This paper uses a unique dataset containing property values and manually collected noise measurements in Memphis, Tennessee to estimate the impact of train noise pollution on commercial and residential property values. Results show that a residential property exposed to 65 decibels or greater of railroad noise results in a 14 to 18 percent decrease in property value. Once a 65 decibel measure is included, there is no additional impact on price of distance to the closest railroad crossing. For commercial property, neither crossing proximity nor noise level significantly affect property value. The results provide evidence of a negative externality that is created by railroad noise for households and the need for more exact measures of noise levels. The findings are also consistent with previous literature suggesting firms have different ideas than individuals about desirable locational attributes.
{"title":"Silence is Golden: Railroad Noise Pollution and Property Values","authors":"Jay K. Walker","doi":"10.2139/ssrn.2622947","DOIUrl":"https://doi.org/10.2139/ssrn.2622947","url":null,"abstract":"This paper uses a unique dataset containing property values and manually collected noise measurements in Memphis, Tennessee to estimate the impact of train noise pollution on commercial and residential property values. Results show that a residential property exposed to 65 decibels or greater of railroad noise results in a 14 to 18 percent decrease in property value. Once a 65 decibel measure is included, there is no additional impact on price of distance to the closest railroad crossing. For commercial property, neither crossing proximity nor noise level significantly affect property value. The results provide evidence of a negative externality that is created by railroad noise for households and the need for more exact measures of noise levels. The findings are also consistent with previous literature suggesting firms have different ideas than individuals about desirable locational attributes.","PeriodicalId":12014,"journal":{"name":"ERN: Microeconometric Studies of Housing Markets (Topic)","volume":"75 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80899518","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 paper analyzes for the Netherlands the need to introduce flexible take-ups of home equity and pension wealth, complementary to recent reforms in Dutch pensions and mortgages. The young may gain from supplementing a possible pension shortfall with additional retirement income from reverse mortgage contracts. The elderly may benefit of the innovation of partial lump sum of accrued pension rights in order to partly redeem mortgage debt, whilst maintaining an adequate net replacement rate from pensions.
{"title":"The Need for Flexible Take-Ups of Home Equity and Pension Wealth in Retirement","authors":"Jori Arts, Eduard H. M. Ponds","doi":"10.2139/ssrn.2727781","DOIUrl":"https://doi.org/10.2139/ssrn.2727781","url":null,"abstract":"This paper analyzes for the Netherlands the need to introduce flexible take-ups of home equity and pension wealth, complementary to recent reforms in Dutch pensions and mortgages. The young may gain from supplementing a possible pension shortfall with additional retirement income from reverse mortgage contracts. The elderly may benefit of the innovation of partial lump sum of accrued pension rights in order to partly redeem mortgage debt, whilst maintaining an adequate net replacement rate from pensions.","PeriodicalId":12014,"journal":{"name":"ERN: Microeconometric Studies of Housing Markets (Topic)","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80242814","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 use a linked housing transaction dataset and a personal bankruptcy dataset to study the impact of housing credit on personal bankruptcy in Singapore. Using a difference-in-differences (DD) approach, we find that an increase in housing credit increases the monthly installment by 560-900 Singapore dollar, and increases the likelihood of personal bankruptcy by 0.15-0.22 percentage points for house buyers who have more exposure to the housing credit increase. To investigate the mechanisms, we show that the observed effect is unlikely to be driven by composition and selection of irresponsible buyers. The effect is mainly due to the increasing debt burden.
