Data quality, concepts and methodology: Explanatory notes on direct program payments to agriculture producers 2022

Payments Enhancing Receipts

Explanatory notes for programs which existed prior to 2007 can be found in the discontinued Direct Payments to Agriculture Producers publication (21-015-X).

Agricultural Revenue Stabilization Account (ARSA) (2000 to 2002)

The objective of the Agricultural Revenue Stabilization Account program was to offer a risk management tool to farming operations in Quebec, based on the operation's gross income. To this effect, the program established two individual funds, for contributions from participants and La Financière agricole du Québec, and made provisions for withdrawals from these funds to compensate for reductions in farm income. The ARSA was a program developed and administered by La Financière agricole du Québec.

Following the introduction of the Canadian Agricultural Income Stabilization Program, La Financière agricole du Québec terminated this program in the 2002 program year. Consequently, participants had five years to make withdrawals from their account, at an annual minimum of 20% of the government contribution held on February 1st, 2005.

AgriInvest (2008 to present)

This program was created under the Growing Forward policy framework (2007 – 2013) and has continued under Growing Forward 2 (2013 – 2018) and the Canadian Agricultural Partnership (effective April 1, 2018). AgriInvest replaces part of the coverage that had been available under the Canadian Agricultural Income Stabilization (CAIS) program, and, operates similar to the former Net Income Stabilization Account (NISA) program.

Through government and producer contributions, AgriInvest provides cash flow to help producers manage small income declines, as well as provide support for investments to mitigate risks or improve market income. Producers can deposit up to 100% of their Allowable Net Sales, with the first 1% matched by governments. The limit on matching government contributions is $10,000 per AgriInvest account. AgriInvest is administered by the Federal government in all provinces except Quebec.

Agri-Québec (2011 to present)

Agri-Québec is a self-directed risk management program offered to all farming and aqua-farming operations in Quebec. The program allows participants to deposit an amount in an account under their name, in order to receive matching contributions from La Financière agricole du Québec. Participants can then withdraw the funds from the accounts, based on their operational needs. Agri-Québec is managed jointly by the provincial and federal governments, as it is similar and complimentary to AgriInvest.

Agri-Québec Plus (2015 to present)

The Agri-Québec Plus program offers additional financial assistance to eligible operations. Agri-Québec Plus complements AgriStability by offering a coverage level of 85% of the reference margin rather than 70%. The program covers agriculture products that are not covered or not associated with the ASRA program (Farm Income Stabilization Program) and are not supply-managed. Participation in the program is linked to the respect of environmental requirements.

AgriRecovery (2008 to present)

The AgriRecovery framework is part of a suite of federal-provincial-territorial (FPT) Business Risk Management (BRM) tools under the Canadian Agricultural Partnership (replacing Growing Forward 2, as of 2018).

AgriRecovery was designed to provide quick, targeted assistance to producers in case of natural disasters, with a focus on the extraordinary costs producers must take on to recover from disasters. Federal and provincial governments jointly determine whether further assistance beyond existing programs already in place is necessary, and what form of assistance should be provided. AgriRecovery initiatives are cost-shared on a 60:40 basis between the federal government and participating provinces or territories. The assistance provided will be unique to the specific disaster situation and often unique to a province or region. Examples of programs included in AgriRecovery are the 2017 and 2018 Canada-BC Wildfire Recovery Initiatives, and the 2017 Canada-Quebec Hail Assistance Initiative.

AgriStability (2007 to present)

This program was created under the Growing Forward policy framework (2007 – 2013) and has continued under Growing Forward 2 (2013 – 2018) and the Canadian Agricultural Partnership (effective April 1, 2018). AgriStability was developed as a margin-based program that provides income support when a producer experiences a large margin decline. AgriStability has replaced part of the coverage that had been provided under the Canadian Agricultural Income Stabilization (CAIS) Program.

AgriStability is delivered in Manitoba, New Brunswick, Nova Scotia, Newfoundland and Labrador and Yukon by the Federal government. In British Columbia, Saskatchewan, Alberta, Ontario, Quebec, and Prince Edward Island, AgriStability is delivered provincially.

Assiniboine Valley Producers Flood Assistance Program (2007 to 2011)

This Province of Manitoba program provided financial assistance for Assiniboine Valley agricultural producers who experienced crop loss or the inability to seed a crop in 2005 and 2006 along the Assiniboine River from the Shellmouth Dam to Brandon, due to flooding. This program also provided assistance in 2011, following flooding in 2010.

These programs were managed through the Manitoba Agricultural Service Corporation (MASC).

Beekeepers Financial Assistance Program (2014)

Due to harsh winter conditions in Ontario in 2014, and other pollinator health issues, Ontario's bee colonies experienced higher than normal mortality rates. To help offset these losses, the Ontario Ministry of Agriculture and Food provided one-time financial assistance of $105 per hive to beekeepers who have 10 hives or more and lost over 40 per cent of their colonies between Jan. 1, 2014, and Oct. 31, 2014.

Canada-Ontario General Top-Up Program (2005 to 2007)

This was a special top-up payment program which provided whole farm coverage to the Canadian Agricultural Income Stabilization (CAIS) Program participants in Ontario, who were automatically enrolled. All commodities eligible for CAIS payment were covered under this program. In order to qualify, participants must have experienced a decline in their program year production margin as calculated by the CAIS Program Administrator and be eligible to receive the government portion of the CAIS payment. The Ontario Ministry of Agriculture, Food and Rural Affairs were responsible for the overall administration of the program.

Canadian Agricultural Income Stabilization (CAIS) Program (2004 to 2008)

The CAIS program was available to producers across Canada and provided assistance to those producers who had experienced a loss of income as a result of bovine spongiform encephalopathy (BSE) or other factors. The program integrated stabilization and disaster protection into a single program, helping producers protect their farming operations from both small and large drops in income.

