This article examines the value of externalities created by the presence of sex workers in the city. Although a legal paid-sex industry might contribute to the economy, it may also generate negative externalities. To identify the net impact of overt prostitution, we estimate changes in housing prices following the sudden closure of the two red light districts (RLDs) in the Dutch City of Utrecht. Our results show that the capitalization effect of RLDs is spatially heterogeneous. While some areas are unaffected, others are up to 12% more expensive if far from operating brothels. Interestingly, though, evidence also shows that RLDs increase local employment in a variety of sectors. All the aversion to living near RLDs is instead explained by petty crimes.
{"title":"The external cost of prostitution: Evidence from shutting down red light districts in the Netherlands","authors":"Erasmo Giambona, Rafael P. Ribas","doi":"10.1111/1540-6229.12404","DOIUrl":"https://doi.org/10.1111/1540-6229.12404","url":null,"abstract":"This article examines the value of externalities created by the presence of sex workers in the city. Although a legal paid-sex industry might contribute to the economy, it may also generate negative externalities. To identify the net impact of overt prostitution, we estimate changes in housing prices following the sudden closure of the two red light districts (RLDs) in the Dutch City of Utrecht. Our results show that the capitalization effect of RLDs is spatially heterogeneous. While some areas are unaffected, others are up to 12% more expensive if far from operating brothels. Interestingly, though, evidence also shows that RLDs increase local employment in a variety of sectors. All the aversion to living near RLDs is instead explained by petty crimes.","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"14 10","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138520888","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}
{"title":"Canceling the admission priority of private schools enlarges housing price gap in public school districts: Evidence from Shanghai's new admission policy","authors":"Pengyu Zhu, Yi Zhang, Juan Wang","doi":"10.1111/1540-6229.12403","DOIUrl":"https://doi.org/10.1111/1540-6229.12403","url":null,"abstract":"","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"71 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81647122","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}
{"title":"Industrial Tail Exposure Risk and Asset Price: Evidence from US REITs For Real Estate Economics","authors":"J. Song, K. Liow","doi":"10.1111/1540-6229.12402","DOIUrl":"https://doi.org/10.1111/1540-6229.12402","url":null,"abstract":",","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"11 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87298823","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}
{"title":"The price effects of greening vacant lots: How neighborhood attributes matter","authors":"Desen Lin, Shane T. Jensen, Susan M. Wachter","doi":"10.1111/1540-6229.12401","DOIUrl":"https://doi.org/10.1111/1540-6229.12401","url":null,"abstract":"","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"54 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84715983","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}
Cigdem Gedikli, R. Hill, Oleksandr Talavera, O. Yılmaz
In this article, we provide novel evidence on the additional costs associated with smoking. While it may not be surprising that smokers pay a rent premium, we are the first to quantify the size of this premium. Our approach is innovative in that we use text mining methods that extract implicit information on landlords’ attitudes to smoking directly from Zoopla UK rental listings. Applying hedonic, matching, and machine-learning methods to the text-mined data, we find a positive smoking rent premium of around 6%. This translates into £ 14.40 of indirect costs, in addition to £ 40 of weekly spending on cigarettes estimated for an average smoker in the United Kingdom.
