Justin Contat, Carrie Hopkins, Luis Mejia, Matthew Suandi
With near unanimity, climate scientists project natural disasters to increase in frequency, severity, and geographic scope over the next century. We survey academic literature at the intersection of these climate risks and real estate. Our review of physical risks includes price, loan performance, and migratory effects stemming from flooding, wildfires, and sea level rise. We review transition risks, including energy use and decarbonization, as they relate to real estate. Where possible, we explain how these topics may intersect with housing affordability, especially in historically disadvantaged communities. We conclude by highlighting critical areas for future research.
{"title":"When climate meets real estate: A survey of the literature","authors":"Justin Contat, Carrie Hopkins, Luis Mejia, Matthew Suandi","doi":"10.1111/1540-6229.12489","DOIUrl":"https://doi.org/10.1111/1540-6229.12489","url":null,"abstract":"With near unanimity, climate scientists project natural disasters to increase in frequency, severity, and geographic scope over the next century. We survey academic literature at the intersection of these climate risks and real estate. Our review of physical risks includes price, loan performance, and migratory effects stemming from flooding, wildfires, and sea level rise. We review transition risks, including energy use and decarbonization, as they relate to real estate. Where possible, we explain how these topics may intersect with housing affordability, especially in historically disadvantaged communities. We conclude by highlighting critical areas for future research.","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"3 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140575991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this article, I quantify the value of access to public transit in New York using the surprise, hurricane‐related announcement of the temporary shutdown of an important piece of transportation infrastructure: the L‐train connecting Brooklyn and Manhattan. My approach allows me to measure changes in housing sales prices by using a change in public transit infrastructure, that is, (a) temporary, and (b) not an outcome of city transit planning, but rather an unexpected consequence of a natural disaster. I find that the L‐train's shutdown announcement caused a temporary decrease in sales prices for affected housing units of 6.4%. This estimate suggests a monthly capitalization rate of public transit access of around $863 for housing units where the L‐train is the nearest subway stop, demonstrating that households in NYC ascribe a high value to transit access. Using these estimates, the benefits of the repair outweigh the costs, with the benefit‐to‐cost ratio of the repairs ranging from 2.76 to 2.78.
在本文中，我利用飓风突如其来地宣布暂时关闭连接布鲁克林和曼哈顿的 L 型列车这一重要交通基础设施，量化了纽约公共交通的使用价值。我的方法允许我利用公共交通基础设施的变化来衡量住房销售价格的变化，这种变化（a）是临时性的，（b）不是城市交通规划的结果，而是自然灾害的意外后果。我发现，L 型列车的停运公告导致受影响住房单位的销售价格暂时下降了 6.4%。这一估算表明，在 L 型列车是最近地铁站的住房单元中，公共交通的月资本化率约为 863 美元，这表明纽约市的家庭对交通便利给予了很高的评价。根据上述估算，修缮的收益大于成本，修缮的收益成本比在 2.76 到 2.78 之间。
{"title":"Valuing public transit: The L‐train shutdown","authors":"Becka Brolinson","doi":"10.1111/1540-6229.12488","DOIUrl":"https://doi.org/10.1111/1540-6229.12488","url":null,"abstract":"In this article, I quantify the value of access to public transit in New York using the surprise, hurricane‐related announcement of the temporary shutdown of an important piece of transportation infrastructure: the L‐train connecting Brooklyn and Manhattan. My approach allows me to measure changes in housing sales prices by using a change in public transit infrastructure, that is, (a) temporary, and (b) not an outcome of city transit planning, but rather an unexpected consequence of a natural disaster. I find that the L‐train's shutdown announcement caused a temporary decrease in sales prices for affected housing units of 6.4%. This estimate suggests a monthly capitalization rate of public transit access of around $863 for housing units where the L‐train is the nearest subway stop, demonstrating that households in NYC ascribe a high value to transit access. Using these estimates, the benefits of the repair outweigh the costs, with the benefit‐to‐cost ratio of the repairs ranging from 2.76 to 2.78.","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"68 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140575995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Natural disasters can cause physical damage and provide information about flood risk. We find that the prices of one to three family homes in New York City hit by high storm surges during Hurricane Sandy dropped by 16% and remained 12% lower than pre‐storm levels 6 years after the storm. Effects were concentrated in areas outside of pre‐existing flood zones, where risks were less salient, and they were more persistent in lower income areas. Finally, flooding may have changed neighborhood demographic trends, as post‐Sandy homebuyers in hard‐hit areas had lower incomes and were less likely to be white.