Canadian Agricultural Income Stabilization Inventory Transition Initiative (CITI) (2006 to 2007)

CITI was a one-time federal government injection of $900 million into Canada's Agriculture and Agri-food industry. The funds were delivered to producers by recalculating how the Canadian Agricultural Income Stabilization (CAIS) program valued inventory change for the 2003, 2004, and 2005 CAIS program years.

Canadian Agricultural Income Stabilization Ontario Inventory Transition Initiative (2006 to 2019)

The Ontario Inventory Transition Payment was an additional one-time payment from the province of Ontario, for the Canadian Agricultural Income Stabilization (CAIS) program participants, as it transitioned to a new method of valuing inventory for CAIS.

Compensation for animal losses (1981 to present)

Formerly a program under the Animal Disease and Protection Act, this compensation program is now administered by the Canadian Food Inspection Agency in accordance with requirements established under the Health of Animals Act. Producers in all provinces are compensated when farm animals infected with certain contagious diseases are ordered to be slaughtered. Compensation also includes applicable transportation and disposal costs and compensation for animals injured during testing.

Cost of Production Payment (COP) (2007 to 2010)

This program helped non-supply managed commodities producers with the rising cost of production. This federal program was based on producers' net sales for 2000-2004 (or in the case of new producers: payments were based on average net sales for 2005-2006).

Cover Crop Protection Program (CCPP) (2006 to 2008)

The CCPP was a Government of Canada initiative designed to provide financial assistance to agricultural producers who were unable to seed commercial crops as a result of flooding in the spring of 2005 and/or 2006.

Crop Insurance (1981 to present)

Crop Insurance (now referred to as AgriInsurance) is a federal-provincial-producer cost-shared program that stabilizes a producer's income by minimizing the economic effects of production losses caused by natural hazards. AgriInsurance is a provincially delivered program to which the federal government contributes a portion of total premiums and administrative costs. Premiums for most crop insurance programs are cost-shared: 40 per cent by participating producers, 36 per cent by the federal government and 24 per cent by the province, while administrative costs are funded by governments, 60 per cent by the federal government and 40 per cent by the province.

AgriInsurance plans are developed and delivered by each province to meet the needs of the producers in that province. AgriInsurance helps to cover production losses as well as losses from poor product quality. Both yield and non-yield based plans are offered. These plans cover traditional crops such as wheat, corn, oats and barley as well as horticultural crops such as lettuce, strawberries, carrots and eggplants. Some provinces also provide coverage for bee mortality as well as maple syrup production. The provinces constantly work to improve their programs by adjusting existing plans and implementing new ones to meet changing industry requirements.

Crop Loss Compensation (1981 to present)

Crop loss compensation programs are generally one element of a province's Wildlife damage compensation programs, which can also include separate Waterfowl damage and Livestock predation programs. This Big Game program reduces the financial loss incurred by producers in these provinces from wildlife damage to eligible crops, and can include compensation for wildlife excreta contaminated crops and silage in pits and tubes. In some provinces damage to honey producers and leafcutter bee products is also included.

Also see Livestock predation compensation, Waterfowl damage and Wildlife damage compensation programs.

Cull Animal Program (2003 to 2006)

This program was intended to assist farmers with the additional cost of feeding surplus animals while the US border was closed to Canadian animals over 30 months of age. With the goal of discouraging on-farm slaughter and encouraging movement of mature animals to domestic markets in an orderly fashion.

Cull Breeding Swine Program (2008)

This federally funded program for 2008, administered by the Canadian Pork Council, was designed to help restructure the industry to bring it in line with market realities. The objective was to reduce the national breeding herd size by up to 10% over and above normal annual reductions. Producers were eligible to receive a per head payment for each animal slaughtered as well as reimbursement for slaughter and disposal costs. Producers had to agree to empty at least one barn, and not restock for a three year period.

Dairy Direct Payment Program (2019-2023)

The objective of the Dairy Direct Payment Program is to support dairy producers as a result of market access commitments made under recent international trade agreements, namely the Canada–European Union Comprehensive Economic and Trade Agreement (CETA) and the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP).

In August 2019, the federal government announced that it will make available $1.75 billion to supply-managed milk producers. Up to $345 million in direct payments was made available in 2019-2020.

In November 2020, the government announced the payment schedule for the remaining $1.405 billion in direct payments over the next three years:

  • $468 million in 2020-21
  • $469 million in 2021-22
  • $468 million in 2022-23

The Canadian Dairy Commission (CDC) has been mandated to deliver the program.

Drought Assistance for Livestock Producers (2007 to 2008)

This program was enacted in 2007, to assist livestock owners in Northern B.C. who suffered economic hardship in 2006 due to drought. Drought conditions in the summer of 2006 reduced hay and forage yields by up to 50% and producers were left with higher costs for feed, water and other expenses.

Fed Cattle Set Aside Program (2005 to 2006)

The program was part of a national strategy to assist Canada's cattle industry to reposition itself to help ensure its long-term viability.

Financial Assistance for Replanting Apple Orchards (2020-2022)

The financial assistance for replanting apple orchards program is being implemented to support the apple industry during the transition period following the termination of the Farm Income Stabilization Insurance Program coverage.

The program is intended to support development of the apple industry from a sustainable development perspective, as a complement to other government assistance available to the apple industry.

More specifically, this program is intended to provide financial support to apple businesses in their apple orchard replanting projects.

Eligible businesses may receive financial assistance of $5,000 per replanted hectare for up to four hectares. If the business is deemed eligible for one of the grants under the Financial Support Program for Aspiring Farmers on the date that they submitted their application to the program, the assistance is increased to $6,250 per eligible hectare.

