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Tools / Nebraska Farmland Valuation / Methodology & Audit

Farmland Valuation — Methodology & Audit Tables

Complete derivation of every constant, factor, and formula used by the Nebraska Farmland Valuation tool, published so that a reviewer, auditor, or examiner can independently reproduce any figure the tool reports.

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Contents
  1. Scope, sources, and data vintages
  2. Equivalent-acre math — formulas and published ratio tables
  3. Reproducing the numbers by hand (and the five traps)
  4. UNL survey data — full audit table and verification steps
  5. The survey fallback basis — published rates, applied as stated
  6. Adjustment guidance — market-derived reference data
1 Scope, Sources, and Data Vintages

The valuation tool produces an internal collateral evaluation consistent with the content elements of the Interagency Appraisal and Evaluation Guidelines (2010). Its primary method is the sales comparison approach; the UNL Farm Real Estate Market Survey serves as a fallback basis and benchmark only.

Every number the tool reports traces to one of four sources:

SourceUsed forVintageVerifiable at
Nebraska DOR Property Assessment Division sales file (Form 521) Comparable sale price, date, acres, land-class acres, arm's-length qualification code Jul 2021 – present County register of deeds; PAT.SalesFileREQ@nebraska.gov
County assessor CAMA / statewide parcel layer Subject description, parcel geometry, unverified sales Current County assessor parcel search (PID links in tool)
UNL Farm Real Estate Market Survey (final reports) Land-class value ratios; fallback valuation basis — cap.unl.edu/realestate
USDA NRCS soil data / Nebraska DOR land valuation methodology Soil series reference for tract descriptions Static NRCS Soil Data Access; NE DOR ag land valuation guidance

The tool and this page read the identical dataset file (/data/nebraska-farmland.json) and apply the identical formulas, so the tables below cannot drift out of sync with the tool.

2 Equivalent-Acre Math

Comparable sales rarely share the subject's land-class mix. The equivalent-acre (EA) method — standard practice in professional agricultural appraisal — converts every land class into a common unit so that sales of different mixes are directly comparable on a single price scale.

Step 1 — Choose the unit basis

The reference class is the subject's dominant land class by acreage (irrigated, dryland, or grassland; "other" can never be the basis). That class is assigned a ratio of 1.000. Re-basing rescales every ratio and unit price by the same constant and therefore does not change any indicated value — it only makes the unit prices read in familiar terms.

Step 2 — Derive class ratios from the published survey
ratio(class) = ROUND( 1000 × survey_value(class, LATEST YEAR) / survey_value(reference class, LATEST YEAR) ) / 1000 special cases: ratio(grass/trees) = ROUND( 850 × survey_value(grassland) / survey_value(reference) ) / 1000 ratio(other) = 0 <- roads, waste, water, sites: no productive capacity

"Grass / trees" is valued at 85% of grassland (a timber-encroachment discount applied to the land-use category, not to soil quality).

Why "other" carries a ratio of zero, and what that constant used to be. Equivalent acres measure productive capacity. The "other" category holds road right-of-way, waste ground, water, shelterbelt, accretion and farmstead sites — land that produces nothing and, in the case of a building site, is accounted for separately as an improvement. Assigning it any positive ratio would require a value that no source publishes: UNL does not survey these classes, and in the Department of Revenue sales file the per-class value columns for waste, roads, shelterbelt and accretion are empty in every record (only farmstead, dwelling and outbuilding values are populated). There is therefore nothing to derive a ratio from.

Correction notice. An earlier build set this ratio to 0.15 × the irrigated rate. That was an unsupported constant, and anchoring it to irrigated land made it worse: at published 2026 rates it implied waste and road ground was worth $478/acre in the Northwest and $1,864/acre in the East — between 50% and 71% of grazing land in every district, and rising wherever irrigated land happened to be expensive. Neither implication is defensible, so the constant has been removed rather than re-derived.

Materiality. Across 21,212 parcels in the sales file, "other" is a median 2.5% of agricultural acres (mean 5.1%, 90th percentile 9.6%). Moving the ratio from 0.15 to 0 therefore changes equivalent acres by about 0.4% on a typical parcel and 1.5% at the 90th percentile — and it moves the subject and every comparable in the same direction, so the effect on the indicated value is smaller still. The change is made because the constant was indefensible, not because it was moving values materially.

