Published September 8, 2026
Research question
How can public USDA Rural Development loan data inform manufactured-home market research?
This brief focuses on Rural Development program activity published in datasets and dashboards. The unit of analysis is loans, guarantees, borrowers, or obligations as defined by the selected product. Those two statements set the boundary for every comparison that follows.
Finding
USDA data can describe activity within named Rural Development programs. A total for a county or lender does not automatically represent manufactured-home lending, applications, denials, or the whole mortgage market.
That finding is deliberately narrow. Public datasets are useful when the question matches the collection program. They become misleading when a national or regional estimate is treated as a property record, or when a screening value is written as though it were a verified condition.
Method
The review used this procedure: select the program before filtering geography, keep fiscal year separate from calendar year, read the data dictionary, retain suppressed or unavailable values, and verify whether the product identifies manufactured homes. We opened the publisher's program page, data page, and technical material on September 8, 2026. We recorded the publisher, page title, URL, unit, geography, reference period, update status, and any warning attached to the measure.
| Method field | What the reviewer records | Why it matters |
|---|---|---|
| Universe | Population the program intends to cover | Defines who or what an estimate represents |
| Unit | Home, shipment, household, loan, place, or record | Prevents unlike counts from being combined |
| Period | Survey year, month, fiscal year, or release date | Keeps time comparisons consistent |
| Geography | National, region, state, county, tract, or place | Shows whether a local inference is supportable |
| Status | Preliminary, revised, final, suppressed, or unavailable | Preserves the publisher's qualification |
| Extraction | Table, filter, variable, weight, and calculation | Lets a second reviewer repeat the work |
We did not estimate a new national total, rank communities, or infer an individual outcome. No property files, resident records, lender files, or site observations were used. The result is a reading guide for the published sources, not a substitute for an analysis built around a specific business question.
How to reproduce the review
Start at the first source below and write down the dataset or program name exactly as the publisher gives it. Open the technical documentation before choosing a variable. If the publisher supplies a codebook, data dictionary, sample weight, standard error, or revision note, keep it with the extract.
Next, make a one-row source log for every value. Include the direct URL and access date. Save the filter selections in words; a screenshot alone may hide them. A second reviewer should be able to reach the same table and explain why the selected unit answers the research question.
For comparisons, put both definitions side by side. Stop if the universes, units, periods, or geographies differ. A comparison may still be useful, but it must be presented as two separate measures rather than a single rate or gap. Do not convert missing, suppressed, or not-applicable values to zero.