Frost loss Program (2018-2019)

The Frost Loss Program helped Nova Scotia Farmers recover from crop and financial losses from the frost in June 2018.

This program provided financial assistance in addition with other Business Risk Management programs that were available, such as AgriInsurance.

Golden Nematode Disaster Program (2007 to 2009)

The objective of this programs was to assist producers affected by Golden Nematode with the costs of disposing potatoes  and a per hectare support payment to assist potato producers and producers of nursery and greenhouse crops with extraordinary costs not covered under existing programs. The program was funded by the federal government.

Grains and Oilseeds Payment (GOPP) (2006)

The Grains and Oilseeds Payment Program was a one-time program for producers of grains, oilseeds, or special crops, to help address the severe economic hardships they were facing.

Hazelnut Renewal Program (2020-2021)

This provincially funded program provides funds to remove infected trees to mitigate the spread of Eastern Filbert Blight and to provide incentives for the planting of new disease-resistant hazelnut trees in British Columbia.

Types of Program Funding:

  • Hazelnut Renewal: Funding to provide incentives for the planting of new Eastern Filbert Blight (EFB) resistant hazelnut trees in British Columbia.
  • Removal of EFB Infected Hazelnut Trees: Funding to remove infected trees to mitigate the spread of EFB and to protect new orchards.

Hog Transition Fund (2008)

This program was designed to assist Nova Scotia hog producers who were having financial difficulties due to declining market prices in 2006-2007. The program was administered through Pork Nova Scotia.

Lake Manitoba Flood Assistance Program (2011 to present)

This program was designed to provide financial compensation to crop and livestock producers affected by the flooding of Lake Manitoba in 2011. Part A - Lake Manitoba Pasture Flooding Assistance Component and Part B - Lake Manitoba Transportation and Crop/Forage Loss Component, are included. This program is funded entirely by the provincial government.

Livestock Insurance Programs (1991 to present)

The Livestock Insurance Programs include a number of provincially administered livestock insurance programs. These programs include:

The Cattle Price Insurance Program (2009 to present), designed to provide Alberta cattle producers with an effective price risk management tool reflective of their risk. As of 2014, this program is now referred to as the Western Livestock Price Insurance Program.

Dairy Livestock Insurance (1991 to present), implemented to assist Nova Scotia producers when a number of cattle were lost due to disease outbreaks. The program continues to exist for situations resulting in a significant loss in production, causing a loss of revenue.

The Hog Price Insurance Program (2011 to present), designed to provide Alberta hog producers with protection against unexpected declines in Alberta hog prices, over a defined period of time. As of 2014, this program is now referred to as the Western Livestock Price Insurance Program.

Livestock Insurance in Newfoundland and Labrador (1991 to present) compensates producers for the death or injury to sheep, goats, dairy cattle or beef cattle caused by dogs or other predators.

Livestock Insurance in Prince Edward Island (2009 to present) offers two types of coverage: compensation to cattle producers for the death of an animal due to disease, as well as compensation to dairy producers whose production levels fall beneath a set threshold, causing a loss of income.

The Overwinter Bee Mortality Insurance (2012 to present) insures Manitoban beekeepers against unmanageable wintering losses, including weather-related damages, diseases and pests. As of 2014 the data for this program is included in Crop Insurance.

Poultry Insurance (2008 to present) compensates Nova Scotia producers for the loss of poultry (which includes broilers, breeders, breeder pullets, layer pullets, commercial layers and integrated layers) to the disease infectious laryngotracheitis (ILT).

The Western Livestock Price Insurance Program (WLPIP) (2014 to present) enables livestock producers to purchase price protection on cattle and hogs in the form of an insurance policy. It offers protection against an unexpected drop in prices over a defined period of time, and is available to producers in British Columbia, Alberta, Saskatchewan and Manitoba.

Administration costs are covered by the federal and provincial governments through Growing Forward 2. Premiums will be fully funded by producers, but any deficit after four years will be made up by the federal government. The four-province program will be managed by the Alberta Agriculture Financial Services Corp, which ran the pre-existing Cattle and Hog Price Insurance programs in Alberta. Crop insurance entities in Manitoba and Saskatchewan will deliver the WLPIP in those provinces. The Business Risk Management Branch of the British Columbia Ministry of Agriculture delivers the program in that province.

Additional notes on the Livestock Insurance Programs

Producer premiums for the Prince Edward Island Livestock Insurance and Dairy Livestock Insurance in Nova Scotia (as of 2006) are partially subsidized by the provincial and federal governments.

Premiums are not subsidized for the Cattle Price Insurance Program, the Hog Price Insurance Program, Livestock Insurance in Newfoundland and Labrador, Poultry Insurance program in Nova Scotia, or the Western Livestock Price Insurance Program. However, the costs of administrating the programs are funded by provincial governments and/or Crown Corporations.

Prior to 2005, Dairy Livestock Insurance in Nova Scotia and Livestock Insurance in Newfoundland and Labrador were reported under Programs funded by the private sector.

Livestock Predation Compensation Program

Manitoba (1999 to present) - This program compensates livestock producers in Manitoba for losses from injury or death of eligible livestock that resulted from losses due to natural predators such as black bear, cougar, wolf or coyote. Compensation is available to 100% of the assessed value of the animal, for a confirmed loss due to predation and to 50% of the value for a probable loss. In respect for livestock injured, the payment will be the lesser of the veterinary treatment or the value of the livestock. The government of Manitoba pays 60% of program payments and the Government of Canada 40%. Administration costs are cost-shared 50/50 between the Government of Canada and the Government of Manitoba.