{"title":"Heterogeneity in the recovery of local real estate markets after extreme events: The case of Hurricane Sandy","authors":"Ingrid Gould Ellen, Rachel Meltzer","doi":"10.1111/1540-6229.12485","DOIUrl":"https://doi.org/10.1111/1540-6229.12485","url":null,"abstract":"Natural disasters can cause physical damage and provide information about flood risk. We find that the prices of one to three family homes in New York City hit by high storm surges during Hurricane Sandy dropped by 16% and remained 12% lower than pre‐storm levels 6 years after the storm. Effects were concentrated in areas <jats:styled-content>outside</jats:styled-content> of pre‐existing flood zones, where risks were less salient, and they were more persistent in lower income areas. Finally, flooding may have changed neighborhood demographic trends, as post‐Sandy homebuyers in hard‐hit areas had lower incomes and were less likely to be white.","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"21 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140299505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dragana Cvijanović, Lyndsey Rolheiser, Alex Van de Minne
We analyze the causal effect of air pollution (acute fine particulate matter) exposure on the commercial real estate (CRE) market. We instrument for air pollution using changes in local wind direction to find that an increase in fine particulate matter exposure leads to a contemporaneous decrease in CRE market values and (net) income as well as an increase in capital expenditures. Heterogeneous treatment analysis within a building-level fixed effects framework uncovers that the negative effect on market values is concentrated in the office sector, consistent with the notion that air pollution-induced decreases in CRE values are driven by a reduction in CRE assets’ productive capacity. Additionally, we document that the negative impact on (net) income is concentrated in the apartment sector, which is consistent with a broad set of local disamenity mechanisms identified in previous residential real estate literature.
{"title":"Commercial real estate and air pollution","authors":"Dragana Cvijanović, Lyndsey Rolheiser, Alex Van de Minne","doi":"10.1111/1540-6229.12484","DOIUrl":"https://doi.org/10.1111/1540-6229.12484","url":null,"abstract":"We analyze the causal effect of air pollution (acute fine particulate matter) exposure on the commercial real estate (CRE) market. We instrument for air pollution using changes in local wind direction to find that an increase in fine particulate matter exposure leads to a contemporaneous decrease in CRE market values and (net) income as well as an increase in capital expenditures. Heterogeneous treatment analysis within a building-level fixed effects framework uncovers that the negative effect on market values is concentrated in the office sector, consistent with the notion that air pollution-induced decreases in CRE values are driven by a reduction in CRE assets’ productive capacity. Additionally, we document that the negative impact on (net) income is concentrated in the apartment sector, which is consistent with a broad set of local disamenity mechanisms identified in previous residential real estate literature.","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"25 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140171353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We provide a US national portrait of annual average exposure to floods across racial/ethnic and income groups, using predictions from the First Street Foundation flooding exposure model. Nationally, we find that Native Americans in inland neighborhoods and Hispanics in coastal ones face (statistically) significantly higher average exposure to flooding than non‐Hispanic Whites, even when neighborhood income composition is controlled. Surprisingly, non‐Hispanic Blacks and Asians generally have significantly lower average exposure to floods than non‐Hispanic Whites. Lower income groups exhibit substantially higher exposure in inland areas than higher income groups—but not in coastal areas—when neighborhood racial/ethnic composition is controlled.
