unrelated to the elasticity of housing supply in the standard urban model. By affecting available land share, regulation raises the level of housing prices and reduces production, but does not change supply elasticity. These results suggest testing for the effects of regulatory or topographical constraints on housing supply should be in levels rather than elasticities.
{"title":"What is the Relation between Land Use Controls and Housing Prices?","authors":"D. Broxterman, Yishen Liu","doi":"10.2139/ssrn.3380629","DOIUrl":"https://doi.org/10.2139/ssrn.3380629","url":null,"abstract":"A comprehensive literature tests the effects of land use regulation on housing supply. Most empirical studies find that regulation increases prices and decreases construction levels. Several papers also find a negative relation between regulation intensity and price elasticity of supply. However, we show the share of land available for development is unrelated to the elasticity of housing supply in the standard urban model. By affecting available land share, regulation raises the level of housing prices and reduces production, but does not change supply elasticity. These results suggest testing for the effects of regulatory or topographical constraints on housing supply should be in levels rather than elasticities.","PeriodicalId":12014,"journal":{"name":"ERN: Microeconometric Studies of Housing Markets (Topic)","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73322138","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}
Markus Baldauf, Lorenzo Garlappi, Constantine Yannelis
This paper studies whether house prices reflect belief differences about climate change. We show that in an equilibrium model of housing choice in which agents derive utility from ownership in a neighborhood of similar agents, prices exhibit different elasticities to climate risk. We use comprehensive transaction data to relate prices to inundation projections of individual homes and measures of beliefs about climate change. We find that houses projected to be underwater in believer neighborhoods sell at a discount compared to houses in denier neighborhoods. Our results suggest that house prices reflect heterogeneity in beliefs about long-run climate change risks.
{"title":"Does Climate Change Affect Real Estate Prices? Only If You Believe in It","authors":"Markus Baldauf, Lorenzo Garlappi, Constantine Yannelis","doi":"10.2139/ssrn.3240200","DOIUrl":"https://doi.org/10.2139/ssrn.3240200","url":null,"abstract":"\u0000 This paper studies whether house prices reflect belief differences about climate change. We show that in an equilibrium model of housing choice in which agents derive utility from ownership in a neighborhood of similar agents, prices exhibit different elasticities to climate risk. We use comprehensive transaction data to relate prices to inundation projections of individual homes and measures of beliefs about climate change. We find that houses projected to be underwater in believer neighborhoods sell at a discount compared to houses in denier neighborhoods. Our results suggest that house prices reflect heterogeneity in beliefs about long-run climate change risks.","PeriodicalId":12014,"journal":{"name":"ERN: Microeconometric Studies of Housing Markets (Topic)","volume":"264 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76402594","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}
Amity James, Steven Rowley, W. Stone, S. Parkinson, Angela Spinney, Margaret Reynolds
This research examined the housing aspirations of older Australians (i.e. aged 55 years and over), including home owners and renters in the private market and in social housing, to provide the evidence-base for policies needed to deliver their required housing and housing assistance.
{"title":"Older Australians and the Housing Aspirations Gap","authors":"Amity James, Steven Rowley, W. Stone, S. Parkinson, Angela Spinney, Margaret Reynolds","doi":"10.18408/AHURI-8117301","DOIUrl":"https://doi.org/10.18408/AHURI-8117301","url":null,"abstract":"This research examined the housing aspirations of older Australians (i.e. aged 55 years and over), including home owners and renters in the private market and in social housing, to provide the evidence-base for policies needed to deliver their required housing and housing assistance.","PeriodicalId":12014,"journal":{"name":"ERN: Microeconometric Studies of Housing Markets (Topic)","volume":"73 6 Suppl 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88684835","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}
Valerie Grossman, Enrique Martínez-García, Luis Bernardo Torres, Yongzhi Sun
This paper investigates the impact of oil price shocks on house prices in the largest urban centers in Texas. We model their dynamic relationship taking into account demand- and supply-side housing fundamentals (personal disposable income per capita, long-term interest rates and rural land prices) as well as their varying dependence on oil activity. We show the following: 1) Oil price shocks have limited pass-through to house prices?the highest pass-through is found among the most oil-dependent cities where, after 20 quarters, the cumulative response of house prices is 21 percent of the cumulative effect on oil prices. Still, among less oil-dependent urban areas, the house price response to a one standard deviation oil price shock is economically significant and comparable in magnitude to the response to a one standard deviation income shock. 2) Omitting oil prices when looking at housing markets in oil-producing areas biases empirical inferences by substantially overestimating the effect of income shocks on house prices. 3) The empirical relationship linking oil price fluctuations to house prices has remained largely stable over time, in spite of the significant changes in Texas? oil sector with the onset of the shale revolution in the 2000s.