Saskatchewan (2010 to present) - Under the Wildlife Damage Compensation Program, the Saskatchewan Compensation for Livestock Predation compensates producers for livestock killed or injured by predators. The first 80 percent of the program funding is cost-shared by federal and provincial governments. The provincial government contributes the remaining amount. The program is administered by the Saskatchewan Crop Insurance Corporation. Other components of the Wildlife Damage Compensation Program include Waterfowl damage compensation and Crops loss compensation (reported separately).

Also see Crop loss compensation, Waterfowl damage and Wildlife damage compensation programs.

Manitoba Ruminant Assistance Program (2008)

This one-time payment for 2008, funded jointly by the province of Manitoba and the federal government, allowed cattle producers to receive a direct payment of up to 3% of historical net sales. The payment, administered by the Manitoba Agricultural Services Corporation (MASC), was provided to all ruminant producers and was in proportion to the size of the producer's livestock operations.

Manitoba Spring Blizzard Livestock Mortalities Assistance Program (2011 to 2012)

The 2011 Manitoba Spring Blizzard Mortalities Assistance program provided assistance to Manitoba producers who experienced livestock losses following the blizzard that hit April 29th and 30th, 2011. Compensation is provided for animal deaths that occurred, as a result of the storm, between April 29th and May 5th 2011. This program is funded and administered by Manitoba Agriculture, Food and Rural Initiatives (MAFRI).

Marketing and Vineyard Improvement Program (MVIP) (2015-2016)

This program provides funds for eligible vineyard improvements to enable growers in Ontario to produce quality grapes in order to respond to the growing demands of Ontario wine manufacturers and to adapt ongoing and emerging vineyard challenges. This payment will be overseen by Agricorp (a provincial crown corporation) and was created under the Wine and Grape Strategy to promote Ontario VQA (Ontario's Wine Authority) and support vineyard production improvements. Only certain non-capital payments to producers are included in the Direct payments data series (e.g. wine grape vine removal, land preparation, etc.).

Measure to support grain corn producers in mitigating the impact of the 2019 rise in propane prices in Québec (2019-2020)

The measure to support grain corn producers in mitigating the impact of the 2019 rise in propane prices in Québec is meant to help reduce the repercussions on grain corn production due to the rise in prices of propane which is used to dry grain corn. This measure covered grain corn not yet harvested by November 19, 2019, the date when Canadian National Railway employees went on strike.

Financial assistance is provided in the form of a maximum flat rate of $23.50 per hectare of eligible grain corn areas for up to $50,000 per farm business.

Net Income Stabilization Account (NISA) (1991 to 2009)

The Net Income Stabilization Account (NISA) was established in 1991 under the Farm Income Protection Act.

The purpose of NISA was to encourage producers to save a portion of their income for use during periods of reduced income. Producers could deposit up to 3% of their Eligible Net Sales (ENS) annually in their NISA account and receive matching government contributions. The federal government and several provinces offered enhanced matching contributions over and above the base 3% on specified commodities. All these deposits earn a 3% interest bonus in addition to the regular rates offered by the financial institution where the account is held.

Most primary agricultural products were included in the calculation of Eligible Net Sales (sales of qualifying commodities minus purchases of qualifying commodities), the main exception being those covered by supply management (dairy, poultry and eggs).

The NISA account was comprised of two funds. Fund No. 1 which held producer deposits while Fund No. 2 contained the matching government contributions and all accumulated interest earned on both Fund 1 and Fund 2. Included as payments in the series «Direct Program Payments to Producers» were the producer withdrawals from Fund 2.

Nova Scotia Beef Kickstart Program (2008)

This one-time payment for 2008 provided funding for Nova Scotia's beef industry with the goal of helping the sector move toward greater economic self-sustainability.

Nova Scotia Margin Enhancement Program (2007 to 2008)

This initiative introduced in 2006, was a provincial initiative that provided additional income support to Nova Scotia producers. Using 2003 CAIS program data, reference margins of CAIS participants were increased by 10%.

Ontario Cattle, Hog and Horticulture Program (OCHHP) (2008)

This one-time payment for 2008, funded by the province of Ontario, was to assist farmers suffering from multiple financial pressures due to the stronger Canadian dollar, and lower market prices. Payments for cattle and hog producers were based on 12% of their historic allowable net sales, while payments for horticulture were based on 2% of allowable net sales.

Ontario Cost Recognition Top-up Program (2007 to 2010)

This program was a 40% matching provincial contribution to the federal Cost of Production Payment Program. This program was a direct payment to producers in recognition of rising production costs over the previous few years. The Ontario Top-Up Program payments were distributed after the payment details regarding the federal program were released.

Ontario Duponchelia Assistance Program (2008)

The purpose of this initiative was to provide financial support to horticulture producers in the Niagara Region of Ontario affected by Duponchelia, a reportable pest. The initiative provided a federal share (60%) of financial compensation to assist these producers in addressing plant replacement costs and in dealing with extraordinary expenses incurred due to quarantine measures imposed by the Canadian Food Inspection Agency (CFIA).

Ontario Edible Horticulture Crop Payment (2006)

This one-time payment compensates Ontario producers of edible horticulture crops for losses experienced on their 2005 crop.

Edible Horticulture Support Program for Edible Horticulture Farmers (2018-2019)

Ontario

This program provides financial support to Ontario producers of edible horticulture products (small and medium-size agricultural operators) to adjust to the changing small business environment. This program is funded by the Government of Ontario and the payments are based on net sales of edible horticulture. Self-Directed Risk Management Program participants are enrolled automatically.

Ontario Special Beekeepers Fund (2007 to 2008)

The Special Beekeepers Fund, enacted in June, 2007, provided direct compensation to beekeepers who suffered higher than normal hive losses during the winter of 2006. The assistance was designed to help bring Ontario's bee population back to near-normal levels, and beekeepers back to normal business.

