Farms and Land In Farms - Quality Measures

Farms and Land in Farms Methodology
and Quality Measures
ISSN: 2167-132X

Released February 17, 2023, by the National Agricultural Statistics Service (NASS), Agricultural Statistics Board, United Sta tes Department
of Agriculture (USDA).

Survey Methodology for Farms and Land in Farms In 2022
Scope and Purpose: Farms and land in farms are estimated annually in February. Estimates made for this program
include the number of farms, land in farms, and average farm size. Estimates are published for the United States and by
state and economic sales class.
In 2022, data were collected by NASS during the June Agricultural Survey using sampling procedures to ensure every
farm and ranch has a chance of being selected. NASS used a multiple sampling frame approach to count farms and
measure land in farms. The Area Frame portion is collected on the June Area Survey in each state except Alaska and
Hawaii and enumerated in early June. Highly trained interviewers located each sampled segment and identified every
farm and ranch operating land in the segment and the number of acres in each operation.
These data were used to compute summaries of farm numbers and acres of land in farms. Additionally, all farms found in
the segments were checked against a list of farms and ranches maintained by NASS to determine whether the farm is on
the list. Operations found in the Area Frame sample that were not on the list provided a measure of incompleteness of the
list. The summarized totals for these non-overlap (or not-on-list) operations were combined with summarized totals
collected from a sample selected from the list to calculate additional indications of farms and land in farms.
Survey Timeline: Some pre-survey screening is done in late March to identify farm operators to be contacted. Data
collection is conducted from the end of May through mid-June. The reference date for the June Area Survey is June 1.
Regional Field Offices (RFOs) conduct editing and analysis from June to mid-July. Once editing is complete, the data are
summarized. Following summarization, RFOs review the survey results and submit State-level recommendations to
NASS headquarters. A National review is completed and National estimates are established. The farms and land in farms
estimates are published annually in mid-February.
Sampling: The target population for the farms and land in farms 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. Although Hawaii has an area frame, NASS
does not conduct the June Area Survey in Hawaii. The frame in each state is stratified by the percentage of land devoted
to agriculture and divided into segments of land, which are about one square mile in size. A stratified random sample is
selected in each state with a National sample size of about 9,000. 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.
Each segment is divided into tracts, each tract representing a unique operating arrangement. Some tracts do not have
agriculture and are screened out. Data are collected on the remaining agricultural tracts.
Data Collection: Each enumerator is responsible for collecting information on all agricultural tracts within each of
several segments of land. The enumerator collects information on each agricultural tract through personal interviews. The
completed survey questionnaires are returned to the RFOs where they are 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 that the design applies sound statistical practice, and ensure that 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 fo rm, 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 data are processed through an interactive analysis tool that 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 Regional Field Office
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.
Non-sampling Errors: Non-sampling 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.
Non-response 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
non-respondents must be accounted for if accurate estimates of farm numbers are to be made. The non-response data
items and sampling units are machine imputed from previously reported data or manually imputed b y Regional Field
Office statisticians, largely by observation. The weights for data items from reporting farms and ranches are not adjusted.
Estimators: The primary estimators used to set farms and land in farms estimates are the area frame direct expansion and
ratio estimators. The direct expansion generates a total for the current year. It is calculated by summing the June Area Survey
data multiplied by the proportion of the farm residing inside the segment and weighted by the original segment sampling
weight. The ratio estimator measures the change from year to year and is the ratio of the current year’s and previous year’s
direct expansions for comparable segments. The sampling weights are adjusted to account for those segments that are not
comparable.
A multiple frame direct expansion is also generated for farms and land in farms. It is the sum of direct expansion from the
June Agricultural Survey data, a NASS list only survey, and the non-overlap (NOL) portion of the direct expansion from
the June Area Survey data. The NOL portion of the June Area Survey refers to those operations identified on the area
frame that are not matched to an operation eligible for sampling for the June Agricultural Survey.
Estimation: For the National estimates, NASS assembles a panel of statisticians to serve as the Agricultural Statistics
Board (ASB), 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 number for total number of farms and land in farms, as well as each of the
economic sales classes. The ASB 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
ASB 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 to determine accuracy and bias using tables and graphs. Each ASB
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Farms and Land in Farms Methodology and Quality Measures (February 2023)
USDA, National Agricultural Statistics Service

