Collaborative Research: Predatory Lending, Predatory Borrowing, and the Mortgage Crisis: Evidence from Loan-Level Data from a Large Bank

合作研究：掠夺性贷款、掠夺性借款和抵押危机：来自大型银行贷款水平数据的证据

• 批准号: 0851428
• 负责人: Wei Jiang
• 金额: $ 24.76万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-01 至 2013-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0851428&HistoricalAwards=false
• 关键词: Collaborative; Research; Predatory; Lending; Borrowing

Developments in the U.S. housing and mortgage debt markets since 2006 are the focus of anxiety and efforts among regulators, researchers, and market participants. This project aims to uncover the causes of, and the paths to, the mortgage crisis from the experience of a major mortgage bank. The bank the PI's study is an ideal place for the study because it provides a epresentative and yet amplified version of the boom-and-bust cycle that the national subprime sector has seen during the past decade. First, the bank was one of the nations ten largest mortgage banks in 2006 and was one of the fastest growing. Second,it specialized in the reduced- and no-documentation loans that has been central to the mortgage crisis, while also providing full-documentation loans. Third, the insolvency of the bank in 2008 was one of the largest bank failures in United States history. Lastly, the borrowers and properties underlying the bank's mortgage loans have fair representations from all the states, and therefore, lessons from the bank's failure have general implications.The project will be based on a new and proprietary data set that represents the most comprehensive, detailed, and disaggregated data sets used in the mortgage loan literature. We have obtained data on more than 700,000 loans made by the bank that were outstanding at any time between January 2004 and March 2008. The dataset includes all the detailed information that the lender collected for loan origination, including loan pricing and other contractual terms, and the borrowers demographic and economic conditions. In addition, the dataset includes detailed information about the loan performance in each month during the sample period, including the payment amount and the loans prepayment, delinquency and foreclosure status. Finally, using the address information in the dataset, the PI's are able to match individual loans to community attributes such as school quality, housing price indices, and business opportunities in narrow localities.The analysis of this unique dataset will include several steps. First, the PI's plan to conduct a descriptive analysis of the evolution of the structuring and performance of loans originated by the bank during the sample period. Second, they will perform a predictive analysis of default, and analyze the differences in the determinants of default among subsamples partitioned by loan types and borrower characteristics. They will also analyze the time series variations of such. Most importantly, they will identify the two-sided moral hazard problems in the mortgage market. On the one hand, there is the possibility of predatory lending, where the lender misleads an uninformed borrower into a high-cost loan when the latter could qualify for a lower-cost alternative; or the lender makes a loan that will cause expected harm to the borrower. On the other hand, predatory borrowing points to the possibility that borrowers falsify or hide unfavorable information in their loan applications.The intellectual merit of the proposed activity: Using a unique dataset, the proposed study will help settle the controversies over lending practice, most importantly the presence of discrimination in loan pricing and predatory lending. The research also aims at identifying key factors in causing the mortgage crisis by assessing the relative importance of irresponsible lending and irresponsible borrowing. The novel empirical design to separately identify the opportunistic behavior of lenders and borrowers will also represent a contribution to the empirical literature on two-sided information asymmetry and moral hazard.The broader impacts resulting from the proposed activity: By conducting an inside study of a major mortgage bank through its expansion and failure, this work will provide a better understanding of the causes of the recent mortgage crisis. The findings will provide useful reference for policy makers who work on laws and rules in order to prevent a crisis of this scale from recurring. The lessons from this study will also benefit banks and financial institutions for better practices in loan provision and securitization, risk management, and monitoring.

自2006年以来，美国住房和抵押贷款债务市场的发展是监管机构、研究人员和市场参与者焦虑和努力的焦点。本课题旨在从一家大型抵押贷款银行的经历中，揭示抵押贷款危机的原因和途径。PI研究的银行是一个理想的研究场所，因为它提供了一个代表性的，但放大版本的繁荣和萧条周期，国家次级抵押贷款部门已经看到在过去十年。首先，该银行是2006年全国十大抵押贷款银行之一，也是增长最快的银行之一。第二，它专门从事减少和无文件贷款，一直是核心的抵押贷款危机，同时也提供完整的文件贷款。第三，2008年的银行破产是美国历史上最大的银行破产之一。最后，借款人和银行抵押贷款的基础属性有来自所有州的公平代表，因此，银行失败的教训具有普遍意义。该项目将基于一个新的专有数据集，代表了抵押贷款文献中使用的最全面，详细和分类的数据集。我们获得了该银行在2004年1月至2008年3月期间任何时候未偿还的70多万笔贷款的数据。该数据集包括贷方为贷款发放收集的所有详细信息，包括贷款定价和其他合同条款，以及借款人的人口统计和经济状况。此外，数据集还包括样本期内每个月贷款表现的详细信息，包括付款金额和贷款提前还款、拖欠和止赎状态。最后，使用数据集中的地址信息，PI能够将个人贷款与社区属性（如学校质量、房价指数和狭窄地区的商业机会）相匹配。首先，PI计划对样本期内银行发放的贷款的结构和业绩的演变进行描述性分析。其次，他们将对违约进行预测分析，并分析按贷款类型和借款人特征划分的子样本之间违约决定因素的差异。他们还将分析这种时间序列的变化。最重要的是，他们将识别抵押贷款市场中的双面道德风险问题。一方面，存在掠夺性贷款的可能性，即放款人误导不知情的借款人获得高成本贷款，而后者有资格获得低成本的替代贷款;或者放款人提供的贷款将对借款人造成预期的损害。另一方面，掠夺性借贷指出借款人在贷款申请中伪造或隐藏不利信息的可能性。拟议活动的智力价值：使用独特的数据集，拟议的研究将有助于解决有关贷款实践的争议，最重要的是贷款定价和掠夺性贷款中存在的歧视。这项研究还旨在通过评估不负责任的贷款和不负责任的借款的相对重要性，确定造成抵押贷款危机的关键因素。新的实证设计，分别确定贷款人和借款人的机会主义行为也将代表的双边信息不对称和道德风险的实证文献的贡献。更广泛的影响所产生的拟议活动：通过进行一个主要的抵押贷款银行通过其扩张和失败的内部研究，这项工作将提供一个更好地了解最近的抵押贷款危机的原因。研究结果将为政策制定者提供有益的参考，他们将制定法律和规则，以防止这种规模的危机再次发生。本研究的经验教训也将有利于银行和金融机构在贷款提供和证券化、风险管理和监测方面采取更好的做法。