PEI Pollination Expansion Program (2021 present)

The Prince Edward Island Department of Agriculture and Land has established the PEI Pollination Expansion Program to support the sustainable increase of local honey bee colonies that are available for the pollination of wild blueberries and other fruit crops and the advancement of the beekeeping sector through strategic industry initiatives.

PEI Potato Seed Recovery Program (2020)

The purpose of the Potato Seed Recovery Program is to offset extraordinary costs and a loss in revenue for Island seed potato producers impacted by the pandemic. This payment is a $1.19 million fund and is a provincially funded program.

Porcine Epidemic Diarrhea Programs (PED)

Prince Edward Island (2014) - The Prince Edward Island PED program provided financial aid to hog farmers for increased sanitation and screening measures to help combat the pig virus. This was a cost-shared program between the federal and provincial governments under Growing Forward 2. The program was administered by the PEI Hog Board.

Québec (2015 to present) - Emergency Fund Program in Response to Porcine Epidemic Diarrhea (PED) and Swine Delta Coronavirus (SDCV) in Québec. The purpose of this program is to provide assistance to affected operations, up to a maximum of $20,000 per production site, to cover certain additional expenses required to combat this disease and prevent it from spreading. The program is financed by La Financière agricole and administered by the Québec swine health team (EQSP). The fund has a maximum budget of $400,000.

Portage Diversion Fail-Safe compensation program (2014 to present)

This program was designed to provide financial assistance to Manitoba agricultural producers affected by the 2014 flooding due to the operation of the Portage diversion fail-safe. This program was fully funded by the Manitoba Government and is being administrated by Manitoba Agricultural Services Corporation (MASC).

Post-tropical Storm Dorian Response Program (DRP) (2020-2021)

The Prince Edward Island Department of Agriculture and Land has established the Post-tropical Storm Dorian Response Program (DRP) to provide financial support to corn, crambe, and tree fruit producers who have incurred extraordinary costs due to Dorian which are not covered by existing Business Risk Management programs.

Prince Edward Island Beef Industry Initiative (2007 to 2008)

This one-time payment for 2008 was designed to assist beef producers in Prince Edward Island to adjust to current market conditions and develop improved quality in their herds. The program provided immediate assistance to producers to help mitigate risk and provided genetics and enhanced herd health incentives. Payments were based on a combination of their average net sales and December 2007 inventory.

Prince Edward Island Hog Transition Fund (2008)

This program was designed to reduce hog numbers through a buyout program. It provided funds for producers to transition out of hog production.

Privately funded programs

Private hail insurance (1981 to present)

Private Hail Insurance is purchased by agricultural producers to protect themselves against the loss of their crops due to hail. Hail insurance is privately funded through producer premiums and producers may have the option to extend coverage for damage to crops due to loss through fire, depending on the insurance provider.

Other Private Programs (2011 to present)

Alberta Hog and Cattle Levy Refund (2011 to present)

In May 2011, Alberta Pork announced it would refund 85 cents for every dollar of levies it had collected from producers during the 2010-2011 fiscal year to assist producers coping with rising feed costs and small profit margins.

Legislation regarding levies in Alberta also changed in 2011. Levies for pork, beef, lamb, and potato producers had been mandatory until a change is legislation gave these producers the right to ask for a refund of the levies paid. Since that time, estimates for the hog and cattle levies refunded have been produced.

Heinz payment (2013)

Due to the closure of the Ontario Heinz processing plant in 2013, Heinz has paid a one-time 'goodwill' payment to compensate the farmers that were under contract to deliver processing tomatoes in 2013. The payment was to help offset costs that farmers may have incurred in preparing for the 2013 crop.

Programme d'aide pour les inondations en Montérégie (2011 to 2012)

This program provided financial assistance to agricultural enterprises affected by the floods of spring 2011, in the Richelieu valley. Compensation was offered to producers for loss of income due to flooded farmland, and/or losses due to unseeded acreage.

Programme d'appui à la replantation des vergers de pommiers au Québec (2007 to 2010)

The first component of this MAPAQ (Ministère de l'Agriculture, des Pêcheries et de l'Alimentation du Québec) program offered replanting help in order to improve efficiency, profitability as well as competitiveness. The objective of the second component was to compensate apple producers for the loss of apple trees due to winter-kill (frost) in 1994.

Provincial Stabilization Programs (1981 to present)

Under provincial stabilization programs, payments are made in order to support producer incomes affected by small profit margins, or low prices, for selected commodities. Provincial stabilization programs are partly funded by the provincial government, either directly through the subsidization of producer premiums, or indirectly by absorbing a part, or the whole, of the cost of administering the program. These programs are optional, and producers are required to pay premiums in order to participate.

Farm Income Stabilization Program (ASRA) (1981 to present)

The Farm Income Stabilization Insurance Program is designed to guarantee a positive net annual income to producers in Quebec. Producers participating in the program receive funds when the average selling price falls below a stabilized income, which is based on the average production cost in a specific sector. ASRA is complementary to AgriStability, but participation in AgriStability is not mandatory. Payments under ASRA decrease in accordance to amounts paid out through AgriStability. ASRA premiums are partially funded by the provincial government, which pays two thirds of the cost of premiums, while producers pay the remaining third.

Ontario Risk Management Program (RMP) (2007 to present)

ORMP is a provincial program that offers compensation to Ontario producers for losses of income caused by fluctuating market prices and rising production costs. Commodities eligible for compensation include a variety of grains and oilseeds, as well as certain livestock, including cattle, calves, hogs and sheep. The program also offers compensation for unseeded acres, under certain conditions. In order to participate in this program, producers must also participate in AgriStability, as well as Production Insurance (for grains and oilseeds). Payments made under ORMP count as an advance on the provincial portion of AgriStability for the corresponding program year. Because ORMP is provincially funded, it has no impact on the federal portion of AgriStability payments. ORMP premiums are partly funded by the provincial government, which pays 40% of the cost of premiums, while producers pay the remaining 60%.