我们利用 First Street 基金会洪水风险模型的预测结果，描绘了美国全国不同种族/族裔和收入群体的年平均洪水风险。我们发现，在全国范围内，内陆社区的美国原住民和沿海社区的西班牙裔美国人面临的洪灾平均风险（在统计上）明显高于非西班牙裔白人，即使在控制社区收入构成的情况下也是如此。令人惊讶的是，非西班牙裔黑人和亚裔的平均洪灾风险一般明显低于非西班牙裔白人。在控制了邻里种族/族裔构成的情况下，低收入群体在内陆地区的洪灾风险大大高于高收入群体，但在沿海地区则不然。
{"title":"The color of water: Racial and income differences in exposure to floods across US neighborhoods","authors":"George C. Galster, Joshua Galster, Karl Vachuska","doi":"10.1111/1540-6229.12480","DOIUrl":"https://doi.org/10.1111/1540-6229.12480","url":null,"abstract":"We provide a US national portrait of annual average exposure to floods across racial/ethnic and income groups, using predictions from the First Street Foundation flooding exposure model. Nationally, we find that Native Americans in inland neighborhoods and Hispanics in coastal ones face (statistically) significantly higher average exposure to flooding than non‐Hispanic Whites, even when neighborhood income composition is controlled. Surprisingly, non‐Hispanic Blacks and Asians generally have significantly lower average exposure to floods than non‐Hispanic Whites. Lower income groups exhibit substantially higher exposure in inland areas than higher income groups—but not in coastal areas—when neighborhood racial/ethnic composition is controlled.","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"22 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140037465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Using the Credit Risk Transfers (CRTs) issued by Fannie Mae and Freddie Mac, we study how, absent government intervention, mortgage markets would price hurricane risk. Currently, such risk is priced equally across locations even if it is location-specific. We hand collect a novel and detailed database to exploit CRTs' heterogeneous exposure to Hurricanes Harvey and Irma. Using a diff-in-diff specification, we estimate the reaction of private investors to hurricane risk. We use the previous results to calibrate a model of mortgage lending. We simulate hurricane frequencies and mortgage default probabilities in each US county to derive the market price of mortgage credit risk, that is, the implied guarantee fees (g-fees). Market-implied g-fees in counties most exposed to hurricanes would be 70% higher than inland counties.
{"title":"Climate risk in mortgage markets: Evidence from Hurricanes Harvey and Irma","authors":"Pedro Gete, Athena Tsouderou, Susan M. Wachter","doi":"10.1111/1540-6229.12477","DOIUrl":"https://doi.org/10.1111/1540-6229.12477","url":null,"abstract":"Using the Credit Risk Transfers (CRTs) issued by Fannie Mae and Freddie Mac, we study how, absent government intervention, mortgage markets would price hurricane risk. Currently, such risk is priced equally across locations even if it is location-specific. We hand collect a novel and detailed database to exploit CRTs' heterogeneous exposure to Hurricanes Harvey and Irma. Using a diff-in-diff specification, we estimate the reaction of private investors to hurricane risk. We use the previous results to calibrate a model of mortgage lending. We simulate hurricane frequencies and mortgage default probabilities in each US county to derive the market price of mortgage credit risk, that is, the implied guarantee fees (g-fees). Market-implied g-fees in counties most exposed to hurricanes would be 70% higher than inland counties.","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"36 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140006215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Considering the prevalent information asymmetry in housing markets, this study demonstrates the predictive power of homebuyers’ geographic proximity on housing prices. At the ZIP‐code level, a 10‐percentage‐point increase in the fraction of local buyers corresponds to a 1.1‐percentage‐point higher housing price growth over the subsequent 2 years. At the individual level, out‐of‐town buyers experience a 0.64‐percentage‐point lower annual return compared to local buyers within a county. These results not only highlight the significant information advantages enjoyed by geographically proximate buyers, but also imply that informationally privileged buyers’ revealed preferences for specific locations could provide informationally disadvantaged buyers with hints about which areas are likely to experience higher housing price growth in the near future.
{"title":"Homebuyers’ geographic proximity as a predictor of future housing price growth","authors":"Hayoung Kim","doi":"10.1111/1540-6229.12479","DOIUrl":"https://doi.org/10.1111/1540-6229.12479","url":null,"abstract":"Considering the prevalent information asymmetry in housing markets, this study demonstrates the predictive power of homebuyers’ geographic proximity on housing prices. At the ZIP‐code level, a 10‐percentage‐point increase in the fraction of local buyers corresponds to a 1.1‐percentage‐point higher housing price growth over the subsequent 2 years. At the individual level, out‐of‐town buyers experience a 0.64‐percentage‐point lower annual return compared to local buyers within a county. These results not only highlight the significant information advantages enjoyed by geographically proximate buyers, but also imply that informationally privileged buyers’ revealed preferences for specific locations could provide informationally disadvantaged buyers with hints about which areas are likely to experience higher housing price growth in the near future.","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"10 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139977804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article investigates the value of access to alcohol consumption by examining housing price changes after a liquor ban that was catalyzed by an unexpected riot in Singapore. The ban restricts alcohol consumption in liquor control zones further than in areas outside such zones. We find that the housing price changes in the liquor control zones were weak, which implies that the utility and disutility of alcohol consumption almost cancel each other out. In contrast, housing prices increased for houses within 800 m of but outside the liquor control zones. We investigate potential explanations for these phenomena.