{"title":"The hidden cost of smoking: Rent premia in the housing market","authors":"Cigdem Gedikli, R. Hill, Oleksandr Talavera, O. Yılmaz","doi":"10.1111/1540-6229.12399","DOIUrl":"https://doi.org/10.1111/1540-6229.12399","url":null,"abstract":"In this article, we provide novel evidence on the additional costs associated with smoking. While it may not be surprising that smokers pay a rent premium, we are the first to quantify the size of this premium. Our approach is innovative in that we use text mining methods that extract implicit information on landlords’ attitudes to smoking directly from Zoopla UK rental listings. Applying hedonic, matching, and machine-learning methods to the text-mined data, we find a positive smoking rent premium of around 6%. This translates into £ 14.40 of indirect costs, in addition to £ 40 of weekly spending on cigarettes estimated for an average smoker in the United Kingdom.","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"65 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91233258","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}
{"title":"Real estate investors and the us housing recovery","authors":"Lauren Lambie‐Hanson, Wenli Li, Michael Slonkosky","doi":"10.1111/1540-6229.12396","DOIUrl":"https://doi.org/10.1111/1540-6229.12396","url":null,"abstract":"","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"1 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77122523","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}
{"title":"Job match and housing tenure","authors":"N. Coulson, Walter D’Lima, D. Jinkins","doi":"10.1111/1540-6229.12398","DOIUrl":"https://doi.org/10.1111/1540-6229.12398","url":null,"abstract":"","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"44 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83416637","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}
Felix Lorenz, Jonas Willwersch, Marcelo Cajias, Franz Fuerst
Machine Learning (ML) excels at most predictive tasks but its complex nonparametric structure renders it less useful for inference and out-of sample predictions. This article aims to elucidate and enhance the analytical capabilities of ML in real estate through Interpretable ML (IML). Specifically, we compare a hedonic ML approach to a set of model-agnostic interpretation methods. Our results suggest that IML methods permit a peek into the black box of algorithmic decision making by showing the web of associative relationships between variables in greater resolution. In our empirical applications, we confirm that size and age are the most important rent drivers. Further analysis reveals that certain bundles of hedonic characteristics, such as large apartments in historic buildings with balconies located in affluent neighborhoods, attract higher rents than adding up the contributions of each hedonic characteristic. Building age is shown to exhibit a U-shaped pattern in that both the youngest and oldest buildings attract the highest rents. Besides revealing valuable distance decay functions for spatial variables, IML methods are also able to visualise how the strength and interactions of hedonic characteristics change over time, which investors could use to determine the types of assets that perform best at any given stage of the real estate investment cycle.
机器学习（ML）在大多数预测任务中表现出色，但其复杂的非参数结构使其在推理和样本外预测中作用不大。本文旨在通过可解释 ML（IML）来阐明和增强 ML 在房地产领域的分析能力。具体来说，我们将对冲式 ML 方法与一套模型无关的解释方法进行了比较。我们的研究结果表明，IML 方法可以通过更高的分辨率显示变量之间的关联关系网，从而窥探算法决策的黑箱。在我们的经验应用中，我们证实规模和年龄是最重要的租金驱动因素。进一步的分析表明，某些组合的享乐特征（如位于富人区的历史建筑中带有阳台的大公寓）所吸引的租金要高于每个享乐特征所带来的租金总和。建筑年龄显示出一种 U 型模式，即最年轻和最古老的建筑都能吸引最高的租金。除了揭示有价值的空间变量距离衰减函数外，IML 方法还能直观地显示享乐特征的强度和相互作用是如何随时间变化的，投资者可以利用这种方法来确定在房地产投资周期的任何特定阶段表现最佳的资产类型。
{"title":"Interpretable machine learning for real estate market analysis","authors":"Felix Lorenz, Jonas Willwersch, Marcelo Cajias, Franz Fuerst","doi":"10.1111/1540-6229.12397","DOIUrl":"https://doi.org/10.1111/1540-6229.12397","url":null,"abstract":"Machine Learning (ML) excels at most predictive tasks but its complex nonparametric structure renders it less useful for inference and out-of sample predictions. This article aims to elucidate and enhance the analytical capabilities of ML in real estate through Interpretable ML (IML). Specifically, we compare a hedonic ML approach to a set of model-agnostic interpretation methods. Our results suggest that IML methods permit a peek into the black box of algorithmic decision making by showing the web of associative relationships between variables in greater resolution. In our empirical applications, we confirm that size and age are the most important rent drivers. Further analysis reveals that certain bundles of hedonic characteristics, such as large apartments in historic buildings with balconies located in affluent neighborhoods, attract higher rents than adding up the contributions of each hedonic characteristic. Building age is shown to exhibit a U-shaped pattern in that both the youngest and oldest buildings attract the highest rents. Besides revealing valuable distance decay functions for spatial variables, IML methods are also able to visualise how the strength and interactions of hedonic characteristics change over time, which investors could use to determine the types of assets that perform best at any given stage of the real estate investment cycle.","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"120 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139497231","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}
Abstract The liquidity strains that contributed to the meltdown of the mortgage market in the Global Financial Crisis (GFC) re‐emerged in the Coronavirus 2019 (COVID‐19) Crisis. Some of these strains were acute. For example, the dependence of mortgage real estate investment trusts (REITs) on short‐term funding amplified market disruption in March 2020. However, other liquidity pressures had only minor repercussions for the overall mortgage market because of reforms since the GFC, a heavy government presence, and strong house prices. The lackluster performance of the private‐label mortgage‐backed securities market provides a glimpse of how the market might have performed in the absence of the heavy government presence.