Saskatchewan Cattle and Hog Support Program (2009)

This program helped producers retain their breeding herds and address immediate cash flow needs.

Saskatchewan Feed and Forage Program - 2011 (2011 to 2012)

This program provided compensation to producers who had to transport additional feed to their livestock, or transport their livestock to alternate locations for feeding and grazing, due to feed shortages caused by excess moisture. In addition, financial assistance was provided to producers who had to reseed hay, forage or pasture land that had been damaged by excess moisture. This provincially-funded program replaces the initial Saskatchewan Feed and Forage Program (2010-2011), which was jointly offered by the provincial and federal governments, as part of AgriRecovery.

Self-Directed Risk Management (SDRM) (2005 to present)

SDRM is a provincial program designed to help Ontarian horticultural producers manage farm operation risk. Under the program, over 150 edible horticultural crops are eligible for coverage, including fruits, vegetables, mushrooms, herbs and spices, nuts, honey and maple products. To be eligible, producers must also participate in AgriStability, and meet the minimum amount of allowable net sales (ANS). Participating producers can deposit up to a maximum of 2% of their ANS into an account, and have their contribution matched by the provincial government. Payments made under SDRM count as an advance on the provincial portion of AgriStability for the corresponding program year. Because SDRM is provincially funded, it has no impact on the federal portion of AgriStability payments. Amounts received under Production Insurance for a crop also covered by SDRM will be deducted from SDRM payments.

Shoal Lakes Agriculture Flooding Assistance Program (2011)

The purpose of this program is to provide financial support to agriculture producers affected by chronic flooding in the Shoal Lakes Complex in the Interlake of Manitoba.

  1. Land payments on a per acre basis were provided to farm operators to compensate for lost income related to agricultural production that cannot be realized due to flooded acres in 2010 and 2011.
  2. Financial assistance for transportation costs incurred between April 1, 2011 and March 15, 2012 to those farm operators who needed to transport feed to livestock or livestock to feed, due to the flooding.

This payment was administered by the Manitoba Agriculture Corporation (MASC), with the assistance of Manitoba Agriculture, Food & Rural Initiatives (MAFRI).

Support Program for the Eradication of Chronic Wasting Disease in Cervids (CWD) (2019 to present)

This program implemented by La Financière agricole du Québec offers financial aid to cervid producers affected by the measures taken to eradicate CWD.

There are two categories of aid under this program:

  • The first compensates cervid producers ordered to slaughter and dispose of animals under the Animal Health Protection Act.
  • The second financially supports cervid producers required to implement sanitary measures stipulated under the Animal Health Protection Act.

Syndrome de dépérissement postsevrage (SDP) (2008 to 2010)

This MAPAQ (Ministère de l'Agriculture, des Pêcheries et de l'Alimentation du Québec) program granted financial support to Quebec feeder hog operations affected by Post Weaning Multisystemic Wasting Syndrome (PMWS).

Transitional Production Adjustment Program (1996) (1993 to 1997 and 1999 to 2008)

Under the Tree Fruit Revitalization Program, British Columbia orchardists were guaranteed specific annual revenue per acre during the first three years, following replant of orchards to new high density tree fruit varieties.

Tree Fruit Replant Program (previously known as Tree fruit grafting/budding and replant program) (2008 to 2011, 2012 to present)

In 2008, the Transitional Production Adjustment Program ended and the Tree fruit grafting/budding and replant program started. In July 2007, the federal and provincial governments jointly announced that they were investing $8 million to help British Columbia's tree fruit and grape industries adapt to changing markets. The cost was shared (60% federal, 40% provincial) and the program lasted for three years.  In 2012, the provincial government invested an additional $2 million to replant tree fruit orchards to expand domestic markets through high-quality products by targeting the planting of premium varieties. The program, which also includes a grafting and budding component, concluded in 2014. The 2015 program is the first year of a 7 year commitment by British Columbia of $8.4 million announced in Nov 2014. This is a British Columbia Agriculture Department program that shares the administration of the program with the British Columbia Fruit Growers Association under contract until 2016.

2019-2020 B.C. AgriStability Enhancement Program 

The British Columbia government is offering greater coverage to farmers who have lost income due to weather, trade challenges or natural disaster. The Program includes:

  • Increasing the compensation rate, for all farms, from 70% to 80% on income margin losses greater than 30%. In other words, B.C. will be adding 14.3% to every AgriStability payment.
    • An AgriStability payment is triggered when a producer's current margin (allowable income less allowable expenses) drops more than 30% below their average historical margin (referred to as Reference Margin)
  • Eliminating the Reference Margin Limit (RML) which reduced compensation for some farms.
    • Farms which have wide margins due to low eligible expenses will no longer have their compensation reduced due to the RML.

Unseeded Acreage Payment - 2006 (2006 to 2007)

This program provided a payment to Saskatchewan farmers who experienced excess moisture conditions prior to June 20, 2006 and were unable to seed 95% of the acres they would normally intend to seed.

Waterfowl Damage (1981 to present)

Waterfowl damage payment programs are designed to compensate producers for crop losses caused by waterfowl. Compensation is also available for cleaning excreta contaminated grain in some provinces, and for prevention management.

Also see Crop loss compensation, Livestock predation compensation and Wildlife damage compensation programs.

Wildlife Damage Compensation Program

British Columbia (2002 to present) - The British Columbia Wildlife Compensation program is part of an Agricultural Environment Partnership Initiative that includes the following programs: The Waterfowl Damage to Forage Fields in Delta, Wild Predator Loss Control and Compensation Program for Cattle and East Kootenay Agriculture Wildlife Pilot Project. These programs are designed to compensate producers for the losses incurred to crops and livestock due to wildlife.

