Land Values Methodology and Quality Measures

Land Values Methodology and Quality
Measures
ISSN: 2167-1362

Released August 3, 2017, by the National Agricultural Statistics Service (NASS), Agricultural Statistics Board, United States Department of
Agriculture (USDA).

Survey Methodology for Land Values
Scope and Purpose: Land values are estimated annually in August. Estimates are published for the United States and by
State, except Alaska and Hawaii, and include the value per acre of all farm real estate, cropland, and pasture. Value per
acre estimates are also published for states with a prevalence of both irrigated and non-irrigated cropland. In addition, the
publication contains estimates for the total value of all farm real estate by state, except Alaska and Hawaii, and for the
United States.
The data are collected as part of the June Area Survey, a multipurpose survey used to estimate crop acreages and measure
incompleteness of the NASS list frame for numerous other surveys. The June Area Survey is conducted every year in all
states except Alaska and Hawaii.
Survey Timeline: Some presurvey screening is done in May to identify farm operators to be interviewed. Data collection
is conducted by personal interview from the end of May through mid-June. The reference date for the June Area Survey is
June 1. Regional Field Offices (RFOs) conduct the first round of editing and analysis over a three-week period, ending in
late June. An additional week of editing and analysis occurs in early July. Once editing is complete, the data are
summarized. Following summarization, RFOs review the survey results for states within their regions and submit State
level recommendations to NASS headquarters in mid-July. A national review is completed and national estimates are
established. The land values estimates are published annually in early August.
Sampling: The target population for the land values estimates is all farms and ranches with $1,000 or more in agricultural
sales (or potential sales). The June Area Survey utilizes an area sampling frame. The area frame consists of all land in all
states, except Alaska, and thus represents all farms and ranches. The frame in each state is divided into segments of land.
For more intense agricultural regions, segments are about one square mile in size. An optimal sample is selected in each
state with a national sample size of approximately 11,000 segments. The cost of building the frame and preparing
materials for enumeration is significant, so sampled segments are in the survey for five consecutive years. About
20 percent of the segments are rotated out and replaced with new ones each year.
Through personal interviews, field enumerators divide the segments into tracts, each tract representing a unique operating
arrangement. Some of the tracts do not qualify under the farm definition and screen out; the remaining agricultural tracts
become the sample for land values. Tracts identified on American Indian Reservations in Arizona, Nevada, New Mexico,
and Utah as well as tracts in public land and non-agricultural land use strata in all States are excluded from the sample.
Data Collection: Each enumerator is responsible for several segments of land. Enumerators must account for all
operations and land contained in their assigned segments. Contact with each respondent for an in person interview is
attempted by an enumerator and, where possible, a personal interview is conducted. Survey questionnaires are returned to
the RFOs where they are visually reviewed and key entered.
Questionnaire content and format are evaluated annually through a specifications process where requests for changes are
evaluated and approved or disapproved. Input may vary from question wording or formatting to a program change
involving the deletion or modification of current questions or addition of new ones. If there are significant changes to
either the content or format proposed, a NASS survey methodologist will pre-test the changes for usability.

