Abstract We exploit the 2007 private label securitization (PLS) freeze as a quasi‐experiment to study the impact of a negative credit supply shock on home purchases and borrowing behavior. Using a difference‐in‐differences estimator, we show that a negative supply shock to first‐lien mortgages has little impact on the volume of purchases financed with a mortgage, but significantly reduces the average first‐lien loan balance. Much of this reduction in loan balances is the result of increased bunching at the conforming loan limit that is achieved through a combination of greater second mortgage utilization and larger downpayments. Importantly, we find significant heterogeneity in the response to the mortgage supply shock across borrower characteristics and house price levels. Home purchase volume does decline after the shock for less creditworthy borrowers and in expensive locations. The reduction in first‐lien balances is fairly uniform across borrower types, however, the effect is slightly more acute in less expensive areas. Our results suggest that financial market frictions (e.g., downpayment constraints, imperfect credit) play an important role in determining how credit supply shocks impact housing purchases and borrowing behavior.
{"title":"Credit supply shocks, home purchase volume, and borrowing behavior","authors":"James N. Conklin, Haoyang Liu, Calvin Zhang","doi":"10.1111/1540-6229.12462","DOIUrl":"https://doi.org/10.1111/1540-6229.12462","url":null,"abstract":"Abstract We exploit the 2007 private label securitization (PLS) freeze as a quasi‐experiment to study the impact of a negative credit supply shock on home purchases and borrowing behavior. Using a difference‐in‐differences estimator, we show that a negative supply shock to first‐lien mortgages has little impact on the volume of purchases financed with a mortgage, but significantly reduces the average first‐lien loan balance. Much of this reduction in loan balances is the result of increased bunching at the conforming loan limit that is achieved through a combination of greater second mortgage utilization and larger downpayments. Importantly, we find significant heterogeneity in the response to the mortgage supply shock across borrower characteristics and house price levels. Home purchase volume does decline after the shock for less creditworthy borrowers and in expensive locations. The reduction in first‐lien balances is fairly uniform across borrower types, however, the effect is slightly more acute in less expensive areas. Our results suggest that financial market frictions (e.g., downpayment constraints, imperfect credit) play an important role in determining how credit supply shocks impact housing purchases and borrowing behavior.","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"62 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":"135483211","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}
William T. Hughes, David C. Ling, Sugata Ray, Luqi Xu
Abstract Daily‐priced real estate (DPRE) funds are designed to provide investors with daily liquidity while investing in illiquid private assets. DPRE fund returns are predictable, allowing for a trading strategy based on predicted returns to generate trading profits of 60–132 bps a year. Funds with higher predicted returns have higher investor flows, but the flow‐to‐future predicted performance relationship is no stronger for DPRE funds with higher return predictability than those with lower return predictability. This appears to be the result of trading constraints on highly predictable institutional DPRE funds. Even modest trading restrictions on monthly redemptions render profits from trading strategies based on return predictability economically insignificant.
{"title":"Price predictability in liquid funds with illiquid underlying assets","authors":"William T. Hughes, David C. Ling, Sugata Ray, Luqi Xu","doi":"10.1111/1540-6229.12460","DOIUrl":"https://doi.org/10.1111/1540-6229.12460","url":null,"abstract":"Abstract Daily‐priced real estate (DPRE) funds are designed to provide investors with daily liquidity while investing in illiquid private assets. DPRE fund returns are predictable, allowing for a trading strategy based on predicted returns to generate trading profits of 60–132 bps a year. Funds with higher predicted returns have higher investor flows, but the flow‐to‐future predicted performance relationship is no stronger for DPRE funds with higher return predictability than those with lower return predictability. This appears to be the result of trading constraints on highly predictable institutional DPRE funds. Even modest trading restrictions on monthly redemptions render profits from trading strategies based on return predictability economically insignificant.","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"80 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":"135696257","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 Using a unique administrative panel data from Denmark, this article documents the dynamic evolution of households' financial wealth, the equity market participation rate (extensive margin), and the conditional risky asset share of financial wealth (intensive margin) over a 7‐year period around a house purchase. We find that households' equity market participation rate falls during the year of house purchase. Conditional on participation, the risky asset share of financial wealth follows a V‐shape around the house purchase. It decreases and reaches the lowest point 1 year before a house purchase, but jumps up immediately after. This finding suggests that of the three channels identified in the literature that are related to the risky asset demand after a house purchase, the debt retirement channel and the diversification effect dominate the liquidity concern.
