{"title":"The Marginal Effect of Government Mortgage Guarantees on Homeownership","authors":"Serafin Grundl, You Suk Kim","doi":"10.17016/FEDS.2019.027","DOIUrl":"https://doi.org/10.17016/FEDS.2019.027","url":null,"abstract":"The U.S. government guarantees a majority of residential mortgages, which is often justified as a means to promote homeownership. In this paper we use property-level data to estimate the effect of government mortgage guarantees on homeownership, by exploiting variation of the conforming loan limits (CLLs) along county borders. We find substantial effects on government guarantees, but find no robust effect on homeownership. This finding suggests that government guarantees could be considerably reduced with modest effects on homeownership, which is relevant for housing finance reform plans that propose to reduce the government?s involvement in the mortgage market by reducing the CLLs.","PeriodicalId":278071,"journal":{"name":"Board of Governors: Finance & Economics Discussion Series (Topic)","volume":"192 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129293449","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}
{"title":"The Limits of P-Hacking: A Thought Experiment","authors":"Andrew Y. Chen","doi":"10.17016/FEDS.2019.016","DOIUrl":"https://doi.org/10.17016/FEDS.2019.016","url":null,"abstract":"Suppose that asset pricing factors are just p-hacked noise. How much p-hacking is required to produce the 300 factors documented by academics? I show that, if 10,000 academics generate 1 factor every minute, it takes 15 million years of p-hacking. This absurd conclusion comes from applying the p-hacking theory to published data. To fit the fat right tail of published t-stats, the p-hacking theory requires that the probability of publishing t-stats < 6.0 is infinitesimal. Thus it takes a ridiculous amount of p-hacking to publish a single t-stat. These results show that p-hacking alone cannot explain the factor zoo.","PeriodicalId":278071,"journal":{"name":"Board of Governors: Finance & Economics Discussion Series (Topic)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122634242","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}
Michael M. Batty, Jesse Bricker, Joseph Briggs, E. Holmquist, Susan Hume McIntosh, Kevin B. Moore, Eric R. Nielsen, Sarah J. Reber, M. Shatto, K. Sommer, Tom Sweeney, Alice Henriques Volz
{"title":"Introducing the Distributional Financial Accounts of the United States","authors":"Michael M. Batty, Jesse Bricker, Joseph Briggs, E. Holmquist, Susan Hume McIntosh, Kevin B. Moore, Eric R. Nielsen, Sarah J. Reber, M. Shatto, K. Sommer, Tom Sweeney, Alice Henriques Volz","doi":"10.17016/FEDS.2019.017","DOIUrl":"https://doi.org/10.17016/FEDS.2019.017","url":null,"abstract":"This paper describes the construction of the Distributional Financial Accounts (DFAs), a new dataset containing quarterly estimates of the distribution of U.S. household wealth since 1989, and provides the first look at the resulting data. The DFAs build on two existing Federal Reserve Board statistical products --- quarterly aggregate measures of household wealth from the Financial Accounts of the United States and triennial wealth distribution measures from the Survey of Consumer Finances --- to incorporate distributional information into a national accounting framework. The DFAs complement other existing sources of data on the wealth distribution by using a more comprehensive measure of household wealth and by providing quarterly data on a timely basis. We encourage policymakers, researchers, and other interested parties to use the DFAs to help understand issues related to the distribution of U.S. household wealth.","PeriodicalId":278071,"journal":{"name":"Board of Governors: Finance & Economics Discussion Series (Topic)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123758593","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}
Gregory J. Cohen, Jacob Dice, M. Friedrichs, Kamran Gupta, William Hayes, Isabel Kitschelt, S. J. Lee, W. Marsh, Nathan Mislang, Maya Shaton, M. Sicilian, Chris Webster
{"title":"The U.S. Syndicated Loan Market: Matching Data","authors":"Gregory J. Cohen, Jacob Dice, M. Friedrichs, Kamran Gupta, William Hayes, Isabel Kitschelt, S. J. Lee, W. Marsh, Nathan Mislang, Maya Shaton, M. Sicilian, Chris Webster","doi":"10.17016/FEDS.2018.085","DOIUrl":"https://doi.org/10.17016/FEDS.2018.085","url":null,"abstract":"We introduce a new software package for determining linkages between datasets without common identifiers. We apply these methods to three datasets commonly used in academic research on syndicated lending: Refinitiv LPC DealScan, the Shared National Credit Database, and S&P Global Market Intelligence Compustat. We benchmark the results of our match using results from the literature and previously matched files that are publicly available. We find that the company level matching is enhanced by careful cleaning of the data and considering hierarchical relationships. For loan level matching, a tailored approach based on a good understanding of the data can be better in certain dimensions than a more pure machine learning approach. The R package for the company level match can be found on Github at https://github.com/seunglee98/fedmatch.","PeriodicalId":278071,"journal":{"name":"Board of Governors: Finance & Economics Discussion Series (Topic)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116553435","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}
{"title":"Rural Affordable Rental Housing: Quantifying Need, Reviewing Recent Federal Support, and Assessing the Use of Low Income Housing Tax Credits in Rural Areas","authors":"Andrew Dumont","doi":"10.17016/FEDS.2018.077","DOIUrl":"https://doi.org/10.17016/FEDS.2018.077","url":null,"abstract":"Recently, there has been significant interest in the high levels of rental cost burden being experienced across the United States. Much of this scholarship has focused on rental cost burdens in larger urban areas, or at the national level, and has not explored differences in the prevalence of rental cost burden in urban versus rural communities. In this paper, I find that rental cost burdens are a challenge facing both urban and rural communities. However, despite the need for affordable rental housing in rural communities identified, I find the amount of resources made available by the federal government to address this challenge are at a low point relative to recent history. My analysis of federal resource availability also finds one program has been an important and resilient tool for the development and preservation of affordable housing in urban and rural communities: the Low Income Housing Tax Credit (LIHTC) program. Congress delegated much of the LIHTC program?s implementation to the states, whereby