All federal data collections require approval by the Office of Management and Budget (OMB). NASS must document the
public need for the data, show the design applies sound statistical practice, ensure the data do not already exist elsewhere,
and that the public is not excessively burdened. The June Area questionnaire must display an active OMB number that
gives NASS the authority to conduct the survey, a statement of the purpose of the survey and the use of the data being
collected, a response burden statement that gives an estimate of the time required to complete the form, a confidentiality
statement that the respondent’s information will only be used for statistical purposes in combination with other producers,
and a statement saying that response to the survey is voluntary and not required by law.
Survey Edit: As survey data are collected and captured, data are edited for consistency and reasonableness using
automated systems. Reported data are edited as a batch of data when first captured. The edit logic ensures the coding of
administrative data follows the methodological rules associated with the survey design. Relationships between data items
(i.e. responses to individual questions) on the current survey are verified. Some data items in the current survey are
compared to data items from earlier surveys to ensure certain relationships are logical. The edit will determine the status
of each record to be either “dirty” or “clean” (i.e. failing or passing the edit requirements for consistency and
reasonableness). Records that fail edit requirements must be updated or must be certified by an analyst to be exempt from
the failed edit requirement. Only records that pass edit requirements are eligible for final summary.
Analysis Tools: Edited June Area data are processed through an interactive analysis tool which displays data for all
reports by item. The tool provides scatter plots, tables, charts, and special tabulations that allow the analyst to compare an
individual record to similar records. Atypical responses and unusual data relationships become evident and RFO and
Headquarters (HQ) staff review them to determine if they are correct. The tool allows comparison to an agricultural
operation’s previously reported data to detect large changes in the operation. Data found to be in error are corrected, while
accepted data are retained.
Outliers: Both RFO and HQ statisticians conduct a review of value outliers to ensure the most accurate data and
indications possible. The RFO statisticians review outliers for states within their regions and the HQ statistician examines
outliers across all states. A determination is made as to whether an adjustment to final estimates will be required for each
outlier. Many outliers trace back to unique situations that do not exist in the target population as much as the survey
weight would indicate.
Nonsampling Errors: Nonsampling errors are present in any survey process. These errors include reporting, recording,
and editing errors. Steps are taken to minimize these errors, such as comprehensive interviewer training, validation, and
verification of processing systems, application of detailed computer edits, and evaluation of the data via the analysis tools.
Nonresponse Adjustment: Response to the June Area Survey is voluntary. Some producers refuse to participate in the
survey, others cannot be located during the data collection period, and some submit incomplete reports. These
nonrespondents must be accounted for if accurate estimates of land values are to be made. The weights for data items
from reporting farms and ranches are not adjusted upward to account for the nonrespondents. For the land value questions,
missing item level data are calculated by an imputation algorithm. All other missing item level data are made usable by
manual imputation.
The land values imputation algorithm uses a nearest neighbor approach and requires a minimum of five complete reports
within the nonresponse group to calculate the imputed value. If five complete reports are not available, the weighting
groups are collapsed until five complete reports are identified. The first nonresponse group is reports within the same
segment. If five complete reports are not found, it then moves on to reports within the same county and in similar strata,
all reports in that county, all reports in the same Agricultural Statistics District (ASD) and lastly the entire State.
Estimators: The primary estimators used to set land values estimates are the area frame item-to-item ratios. The
estimators calculate the weighted average value per acre by taking the ratio of total dollars to acres. Two area frame
estimators are utilized in the NASS estimation program. Items that pertain to data entirely within the segment boundaries
are weighted by the sampling weight associated with the segment. Items that pertain to entire farm level data are weighted
by the original segment sampling weight and by the proportion of the farm residing inside the segment boundaries.
Cropland and pasture land values are based on land within the segment boundaries, thus the numerator and denominator
are weighted by only the segment sampling weight. For farm real estate land values, the numerator and denominator are
2

Land Values Methodology and Quality Measures (August 2017)
USDA, National Agricultural Statistics Service

multiplied by the proportion of the farm residing inside the segment and the original segment sampling weight. Ratio
indications are calculated excluding and including the imputed data.
Estimation: The land values data are summarized from the June Area dataset. Since all RFOs conduct identical surveys,
the State data can be summarized and national survey point estimates, or indications, computed. RFOs are responsible for
performing a detailed review of the survey data for states within their regions. Any irregularities revealed by the analysis
must be investigated and, if necessary, resolved. The summary results provide multiple direct and ratio indications for
each data series being estimated. RFOs interpret the survey indications and submit State recommendations to NASS
headquarters, providing justification in cases where recommendations deviate from survey results.
For the national estimates, NASS assembles a panel of statisticians to serve as the Agricultural Statistics Board which
reviews the national results and establishes the national estimates. Since larger sample sizes yield more precise results,
NASS employs the “top-down” approach by determining the national estimates first and reconciling the state
recommendations to the national estimate. Using the acreage for each type of land for each state as a weight, state land
value estimates are weighted to the national estimate. The Board also enjoys an advantage in being able to examine results
across states, and compare the state recommendations. The same estimators used in the state summaries are produced by
the national summary. The Board follows the same approach the states do in determining the national estimate. The
historical relationship of the survey estimates to the official estimate is evaluated over time to determine accuracy and bias
using tables and graphs. Each Board member completes an independent interpretation of the survey results which are
shared with the other members and a consensus is reached. Often the state recommendations weighted by acreage do not
equal the national estimate. Board members must reexamine the state results and revise some states to make the product of
the state estimates agree with the national estimate.

