ICES III June 2007 The Redesign of Agriculture Surveys by Laurie Reedman and Claude Poirier

Outline Background Current Situation Priorities Scope Issues Next Steps

Mandate of the Agriculture Statistics Program Estimates of agriculture production for crops, horticulture, livestock and animal products, as well as revenues and expenses To conduct the Census of Agriculture (CEAG) every 5 years To manage the statistical system of Canada's agriculture sector from data collection to publication Ensure quality outputs for economic analysis and policy making in Canada

Current Situation Large regular surveys: Crops, Livestock, Hogs, Atlantic, Farm Financial, Fruit and Vegetables, Greenhouse, Sod and Nursery Smaller regular surveys: Potato Area and Yield, Potato Prices, other prices Irregular surveys: cost recovery surveys on the environment, farming practices, risk management Administrative data Farm Register (FR)

Priorities Reduce response burden Individual; whole population Improve robustness Standardize methods and adopt best practices Coverage Efficient use of internal resources Efficient use of the farming communitys capacity to respond

Scope The surveys that use a static frame for the 5 year period between censuses: Crops Livestock Atlantic Farm Financial The methodology of survey design

Small Farm Exclusion Threshold Want to reduce burden on the many small farms that do not have much impact on survey estimates Propose a method to compensate for the under- coverage that would result from excluding the small farms from the regular survey sampling

Who are the small farms? Current small farm threshold is $10K reported for the sale of agriculture products on CEAG 21% of all farms and 0.6% of total sales Other small farm thresholds could be: $25K, 39% of all farms, 2.4% of total sales $50K, 53% of all farms, 5.6% of total sales The bottom 5% of sales in each province, 50% of farms

What do the small farms contribute? Say threshold is $25K in sales on CEAG 2006 … 2% of hogs in Canada 4% of field crop area in Manitoba 9% of the field crop area in Atlantic Canada 10% of program payments in Alberta 22% of total farm capital in New Brunswick 30% of sheep in Alberta 35% of beef cattle in Ontario Nearly 100,000 acres in different varieties of lentils, beans, dry peas and chick peas in Saskatchewan and Alberta

How to estimate for the small farms if not through regular surveys Admin sources (tax) do not have commodity data, not adequate CEAG 2006 Annual Farm Update Survey (FUS) Sample is drawn from tax records, producer lists and the margins of the FR to detect farms not already in the active population Expand scope to also represent the small farms Augment questionnaire to cover more commodities Increase sample size to provide reliable estimates

Factors in Decision Making CEAG and/or FUS can adequately estimate livestock variables, the major crops and many components of the Farm Financial Survey (FFS) CEAG questionnaire does not have the varieties of lentils, beans, dry peas and chick peas Unlikely that the FUS questionnaire would have detailed commodities Small farms are part of the target population for some FFS concepts

Decision for 2006 Redesign Risk of under coverage is too high …Crops and FFS are not ready to raise the small farm exclusion threshold Not feasible to redesign FUS just for Livestock and Atlantic Decision: keep small farm threshold at $10K for all surveys pilot redesign of FUS, to demonstrate its ability to measure the under coverage stratum boundary at $25K

Stratification and Sample Allocation Reduce sample sizes, ensure reliable estimates for domains of interest As few strata as necessary As few take-all strata as necessary Use generalized software Stratify once for the 5 year period

Crops Survey Estimate acreage of crops, production and yield at provincial as well as sub-provincial level, 6 surveys annually Size classes based on total field crop area Key crops are barley, corn for grain, oats, soybeans, winter wheat and hay Target sample size is 16,000

Crops Survey continued Allocated sample to the provinces proportional to the square root of number of farms Multivariate allocation to strata, using key variables Calculated theoretical coefficients of variation (CVs) and also selected a random sample and verified that there were no deviations in the estimates

Livestock Survey Estimates totals of different types of cattle, sheep and hogs, at provincial level, 2 surveys annually Size classes (counts of animals) within farm type Key variables are total cattle, beef cows, total pigs, sows, total sheep, and also milk cows in some provinces Target sample size 10,000

Atlantic Survey Estimates both crops and livestock variables in Atlantic provinces, 2 surveys annually Challenge to measure crops and livestock with one sample, farms tend to be mixed Size classes within farm type Key variables are total cattle, total pigs and total field crops, and potatoes in Prince Edward Island Target sample size 1,200

Farm Financial Survey Estimates financial activity and farm characteristics at provincial level, 1 survey annually Size classes (total assets) within farm type Sample is allocated based on total farm revenue Sample size is usually 18,000

Summary of Sample Allocation Population Size Sample Size CVs on key variables CVs on other variables Crops Survey 155,00016,0001-2%3-15% Livestock Survey 100,00010,0001-2%3-15% Atlantic Survey 6,0001,2001-4%5-30% Financial Survey 179,00018,0001-3%4-30%

Large or Complex Farms Group of people dedicated to collecting and maintaining data pertaining to the biggest and most influential farms Manage the response burden Profiling once each year Control number of times they are contacted, carry-forward information for some survey occasions

Frame Maintenance Changes in stratification variables Minimized by having a robust stratification Births from the Farm Update Survey Same probability of selection as rest of frame Updates from Farm Register Are they independent, is there a risk of bias? Deaths Are they independent, can we drop them? Partnerships, buy-outs, splits

Sample Co-ordination Permanent random numbers Moving, growing sampling windows What to do about strata with high sampling fractions What to do about births What to do about irregular surveys What to do about special requests, for example, when more sample is needed to improve precision for a particular domain

Next Steps Confirm all assumptions and decisions with CEAG 2006 data Create new survey frames Select samples Monitor performance on first few survey occasions, evaluate performance Estimation system, review of the Farm Register Redesign FUS Examine target population definition

Thank-you For more information, or to obtain a French copy of this presentation, please contact: Pour de plus amples informations ou pour obtenir une copie en français du document, veuillez contacter: Laurie Reedman / Courriel: Phone number / Téléphone: