Share
Classifying Applicants for Fair Lending Analyses: What Do the Data Have to Say?
Jason Dietrich
(Author)
·
Createspace Independent Publishing Platform
· Paperback
Classifying Applicants for Fair Lending Analyses: What Do the Data Have to Say? - Dietrich, Jason
Choose the list to add your product or create one New List
✓ Product added successfully to the Wishlist.
Go to My Wishlists
Origin: U.S.A.
(Import costs included in the price)
It will be shipped from our warehouse between
Tuesday, August 13 and
Friday, August 23.
You will receive it anywhere in United Kingdom between 1 and 3 business days after shipment.
Synopsis "Classifying Applicants for Fair Lending Analyses: What Do the Data Have to Say?"
Testing for discrimination in mortgage lending requires classifying consumers into treatment groups and control groups. Although this may seem like a straightforward task, it is actually quite complicated. Home Mortgage Disclosure Act (HMDA) data, the primary source of data for these analyses, contain information on the ethnicity, race, and gender for both primary and coapplicants. In addition, applicants have the option of reporting up to five races. Using these detailed data to construct the standard groups, such as "Black," "Hispanic," and "White," requires subjective decisions on how to appropriately aggregate applications.
- 0% (0)
- 0% (0)
- 0% (0)
- 0% (0)
- 0% (0)
All books in our catalog are Original.
The book is written in English.
The binding of this edition is Paperback.
✓ Producto agregado correctamente al carro, Ir a Pagar.