{"title":"Liquidity in the mortgage market: How does the COVID‐19 crisis compare with the global financial crisis?","authors":"Karen Pence","doi":"10.1111/1540-6229.12389","DOIUrl":"https://doi.org/10.1111/1540-6229.12389","url":null,"abstract":"Abstract The liquidity strains that contributed to the meltdown of the mortgage market in the Global Financial Crisis (GFC) re‐emerged in the Coronavirus 2019 (COVID‐19) Crisis. Some of these strains were acute. For example, the dependence of mortgage real estate investment trusts (REITs) on short‐term funding amplified market disruption in March 2020. However, other liquidity pressures had only minor repercussions for the overall mortgage market because of reforms since the GFC, a heavy government presence, and strong house prices. The lackluster performance of the private‐label mortgage‐backed securities market provides a glimpse of how the market might have performed in the absence of the heavy government presence.","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"20 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87526491","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}
Rohan Ganduri, Steven Chong Xiao, Serena Wenjing Xiao
We show that profit-seeking institutional investors provide valuable liquidity and spur the recovery of distressed housing markets. Using a quasi-natural experiment wherein investors purchased prepackaged distressed home portfolios from government-sponsored enterprises, we find that transaction prices of properties located within 0.25 miles of bulk-sale properties increased by 1.4% more than homes located farther away. This positive price spillover effect helped reverse the discounts at which such properties were being sold prior to the bulk-sale event. The price spillover effect due to the bulk-sale event is greater for foreclosed homes (4.1%), homes similar to the bulk-sale homes (2.5%), and homes in highly distressed neighborhoods (7.0%). Our results highlight asset disposition through pooling and institutional participation as a potential market-driven channel for the recovery of distressed housing markets.
{"title":"Tracing the source of liquidity for distressed housing markets","authors":"Rohan Ganduri, Steven Chong Xiao, Serena Wenjing Xiao","doi":"10.1111/1540-6229.12388","DOIUrl":"https://doi.org/10.1111/1540-6229.12388","url":null,"abstract":"We show that profit-seeking institutional investors provide valuable liquidity and spur the recovery of distressed housing markets. Using a quasi-natural experiment wherein investors purchased prepackaged distressed home portfolios from government-sponsored enterprises, we find that transaction prices of properties located within 0.25 miles of bulk-sale properties increased by 1.4% <i>more</i> than homes located farther away. This positive price spillover effect helped reverse the discounts at which such properties were being sold prior to the bulk-sale event. The price spillover effect due to the bulk-sale event is greater for foreclosed homes (4.1%), homes similar to the bulk-sale homes (2.5%), and homes in highly distressed neighborhoods (7.0%). Our results highlight asset disposition through pooling and institutional participation as a potential market-driven channel for the recovery of distressed housing markets.","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"345 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139497233","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}
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