{"title":"Household portfolio choice before and after a house purchase","authors":"Ran Sun Lyng, Jie Zhou","doi":"10.1111/1540-6229.12459","DOIUrl":"https://doi.org/10.1111/1540-6229.12459","url":null,"abstract":"Abstract Using a unique administrative panel data from Denmark, this article documents the dynamic evolution of households' financial wealth, the equity market participation rate (extensive margin), and the conditional risky asset share of financial wealth (intensive margin) over a 7‐year period around a house purchase. We find that households' equity market participation rate falls during the year of house purchase. Conditional on participation, the risky asset share of financial wealth follows a V‐shape around the house purchase. It decreases and reaches the lowest point 1 year before a house purchase, but jumps up immediately after. This finding suggests that of the three channels identified in the literature that are related to the risky asset demand after a house purchase, the debt retirement channel and the diversification effect dominate the liquidity concern.","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135476198","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 Redlining refers to discriminatory lending practices based on the demographic composition of neighborhoods. The term is often attributed to boundaries drawn on maps by the Home Owners’ Loan Corporation (HOLC) in the 1930s to represent the perceived credit risk of neighborhoods. Combined with other discriminatory actions, redlining restricted access to mortgage financing for racial minorities, and areas subject to historic redlining practices still exhibit worse outcomes on various socio‐economic dimensions. This study examines contemporary differences in residential housing values along historic redlined boundaries. Boundary fixed effects models are constructed using contemporary property sale data for Seattle, WA and Richmond, VA from 2000 to 2018. Results indicate that properties inside a redlined boundary continue to sell at significantly discounted prices compared to houses across the redlined border. Further investigation, using historic data from the 1930s and 1940s, finds that there was also a large and significant historic difference in housing values across the redlined boundaries at that time, including before the advent of HOLC maps. This suggests that contemporary differences in housing values are likely not a direct effect of HOLC maps but rather depict the lingering effect of broader redlining and discriminatory practices that existed before the advent of these maps.
{"title":"Contemporary differences in residential housing values along historic redlining boundaries","authors":"Aakrit Joshi, Brady P. Horn, Robert P. Berrens","doi":"10.1111/1540-6229.12458","DOIUrl":"https://doi.org/10.1111/1540-6229.12458","url":null,"abstract":"Abstract Redlining refers to discriminatory lending practices based on the demographic composition of neighborhoods. The term is often attributed to boundaries drawn on maps by the Home Owners’ Loan Corporation (HOLC) in the 1930s to represent the perceived credit risk of neighborhoods. Combined with other discriminatory actions, redlining restricted access to mortgage financing for racial minorities, and areas subject to historic redlining practices still exhibit worse outcomes on various socio‐economic dimensions. This study examines contemporary differences in residential housing values along historic redlined boundaries. Boundary fixed effects models are constructed using contemporary property sale data for Seattle, WA and Richmond, VA from 2000 to 2018. Results indicate that properties inside a redlined boundary continue to sell at significantly discounted prices compared to houses across the redlined border. Further investigation, using historic data from the 1930s and 1940s, finds that there was also a large and significant historic difference in housing values across the redlined boundaries at that time, including before the advent of HOLC maps. This suggests that contemporary differences in housing values are likely not a direct effect of HOLC maps but rather depict the lingering effect of broader redlining and discriminatory practices that existed before the advent of these maps.","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"95 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":"136374475","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 This study demonstrates that the housing market can incorporate information quickly instead of slowly over time, using Amazon's gradual revelation of its new headquarters locations in Virginia and New York. Spatial difference‐in‐differences analysis shows that housing prices near the Virginia headquarters exhibit 4.9% premia months before the decision, while price premia for New York reach 17.5% before the decision but disappear upon cancellation. The absence of significant effects on transaction volume, construction, or price premia for other finalist cities rules out the possibility of speculation. Overall, this study provides a counterpoint to the commonly held belief that the real estate market is always slow to respond to information about future demand shocks.