Land Values Methodology and Quality Measures (August 2017)
USDA, National Agricultural Statistics Service

3

Quality Metrics for Land Values
Purpose and Definitions: Under the guidance of the Statistical Policy Office of the Office of Management and Budget
(OMB), the United States Department of Agriculture’s National Agricultural Statistics Service (NASS) provides data users
with quality metrics for its published data series. The metrics tables below describe the performance data for the survey
contributing to the publication. The accuracy of data products may be evaluated through sampling and non-sampling error.
The measurement of error due to sampling in the current period is evaluated by the coefficient of variation for each estimated
item. Non-sampling error is evaluated by response rates.
Farm Tract is a portion of a sampled segment that represents a unique operating arrangement that meets the
definition of a farm.
Sample Size is the total number of farm tracts found in the sample segments in the June Area Survey excluding
tracts on American Indian Reservations in Arizona, Nevada, New Mexico, and Utah and tracts in public and nonagricultural land use strata in all States.
Response rates measure the proportion of the farm tracts in the land values sample that responded to the June Area
Survey.
Coefficient of Variation provides a measure of the size for the standard error relative to the point estimate and is
used to measure the precision of the results of a survey estimator.
June Area Survey Land Values Sample Size and Response Rates: To assist in evaluating the performance of the
estimates in the Land Values report, the sample size and response rates are displayed. The sample size changes from year
to year as the number of farm tracts identified within the sampled segments varies.

4

Land Values Methodology and Quality Measures (August 2017)
USDA, National Agricultural Statistics Service

Land Values Sample Size and Response Rate – Region, State, and United States: 2016 and 2017
Region and state

Sample size

Response rate

2016

2017

(number)

2016

(number)

2017

(percent)

(percent)

Northeast ...............
Connecticut ........
Delaware ...........
Maine .................
Maryland ............
Massachusetts ...
New Hampshire .
New Jersey ........
New York ...........
Pennsylvania .....
Rhode Island .....
Vermont .............

1,721
25
74
76
203
46
17
195
309
657
28
91

1,693
25
75
67
200
42
25
192
315
624
26
102

74.3
72.0
79.7
82.9
69.5
69.6
82.4
76.9
71.5
76.9
39.3
70.3

69.4
80.0
58.7
68.7
69.0
69.0
72.0
77.6
69.2
69.2
26.9
72.5

Lake ......................
Michigan ............
Minnesota ..........
Wisconsin ..........

3,370
735
1,697
938

3,328
724
1,664
940

78.3
74.4
77.7
82.3

71.6
65.6
75.2
69.8

Corn Belt ...............
Illinois ................
Indiana ...............
Iowa ...................
Missouri .............
Ohio ...................

7,330
1,749
1,031
1,922
1,633
995

7,289
1,744
1,012
1,929
1,614
990

72.8
74.7
70.2
81.0
57.8
81.2

66.8
67.9
62.1
71.7
55.3
79.2

Northern Plains ......
Kansas ..............
Nebraska ...........
North Dakota .....
South Dakota .....

5,827
1,526
1,631
1,523
1,147

5,720
1,517
1,534
1,531
1,138

57.1
48.6
61.7
69.3
45.8

51.3
40.8
57.2
58.7
47.4

Appalachian ...........
Kentucky ............
North Carolina ...
Tennessee .........
Virginia ..............
West Virginia .....

3,647
744
937
1,151
517
298

3,538
735
938
1,101
513
251

80.0
71.4
75.3
87.4
77.6
91.3

74.6
70.5
70.3
79.7
72.3
84.5

See footnote(s) at end of table.