If "other" land does carry value. Rough ground that genuinely grazes should be classified as Grassland rather than Other. A building site's contributory value belongs in Section 3 with the improvements. A tract left as Other still carries its county unit value in the survey fallback; it simply adds no productive capacity to the sales comparison. If every tract is Other, the subject has no productive acres and the equivalent-acre method cannot produce a value — the tool says so rather than reporting zero.
Published ratio table — all districts, irrigated basis

Step 3 — Convert the subject and each comparable to EA
subject EA = Σ ( tract acres × ratio(tract class) ) comp EA per acre = ( %irr×ratio(irr) + %dry×ratio(dry) + %grass×ratio(grass) + %other×ratio(other) ) / (sum of those percentages) comp EA = comp acres × comp EA per acre comp $ per EA = comp sale price / comp EA

The division by the sum of the percentages normalizes mixes that do not total exactly 100% (assessor-reported mixes are rounded to whole percents and frequently sum to 99% or 101%). If a comparable has no land mix at all, the subject's mix is assumed and the grid flags it.

Step 4 — Adjust, weight, and reconcile
adjusted $/EA = comp $ per EA × ( 1 + net adjustment% / 100 ) net adjustment = sum of the five analyst adjustment percentages (simple addition, not compounded) weight(i) = entered weight, or an equal share of the unassigned remainder if blank (all weights are then normalized to total 100%) indicated value = Σ ( adjusted $/EA(i) × normalized weight(i) ) × subject EA low / high = least / greatest adjusted $/EA × subject EA total value = indicated land value + improvements (county assessed)
Rounding policy. Class ratios are rounded to three decimals before any EA computation — the tool uses the same rounded ratios it displays. Equivalent acres are carried at full precision internally and displayed to one decimal. Dollar figures are rounded only at final display. To reproduce a figure exactly, use the three-decimal ratios shown above, not unrounded quotients.
3 Reproducing the Numbers by Hand
If your spreadsheet does not match the tool, it is almost certainly trap #1 below. The class ratios come from the latest survey year alone — not the three-year weighted average that the tool displays in its survey benchmark table.
The five traps
  1. Latest year only, not the weighted average. Ratios use the most recent survey year. The weighted average (20/30/50 across three years) is used only for the survey fallback basis — never for ratios. In the North District this changes the grassland ratio from 0.228 (correct) to 0.211 (wrong) — an 8% error that flows into every EA figure.
  2. Ratios are rounded to three decimals before use. Carrying full precision through the chain gives slightly different EA totals.
  3. "Other" acres carry a ratio of zero and drop out of the equivalent-acre total entirely — they are not a small fraction. A spreadsheet that spreads the sale price across all acres rather than only the productive ones will not match. (An earlier build used 0.15 × the irrigated rate here; see section 2.)
  4. Comparable mixes are normalized by their own sum, which is often 99% or 101%, not 100%.
  5. "Grass / trees" is 85% of grassland, and the unit basis follows the subject's dominant class — so the same comparable shows a different $/EA against a grass subject than against an irrigated subject (the indicated value is unaffected).
Fully worked example — Holt County (North District)

Subject: 120 acres irrigated + 40 acres grassland. Comparable: $1,153,518 for 156 acres, assessor-reported mix 83% irrigated / 0% dryland / 14% grassland / 2% other.

Every value above is computed live from the same dataset the tool uses. Reproduce it in a spreadsheet with the three-decimal ratios and you will match the tool to the cent.

4 UNL Survey Data — Full Audit Table

These are the exact values embedded in the tool. They are transcribed from the published Nebraska Farm Real Estate Market Highlights final report (Appendix Table 4 carries the full district history; Table 1 carries the current year). Values are as of February 1 of each survey year.

Class mapping — tool label to published report line
Tool labelPublished report land typeNote
IrrigatedCenter Pivot Irrigated CroplandGravity irrigated runs lower; pivot is the market norm
DrylandDryland Cropland (No Irrigation Potential)The "irrigation potential" line runs higher
GrasslandGrazing Land (Nontillable)Tillable grazing runs higher
Grass / TreesGrazing Land (Nontillable) × 0.85Timber-encroachment factor on the grassland rate
Why there is no CRP land class. The UNL survey reports eight land types and none of them is CRP — the phrase does not appear anywhere in the report. Nebraska's assessment system likewise has no separate CRP class: county assessors carry enrolled acres inside the ordinary land classes and set a CRP flag on the parcel. Measured across 915 CRP-flagged qualified sales in the Department of Revenue sales file, those acres are 61% dryland, 26% grassland, and 13% irrigated, and 63% of the parcels are dryland-dominant.

An analyst reading a county land table will therefore never encounter a CRP row, so the tool offers no CRP land use: enrolled acres are entered as the class the assessor assigned them, which also keeps the subject consistent with the comparables, whose land-mix percentages come from that same classification. A CRP contract encumbering a comparable sale is a different matter — it is an element of comparison affecting that sale's price, and belongs in the analyst's "Other" adjustment with a note.

