We analyse the cross-country dimension of financial cycles by studying cyclical co-movements in credit, house prices, equity prices and interest rates across the G7 economies. We use wavelet-based statistics to assess at which frequencies cyclical fluctuations and their crosscountry co-movements are important and how these change over time. We show cycles in interest rates and equity prices to be at least as synchronised as cycles in real GDP while cycles in credit and house prices are less synchronised. As a result, cross-country common cycles in equity prices and long-term interest rates account for a larger share of the volatility of these variables at the country level than common cycles in credit aggregates and house prices. A cluster analysis shows a high degree of similarity in the spectral characteristics of cycles in interest rates and equity prices across all countries but less similarities for cycles in credit and house price. For credit and house price cycles country-specific developments turn out to be more important than the common cross-country cycles.
{"title":"Financial Cycles Across G7 Economies: A View from Wavelet Analysis","authors":"Martin Mandler, Michael Scharnagl","doi":"10.2139/ssrn.3422650","DOIUrl":"https://doi.org/10.2139/ssrn.3422650","url":null,"abstract":"We analyse the cross-country dimension of financial cycles by studying cyclical co-movements in credit, house prices, equity prices and interest rates across the G7 economies. We use wavelet-based statistics to assess at which frequencies cyclical fluctuations and their crosscountry co-movements are important and how these change over time. We show cycles in interest rates and equity prices to be at least as synchronised as cycles in real GDP while cycles in credit and house prices are less synchronised. As a result, cross-country common cycles in equity prices and long-term interest rates account for a larger share of the volatility of these variables at the country level than common cycles in credit aggregates and house prices. A cluster analysis shows a high degree of similarity in the spectral characteristics of cycles in interest rates and equity prices across all countries but less similarities for cycles in credit and house price. For credit and house price cycles country-specific developments turn out to be more important than the common cross-country cycles.","PeriodicalId":21047,"journal":{"name":"Real Estate eJournal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89449694","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}
This is a simple practice undertaking assessing Lithuanian housing market for bubble. A triangulation of historical comparison and Price to Income Ratio are used to screen the market. The overall estimates suggest that current house prices in Lithuania are within historical averages and statistical thresholds. Housing is certainly not in a bubble. Considering market prospects, prices have room for further inflation, ceteris paribus. Prospective buyers are advised to enter the market even though current house price levels may seem elevated for some, whereas the best time to buy a property was twenty years ago anyway. For institutions that have a long-term investment horizon, multifamily in key Lithuanian cities is an attractive investment conduit.
{"title":"Assessing Lithuanian housing market for bubble","authors":"Arvydas Jadevicius","doi":"10.2139/ssrn.3947661","DOIUrl":"https://doi.org/10.2139/ssrn.3947661","url":null,"abstract":"This is a simple practice undertaking assessing Lithuanian housing market for bubble. A triangulation of historical comparison and Price to Income Ratio are used to screen the market. The overall estimates suggest that current house prices in Lithuania are within historical averages and statistical thresholds. Housing is certainly not in a bubble. Considering market prospects, prices have room for further inflation, ceteris paribus. Prospective buyers are advised to enter the market even though current house price levels may seem elevated for some, whereas the best time to buy a property was twenty years ago anyway. For institutions that have a long-term investment horizon, multifamily in key Lithuanian cities is an attractive investment conduit.","PeriodicalId":21047,"journal":{"name":"Real Estate eJournal","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75569522","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}
This article investigates how the market valuation of properties is related to the income growth of their asset locations. Based on the income tax data from the Internal Revenue Service (IRS) and the individual property information of U.S. equity real estate investment trusts (REITs) from 2000-2018, the article constructs an aggregated measure of household income growth for each REIT based on its asset locations in different metropolitan areas. The paper adopts an identification strategy that links household income shocks to real estate value. First, it shows that REITs with more properties located in high household income growth areas are associated with lower cap rates (higher market valuation). Then, it illustrates that household income growth positively affects REITs' firm value (measured as firm Q) and shareholder value (measured as market-to-book equity ratio). Moreover, the magnitude of the impact on real estate value from wages & salaries growth is much higher than from investment income growth. Further analysis provides evidence that REITs with more properties located in high income growth areas have, on average, higher occupancy rates and that the main results are robust when a different empirical approach is used. These findings suggest that local residents' income matters and should be considered in real estate portfolio construction and operation.