states choose many of the factors to prioritize when allocating LIHTCs to specific projects. Therefore, I explored each state?s qualified allocation plan to identify whether specific factors make it more or less likely rural areas will receive a ?fair share? of LIHTC allocations based on their need relative to non-rural areas. My analysis did not identify a specific factor or set of factors that systematically increased or decreased the likelihood of allocations being proportionate to the relative needs of a state?s rural communities. However, I did identify a number of factors that by their very design appeared to affect positively or negatively the likelihood that specific types of projects or project locations would receive allocations. Interviews with industry stakeholders confirmed that many of these factors are affecting developer decisions and may be unintentionally disadvantaging smaller, more remote rural projects.","PeriodicalId":278071,"journal":{"name":"Board of Governors: Finance & Economics Discussion Series (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129814963","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}
{"title":"Employment in the Great Recession: How Important Were Household Credit Supply Shocks?","authors":"Daniel Garcia","doi":"10.17016/FEDS.2018.074","DOIUrl":"https://doi.org/10.17016/FEDS.2018.074","url":null,"abstract":"I pool data from all large multimarket lenders in the U.S. to estimate how many of the over seven million jobs lost in the Great Recession can be explained by reductions in the supply of mortgage credit. I construct a mortgage credit supply instrument at the county level, the weighted average (by prerecession mortgage market shares) of liquidity-driven lender shocks during the recession. The reduction in mortgage supply explains about 15 percent of the employment decline. The job losses are concentrated in construction and finance.","PeriodicalId":278071,"journal":{"name":"Board of Governors: Finance & Economics Discussion Series (Topic)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129538858","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}
Simon Gilchrist, Raphael S. Schoenle, J. Sim, Egon Zakraǰsek
{"title":"Financial Heterogeneity and Monetary Union","authors":"Simon Gilchrist, Raphael S. Schoenle, J. Sim, Egon Zakraǰsek","doi":"10.17016/FEDS.2018.043","DOIUrl":"https://doi.org/10.17016/FEDS.2018.043","url":null,"abstract":"We analyze the economic consequences of forming a monetary union among countries with varying degrees of financial distortions, which interact with the firms' pricing decisions because of customer-market considerations. In response to a financial shock, firms in financially weak countries (the periphery) maintain{{p}}cashflows by raising markups--in both domestic and export markets--while firms in financially strong countries (the core) reduce markups, undercutting their financially constrained competitors to gain market share. When the two regions are experiencing different shocks, common monetary policy results in a substantially higher macroeconomic volatility in the periphery, compared with a flexible exchange rate regime; this translates into a welfare loss for the union as a whole, with the loss borne entirely by the periphery. By helping firms from the core internalize the pecuniary externality engendered by the interaction of financial frictions and customer markets, a unilateral fiscal devaluation by the periphery can improve the union's overall welfare.","PeriodicalId":278071,"journal":{"name":"Board of Governors: Finance & Economics Discussion Series (Topic)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131957555","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}
{"title":"The Nature of Household Labor Income Risk","authors":"Seth Pruitt, Nick Turner","doi":"10.17016/FEDS.2018.034","DOIUrl":"https://doi.org/10.17016/FEDS.2018.034","url":null,"abstract":"What is the nature of labor income risk facing households? We answer this question using detailed administrative data on household earnings from the U.S. Internal Revenue Service. By analyzing total household labor earnings as well as each member's earnings, we offer several new findings. One, households face substantially less risk than males in isolation. Second, households face roughly half the countercyclical increase in risk that males face. Third, spousal labor income ameliorates household earnings risk through both extensive and intensive margins.","PeriodicalId":278071,"journal":{"name":"Board of Governors: Finance & Economics Discussion Series (Topic)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121536161","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}
{"title":"New Perspectives on the Decline of U.S. Manufacturing Employment","authors":"Teresa C. Fort, Justin Pierce, Peter K. Schott","doi":"10.17016/FEDS.2018.023","DOIUrl":"https://doi.org/10.17016/FEDS.2018.023","url":null,"abstract":"We use relatively unexplored dimensions of US microdata to examine how US manufacturing employment has evolved across industries, firms, establishments, and regions from 1977 to 2012. We show that these data provide support for both trade- and technology-based explanations of the overall decline of employment over this period, while also highlighting the difficulties of estimating an overall contribution for each mechanism. Toward that end, we discuss how further analysis of these trends might yield sharper insights.","PeriodicalId":278071,"journal":{"name":"Board of Governors: Finance & Economics Discussion Series (Topic)","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121726503","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}
{"title":"Parental Proximity and Earnings after Job Displacements","authors":"Pawel M. Krolikowski, Mike Zabek, Patrick Coate","doi":"10.17016/FEDS.2019.062","DOIUrl":"https://doi.org/10.17016/FEDS.2019.062","url":null,"abstract":"The earnings of young adults living in their parents' neighborhoods completely recover after a job displacement, while the earnings of those living farther away permanently decline. Nearby workers appear to benefit from help with childcare. Earnings improvements are larger in states with expensive childcare and among workers in inflexible occupations, and workers' parents do less market work following their child's displacement. Differences in job search durations, transfers of housing services, and geographic mobility are too small to explain the result. Our results are also consistent with workers benefiting from parental employment networks.","PeriodicalId":278071,"journal":{"name":"Board of Governors: Finance & Economics Discussion Series (Topic)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122009055","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}