Land Values Methodology and Quality Measures (August 2017)
USDA, National Agricultural Statistics Service

--continued

5

Land Values Sample Size and Response Rate – Region, State, and United States:
2016 and 2017 (continued)
Region and state

Sample size
2016

Response rate
2017

(number)

2016

(number)

2017

(percent)

(percent)

Southeast ..............
Alabama .............
Florida ................
Georgia ..............
South Carolina ...

2,023
659
274
766
324

2,004
689
238
760
317

72.8
81.8
69.0
64.8
76.9

70.3
83.5
61.3
57.0
80.1

Delta ......................
Arkansas ............
Louisiana ...........
Mississippi .........

2,331
956
674
701

2,288
928
663
697

85.1
80.4
83.7
92.7

83.3
80.8
82.1
87.9

Southern Plains ......
Oklahoma ..........
Texas .................

5,020
1,125
3,895

4,857
1,112
3,745

73.6
55.7
78.8

70.5
54.7
75.2

Mountain ................
Arizona ..............
Colorado ............
Idaho ..................
Montana .............
Nevada ..............
New Mexico .......
Utah ...................
Wyoming ............

3,354
308
689
539
966
21
369
296
166

3,290
294
691
530
968
22
349
275
161

72.2
77.9
57.5
67.0
78.0
76.2
80.2
83.8
66.9

69.2
72.1
52.8
65.1
78.6
81.8
73.4
79.3
63.4

Pacific ....................
California ............
Oregon ...............
Washington ........

2,036
845
524
667

1,948
804
505
639

71.8
74.9
78.2
62.8

66.7
70.9
70.9
58.2

United States .........

36,659

35,955

72.4

67.6

6

Land Values Methodology and Quality Measures (August 2017)
USDA, National Agricultural Statistics Service

Land Values Coefficient of Variation – Region, State, and United States: 2016 and 2017
Coefficient of variation
Region and state

Farm real estate

Cropland

Pasture

2016

2017

2016

2017

2016

2017

(number)

(number)

(number)

(number)

(number)

(number)

Northeast ...............
Connecticut ........
Delaware ...........
Maine .................
Maryland ............
Massachusetts ...
New Hampshire .
New Jersey ........
New York ...........
Pennsylvania .....
Rhode Island .....
Vermont .............

2.6
19.2
6.5
9.8
5.5
8.7
21.5
7.5
5.6
3.5
13.1
9.9

3.4
18.7
7.1
9.1
3.6
10.7
12.2
7.9
4.2
4.5
5.4
14.0

2.6
(NA)
1.9
(NA)
2.0
(NA)
(NA)
7.8
4.9
4.6
(NA)
(NA)

3.6
(NA)
3.5
(NA)
2.9
(NA)
(NA)
18.6
4.9
5.0
(NA)
(NA)

7.4
(NA)
(NA)
(NA)
10.4
(NA)
(NA)
25.6
6.9
6.5
(NA)
(NA)

8.3
(NA)
(NA)
(NA)
3.3
(NA)
(NA)
0.2
7.1
8.0
(NA)
(NA)

Lake ......................
Michigan ............
Minnesota ..........
Wisconsin ..........

1.5
2.6
2.1
3.4

1.9
1.8
1.8
5.5

2.4
2.7
1.7
7.8

1.6
2.2
1.5
5.1

4.5
9.7
6.5
4.5

4.3
4.1
5.0
6.5

Corn Belt ...............
Illinois ................
Indiana ...............
Iowa ...................
Missouri .............
Ohio ...................

0.8
1.2
1.3
1.0
2.0
2.4

0.8
1.0
1.2
1.0
1.9
2.3

0.8
1.0
1.6
1.9
1.5
2.0

0.9
1.0
1.6
2.3
1.5
2.1

2.3
5.1
4.6
3.6
2.6
6.2

2.7
2.7
2.7
2.1
3.2
12.3

Northern Plains ......
Kansas ..............
Nebraska ...........
North Dakota .....
South Dakota .....