{"title":"Amazon is coming to town: Sequential information revelation in the housing market","authors":"Yifan Chen, Sean Wilkoff, Jiro Yoshida","doi":"10.1111/1540-6229.12457","DOIUrl":"https://doi.org/10.1111/1540-6229.12457","url":null,"abstract":"Abstract This study demonstrates that the housing market can incorporate information quickly instead of slowly over time, using Amazon's gradual revelation of its new headquarters locations in Virginia and New York. Spatial difference‐in‐differences analysis shows that housing prices near the Virginia headquarters exhibit 4.9% premia months before the decision, while price premia for New York reach 17.5% before the decision but disappear upon cancellation. The absence of significant effects on transaction volume, construction, or price premia for other finalist cities rules out the possibility of speculation. Overall, this study provides a counterpoint to the commonly held belief that the real estate market is always slow to respond to information about future demand shocks.","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135885541","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 Nonbank mortgage originators, which operate through the originate‐to‐distribute (OTD) model, account for more than half of all the mortgage origination in the United States. However, less is known about which factors drive the quality of mortgage originations through nonbanks. I show that an exogenous shock that reduced collateral risk for funding intermediaries of nonbank mortgage originators led to a greater issuance of riskier mortgages that culminated in 10–30% higher ex post defaults. These results show how the quality of mortgage origination in the OTD model of nonbanks is affected by the collateral risk borne by their funding intermediaries. Overall, the results highlight funding intermediaries' monitoring incentives as one of the factors that drive the quality of mortgage originations through nonbanks .
{"title":"What drives screening incentives in nonbank mortgage originators?","authors":"Rohan Ganduri","doi":"10.1111/1540-6229.12456","DOIUrl":"https://doi.org/10.1111/1540-6229.12456","url":null,"abstract":"Abstract Nonbank mortgage originators, which operate through the originate‐to‐distribute (OTD) model, account for more than half of all the mortgage origination in the United States. However, less is known about which factors drive the quality of mortgage originations through nonbanks. I show that an exogenous shock that reduced collateral risk for funding intermediaries of nonbank mortgage originators led to a greater issuance of riskier mortgages that culminated in 10–30% higher ex post defaults. These results show how the quality of mortgage origination in the OTD model of nonbanks is affected by the collateral risk borne by their funding intermediaries. Overall, the results highlight funding intermediaries' monitoring incentives as one of the factors that drive the quality of mortgage originations through nonbanks .","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135048215","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 We identify occupancy fraud—borrowers who misrepresent their occupancy status as owner‐occupants rather than investors—in residential mortgage originations. Unlike previous work, we show that fraud was prevalent in originations not just during the housing bubble but also persists through more recent times. We also demonstrate that fraud is broad‐based and appears in government‐sponsored enterprise and bank portfolio loans, not just in private securitization; these fraudulent borrowers make up one third of the effective investor population. Occupancy frauds obtain credit at lower interest rates, suggesting a motivation for undertaking fraud. These fraudulent borrowers perform substantially worse than similar declared investors, defaulting at a 75% higher rate. We also provide evidence consistent with fraudulent borrowers’ defaults being more “strategic,” suggesting that this population poses a risk in the face of declining house prices.