New Brunswick (2014 to present) - This cost-shared program compensates producers who suffer livestock or crop losses due to wildlife. Compensation is available for specified crops and livestock for damage caused by eligible wildlife. The maximum compensation per producer is $50,000 per year. The New Brunswick Agricultural Insurance Commission (NBAIC) administers this program, applicants are not required to be an insurance client to receive compensation.

Nova Scotia (2008 to present) - This cost-shared program, announced in 2008, will help address some of the risks experienced by Nova Scotia farmers regarding damage to eligible agricultural products because of the activities of wildlife, including wildlife predation on livestock and damage to crops. Applicants are not required to have crop insurance.

Ontario (2008 to present) - The Ontario Wildlife Damage Compensation Program provides financial assistance to eligible applicants whose livestock and poultry have been injured or killed by wolves, coyotes, bears and other species of wildlife identified in the program guidelines, or whose bee-colonies, bee-hives and bee-hive related equipment have been damaged by bears, raccoons, deer and skunks. The program was funded by the provincial government up to the fiscal year of 2008/2009 and became part of Growing Forward - a federal, provincial and territorial initiative starting from fiscal year 2009/2010, when cost-sharing of the program began between the governments of Canada and Ontario.

Also see Crop loss compensation, Livestock predation compensation and Waterfowl damage programs.

Quarterly Survey of Financial Statements: Weighted Asset Response Rate - first quarter 2022

Weighted Asset Response Rate
Table summary
This table displays the results of Weighted Asset Response Rate. The information is grouped by Release date (appearing as row headers), 2020, Q3 and Q4 and 2021, Q1, Q2 and Q3 calculated using percentage units of measure (appearing as column headers).
Release date 2021 2022
Q1 Q2 Q3 Q4 Q1
quarterly (percentage)
May 25, 2022 81.6 80.7 79.0 77.3 56.7
February 23, 2022 81.0 77.2 75.6 54.2 ..
November 23, 2021 80.4 74.5 56.7 .. ..
August 24, 2021 77.2 60.9 .. .. ..
May 25, 2021 57.6 .. .. .. ..
.. not available for a specific reference period
Source: Quarterly Survey of Financial Statements (2501)

Brochure - Canadian Survey on Disability

Your experience. Your voice. Your needs.

About the survey

The Canadian Survey on Disability (CSD) is one of the most comprehensive national surveys on Canadians aged 15 and older whose everyday activities are limited because of a long-term condition or health-related problem. It provides valuable insights about the lived experiences, challenges and well-being of persons with disabilities.

Why should I participate?

Your answers represent those of other Canadians just like you. Your participation is essential to ensure that the data are as complete as possible!

The information you provide will help guide decisions about policies, programs and services designed to improve the lives of persons with disabilities.

With your support, we can move one step closer to a barrier-free Canada.

What do you want to know about me?

The CSD asks important questions about a wide range of topics, including education and employment experiences; use of specialized aids and assistive devices; and need for help, therapies and supports.

New topics for 2022

  • Food security
  • Social isolation
  • Accessibility barriers
  • Homelessness
  • Sexual orientation
  • Cannabis use
  • COVID-19

When will the results be available?

Survey results will be available in the winter of 2023/2024.

Where can I get more information about the survey?

Statistics Canada Help Line: 1-833-977-8287

Telecommunications device for the hearing impaired (TTY): 1-866-753-7083

*If you use an operator-assisted relay service, you can call us during regular business hours. You do not need to authorize the operator to contact us.

Statistics Canada website: Canadian Survey on Disability (CSD)

Thank you for participating!

National Travel Survey: C.V.s for Visit-Expenditures by Duration of Visit, Main Trip Purpose and Country or Region of Expenditures – Q4 2021

National Travel Survey: C.V.s for Visit-Expenditures by Duration of Visit, Main Trip Purpose and Country or Region of Expenditures, including expenditures at origin and those for air commercial transportation in Canada, in Thousands of Dollars (x 1,000)
Table summary
This table displays the results of C.V.s for Visit-Expenditures by Duration of Visit, Main Trip Purpose and Country or Region of Expenditures. The information is grouped by Duration of trip (appearing as row headers), Main Trip Purpose, Country or Region of Expenditures (Total, Canada, United States, Overseas) calculated using Visit-Expenditures in Thousands of Dollars (x 1,000) and c.v. as units of measure (appearing as column headers).
Duration of Visit Main Trip Purpose Country or Region of Expenditures
Total Canada United States Overseas
$ '000 C.V. $ '000 C.V. $ '000 C.V. $ '000 C.V.
Total Duration Total Main Trip Purpose 14,462,173 A 10,923,996 A 1,556,359 B 1,981,817 B
Holiday, leisure or recreation 6,191,335 A 4,317,768 A 811,531 B 1,062,036 B
Visit friends or relatives 4,377,211 B 3,461,362 A 369,965 C 545,883 D
Personal conference, convention or trade show 117,387 C 116,797 C 590 E ..  
Shopping, non-routine 822,915 B 760,444 B 60,992 C 1,479 E
Other personal reasons 1,146,858 B 826,902 B 51,207 D 268,750 E
Business conference, convention or trade show 396,991 C 279,780 C 73,663 D 43,548 E
Other business 1,409,475 B 1,160,944 B 188,410 E 60,121 E
Same-Day Total Main Trip Purpose 3,679,201 A 3,604,902 A 73,089 C 1,210 E
Holiday, leisure or recreation 1,172,807 B 1,157,398 B 14,202 E 1,206 E
Visit friends or relatives 1,046,253 B 1,035,932 B 10,321 E ..  
Personal conference, convention or trade show 39,009 C 39,009 C ..   ..  
Shopping, non-routine 691,073 B 655,008 B 36,065 C ..  
Other personal reasons 405,403 B 402,971 B 2,432 E ..  
Business conference, convention or trade show 47,520 D 47,520 D ..   ..  
Other business 277,136 C 267,064 C 10,069 E 4 E
Overnight Total Main Trip Purpose 10,782,971 A 7,319,094 A 1,483,270 B 1,980,608 B
Holiday, leisure or recreation 5,018,528 B 3,160,370 A 797,329 B 1,060,830 B
Visit friends or relatives 3,330,958 B 2,425,430 A 359,644 C 545,883 D
Personal conference, convention or trade show 78,379 D 77,788 D 590 E ..  
Shopping, non-routine 131,842 C 105,436 C 24,927 E 1,479 E
Other personal reasons 741,455 C 423,931 B 48,775 D 268,750 E
Business conference, convention or trade show 349,471 C 232,259 C 73,663 D 43,548 E
Other business 1,132,338 B 893,880 B 178,342 E 60,117 E
..
data not available