{"title":"Household Income, Asset Location and Real Estate Value: Evidence from REITs","authors":"Zifeng Feng","doi":"10.2139/ssrn.3828223","DOIUrl":"https://doi.org/10.2139/ssrn.3828223","url":null,"abstract":"This article investigates how the market valuation of properties is related to the income growth of their asset locations. Based on the income tax data from the Internal Revenue Service (IRS) and the individual property information of U.S. equity real estate investment trusts (REITs) from 2000-2018, the article constructs an aggregated measure of household income growth for each REIT based on its asset locations in different metropolitan areas. The paper adopts an identification strategy that links household income shocks to real estate value. First, it shows that REITs with more properties located in high household income growth areas are associated with lower cap rates (higher market valuation). Then, it illustrates that household income growth positively affects REITs' firm value (measured as firm Q) and shareholder value (measured as market-to-book equity ratio). Moreover, the magnitude of the impact on real estate value from wages & salaries growth is much higher than from investment income growth. Further analysis provides evidence that REITs with more properties located in high income growth areas have, on average, higher occupancy rates and that the main results are robust when a different empirical approach is used. These findings suggest that local residents' income matters and should be considered in real estate portfolio construction and operation.","PeriodicalId":21047,"journal":{"name":"Real Estate eJournal","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88083665","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}
Different industries exhibit significantly different leverage - the REIT sector is an extreme example. Their leverage ratio is twice as high as that of non-real estate firms in the U.S. We theoretically and empirically analyse why we observe a leverage ratio difference of 25.5 percentage points between these two groups. Firstly, we find that tangibility and operating risk are the most important capital structure determinants for deviation. By decomposing the difference into three channels (differences in determinants’ average values, varying sensitivities to changes in the values of the determinants and an industry-specific fixed effect), we find that the industry-specific channel explains around 67% of the difference. The value-based channel is mostly responsible for the remaining part. However, when comparing samples of REITs and non-real estate firms matched according to tangibility and operating risk in order to take non-linear influences of extreme values into account, the relevance of the industry-specific channel is considerably reduced. Therefore, the REIT debt puzzle is not mainly a consequence of an unexplainable industry-specific fixed effect but, with careful analysis, can ultimately be traced back almost completely to a value-based effect driven by the characteristics of tangible assets and stock returns’ risk.
{"title":"Decomposing Industry Leverage in the U.S.: the REIT Debt Puzzle","authors":"Wolfgang Breuer, L. Nguyen, Bertram I. Steininger","doi":"10.2139/ssrn.3259946","DOIUrl":"https://doi.org/10.2139/ssrn.3259946","url":null,"abstract":"Different industries exhibit significantly different leverage - the REIT sector is an extreme example. Their leverage ratio is twice as high as that of non-real estate firms in the U.S. We theoretically and empirically analyse why we observe a leverage ratio difference of 25.5 percentage points between these two groups. Firstly, we find that tangibility and operating risk are the most important capital structure determinants for deviation. By decomposing the difference into three channels (differences in determinants’ average values, varying sensitivities to changes in the values of the determinants and an industry-specific fixed effect), we find that the industry-specific channel explains around 67% of the difference. The value-based channel is mostly responsible for the remaining part. However, when comparing samples of REITs and non-real estate firms matched according to tangibility and operating risk in order to take non-linear influences of extreme values into account, the relevance of the industry-specific channel is considerably reduced. Therefore, the REIT debt puzzle is not mainly a consequence of an unexplainable industry-specific fixed effect but, with careful analysis, can ultimately be traced back almost completely to a value-based effect driven by the characteristics of tangible assets and stock returns’ risk.","PeriodicalId":21047,"journal":{"name":"Real Estate eJournal","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84513642","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}
Philip D. Bunn, J. Chadha, Thomas Lazarowicz, S. Millard, E. Rockall
In this paper, we first develop a theoretical framework with three types of household: outright homeowners, mortgagors and renters. We then examine empirically how household debt affects the response of labour supply to shocks to income, mortgage interest rates and house prices for each type of household. In line with our framework, we find that negative income shocks lead to lower participation among outright homeowners while increasing mortgagors’ desired hours; surprise rises in interest rates lead to increases in desired hours that are larger the higher is the household’s debt level; and falls in house prices increase mortgagors’ desired hours.
