Datasets:

ShawnChamberlain
/

open-economic-quant-research-data

Two tiers of data are used. Tier P (public) is downloaded automatically. Tier R (registered) requires you to register and accept terms yourself; this repository will not and cannot do that for you.

Run make fetch-public-data for Tier P. Everything lands in data/cache/ with a manifest, and nothing in data/cache/ is committed.

Tier P — public, fetched automatically

P1. Freddie Mac Primary Mortgage Market Survey (PMMS) — market mortgage rates

URL: https://www.freddiemac.com/pmms/docs/PMMS_history.csv
Contents: weekly national average offered rates. Columns date, pmms30, pmms30p, pmms15, pmms15p, pmms51, pmms51p, pmms51m, pmms51spread. *p = points/fees, pmms51* = 5/1 ARM series.
Coverage: 1971-04-02 onward (30-yr); 15-yr from 1991-08-30; 5/1 ARM 2005–2022.
Methodology regimes we record:
- lender_survey_1971_2022 — the original survey of lenders.
- application_based_2022_11+ — from 2022-11-17 Freddie Mac moved PMMS to a methodology based on loan applications received from lenders; the fees/points series and the 5/1 ARM series were discontinued at the same time. Rates before and after are not produced the same way.
- The 1-yr ARM series was discontinued in 2015 and is not in this file.
Terms: Freddie Mac permits use with attribution; commercial redistribution is restricted. We cache locally and never commit the file.
Adapter: src/lockin/adapters/pmms.py.

P2. FHFA House Price Indexes

URL: https://www.fhfa.gov/hpi/download/monthly/hpi_master.csv (~17 MB)
Contents: long-format panel. Columns hpi_type, hpi_flavor, frequency, level, place_name, place_id, yr, period, index_nsa, index_sa, rstderr, note.
hpi_flavor distinguishes index concepts — purchase-only, all-transactions, expanded-data. Never mix these. Default for this project: purchase-only, monthly, seasonally adjusted where available.
level distinguishes geography: USA or Census Division, State, MSA, Puerto Rico.
Terms: U.S. Government work, public domain. Cite FHFA and the release date.
Adapter: src/lockin/adapters/fhfa_hpi.py.

P3. HMDA — CFPB Data Browser aggregations API

Endpoint: https://ffiec.cfpb.gov/v2/data-browser-api/view/aggregations
Example: ?years=2022&states=WV&loan_purpose=1&actions_taken=1 returns {"aggregations":[{"count":…,"sum":…}]} — loan count and dollar sum. One call per (year, state, purpose, action) cell; responses cached.
loan_purpose: 1 = Home purchase, 31 = Refinancing, 32 = Cash-out refinancing, 2 = Home improvement, 4 = Other, 5 = Not applicable. (2018+ codes. Pre-2018 HMDA used 1/2/3.)
actions_taken: 1 = Loan originated, 2 = Approved not accepted, 3 = Denied, 4 = Withdrawn, 5 = File closed incomplete, 6 = Purchased loan, 7/8 = preapproval outcomes.
Coverage breaks: the 2018 HMDA rule changed reported fields and institutional coverage; the closed-end reporting threshold moved from 25 to 100 loans effective 2022 data (after litigation history in 2020–2022). Counts are therefore not comparable across 2017/2018 or across the threshold change. Adapter records coverage_regime per year.
Privacy: the public LAR is released with privacy modifications (binned/rounded fields). The aggregations endpoint returns counts and sums only.
Terms: public. Adapter: src/lockin/adapters/hmda.py.

P4. Census Building Permits Survey

Monthly state file: https://www2.census.gov/econ/bps/State/st{YYMM}c.txt (c = current/preliminary; r = revised). Annual and MSA/county files follow parallel paths under https://www2.census.gov/econ/bps/.
Contents: buildings, units, and construction value by structure size (1-unit, 2-units, 3-4 units, 5+ units), plus "rep" (reported-only) columns. The non-rep columns include imputation for non-responding permit places; the rep columns do not. We store both and default to the imputed series, documented.
Preliminary vs final: monthly c files are preliminary and are revised. We record which vintage was fetched.
Measures permits authorized, not starts or completions.
Terms: U.S. Government work, public domain.
Adapter: src/lockin/adapters/census_bps.py.

P5. Official Freddie Mac dataset documentation (public)

https://www.freddiemac.com/fmac-resources/research/pdf/user_guide.pdf
https://www.freddiemac.com/fmac-resources/research/pdf/file_layout.xlsx

These two are publicly downloadable without registration and are the source of truth for the schema in src/lockin/schemas/freddie.py. The data files are not. Re-run lockin verify-schema after any Freddie Mac release to confirm the layout has not changed.

P6. Optional cross-check: FRED

https://fred.stlouisfed.org/graph/fredgraph.csv?id=MORTGAGE30US
The St. Louis Fed's redistribution of PMMS 30-yr FRM. Used only as an independent cross-check on P1, not as a substitute.

Tier R — registered; you must do this yourself

R1. Freddie Mac Single-Family Loan-Level Dataset

We will not bypass registration, authentication, or licence acceptance.

Go to https://www.freddiemac.com/research/datasets/sf-loanlevel-dataset. The page states: "To access the Single-Family Loan-Level Dataset, register and sign-in to Clarity Data Intelligence."

