The Home Mortgage Disclosure Act (HMDA) database (Consumer Financial Protection Bureau, 2022) has compiled mortgage lending data since 1981, but the collection and dissemination methods have changed over time (Federal Financial Institutions Examination Council, 2018), creating barriers to conducting longitudinal analyses. This HMDA Longitudinal Dataset (HLD) organizes and standardizes information across different eras of HMDA data collection between 1981 and 2021, enabling such analysis. This collection contains two types of datasets: 1) HMDA aggregated data by census tract for each decade and 2) HMDA aggregated data by census tract for individual years. Items for analysis include borrower income values, mortgages by loan type (e.g., conventional, Federal Housing Administration (FHA), Veterans Affairs (VA), refinances), and mortgages by borrower race and gender.

Python script used to examine how the marketing of properties explains neighborhood racial and income change using historical public remarks in real estate listings from Multiple Listing Services (MLS) collected and curated by CoreLogic.The primary dataset used for this research consists of 158,253 geocoded real estate listings for single-family homes in Mecklenburg County, North Carolina between 2001 and 2020. The historical MLS data which include public remarks is proprietary and can be obtained through purchase agreement with CoreLogic. The MLS is not publicly available and only available for members of the National Association of Realtors. Public remarks for homes currently listed for sale can be collected from online real estate websites such as Zillow, Trulia, Realtor.com, Redfin, and others.Since we cannot share this data, users need to, before running the script provided here, run the script provided by Nilsson and Delmelle (2023) which can be accessed here: https://doi.org/10.6084/m9.figshare.20493012.v1. This in order to get a fabricated/mock dataset of classified listings called classes_mock.csv. The article associated with Nilsson and Delmelle's (2023) script can be accessed here: https://www.tandfonline.com/doi/abs/10.1080/13658816.2023.2209803The user can then run the code together with the data provided here to estimate the threshold models together with data derived from the publicly available HMDA data. To compile a historical data set of loan/application records (LAR) for the user's own study are, the user will need to download data from the following websites:https://ffiec.cfpb.gov/data-publication/snapshot-national-loan-level-dataset/2022 (2017-forward)https://www.ffiec.gov/hmda/hmdaproducts.htm (2007-2016)https://catalog.archives.gov/search-within/2456161?limit=20&levelOfDescription=fileUnit&sort=naId:asc (for data prior to 2007)