member completes an independent interpretation of the survey results which is shared with the other members and a
consensus is reached. Often the state recommendations do not sum to the National estimate. ASB members must
reexamine the state results and revise some states to make the sum of the state estimates agree with the National estimate.
Reliability: In 2022, two types of survey errors, sampling and non-sampling, are possible in the final estimates, and both
can affect the quality of the estimates. Sampling error occurs because a complete census is not taken. The sampling error
measures the variation in estimates from the average of all possible samples. An estimate of 100 with a sampling error of
1 would mean that chances are 19 out of 20 that the true population value lies between 98 and 102 (the survey estimate,
plus or minus 1.96 times the sampling error). In 2022, the coefficient of variation for the United States number of farms
was 1.9 percent and land in farms 1.7 percent. The coefficients of variation by economic sales class ranged from 3.0
percent to 3.6 percent for number of farms and 4.0 to 6.0 percent for land in farms at the National level.

Farms and Land in Farms Methodology and Quality Measures (February 2023)
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3

Quality Metrics for Farms and Land in Farms
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 in this document 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.
Response rates measure the proportion of total farm tracts responding to the June Area Survey.
Coefficient of Variation provides a measure of the size of 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 Farms and Land in Farms Sample Size and Response Rates: To assist in evaluating the
performance of the estimates in the Farms and Land in Farms 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.

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Farms and Land in Farms Methodology and Quality Measures (February 2023)
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Farms and Land in Farms Sample Size and Response Rate – States and United States: 2021-2022
State

Sample size
2021

Response rate
2022

(number)

2021

(number)

2022

(percent)

(percent)

Alabama ...................................................
Alaska ......................................................
Arizona .....................................................
Arkansas ..................................................
California ..................................................
Colorado ..................................................
Connecticut ..............................................
Delaware ..................................................
Florida ......................................................
Georgia ....................................................

380
(NA)
157
767
664
638
23
56
226
502

351
(NA)
114
760
639
623
17
50
220
518

73.4
(NA)
60.5
50.3
64.5
51.3
39.1
14.3
50.0
35.5

66.4
(NA)
56.1
66.6
63.1
42.2
41.2
28.0
39.5
38.8

Hawaii ......................................................
Idaho ........................................................
Illinois .......................................................
Indiana .....................................................
Iowa ..........................................................
Kansas .....................................................
Kentucky ..................................................
Louisiana ..................................................
Maine .......................................................
Maryland ..................................................

(NA)
491
1,587
937
1,527
1,559
670
321
42
137

(NA)
455
1,624
942
1,576
1,564
666
323
48
165

(NA)
53.0
57.8
59.1
55.1
27.2
50.9
75.1
45.2
45.3

(NA)
37.1
65.6
51.8
54.3
27.9
43.7
75.9
52.1
38.8

Massachusetts .........................................
Michigan ...................................................
Minnesota ................................................
Mississippi ................................................
Missouri ....................................................
Montana ...................................................
Nebraska ..................................................
Nevada .....................................................
New Hampshire .......................................
New Jersey ..............................................

30
633
1,476
569
1,618
743
1,202
23
21
65

25
579
1,429
534
1,515
740
1,212
14
14
68

60.0
58.5
56.6
64.9
38.4
60.2
47.8
82.6
28.6
38.5

72.0
68.9
50.8
68.5
41.5
59.1
43.2
57.1
21.4
48.5

New Mexico .............................................
New York .................................................
North Carolina .........................................
North Dakota ............................................
Ohio ..........................................................
Oklahoma .................................................
Oregon .....................................................
Pennsylvania ...........................................
Rhode Island ............................................
South Carolina .........................................

318
218
597
1,264
1,033
1,038
430
347
15
190

286
247
585
1,262
986
1,052
424
331
15
183

47.5
61.0
55.4
46.5
62.3
42.4
49.5
53.9
33.3
52.6

39.9
69.6
54.2
46.6
68.5
41.2
39.4
51.7
26.7
64.5

South Dakota ...........................................
Tennessee ...............................................
Texas .......................................................
Utah ..........................................................
Vermont ...................................................
Virginia .....................................................
Washington ..............................................
West Virginia ............................................
Wisconsin .................................................
Wyoming ..................................................

1,051
868
3,036
252
68
323
453
167
628
170

1,063
815
2,915
263
78
325
454
223
691
151

39.3
63.9
54.8
80.2
44.1
58.2
39.3
84.4
59.6
52.9

38.1
66.9
60.7
46.4
43.6
52.3
40.5
82.1
58.0
36.4

United States ...........................................

29,530

29,134

52.1

52.1

(NA) Not available.