{"title":"The Impact of Housing Credit on Personal Bankruptcy","authors":"Sumit Agarwal, Changcheng Song","doi":"10.2139/ssrn.2588145","DOIUrl":"https://doi.org/10.2139/ssrn.2588145","url":null,"abstract":"We use a linked housing transaction dataset and a personal bankruptcy dataset to study the impact of housing credit on personal bankruptcy in Singapore. Using a difference-in-differences (DD) approach, we find that an increase in housing credit increases the monthly installment by 560-900 Singapore dollar, and increases the likelihood of personal bankruptcy by 0.15-0.22 percentage points for house buyers who have more exposure to the housing credit increase. To investigate the mechanisms, we show that the observed effect is unlikely to be driven by composition and selection of irresponsible buyers. The effect is mainly due to the increasing debt burden.","PeriodicalId":12014,"journal":{"name":"ERN: Microeconometric Studies of Housing Markets (Topic)","volume":"61 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84471344","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}
Real estate indices are an increasingly important aspect of real estate investment management. The uses of these indices include the estimation of risks and returns for assisting the asset allocation decision-making process, as well as the specification of benchmarks for performance attribution. Performance attribution provides valuable information both for bottom-up investment management (e.g., in the selection of properties or managers) and for top-down investment management (in the determination of allocation to various categories of real estate investments). The two main approaches to indexation are appraisal-based and transaction-based, each of which has its own potential problems. The chapter compares these approaches and reviews many of the most popular real estate indices, which vary in terms of methodology used. The prevalence of a variety of indexation methodologies highlights the fact that all methodologies have nontrivial problems and that real estate analysts should be aware of the challenges associated with each methodology. The first part of this chapter discusses un-smoothing of a price index or return series — the process of removing the effects of smoothing from a data series. It begins by introducing smoothed pricing and the principles of un-smoothing. The chapter also explains transaction noise, which arises when real estate transaction prices contain errors that make those prices less reliable when compared to prices of more liquid assets. For example, the reported transaction prices result from a negotiation process between buyers and sellers and therefore represent one set of possible values from a range of prices that would have been acceptable to both buyers and sellers. Transaction noise is another important technical issue when dealing with real estate indices. Property values are noisy (in the sense that they reflect random error) because empirical real estate values are imprecise indicators of true value. Finally, the chapter discusses the performance of various appraisal-based and transaction-based real estate indices.
{"title":"Real Estate Indices and Unsmoothing Techniques","authors":"Urbi Garay","doi":"10.2139/ssrn.3628823","DOIUrl":"https://doi.org/10.2139/ssrn.3628823","url":null,"abstract":"Real estate indices are an increasingly important aspect of real estate investment management. The uses of these indices include the estimation of risks and returns for assisting the asset allocation decision-making process, as well as the specification of benchmarks for performance attribution. Performance attribution provides valuable information both for bottom-up investment management (e.g., in the selection of properties or managers) and for top-down investment management (in the determination of allocation to various categories of real estate investments). The two main approaches to indexation are appraisal-based and transaction-based, each of which has its own potential problems. The chapter compares these approaches and reviews many of the most popular real estate indices, which vary in terms of methodology used. The prevalence of a variety of indexation methodologies highlights the fact that all methodologies have nontrivial problems and that real estate analysts should be aware of the challenges associated with each methodology. The first part of this chapter discusses un-smoothing of a price index or return series — the process of removing the effects of smoothing from a data series. It begins by introducing smoothed pricing and the principles of un-smoothing. The chapter also explains transaction noise, which arises when real estate transaction prices contain errors that make those prices less reliable when compared to prices of more liquid assets. For example, the reported transaction prices result from a negotiation process between buyers and sellers and therefore represent one set of possible values from a range of prices that would have been acceptable to both buyers and sellers. Transaction noise is another important technical issue when dealing with real estate indices. Property values are noisy (in the sense that they reflect random error) because empirical real estate values are imprecise indicators of true value. Finally, the chapter discusses the performance of various appraisal-based and transaction-based real estate indices.","PeriodicalId":12014,"journal":{"name":"ERN: Microeconometric Studies of Housing Markets (Topic)","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74665061","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}
Spanish Abstract: En el documento se utiliza el metodo de las tasas de jefatura para elaborar diversos escenarios de creacion neta de hogares y, por extension, de la demanda de vivienda principal en Espana hasta finales de la proxima decada. Para ello, se toma la "Proyeccion de Hogares" del INE como el escenario base y se plantean diferentes escenarios, bajo distintos supuestos, acerca del ritmo de creacion de hogares y del flujo de entrada de inmigrantes. Todos los escenarios ofrecen una demanda potencial de vivienda muy alejada de las 427.000 que se registraron entre 2002 y 2008, situando la horquilla entre las 63.000 y las 236.000 viviendas por ano.English Abstract: The paper uses the headship rate method to draw up various scenarios of net household formation and, by extension, of the demand for primary dwellings in Spain to 2029. INE’s Household Projection is taken as a baseline scenario and different scenarios are prepared, under different assumptions about the pace of household formation and immigrant inflows. All the scenarios present a potential demand for dwellings far removed from the figure of 427,000 recorded between 2002 and 2008, placing the range between 63,000 and 236,000 dwellings per year.