{"title":"Alcohol consumption and the value of community","authors":"Xiaoyu Zhang, Yunqi Zhang","doi":"10.1111/1540-6229.12473","DOIUrl":"https://doi.org/10.1111/1540-6229.12473","url":null,"abstract":"This article investigates the value of access to alcohol consumption by examining housing price changes after a liquor ban that was catalyzed by an unexpected riot in Singapore. The ban restricts alcohol consumption in liquor control zones further than in areas outside such zones. We find that the housing price changes in the liquor control zones were weak, which implies that the utility and disutility of alcohol consumption almost cancel each other out. In contrast, housing prices increased for houses within 800 m of but outside the liquor control zones. We investigate potential explanations for these phenomena.","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"222 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139677979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The major issue which we address in this article is the one-size-fits-all nature of the typical city-level housing price index. In this vein, we make two contributions. First, we develop a new algorithm to ensure feasible estimation of geographically granular repeat-sales price indices in cases of low transactions counts. This facilitates the estimation of a balanced panel of 63,084 U.S. Census tract-level indices (2010 definitions) at an annual frequency between 1989 and 2021, which we release alongside this article. Second, we use these indices to estimate city-level price indices that are robust to heterogeneous submarket appreciation and nonrandom sampling, two issues that confound classic approaches. Different index targets require alternative weighting schemes, and these formulations can result in index differences that can widen over time horizons. However, in some cases, sample-based indices are quite similar to more strictly defined index targets; for instance, in the early COVID-19 period, standard sample-based indices are actually quite similar to a unit-representative house price index for large cities.
{"title":"A flexible method of housing price index construction using repeat-sales aggregates","authors":"Justin Contat, William D. Larson","doi":"10.1111/1540-6229.12474","DOIUrl":"https://doi.org/10.1111/1540-6229.12474","url":null,"abstract":"The major issue which we address in this article is the one-size-fits-all nature of the typical city-level housing price index. In this vein, we make two contributions. First, we develop a new algorithm to ensure feasible estimation of geographically granular repeat-sales price indices in cases of low transactions counts. This facilitates the estimation of a balanced panel of 63,084 U.S. Census tract-level indices (2010 definitions) at an annual frequency between 1989 and 2021, which we release alongside this article. Second, we use these indices to estimate city-level price indices that are robust to heterogeneous submarket appreciation and nonrandom sampling, two issues that confound classic approaches. Different index targets require alternative weighting schemes, and these formulations can result in index differences that can widen over time horizons. However, in some cases, sample-based indices are quite similar to more strictly defined index targets; for instance, in the early COVID-19 period, standard sample-based indices are actually quite similar to a unit-representative house price index for large cities.","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"11 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139517269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article investigates whether and how strongly the share of homeowners in a community affects residential property taxation by local governments. Different from renters, homeowners bear the full property tax burden, irrespective of local market conditions, and the tax is more salient to them. “Homeowner communities” may hence oppose high property taxes in order to protect their housing wealth. By merging granular spatial data from a complete housing inventory in the 2011 German Census with historical homeownership rates and housing damages during the Second World War as sources of exogenous variation in local homeownership, we provide empirical evidence that otherwise identical jurisdictions charge significantly lower property taxes when the share of homeowners in their population is higher. This result is invariant to local market conditions, which suggests tax salience is the key mechanism behind this effect. Moreover, we find positive spatial dependence on tax multipliers, indicative of property tax mimicking by local governments.
{"title":"Do local governments tax homeowner communities differently?","authors":"Roland Füss, Oliver Lerbs, Alois Weigand","doi":"10.1111/1540-6229.12469","DOIUrl":"https://doi.org/10.1111/1540-6229.12469","url":null,"abstract":"This article investigates whether and how strongly the share of homeowners in a community affects residential property taxation by local governments. Different from renters, homeowners bear the full property tax burden, irrespective of local market conditions, and the tax is more salient to them. “Homeowner communities” may hence oppose high property taxes in order to protect their housing wealth. By merging granular spatial data from a complete housing inventory in the 2011 German Census with historical homeownership rates and housing damages during the Second World War as sources of exogenous variation in local homeownership, we provide empirical evidence that otherwise identical jurisdictions charge significantly lower property taxes when the share of homeowners in their population is higher. This result is invariant to local market conditions, which suggests tax salience is the key mechanism behind this effect. Moreover, we find positive spatial dependence on tax multipliers, indicative of property tax mimicking by local governments.","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"135 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139412547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：