Submitted to Journal of Housing Economics, March 20262026

Persistent Racial Disparities in U.S. Mortgage Approval: Evidence from 42 Million Applications, 2020–2024

Rajveer Singh Pall

The public-data Black–White mortgage approval gap at national scale: how large, where it lives, and how it responds to institutional boundaries.

The discovery in one figure

42M APPLICATIONS · RAW GAP 14.95 pp — BUT WHERE DOES IT LIVE?ApplicantINSIDE ONE LENDER74.6%of the gap is within-lenderrising 66.8% → 78.3% (2020→2024)only a minority sits between institutionsBOUNDARIES WIDEN IT+2.0 pp @ 80% LTV+1.5 pp · 2022 tightening68% unexplainedby observables
The disparity is concentrated inside institutions — and widens at their boundaries.

The paper in five minutes

Every U.S. mortgage application leaves a public record. Reading all 42 million of them from 2020–2024, Black applicants are approved about 15 percentage points less often than White applicants. This paper measures that gap carefully: most of it (68%) cannot be explained by anything visible in the public data, and three-quarters of it lives inside individual lenders rather than between them. Two natural experiments — an insurance-driven threshold at 80% loan-to-value, and the Federal Reserve's 2022 tightening — each widen the gap further. The paper never claims to prove intent; it maps the scale and the structure.

The research question

How large is the observable racial approval gap in U.S. mortgage lending, how much sits within lenders, and what do quasi-experimental boundaries reveal about its structure?

How it works

42,323,519 HMDA applications, 2020–2024. DFL reweighting, within-lender fixed effects, regression discontinuity at the 80% LTV / PMI boundary, difference-in-differences around the 2022 tightening, HonestDiD sensitivity, Manski partial-identification bounds, permutation tests.

  1. 01
    Assemble42,323,519 applications, 5,500+ lenders, 2020–2024
  2. 02
    ReweightDiNardo–Fortin–Lemieux: compare statistically similar applicants
  3. 03
    Look within lendersfixed effects — is it between institutions, or inside them?
  4. 04
    Natural experimentsRDD at the 80% LTV insurance boundary · DiD around 2022 tightening
  5. 05
    Bound the unknownpartial identification calibrated to consumer-finance data

Experimental results

Raw gap 14.95 pp; 68% unexplained by public observables; 74.6% of the gap is within-lender; the RDD adds ≈ +2.0 pp above the 80% LTV threshold in purchase loans; scale ≈ 126,000 fewer approvals for Black applicants annually. Bounds keep ≥ 44–55% unexplained under conservative assumptions.

Black–White approval gap in percentage points
National raw gap
14.95 pp
Midwest regional mean
16.1 pp
West regional mean
9.3 pp

74.6% of the national gap sits within individual lenders; scale ≈ 126,000 fewer approvals per year.

  • 14.95 ppraw Black–White approval gap
  • 74.6%of gap within-lender
  • ≈126,000fewer annual approvals at scale

Stated honestlyHMDA lacks credit scores/assets; estimates framed as upper bounds on conditional differentials.

What this changes

Documents scale and institutional structure without overclaiming intent — the paper explicitly positions public-data estimates against confidential-data literature.

Resources

  • Fairness
  • Causal Inference
  • Deployment Shift

Citation

Manuscript under review — citation will be posted on acceptance. Reach me at rajveerpall04@gmail.com.