{"title":"Household Debt and Labour Supply","authors":"Philip D. Bunn, J. Chadha, Thomas Lazarowicz, S. Millard, E. Rockall","doi":"10.2139/ssrn.3936001","DOIUrl":"https://doi.org/10.2139/ssrn.3936001","url":null,"abstract":"In this paper, we first develop a theoretical framework with three types of household: outright homeowners, mortgagors and renters. We then examine empirically how household debt affects the response of labour supply to shocks to income, mortgage interest rates and house prices for each type of household. In line with our framework, we find that negative income shocks lead to lower participation among outright homeowners while increasing mortgagors’ desired hours; surprise rises in interest rates lead to increases in desired hours that are larger the higher is the household’s debt level; and falls in house prices increase mortgagors’ desired hours.","PeriodicalId":21047,"journal":{"name":"Real Estate eJournal","volume":"8 1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83405142","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}
Jaclene Begley, Hamilton B. Fout, Michael LaCour-Little, Nuno Mota
Expanding sustainable homeownership opportunities for lower-income households has long been a housing policy goal. In this paper, we benchmark performance of HomeReady®, a new product targeted at such households, against other low-down payment loan types. Results show that HomeReady® loans have lower relative odds of 90-day delinquency or prepayment compared to FHA or VA loans, and similar performance to HFA loans. Robustness tests focusing on lower income borrowers, lender specialization, and loans to borrowers on the margin between FHA and HomeReady® in terms of pricing yield similar results. Together, these findings suggest that well-designed conventional products to address low- and moderate-income household needs can promote sustainable homeownership.
{"title":"Benchmarking a New Affordable Home Mortgage","authors":"Jaclene Begley, Hamilton B. Fout, Michael LaCour-Little, Nuno Mota","doi":"10.2139/ssrn.3910816","DOIUrl":"https://doi.org/10.2139/ssrn.3910816","url":null,"abstract":"Expanding sustainable homeownership opportunities for lower-income households has long been a housing policy goal. In this paper, we benchmark performance of HomeReady®, a new product targeted at such households, against other low-down payment loan types. Results show that HomeReady® loans have lower relative odds of 90-day delinquency or prepayment compared to FHA or VA loans, and similar performance to HFA loans. Robustness tests focusing on lower income borrowers, lender specialization, and loans to borrowers on the margin between FHA and HomeReady® in terms of pricing yield similar results. Together, these findings suggest that well-designed conventional products to address low- and moderate-income household needs can promote sustainable homeownership.","PeriodicalId":21047,"journal":{"name":"Real Estate eJournal","volume":"146 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74698322","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}
We study the propagation of valuation errors through house prices. Verifying prior research, we first show that house sellers and landlords exhibit long memory: those having purchased when aggregate prices were high (low) ask, and obtain, abnormally high (low) prices and rents many years later. These distortions alter the strategies of nearby sellers and landlords, irrespective of their own historical purchase timing. If competing with one or more “bust-acquired” houses bought from 2008-2012, sellers and landlords accept discounts exceeding 1%. Although bust-acquired houses constitute less than ten percent of all sales, spillovers through competition appear to have aggregate effects. Zip codes with more bust acquired houses are associated with lower prices and rents per square foot.
{"title":"Propagating Experiences by Competing: Micro-Level Evidence from Real Estate","authors":"M. Giacoletti, Christopher Parsons","doi":"10.2139/ssrn.3875752","DOIUrl":"https://doi.org/10.2139/ssrn.3875752","url":null,"abstract":"We study the propagation of valuation errors through house prices. Verifying prior research, we first show that house sellers and landlords exhibit long memory: those having purchased when aggregate prices were high (low) ask, and obtain, abnormally high (low) prices and rents many years later. These distortions alter the strategies of nearby sellers and landlords, irrespective of their own historical purchase timing. If competing with one or more “bust-acquired” houses bought from 2008-2012, sellers and landlords accept discounts exceeding 1%. Although bust-acquired houses constitute less than ten percent of all sales, spillovers through competition appear to have aggregate effects. Zip codes with more bust acquired houses are associated with lower prices and rents per square foot.","PeriodicalId":21047,"journal":{"name":"Real Estate eJournal","volume":"263 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76717059","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}
Recurrent list-price reductions of a house may signal a movement towards fair pricing or underpricing, and the impatience of sellers to enter a sell transaction more quickly. Recurrent list-price reductions may also provide a market signal that the listings are problematic and thus harder to sell in the absence of a list-price reduction. Considering the inter-dependence among recurrent list-price reductions and the dependence between the recurrent reductions and the sold event which bias the results from a standard survival analysis, this paper uses the joint frailty model to investigate the two conflicting signaling effects of list-price reductions on the likelihood of a house sale. Our novel dataset contains the time-dated recurrent list-price reductions for each house listed on the market. The results from the joint frailty model show time-varying negative impacts of list-price reductions on the likelihood of a house sale, supporting the negative signaling effects of recurrent list-price reductions.