{"title":"La Demanda Potencial De Vivienda Principal (Potential Demand of Primary Dwellings)","authors":"María de los Llanos Matea","doi":"10.2139/SSRN.2692047","DOIUrl":"https://doi.org/10.2139/SSRN.2692047","url":null,"abstract":"Spanish Abstract: En el documento se utiliza el metodo de las tasas de jefatura para elaborar diversos escenarios de creacion neta de hogares y, por extension, de la demanda de vivienda principal en Espana hasta finales de la proxima decada. Para ello, se toma la \"Proyeccion de Hogares\" del INE como el escenario base y se plantean diferentes escenarios, bajo distintos supuestos, acerca del ritmo de creacion de hogares y del flujo de entrada de inmigrantes. Todos los escenarios ofrecen una demanda potencial de vivienda muy alejada de las 427.000 que se registraron entre 2002 y 2008, situando la horquilla entre las 63.000 y las 236.000 viviendas por ano.English Abstract: The paper uses the headship rate method to draw up various scenarios of net household formation and, by extension, of the demand for primary dwellings in Spain to 2029. INE’s Household Projection is taken as a baseline scenario and different scenarios are prepared, under different assumptions about the pace of household formation and immigrant inflows. All the scenarios present a potential demand for dwellings far removed from the figure of 427,000 recorded between 2002 and 2008, placing the range between 63,000 and 236,000 dwellings per year.","PeriodicalId":12014,"journal":{"name":"ERN: Microeconometric Studies of Housing Markets (Topic)","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83311765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The topic of Adjustable Rate Mortgage (ARM) in its first glimpse, takes us to the reader of terms like Global Financial Crisis, Meltdown, Subprime crisis and its horrors. Global Financial Crisis (GFC) – The greatest of all financial crisis after the great depression of 1930, emancipated from a complicated interplay of policy to improve home ownership, by greater credit supply, laxed terms, overoptimistic assumption of real estate growth, predatory lending stunts instincts, and option to offload the balance sheet by securitization, poor remuneration to promote short term gain versus long-term value and last but not the least and macro-prudential governance shortfalls. The reason we discuss GFC here is that ARM were employed by Financial Institutions to finance the subprime i.e. the under-privileged. So did it work? No, it actually coasted them a USD 4.1 Trillion losses, 9 Million families displaced and thousands unemployed. Notwithstanding the fact that, a lot many other factors such as weak underwriting, monetary tightening, moral hazard across the value chain, unrealistic assumption on real estate valuation contributed to the GFC. Farhi, E., & Tirole, J. (2009) termed the GFC as Collective Moral Hazard while reviewing the role of macro prudential regulation, Interest rates, Lender and Investment Banks. This article would assess the structural dynamics of ARMs and subsequently rationalize its inability to alleviate or address the financing needs of the underprivileged.