{"title":"Owner‐occupancy fraud and mortgage performance","authors":"Ronel Elul, Aaron Payne, Sebastian Tilson","doi":"10.1111/1540-6229.12455","DOIUrl":"https://doi.org/10.1111/1540-6229.12455","url":null,"abstract":"Abstract We identify occupancy fraud—borrowers who misrepresent their occupancy status as owner‐occupants rather than investors—in residential mortgage originations. Unlike previous work, we show that fraud was prevalent in originations not just during the housing bubble but also persists through more recent times. We also demonstrate that fraud is broad‐based and appears in government‐sponsored enterprise and bank portfolio loans, not just in private securitization; these fraudulent borrowers make up one third of the effective investor population. Occupancy frauds obtain credit at lower interest rates, suggesting a motivation for undertaking fraud. These fraudulent borrowers perform substantially worse than similar declared investors, defaulting at a 75% higher rate. We also provide evidence consistent with fraudulent borrowers’ defaults being more “strategic,” suggesting that this population poses a risk in the face of declining house prices.","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135889712","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 examines how the disclosure of local gun‐ownership information affects property values. Using the sudden disclosure of a gun‐ownership map in two New York counties, we explore how home sellers respond to this exogenous information shock. Our results show that an additional permit holder in the neighborhood leads to a 1% decrease in housing prices after the disclosure. This effect is highly localized in that property values are only negatively impacted by gun‐permit holders within 0.1 mi of the focal property. These findings highlight the negative effect of the disclosure of gun‐ownership information on localized home prices.
{"title":"Gun‐ownership disclosure and localized home prices","authors":"Michael J. Seiler, Liuming Yang","doi":"10.1111/1540-6229.12454","DOIUrl":"https://doi.org/10.1111/1540-6229.12454","url":null,"abstract":"This article examines how the disclosure of local gun‐ownership information affects property values. Using the sudden disclosure of a gun‐ownership map in two New York counties, we explore how home sellers respond to this exogenous information shock. Our results show that an additional permit holder in the neighborhood leads to a 1% decrease in housing prices after the disclosure. This effect is highly localized in that property values are only negatively impacted by gun‐permit holders within 0.1 mi of the focal property. These findings highlight the negative effect of the disclosure of gun‐ownership information on localized home prices.","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"37 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75128350","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 estimate nonmarket values for natural views in an urban setting. These views contain the aesthetics of natural areas commonly found in public parks and open space, and offer an aspect of property valuation that previous research is unable to disentangle from proximity to parks and open space. We incorporate machine learning techniques on Google Street View images to identify natural views in an urban setting. We find positive capitalization rates associated with household views of park‐like properties. Estimates are robust to a variety of specifications, including models that are identified off of new developments on neighboring properties and falsification tests that help to rule out the effect of a broader neighborhood environment. From a policy perspective, our results inform as to the optimal size, location, and shape of open space. Furthermore, machine learning methods used in the construction of our view variable provide a potentially powerful tool for other nonmarket valuation studies.
{"title":"The amenity value of natural views","authors":"Timothy L. Hamilton, Erik B. Johnson","doi":"10.1111/1540-6229.12451","DOIUrl":"https://doi.org/10.1111/1540-6229.12451","url":null,"abstract":"We estimate nonmarket values for natural views in an urban setting. These views contain the aesthetics of natural areas commonly found in public parks and open space, and offer an aspect of property valuation that previous research is unable to disentangle from proximity to parks and open space. We incorporate machine learning techniques on Google Street View images to identify natural views in an urban setting. We find positive capitalization rates associated with household views of park‐like properties. Estimates are robust to a variety of specifications, including models that are identified off of new developments on neighboring properties and falsification tests that help to rule out the effect of a broader neighborhood environment. From a policy perspective, our results inform as to the optimal size, location, and shape of open space. Furthermore, machine learning methods used in the construction of our view variable provide a potentially powerful tool for other nonmarket valuation studies.","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"64 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89685750","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 heterogeneous impact of house purchase limits policy on housing prices: Comparison between elite and non‐elite school district houses","authors":"Yongbin Huang, Hai Hong","doi":"10.1111/1540-6229.12452","DOIUrl":"https://doi.org/10.1111/1540-6229.12452","url":null,"abstract":"","PeriodicalId":47731,"journal":{"name":"Real Estate Economics","volume":"298 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78326579","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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