Abstract (en): The Home Mortgage Disclosure Act (HMDA): Loan Application Register (LAR) and Transmittal Sheet (TS) Raw Data, 2007 contains information collected in calendar year 2006. The HMDA, enacted by Congress in 1975, requires most mortgage lenders located in metropolitan areas to report data about their housing-related lending activity. The HMDA data were collected from 8,886 lending institutions and cover approximately 34.1 million home purchase and home improvement loans and refinancings, including loan originations, loan purchases, and applications that were denied, incomplete or withdrawn. The Private Mortgage Insurance Companies (PMIC) data refer to applications for mortgage insurance to insure home purchase mortgages and to insure mortgages to refinance existing obligations. Part 1, HMDA Transmittal Sheet (TS), and Part 4, PMIC Transmittal Sheet (TS), include information submitted by reporting institutions with the Loan Application Register (LAR), such as the reporting institution's name, address, and Tax ID. Part 2, HMDA Reporter Panel, and Part 5, PMIC Reporter Panel, contain information on all institutions that reported data in activity year 2006. Part 3, HMDA MSA Offices, and Part 6, PMIC MSA Offices, contain information on all metropolitan statistical areas in the data. Parts 7 through 789 contain HMDA and PMIC Loan Application Register (LAR) files at the national level, at the agency level, and by MSA/MD. With some exceptions, for each transaction the institution reported data about the loan (or application), such as the type and amount of the loan made (or applied for) and, in limited circumstances, its price, the disposition of the application, such as whether it was denied or resulted in an origination of a loan, the property to which the loan relates, such as its type (single-family versus multi-family), and location (including the census tract), the sale of the loan, if it was sold, and the applicant's and co-applicant's ethnicity, race, sex, and income. The data are not weighted and do not contain any weight variables. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Created variable labels and/or value labels.; Created online analysis version with question text.. Home purchase and home improvement loans and refinancings (or applications) lended or insured by financial institutions in the United States that were required to report HMDA data in 2007. Smallest Geographic Unit: city HMDA data were collected from 8,886 depository and nondepository institutions that were required to report HMDA data if they met the law's criteria for coverage. Generally, whether a lender is covered by HMDA depended on the lender's asset size, its location, and whether it is in the business of residential mortgage lending. PMIC data were collected from eight mortgage insurance companies that insured home purchase mortgages and to insure mortgages to refinance existing obligations. For more information about how respondents reported, please refer to A Guide to HMDA Reporting. 2016-12-12 The study title and collection dates have been revised to reflect the 2006 activity year, with data reported in 2007. Filesets 1 through 6 and the multi-part setup files will also be replaced to correct the study year. Variable descriptions for parts 1 through 6 have been incorporated into the ICPSR Codebooks; "Frequencies" documents that were included in previous releases have been retired with this update. SDA was removed from this study as the original SDA pages were processed without using hermes, and the SDA title could not be updated to reflect the correct reporting year. For datasets 7 through 789, ICPSR is releasing the original deposited data files in the condition they were received, along with SPSS, Stata, and SAS setup files.The data file for Part 7, HMDA Loan Application Register (LAR): National File, contains over 34 million records. Due to its large size, users are encouraged to open this dataset in SAS. All Census tract, county definitions, and population counts were based on the 2000 Census of Population and Housing. Value labels for the variable STATE_...

I was curious about race and mortgage origination in my area of the country, so I downloaded and cleaned up data from the HMDA database. The data includes location, local median incomes, loan amount, applicant income, applicant and co-applicant race and sex and other elements of the loan. It also includes the final outcomes of application attempts.

Context

The Home Mortgage Disclosure Act (HMDA) requires many financial institutions to maintain, report, and publicly disclose information about mortgages. These public data are important because they help show whether lenders are serving the housing needs of their communities; they give public officials information that helps them make decisions and policies; and they shed light on lending patterns that could be discriminatory.

Content

Inside this data set contains 466,566 observations of Washington State home loans - variables include; demographic information, area specific data, loan status, property type, loan type, loan purpose and originating agency.

Acknowledgements

This data set was compiled by the Consumer Finance Protection Bureau using their automatic filtering for Washington State.

Inspiration

Looking at home loans in Washington State are there any current trends? What are the significant factors that go into loan approval decisions? Are there any area, demographic or gender bias? Can I build a MLA to predict loan decisions?

Abstract

The purpose of the SEPHER data set is to allow for testing, assessing and generating new analysis and metrics that can address inequalities and climate injustice. The data set was created by Tedesco, M., C. Hultquist, S. E. Char, C. Constantinides, T. Galjanic, and A. D. Sinha.

Methodology

SEPHER draws upon four major source datasets: CDC Social Vulnerability Index, FEMA National Risk Index, Home Mortgage Disclosure Act, and Evictions datasets. The data from these source datasets have been merged, cleaned, and standardized and all of the variables documented in the data dictionary.

CDC Social Vulnerability Index

CDC Social Vulnerability Index (SVI) dataset is a dataset prepared for the Centers for Disease Control and Prevention for the purpose of assessing the degree of social vulnerability of American communities to natural hazards and anthropogenic events. It contains data on 15 social factors taken or derived from Census reports as well as rankings of each tract based on these individual factors, groups of factors corresponding to four related themes (Socioeconomic, Household Composition & Disability, Minority Status & Language, and Housing Type & Transportation) and overall. The data is available for the years 2000, 2010, 2014, 2016, and 2018.

FEMA National Risk Index

The National Risk Index (NRI) dataset compiled by the Federal Emergency Management Agency (FEMA) consists of historic natural disaster data from across the United States at a tract-level. The dataset includes information about 18 natural disasters including earthquakes, tsunamis, wildfires, volcanic activity and many others. Each disaster is detailed out in terms of its frequency, historic impact, potential exposure, expected annual loss and associated risk. The dataset also includes some summary variables for each tract including the total expected loss in terms of building loss, human loss and agricultural loss, the population of the tract, and the area covered by the tract. It finally includes a few more features to characterize the population such as social vulnerability rating and community resilience.

Home Mortgage Disclosure Act

The Home Mortgage Disclosure Act (HMDA) dataset contains loan-level data for home mortgages including information on applications, denials, approvals, and institution purchases. It is managed and expanded annually by the Consumer Financial Protection Bureau based on the data collected from financial institutions. The dataset is used by public officials to make decisions and policies, uncover lending patterns and discrimination among mortgage applicants, and investigate if lenders are serving the housing needs of the communities. It covers the period from 2007 to 2017.

Evictions

The Evictions dataset is compiled and managed by the Eviction Lab at Princeton University and consists of court records related to eviction cases in the United States between 2000 and 2016. Its purpose is to estimate the prevalence of court-ordered evictions and compare eviction rates among states, counties, cities, and neighborhoods. Besides information on eviction filings and judgments, the dataset includes socioeconomic and real estate data for each tract including race/ethnic origin, household income, poverty rate, property value, median gross rent, rent burden, and others.