{"title":"Out of the Frying Pan – in to the Fire: The Case of Adjustable Rate Mortgage for Funding of Homes of the Underprivileged","authors":"Muhammad Arsalan Aqeeq","doi":"10.2139/ssrn.2676172","DOIUrl":"https://doi.org/10.2139/ssrn.2676172","url":null,"abstract":"The topic of Adjustable Rate Mortgage (ARM) in its first glimpse, takes us to the reader of terms like Global Financial Crisis, Meltdown, Subprime crisis and its horrors. Global Financial Crisis (GFC) – The greatest of all financial crisis after the great depression of 1930, emancipated from a complicated interplay of policy to improve home ownership, by greater credit supply, laxed terms, overoptimistic assumption of real estate growth, predatory lending stunts instincts, and option to offload the balance sheet by securitization, poor remuneration to promote short term gain versus long-term value and last but not the least and macro-prudential governance shortfalls. The reason we discuss GFC here is that ARM were employed by Financial Institutions to finance the subprime i.e. the under-privileged. So did it work? No, it actually coasted them a USD 4.1 Trillion losses, 9 Million families displaced and thousands unemployed. Notwithstanding the fact that, a lot many other factors such as weak underwriting, monetary tightening, moral hazard across the value chain, unrealistic assumption on real estate valuation contributed to the GFC. Farhi, E., & Tirole, J. (2009) termed the GFC as Collective Moral Hazard while reviewing the role of macro prudential regulation, Interest rates, Lender and Investment Banks. This article would assess the structural dynamics of ARMs and subsequently rationalize its inability to alleviate or address the financing needs of the underprivileged.","PeriodicalId":12014,"journal":{"name":"ERN: Microeconometric Studies of Housing Markets (Topic)","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80813837","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 assesses the predictive power of variables that measure market tightness, such as seller's bargaining power and sale probabilities, on future home prices. Theoretical insights from a stylized search‐and‐matching model illustrate that such indicators can be associated with subsequent home price appreciation. The empirical analysis employs listings data on residential units offered for sale through a real estate broker in the Netherlands and for certain U.S. regions. Individual records are used to construct quarterly home price indices, an index that measures seller's bargaining power and (quality‐adjusted) home sale probabilities. Using conventional time‐series models we show that current sale probabilities and bargaining power can significantly reduce home price appreciation forecast errors and help to predict turning points in local area housing markets. The measures and approaches in this article help to demonstrate ways in which researchers and practitioners can leverage listings data to gain knowledge about the current and future state of the housing market.
{"title":"Can Tightness in the Housing Market Help Predict Subsequent Home Price Appreciation? Evidence from the United States and the Netherlands","authors":"Paul E. Carrillo, Erik R. de Wit, W. Larson","doi":"10.1111/1540-6229.12082","DOIUrl":"https://doi.org/10.1111/1540-6229.12082","url":null,"abstract":"This article assesses the predictive power of variables that measure market tightness, such as seller's bargaining power and sale probabilities, on future home prices. Theoretical insights from a stylized search‐and‐matching model illustrate that such indicators can be associated with subsequent home price appreciation. The empirical analysis employs listings data on residential units offered for sale through a real estate broker in the Netherlands and for certain U.S. regions. Individual records are used to construct quarterly home price indices, an index that measures seller's bargaining power and (quality‐adjusted) home sale probabilities. Using conventional time‐series models we show that current sale probabilities and bargaining power can significantly reduce home price appreciation forecast errors and help to predict turning points in local area housing markets. The measures and approaches in this article help to demonstrate ways in which researchers and practitioners can leverage listings data to gain knowledge about the current and future state of the housing market.","PeriodicalId":12014,"journal":{"name":"ERN: Microeconometric Studies of Housing Markets (Topic)","volume":"353 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91477388","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}
While reverse mortgages are intended as a tool to enable financial security for older homeowners, in 2014, nearly 12 percent of reverse mortgage borrowers in the federally insured Home Equity Conversion Mortgage (HECM) program were in default on their property taxes or homeowners insurance. Unlike the traditional mortgage market, there were no risk-based underwriting guidelines for HECMs through 2014. In response to the relatively high default rate, a variety of policy responses were implemented, including establishing underwriting guidelines. However, there is a lack of data and analysis to inform such criteria. Our analysis follows 30,000 seniors counseled for reverse mortgages between 2006 and 2011. The data includes comprehensive financial and credit report attributes, not typically available in analyses of reverse mortgage borrowers. Using a bivariate probit model that accounts for selection, we estimate the likelihood of tax and insurance default. Financial characteristics that increase default risk include the percentage of funds withdrawn in the first month of the loan, a lower credit score, higher property tax to income ratio, low or no unused revolving credit, and a history of being past due on mortgage payments or having a tax lien on the property. Our estimate of the elasticity of default with respect to credit scores is similar to that for closed-end home equity loans, but higher than that for HELOCs. We simulate the effects of alternative underwriting criteria and policy changes on the probability of take-up and default. Reductions in the default rate with a minimal effect on participation can be achieved by requiring that participants with low credit scores set aside some of their HECM funds for future property tax and insurance payments, a form of escrowing.