{"title":"Signaling Effects of Recurrent List-price Reductions on the Likelihood of House Sales","authors":"L. Kryzanowski, Yanting Wu","doi":"10.2139/ssrn.3879795","DOIUrl":"https://doi.org/10.2139/ssrn.3879795","url":null,"abstract":"Recurrent list-price reductions of a house may signal a movement towards fair pricing or underpricing, and the impatience of sellers to enter a sell transaction more quickly. Recurrent list-price reductions may also provide a market signal that the listings are problematic and thus harder to sell in the absence of a list-price reduction. Considering the inter-dependence among recurrent list-price reductions and the dependence between the recurrent reductions and the sold event which bias the results from a standard survival analysis, this paper uses the joint frailty model to investigate the two conflicting signaling effects of list-price reductions on the likelihood of a house sale. Our novel dataset contains the time-dated recurrent list-price reductions for each house listed on the market. The results from the joint frailty model show time-varying negative impacts of list-price reductions on the likelihood of a house sale, supporting the negative signaling effects of recurrent list-price reductions.","PeriodicalId":21047,"journal":{"name":"Real Estate eJournal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72551681","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}
Gennaro Catapano, Francesco Franceschi, M. Loberto, V. Michelangeli
In this paper, we extend and calibrate with Italian data the Agent-based model of the real estate sector described in Baptista et al., 2016. We design a novel calibration methodology that is built on a multivariate moment-based measure and a set of three search algorithms: a low discrepancy series, a machine learning surrogate and a genetic algorithm. The calibrated and validated model is then used to evaluate the effects of three hypothetical borrower-based macroprudential policies: an 80 per cent loan-to-value cap, a 30 per cent cap on the loan-service-to-income ratio and a combination of both policies. We find that, within our framework, these policy interventions tend to slow down the credit cycle and reduce the probability of defaults on mortgages. However, with respect to the Italian housing market, we only find very small effects over a five-year horizon on both property prices and mortgage defaults. This latter result is consistent with the view that the Italian household sector is financially sound. Finally, we find that restrictive policies lead to a shift in demand toward lower quality dwellings.
{"title":"Macroprudential Policy Analysis via an Agent Based Model of the Real Estate Sector","authors":"Gennaro Catapano, Francesco Franceschi, M. Loberto, V. Michelangeli","doi":"10.2139/ssrn.3891583","DOIUrl":"https://doi.org/10.2139/ssrn.3891583","url":null,"abstract":"In this paper, we extend and calibrate with Italian data the Agent-based model of the real estate sector described in Baptista et al., 2016. We design a novel calibration methodology that is built on a multivariate moment-based measure and a set of three search algorithms: a low discrepancy series, a machine learning surrogate and a genetic algorithm. The calibrated and validated model is then used to evaluate the effects of three hypothetical borrower-based macroprudential policies: an 80 per cent loan-to-value cap, a 30 per cent cap on the loan-service-to-income ratio and a combination of both policies. We find that, within our framework, these policy interventions tend to slow down the credit cycle and reduce the probability of defaults on mortgages. However, with respect to the Italian housing market, we only find very small effects over a five-year horizon on both property prices and mortgage defaults. This latter result is consistent with the view that the Italian household sector is financially sound. Finally, we find that restrictive policies lead to a shift in demand toward lower quality dwellings.","PeriodicalId":21047,"journal":{"name":"Real Estate eJournal","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83866674","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}
We study the genesis of the 2000s housing boom in Denmark, a country with a similar mortgage-finance system to the U.S., but with strictly enforced recourse borrowing and a robust regulatory mortgage lending framework that limits housing speculation. The rapid legalization of interest-only (IO) mortgages ignited the boom. Due to their introduction, house prices increased 36 percent, with larger impacts in areas with greater ex-ante benefits of such mortgages. These results are congruent with IO mortgages easing debt-service burdens in a wide-scale credit supply expansion, which in turn fueled house price expectations and the further use of alternative mortgage products.
{"title":"Mortgage Innovation and House Price Booms","authors":"Claes Bäckman, Chandler Lutz","doi":"10.2139/ssrn.2699824","DOIUrl":"https://doi.org/10.2139/ssrn.2699824","url":null,"abstract":"We study the genesis of the 2000s housing boom in Denmark, a country with a similar mortgage-finance system to the U.S., but with strictly enforced recourse borrowing and a robust regulatory mortgage lending framework that limits housing speculation. The rapid legalization of interest-only (IO) mortgages ignited the boom. Due to their introduction, house prices increased 36 percent, with larger impacts in areas with greater ex-ante benefits of such mortgages. These results are congruent with IO mortgages easing debt-service burdens in a wide-scale credit supply expansion, which in turn fueled house price expectations and the further use of alternative mortgage products.","PeriodicalId":21047,"journal":{"name":"Real Estate eJournal","volume":"121 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75964968","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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