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Martin Pantel

Business Surveys Methods Division

Third International Conference on

Establishment Surveys

June 2007

Classifying Agricultural Operations for the Farm Environmental

Management Survey

2

Outline

The 2006 Farm Environmental Management Survey (FEMS)

Targets both Crop and Livestock farms

SolutionsNAICS coding system

New strategy

Some results

3

Background: FEMS 2006

Agriculture and Agri-Food Canada initiativeEnvironmental management in the media Importance of agricultural industry in CanadaSupport the industry’s environmental initiatives, address federal and provincial policy needs, and guide sustainable development actions in Canada’s agriculture sector.

Use of 2006 Census of Agriculture dataCATI, ≈ 20,000 farms

4

Background: FEMS 2006

Some farms excluded from FEMS:Total gross sales of less than $10,000

Institutional farms (prisons, research stations, colleges, etc.)

Farms located on Indian reserves

Insufficient livestock inventory / crop area

Greenhouse/sod/nursery operations

Farms in the 3 northern territories.

5

Background: FEMS 2006

Crop vs. Livestock: Different issuesCrop and Nutrient Management, Pesticide Application

Livestock Inventories and Buildings, Manure, Grazing Livestock Management

Some common issues: Land and Water Management, Wildlife Damage, Waste Management and Hazardous Materials, Environmental Farm Plan

6

Problem: Crop or Livestock?

Frame includes Crop and Livestock farmsTwo questionnaires - nobody can receive both

What about the farm that has 30 cows and 50 acres of canola?

Force it into a group based on some criteria

Create a “Mixed” category

7

Solution 1 - NAICS

The North American Industrial Classification System (NAICS)

Well-established system

Based on main product or group of products, generating at least 50% of the total cash receipts for the farm.

8

NAICS categoriesCattle ranching and farmingHog and pig farmingPoultry and egg productionSheep and goat farmingOther animal productionOilseed and grain farmingVegetable and melon farmingFruit and tree nut farmingGreenhouse, nursery and floriculture productionOther crop farming

Solution 1 - NAICS

9

Solution 1 - NAICS

Coverage, bias problems?Results inferred upon the survey population; but how close is it to the target population?

wheat

CROPS

LIVESTOCK•

•• •

••

10

Solution 2 - New approach

Allow for Mixed farms

Crop population: C+M

Livestock population: L+M

C LM

11

Summary measuresCropland: sum of acres for crops of interest (wheat, grain, oilseeds, hay, potatoes, fruits, vegetables, other field crops)

Animal Units (or AUnits): Combines the livestock types of interest (cattle, hogs, poultry) on a uniform scale.

1 AUnit ≈ 1 cow ≈ 5 hogs ≈ 200 chickens

Solution 2 - New approach

12

Solution 2 - New approach

ClassificationA large proportion of any commodity will be produced by a small number of large farms. (e.g. the largest 60% of farms have 95% of the livestock).

Find each farm’s percentile according to each commodity (a “small” livestock farm may still be important for poultry).

13

Classification (cont.)Compare the largest of the farm’s percentiles to the threshold for that province, to see if the farm should be flagged as an important contributor for that type (Crop / Livestock).

If the farm is flagged for both types, it is classified as a Mixed farm.

Solution 2 - New approach

14

Solution 2 - New approach

Example

Farm Cattle Hogs Poultry AUnits

F1 30 25 0 35

F2 2 0 200 3

F3 0 75 0 15

F4 1 0 50 1.25

F5 35 10 1000 42

15

Solution 2 - New approach

Example (cont.)Total AUnits in the province = 96.25

95% of the total = 91.44

How many farms do we need?

Farm AUnits Cumulative Sum

F5 42 42

F1 35 77

F3 15 92

F2 3 95

F4 1.25 96.25

16

Solution 2 - New approach

Example (cont.)By taking the 3 largest of the 5 farms (or 60% of them), 95% of the AUnits are covered.

Set this threshold (0.60) aside for now.

Each farm can get up to four percentiles: one for each livestock commodity they produce and one for AUnits as a whole.

First, sort the cattle farms in increasing order of cattle inventory and find their percentiles.

17

Solution 2 - New approach

Example (cont.)Note: P_Cattle = FarmRank / NumFarms

Merge into the original dataset

Farm No. of Cattle P_Cattle

F4 1 0.25

F2 2 0.50

F1 30 0.75

F5 35 1.00

18

Solution 2 - New approach

Farm Cattle P_Cattle Hogs Poultry AUnits

F1 30 0.75 25 0 35

F2 2 0.50 0 200 3

F3 0 -- 75 0 15

F4 1 0.25 0 50 1.25

F5 35 1.00 10 1000 42

Example (cont.)

19

Solution 2 - New approach

Example (cont.)Repeat the same procedure for the Hog and Poultry producers, as well as for the summary measure AUnits.

Re-merge the results, and compare the largest percentile against the threshold of 0.60.

20

Solution 2 - New approach

Farm P_Cttl P_Hog P_Plt P_AU LFlag

F1 0.75 0.66 -- 0.8 1

F2 0.50 -- 0.66 0.4 1

F3 -- 1.00 -- 0.6 1

F4 0.25 -- 0.33 0.2 0

F5 1.00 0.33 1.00 1.00 1

Example (cont.)

21

Solution 2 - New approach

Repeat the same procedure for crops:Find the threshold (for 95% of Cropland).

Calculate the percentiles according to the 8 crops of interest, and according to the summary measure.

Assign a “Crop flag” accordingly.

Using the two flags, determine if each farm is Crop, Livestock or Mixed.

22

Solution 2 - New approach

Example (cont.)

Farm LvstkFlag CropFlag Type

F1 1 0 Livestock

F2 1 1 Mixed

F3 1 0 Livestock

F4 0 1 Crop

F5 1 0 Livestock

23

Solution 2 - New approach

NC=79,830 NM=35,030 NL=39,976 N=154,836

nC + nMC

= 7,454 + 3,099= 10,553

nL + nML

= 5,782 + 4,377= 10,159

n=20,712

↓ ↓

24

Solution 2 - New approach

Sampling from the Mixed poolResponse burden: cannot sample the same farm for both questionnaires.

Random number assigned to each farm, list of farms sorted accordingly.

Crop / Livestock farms are selected from opposite ends of the list.

25

Coverage

wheat

CROPS

LIVESTOCK

••

••

Results – New approach vs. NAICS

26

Results – New approach vs. NAICS

27

Next Steps

Weighting, EstimationTwo distinct surveys

Crop + Livestock ≠ Canada

Some Canada-wide data available (e.g. Environmental Farm Plan)

Dissemination

Pour plus d’information, veuillez contacter

For more Information please contact

Visit our web site atwww.statcan.ca

Martin Pantel

(613) 951-3029

Martin.Pantel@statcan.ca

For more details…

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