{"title":"An Analysis of Default Risk in the Home Equity Conversion Mortgage (HECM) Program","authors":"Stephanie Moulton, D. Haurin, Wei Shi","doi":"10.2139/ssrn.2468247","DOIUrl":"https://doi.org/10.2139/ssrn.2468247","url":null,"abstract":"While reverse mortgages are intended as a tool to enable financial security for older homeowners, in 2014, nearly 12 percent of reverse mortgage borrowers in the federally insured Home Equity Conversion Mortgage (HECM) program were in default on their property taxes or homeowners insurance. Unlike the traditional mortgage market, there were no risk-based underwriting guidelines for HECMs through 2014. In response to the relatively high default rate, a variety of policy responses were implemented, including establishing underwriting guidelines. However, there is a lack of data and analysis to inform such criteria. Our analysis follows 30,000 seniors counseled for reverse mortgages between 2006 and 2011. The data includes comprehensive financial and credit report attributes, not typically available in analyses of reverse mortgage borrowers. Using a bivariate probit model that accounts for selection, we estimate the likelihood of tax and insurance default. Financial characteristics that increase default risk include the percentage of funds withdrawn in the first month of the loan, a lower credit score, higher property tax to income ratio, low or no unused revolving credit, and a history of being past due on mortgage payments or having a tax lien on the property. Our estimate of the elasticity of default with respect to credit scores is similar to that for closed-end home equity loans, but higher than that for HELOCs. We simulate the effects of alternative underwriting criteria and policy changes on the probability of take-up and default. Reductions in the default rate with a minimal effect on participation can be achieved by requiring that participants with low credit scores set aside some of their HECM funds for future property tax and insurance payments, a form of escrowing.","PeriodicalId":12014,"journal":{"name":"ERN: Microeconometric Studies of Housing Markets (Topic)","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85830824","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 paper measures the value households place on street-level intensive policing practices. It utilizes a large, spatially detailed data set that includes more than one hundred thousand real property sales and four million police-citizen encounters in New York City from 2006-2012. A hedonic analysis of this data shows that the New York Police Department's practice of Stop, Question & Frisk policing was likely seen as a neighborhood dis-amenity by home buyers. Using finely partitioned geographical areas to control for variation in omitted variables and precise spatial statistics describing location relative to surrounding amenities and dis-amenities, I find that properties exposed to more intense Stop & Frisk activity sold for significantly lower prices. In a novel application, this paper shows one way in which housing prices can be used to inform administrative policy related to the provision of public services.