Farms and Land in Farms Methodology and Quality Measures (February 2023)
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Quality Metrics for Farms and Land in Farms – States and United States: 2021-2022
Coefficient of variation
State

Number of farms
2021

Land in farms
2022

(percent)

2021

(percent)

2022

(percent)

(percent)

Alabama ...................................................
Alaska .......................................................
Arizona .....................................................
Arkansas ..................................................
California ..................................................
Colorado ...................................................
Connecticut ..............................................
Delaware ..................................................
Florida .......................................................
Georgia .....................................................

10.1
(NA)
25.4
12.9
18.9
17.8
43.5
22.0
16.9
26.2

9.8
(NA)
34.5
11.8
13.7
16.7
5.6
17.5
16.8
22.1

9.8
(NA)
10.0
6.0
11.5
5.7
64.4
9.0
14.4
7.4

9.5
(NA)
10.8
5.7
11.7
10.0
49.4
8.7
20.7
7.8

Hawaii .......................................................
Idaho .........................................................
Illinois ........................................................
Indiana ......................................................
Iowa ..........................................................
Kansas .....................................................
Kentucky ...................................................
Louisiana ..................................................
Maine ........................................................
Maryland ...................................................

(NA)
12.8
4.2
7.4
3.9
5.9
8.8
17.4
37.0
16.0

(NA)
11.6
4.4
8.1
3.9
5.2
7.5
18.8
40.7
18.4

(NA)
15.9
1.4
2.1
1.0
1.0
5.4
5.7
30.6
9.9

(NA)
23.3
1.2
2.2
1.0
1.0
5.3
8.2
24.9
9.3

Massachusetts .........................................
Michigan ...................................................
Minnesota .................................................
Mississippi ................................................
Missouri ....................................................
Montana ...................................................
Nebraska ..................................................
Nevada .....................................................
New Hampshire .......................................
New Jersey ..............................................

55.2
8.4
4.6
12.0
6.0
10.9
4.7
35.7
52.7
29.1

8.1
8.1
4.4
15.1
7.5
13.3
5.4
27.7
68.0
24.9

46.6
4.7
2.1
6.1
3.2
5.9
3.6
63.1
57.1
23.1

37.3
5.1
1.9
8.5
3.4
4.6
3.6
44.0
69.1
28.9

New Mexico ..............................................
New York ..................................................
North Carolina ..........................................
North Dakota ............................................
Ohio ..........................................................
Oklahoma .................................................
Oregon .....................................................
Pennsylvania ............................................
Rhode Island ............................................
South Carolina .........................................

19.4
11.3
16.3
4.8
7.6
8.3
13.6
11.7
16.5
42.7

21.0
15.1
17.0
5.1
8.6
9.2
13.7
12.3
63.9
45.5

5.7
8.2
8.7
2.4
3.6
3.0
13.5
7.4
0.2
17.4

15.2
8.3
9.4
2.1
4.3
2.9
13.1
8.1
72.3
19.4

South Dakota ...........................................
Tennessee ...............................................
Texas ........................................................
Utah ..........................................................
Vermont ....................................................
Virginia .....................................................
Washington ..............................................
West Virginia ............................................
Wisconsin .................................................
Wyoming ..................................................

5.2
7.5
8.1
16.1
24.9
11.6
14.7
19.3
7.0
18.4

4.9
8.6
8.2
14.3
20.1
11.4
14.3
13.2
8.9
15.1

2.8
4.8
4.6
29.4
20.4
10.4
13.6
18.7
3.8
24.7

2.1
5.3
4.2
48.9
19.7
8.6
8.5
10.6
3.7
6.1

United States ...........................................

2.0

1.9

1.6

1.7

(NA) Not available.

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Farms and Land in Farms Methodology and Quality Measures (February 2023)
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Quality Metrics for Farms and Land in Farms by Economics Sales Class – United States: 2021-2022
Coefficient of variation
Economic sales class

Number of farms
2021

Land in farms
2022

(percent)

2021

(percent)

2022

(percent)

(percent)

$1,000 - $9,999 .......................................
$10,000 - $99,999 ...................................
$100,000 - $249,999 ...............................
$250,000 - $499,999 ...............................
$500,000 - $999,999 ...............................
$1,000,000 or more .................................

3.5
2.9
3.4
3.2
3.3
3.3

3.6
3.0
3.0
3.5
3.5
3.0

4.4
6.5
4.4
4.9
4.8
2.3

5.6
4.6
4.5
4.0
6.0
4.1

Total .........................................................

2.0

1.9

1.6

1.7

Farms and Land in Farms Methodology and Quality Measures (February 2023)
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