Correction notice. Two earlier builds handled this differently. The first used UNL Hayland as a CRP proxy — incorrect, because hayland is actively farmed and produces a marketable crop, whereas CRP is idled land under a federal contract whose value turns on the remaining payment stream and the land's reversionary use; the two are not economically equivalent, and no CRP figure was ever published to proxy in the first place. The second kept a CRP land use that mapped to dryland, which was accurate but redundant once it was established that assessors never present CRP as a separate class. Both have been removed.
Survey values by district, year, and class ($/acre)

How to verify. Download the current final report from cap.unl.edu/realestate, open Appendix Table 4, and read across the row for the survey year and down to the district column for each of the four land types above. The figures must match this table cell for cell. Note that the tool's "West" district is not a USDA/NASS district — Nebraska's published survey has eight districts, and the tool's West district uses the published Northwest values, because 8 of its 11 counties fall in NASS Northwest.
5 The Survey Fallback Basis

When fewer than three usable comparable sales exist, or when the analyst elects it, the tool falls back to the UNL survey. That fallback is deliberately the simplest possible calculation:

tract value = tract acres × published UNL district $/acre for that land use (latest survey year) Grass / Trees tracts use the grassland rate × 0.85 (a timber-encroachment factor tied to the land-use category, applied consistently with the equivalent-acre ratios in section 2). "Other" tracts are carried at the county assessor's unit value for that tract. land value = Σ tract values (no range, no soil-quality adjustment)
What was removed, and why. Earlier versions scaled each tract by a soil quality factor (Land Value Group / Grassland Quality Class) and reported a ±15% indicated range around a three-year weighted average. All three constructs have been retired:
  • The ±15% range was an undocumented constant. Tested against 4,369 state-qualified sales it captured only 26.9% of them, with the central 50% spanning roughly ±27% — it implied a precision the survey basis does not have.
  • The soil-quality factors were an unpublished adjustment layered on top of published data, which made the fallback harder to audit and risked double-counting quality against the analyst's Land quality adjustment in the sales grid.
  • The three-year weighting produced a figure that appears in no published source, and differed from the latest-year values used for the class ratios.
The fallback now reports exactly what UNL published, so a reviewer can verify it with a single lookup. Soil quality class is still captured per tract as descriptive assessor data, and still informs the analyst's judgment in the sales grid, but it no longer scales any figure.

How to read the fallback. It is a district-average indicator, not a property-specific estimate of value. Nebraska district averages diverge widely from individual sale prices — in testing, the median qualified sale traded at about 1.2× its survey-implied value, driven substantially by the small-tract premium documented in section 6. This is precisely why the tool treats the sales comparison approach as primary: comparable sales of similar land in the same neighborhood are a materially better estimator than a district average.

6 Adjustment Guidance — Market-Derived Reference Data

There is no published schedule of "standard" dollar adjustments for farmland, and none should be invented: recognized appraisal practice requires adjustments to be derived from the market, ordinarily through paired-sales analysis. What follows is reference data computed from Nebraska's own state-qualified sales — a defensible starting point for judgment, with the derivation stated so a reviewer can test it.

Sequence of adjustments

Standard practice applies transaction-related elements first, then physical ones: property rights conveyed → financing terms → conditions of sale → market conditions (time) → location → physical characteristics (land quality, size, shape, access). The tool's five adjustment rows map onto the latter part of this sequence; transaction-related elements belong in the "Other" row with a note.

Market conditions (time) — median $/acre by year

State-qualified arm's-length sales, 40+ ag acres, statewide, classified by predominant land class. Note the divergence: irrigated and dryland have been roughly flat to modestly negative since 2023, while grassland has risen 12–18% per year. A two-year-old grassland comparable therefore requires a substantial positive time adjustment, whereas a two-year-old irrigated comparable may require little or none.

Size — median $/acre by tract size within land class

Qualified sales, 2023 to present. Percentages are relative to the 40–80 acre band within the same class. The small-tract premium is large and persists within every class — but acreage also correlates with quality, location, and buyer type, so these figures overstate the pure size effect. Use them to sanity-check the direction and rough magnitude of a size adjustment, not as a lookup table.

Location, land quality, and other elements

No generalizable rate exists for these. Derive them from paired sales within the subject's market area and record the basis in the adjustment note. One caution specific to this tool: the equivalent-acre conversion already normalizes for land-class mix, so the Land quality / productivity adjustment should capture only residual differences — soil productivity within class, drainage, topography, irrigation adequacy. Adjusting again for the class mix would double-count it.

Reference data in section 7 was computed from the Nebraska DOR sales file on 2026-07-21. Sections 2 and 4 render live from the tool's dataset and update automatically when it does.