{"title":"Valuing Proactive Policing: A Hedonic Analysis of Stop & Frisk's Amenity Value","authors":"Matthew Friedman","doi":"10.2139/ssrn.2695584","DOIUrl":"https://doi.org/10.2139/ssrn.2695584","url":null,"abstract":"This paper measures the value households place on street-level intensive policing practices. It utilizes a large, spatially detailed data set that includes more than one hundred thousand real property sales and four million police-citizen encounters in New York City from 2006-2012. A hedonic analysis of this data shows that the New York Police Department's practice of Stop, Question & Frisk policing was likely seen as a neighborhood dis-amenity by home buyers. Using finely partitioned geographical areas to control for variation in omitted variables and precise spatial statistics describing location relative to surrounding amenities and dis-amenities, I find that properties exposed to more intense Stop & Frisk activity sold for significantly lower prices. In a novel application, this paper shows one way in which housing prices can be used to inform administrative policy related to the provision of public services.","PeriodicalId":12014,"journal":{"name":"ERN: Microeconometric Studies of Housing Markets (Topic)","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78373947","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}
After the mortgage market meltdown in mid-2007 and during the financial crisis in 2008, major financial institutions around the world were on the verge of collapsing one after another. Faced with these troubles, the government had to respond quickly to contain the crisis as efficiently as possible. It was, however, limited in resources, time and experience. To make matters worse, the complexity and opaqueness of the financial market and these institutions greatly affected the governments’ ability to design an efficient and consistent method to contain the crisis. Shortly after Lehman Brothers filed for bankruptcy on September 15, 2008, American International Group (AIG) was also in deep trouble and close to failure when the Federal Reserve decided to bailout the institution. Washington Mutual (WaMu) and Wachovia were also facing collapse due to their exposure in risky mortgage products around the same time. WaMu closed and the Federal Deposit Insurance Corporation (FDIC), appointed as a receiver. When the FDIC was appointed, the FDIC was able to arrange a transaction that protected all depositors in the bank and transferred all ongoing operations to JP Morgan Chase without any cost to the FDIC Deposit Insurance Fund. In contrast to WaMu, in the case of Wachovia the FDIC Board of Directors initially approved a sale of Wachovia through a closed bank resolution to Citigroup under the FDIC’s systemic risk authority. However, Wachovia’s Board of Directors subsequently decided to approve a sale – with no FDIC assistance – to Wells Fargo. This case provides details on the background and government response for each troubled financial institution during the financial crisis, and the rationale behind the design of each response.
{"title":"Guarantees and Capital Infusions in Response to Financial Crises A: Haircuts and Resolutions","authors":"J. Rhee, Andrew Metrick","doi":"10.2139/SSRN.2723446","DOIUrl":"https://doi.org/10.2139/SSRN.2723446","url":null,"abstract":"After the mortgage market meltdown in mid-2007 and during the financial crisis in 2008, major financial institutions around the world were on the verge of collapsing one after another. Faced with these troubles, the government had to respond quickly to contain the crisis as efficiently as possible. It was, however, limited in resources, time and experience. To make matters worse, the complexity and opaqueness of the financial market and these institutions greatly affected the governments’ ability to design an efficient and consistent method to contain the crisis. Shortly after Lehman Brothers filed for bankruptcy on September 15, 2008, American International Group (AIG) was also in deep trouble and close to failure when the Federal Reserve decided to bailout the institution. Washington Mutual (WaMu) and Wachovia were also facing collapse due to their exposure in risky mortgage products around the same time. WaMu closed and the Federal Deposit Insurance Corporation (FDIC), appointed as a receiver. When the FDIC was appointed, the FDIC was able to arrange a transaction that protected all depositors in the bank and transferred all ongoing operations to JP Morgan Chase without any cost to the FDIC Deposit Insurance Fund. In contrast to WaMu, in the case of Wachovia the FDIC Board of Directors initially approved a sale of Wachovia through a closed bank resolution to Citigroup under the FDIC’s systemic risk authority. However, Wachovia’s Board of Directors subsequently decided to approve a sale – with no FDIC assistance – to Wells Fargo. This case provides details on the background and government response for each troubled financial institution during the financial crisis, and the rationale behind the design of each response.","PeriodicalId":12014,"journal":{"name":"ERN: Microeconometric Studies of Housing Markets (Topic)","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80767048","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}
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：