1.3
3.7
2.4
1.8
1.6

1.1
2.0
2.3
1.7
2.2

1.0
1.6
2.5
1.5
2.0

1.0
1.6
2.6
1.5
2.0

1.9
3.2
3.5
3.4
3.8

1.8
1.8
2.8
8.5
3.5

Appalachian ...........
Kentucky ............
North Carolina ...
Tennessee .........
Virginia ..............
West Virginia .....

2.0
3.0
3.9
2.5
6.5
4.6

2.4
3.4
8.0
2.7
4.9
4.9

1.5
2.7
2.4
2.1
5.4
3.4

1.3
2.6
2.0
2.1
4.1
4.9

3.3
4.5
9.4
4.5
7.1
3.9

3.1
4.7
8.5
3.9
5.5
13.3

See footnote(s) at end of table.

Land Values Methodology and Quality Measures (August 2017)
USDA, National Agricultural Statistics Service

--continued

7

Land Values Coefficient of Variation – Region, State, and United States: 2016 and 2017 (continued)
Coefficient of variation
Region and state

Farm real estate

Cropland

Pasture

2016

2017

2016

2017

2016

2017

(number)

(number)

(number)

(number)

(number)

(number)

Southeast ..............
Alabama .............
Florida ................
Georgia ..............
South Carolina ...

3.5
4.7
9.6
3.6
4.7

5.2
4.6
11.7
4.9
2.8

5.7
4.0
9.2
2.2
4.0

3.3
3.5
5.5
2.6
2.8

11.9
4.1
16.8
4.1
11.4

3.2
3.5
4.9
4.7
4.3

Delta ......................
Arkansas ............
Louisiana ...........
Mississippi .........

2.2
2.3
5.6
3.8

2.2
3.2
5.7
3.2

2.0
1.2
6.8
1.6

1.4
1.3
4.6
1.4

5.4
8.3
5.6
12.8

4.7
8.2
5.5
7.3

Southern Plains ......
Oklahoma ..........
Texas .................

9.0
4.6
11.5

1.8
5.0
1.8

2.0
2.2
2.5

3.2
2.3
4.1

10.4
3.2
12.9

13.6
2.9
17.2

Mountain ................
Arizona ..............
Colorado ............
Idaho ..................
Montana .............
Nevada ..............
New Mexico .......
Utah ...................
Wyoming ............

10.4
8.0
7.8
6.8
18.0
4.6
40.1
11.5
8.9

15.3
14.7
11.0
5.0
11.9
5.5
63.1
39.1
9.9

4.1
8.1
6.2
4.5
8.8
(NA)
16.0
23.5
14.6

4.2
10.8
5.9
3.6
5.7
(NA)
15.1
21.0
16.6

20.2
(NA)
11.2
24.8
9.1
(NA)
63.3
15.7
3.9

20.5
(NA)
9.1
18.6
5.3
(NA)
54.3
13.8
6.2

Pacific ....................
California ............
Oregon ...............
Washington ........

5.8
9.1
8.7
9.2

5.2
7.4
9.8
9.8

4.4
5.4
6.9
6.9

3.7
4.3
5.8
6.0

8.2
9.6
12.1
11.5

14.2
18.1
25.5
24.0

United States .........

2.2

2.4

0.8

0.7

5.3

6.4

(NA) Not available.

8

Land Values Methodology and Quality Measures (August 2017)
USDA, National Agricultural Statistics Service

Information Contacts
Process

Unit

Estimation ............................................... Environmental Economics and
Demographics
Data Collection ....................................... Survey Administration Branch
Questionnaires ....................................... Data Collection Branch
Sampling and Editing .............................. Sampling Editing and Imputation
Methodology Branch
Summary and Estimators ........................ Summary Estimation and Disclosure
Methodology Branch
Dissemination ......................................... Data Dissemination Office
Media Contact and Webmaster ............... Public Affairs Office

Telephone

Email

(202) 720-6146
(202) 720-3895
(202) 720-6201

[email protected]
[email protected]
[email protected]

(202) 720-5805

[email protected]

(202) 720-4008
(202) 720-3400
(202) 720-2639

[email protected]
[email protected]
[email protected]

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