Register for a Clarity Data Intelligence account and accept the terms of use. Read them: they prohibit redistribution of the loan-level records.


Dataset landing page	`https://www.freddiemac.com/research/datasets/sf-loanlevel-dataset`
Download portal (SAML sign-in)	`https://claritydownload.fmapps.freddiemac.com/CRT/`
Reporting/BI portal	`https://claritybi.freddiemac.com/MicroStrategyLibrary/`

⚠️ Many older guides still point at freddiemac.embs.com. That host now returns HTTP 403 and is not the current route (verified 2026-08-11). If a tutorial sends you there, it is out of date.

The sample files are behind the same sign-in as the full dataset — there is no unauthenticated sample download, which is why this repository ships synthetic fixtures instead.

Download either
- the official sample dataset (sample_YYYY.zip files — a random 50,000-loan sample per origination year, with matching monthly performance), or
- the standard full dataset (historical_data_YYYYQn.zip per quarterly cohort).
Place the archives, unmodified, in data/raw/freddie/.
Preflight before you commit hours to it:
```
make check-registered-data
```
This reads only the first few hundred lines of each member (seconds, not hours) and answers: are these the expected files, does each parse at the verified 32-field layout, are all Zero Balance Codes ones we document, do the origination and performance files pair up, and roughly how much disk and time will the real run need. It exits non-zero on a blocker. A layout change or an undocumented Zero Balance Code is a blocker on purpose -- an unknown code would otherwise be silently censored, discarding real exits.
Set mortgage.mode: registered_sample or registered_full in your config, set mortgage.cohorts to what you actually downloaded, and run make reproduce-sample.

Expected archive contents per cohort:

historical_data_YYYYQn.txt — origination, pipe-delimited, 32 fields, no header.
historical_data_time_YYYYQn.txt — monthly performance, pipe-delimited, 32 fields, no header.

Sizes: the full dataset is tens of GB decompressed and billions of loan-months. The ingestion is streaming and per-cohort; see docs/PROJECT_PLAN.md §4.4.

Until you complete R1, the pipeline runs on labeled synthetic fixtures (data/fixtures/, generated by make prepare-sample-data). Every artifact and report produced in that mode is stamped SYNTHETIC and must not be read as an empirical finding.

R2. Optional local economic controls

BLS LAUS state unemployment — IMPLEMENTED, and it needs no registration. src/lockin/adapters/bls_laus.py. Note the route: the bulk flat files at https://download.bls.gov/pub/time.series/la/ return HTTP 403 to a generic client, because BLS asks automated downloaders to identify themselves with a contact email. This repository will not put your personal email into an outbound header without being asked to, so it uses the public JSON API v2 instead (https://api.bls.gov/publicAPI/v2/timeseries/data/), which serves the same series without a registration key within published unregistered limits (~25 queries/day, 25 series and 20 years per query). Three queries cover all 51 states.

Series: LASST{fips}0000000000003 — LAUS, State, Seasonally adjusted, measure 03 = unemployment rate. Fetched by make fetch-public-data; the pipeline runs without it and records its absence.

If you want the bulk-file route instead (higher volume, no rate limit), set a User-Agent containing your own contact email — that is your decision to make, not this repository's.

Teleworkable employment share — IMPLEMENTED, no registration. src/lockin/adapters/teleworkable.py. Dingel & Neiman (2020), "How many jobs can be done at home?", J. Public Economics 189:104235 — the authors' public replication outputs on GitHub. State and CBSA levels, four published measures; the default is teleworkable_emp (O*NET survey rule, employment-weighted), not the manual pair, which is the authors' own subjective classification.

Addresses the remote-work-exposure threat in docs/IDENTIFICATION_STRATEGY.md §3.2. It measures the feasibility of remote work, not its realisation — that distinction is carried on every artifact. Because it is a single cross-section it enters the event study interacted with every period, never as a level control; as a level it would be exactly collinear with the geography fixed effects and would constrain nothing. See DECISION_LOG D027, which also records the two specification bugs this exposed.

OMB CBSA delineation crosswalk — IMPLEMENTED, no registration. src/lockin/adapters/omb_cbsa.py. Census Bureau List 1 delineation files for six OMB vintages (2013, 2015, 2017, 2018, 2020, 2023), public domain.

Required for any MSA-level analysis, because Freddie Mac's MSA field is as-of-origination and is not restated when OMB redraws a boundary. The adapter records, per code, whether its county composition, title, or metro/micro status ever changed. Measured result: of 1,054 codes only 609 are stable across all six vintages, and 215 metropolitan CBSAs are both stable and usable as panel units. See DECISION_LOG D028.

Not yet implemented, and each leaves a documented gap:

IRS SOI county-to-county migration — public, but requires manual file selection.
Census ACS housing tenure / vacancy — public API; a free key is needed for high-volume use.

The core project must run without any of these. They are optional: true in the config.

Reproducibility contract

Every fetch writes data/cache/<source>/<name>.manifest.json containing source URL, retrieval timestamp, release date where discoverable, coverage period, licence/terms, redistribution status, schema version, row count, SHA-256 checksum, geographic level, and known limitations. make validate-data fails if a manifest is missing or its checksum does not match.