{"title":"Drilling Down: The Impact of Oil Price Shocks on Housing Prices","authors":"Valerie Grossman, Enrique Martínez-García, Luis Bernardo Torres, Yongzhi Sun","doi":"10.24149/gwp369","DOIUrl":"https://doi.org/10.24149/gwp369","url":null,"abstract":"This paper investigates the impact of oil price shocks on house prices in the largest urban centers in Texas. We model their dynamic relationship taking into account demand- and supply-side housing fundamentals (personal disposable income per capita, long-term interest rates and rural land prices) as well as their varying dependence on oil activity. We show the following: 1) Oil price shocks have limited pass-through to house prices?the highest pass-through is found among the most oil-dependent cities where, after 20 quarters, the cumulative response of house prices is 21 percent of the cumulative effect on oil prices. Still, among less oil-dependent urban areas, the house price response to a one standard deviation oil price shock is economically significant and comparable in magnitude to the response to a one standard deviation income shock. 2) Omitting oil prices when looking at housing markets in oil-producing areas biases empirical inferences by substantially overestimating the effect of income shocks on house prices. 3) The empirical relationship linking oil price fluctuations to house prices has remained largely stable over time, in spite of the significant changes in Texas? oil sector with the onset of the shale revolution in the 2000s.","PeriodicalId":12014,"journal":{"name":"ERN: Microeconometric Studies of Housing Markets (Topic)","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89185196","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}
I study whether banks’ loan loss provisioning contributed to economic downturns by examining the U.S. housing market. Specifically, I examine the influence of delayed loan loss recognition (DLR) on bank lending and risk-taking in the U.S. mortgage market and the aggregate effects of DLR on house prices and household consumption during the Great Recession. I first examine the effects of DLR on individual banks’ behavior. Then I construct ZIP code-level exposure to banks’ DLR to examine the aggregate effects of banks’ DLR on the housing market. I find high DLR banks reduced mortgage supply, leading high exposure ZIP codes to experience larger decreases in mortgage supply during the crisis. Mortgages from high DLR banks were also more likely to become distressed, leading to more foreclosures and short sales in high exposure ZIP codes during the crisis. Consequently, banks’ DLR negatively affected house prices during the crisis, implying a significant decrease in household consumption. These findings suggest banks’ loan loss provisioning affected loan supply and risk-taking, exacerbating the economic downturn via the household channel.
{"title":"Delays in Banks’ Loan Loss Provisioning and Economic Downturns: Evidence from the U.S. Housing Market","authors":"Sehwa Kim","doi":"10.2139/ssrn.3395911","DOIUrl":"https://doi.org/10.2139/ssrn.3395911","url":null,"abstract":"I study whether banks’ loan loss provisioning contributed to economic downturns by examining the U.S. housing market. Specifically, I examine the influence of delayed loan loss recognition (DLR) on bank lending and risk-taking in the U.S. mortgage market and the aggregate effects of DLR on house prices and household consumption during the Great Recession. I first examine the effects of DLR on individual banks’ behavior. Then I construct ZIP code-level exposure to banks’ DLR to examine the aggregate effects of banks’ DLR on the housing market. I find high DLR banks reduced mortgage supply, leading high exposure ZIP codes to experience larger decreases in mortgage supply during the crisis. Mortgages from high DLR banks were also more likely to become distressed, leading to more foreclosures and short sales in high exposure ZIP codes during the crisis. Consequently, banks’ DLR negatively affected house prices during the crisis, implying a significant decrease in household consumption. These findings suggest banks’ loan loss provisioning affected loan supply and risk-taking, exacerbating the economic downturn via the household channel.","PeriodicalId":12014,"journal":{"name":"ERN: Microeconometric Studies of Housing Markets (Topic)","volume":"142 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80562706","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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