Estimates contained in this table have been assigned a letter to indicate their coefficient of variation (c.v.) (expressed as a percentage). The letter grades represent the following coefficients of variation:

A
c.v. between or equal to 0.00% and 5.00% and means Excellent.
B
c.v. between or equal to 5.01% and 15.00% and means Very good.
C
c.v. between or equal to 15.01% and 25.00% and means Good.
D
c.v. between or equal to 25.01% and 35.00% and means Acceptable.
E
c.v. greater than 35.00% and means Use with caution.

National Travel Survey: C.V.s for Person-Trips by Duration of Trip, Main Trip Purpose and Country or Region of Trip Destination – Q4 2021

National Travel Survey: C.V.s for Person-Trips by Duration of Trip, Main Trip Purpose and Country or Region of Trip Destination – Q4 2021
Table summary
This table displays the results of C.V.s for Person-Trips by Duration of Trip, Main Trip Purpose and Country or Region of Trip Destination. The information is grouped by Duration of trip (appearing as row headers), Main Trip Purpose, Country or Region of Trip Destination (Total, Canada, United States, Overseas) calculated using Person-Trips in Thousands (× 1,000) and C.V. as a units of measure (appearing as column headers).
Duration of Trip Main Trip Purpose Country or Region of Trip Destination
Total Canada United States Overseas
Person-Trips (x 1,000) C.V. Person-Trips (x 1,000) C.V. Person-Trips (x 1,000) C.V. Person-Trips (x 1,000) C.V.
Total Duration Total Main Trip Purpose 53,924 A 51,330 A 1,615 B 978 B
Holiday, leisure or recreation 16,887 A 15,881 A 464 B 541 B
Visit friends or relatives 23,973 A 23,182 A 475 B 316 B
Personal conference, convention or trade show 564 C 564 C 1 E ..  
Shopping, non-routine 3,722 B 3,431 B 289 C 1 E
Other personal reasons 4,567 B 4,363 B 119 D 85 D
Business conference, convention or trade show 608 B 553 C 41 D 14 E
Other business 3,603 B 3,356 B 226 D 21 E
Same-Day Total Main Trip Purpose 34,984 A 34,371 A 613 B ..  
Holiday, leisure or recreation 10,048 A 9,981 A 67 D ..  
Visit friends or relatives 14,573 A 14,497 B 76 E ..  
Personal conference, convention or trade show 397 C 397 C ..   ..  
Shopping, non-routine 3,480 B 3,228 B 252 C ..  
Other personal reasons 3,637 B 3,563 B 74 E ..  
Business conference, convention or trade show 275 C 275 C ..   ..  
Other business 2,574 B 2,430 C 144 E ..  
Overnight Total Main Trip Purpose 18,939 A 16,959 A 1,002 B 978 B
Holiday, leisure or recreation 6,839 A 5,900 A 397 B 541 B
Visit friends or relatives 9,400 A 8,685 A 398 B 316 B
Personal conference, convention or trade show 167 D 166 D 1 E ..  
Shopping, non-routine 242 C 203 C 37 D 1 E
Other personal reasons 930 B 800 B 45 D 85 D
Business conference, convention or trade show 333 C 278 C 41 D 14 E
Other business 1,029 B 927 B 82 D 21 E
..
data not available

Estimates contained in this table have been assigned a letter to indicate their coefficient of variation (c.v.) (expressed as a percentage). The letter grades represent the following coefficients of variation:

A
c.v. between or equal to 0.00% and 5.00% and means Excellent
B
c.v. between or equal to 5.01% and 15.00% and means Very good.
C
c.v. between or equal to 15.01% and 25.00% and means Good.
D
c.v. between or equal to 25.01% and 35.00% and means Acceptable.
E
c.v. greater than 35.00% and means Use with caution.

National Travel Survey: Response Rate – Q4 2021

National Travel Survey: Response Rate – Q4 2021
Table summary
This table displays the results of Response Rate. The information is grouped by Province of residence (appearing as row headers), Unweighted and Weighted (appearing as column headers), calculated using percentage unit of measure (appearing as column headers).
Province of residence Unweighted Weighted
Percentage
Newfoundland and Labrador 22.8 21.2
Prince Edward Island 22.8 20.6
Nova Scotia 29.4 26.5
New Brunswick 28.5 25.2
Quebec 32.6 28.1
Ontario 31.0 28.7
Manitoba 32.2 29.0
Saskatchewan 29.3 26.6
Alberta 26.9 24.9
British Columbia 30.9 29.0
Canada 29.9 28.0

Statistics 101: Confidence intervals

Catalogue number: 892000062022003

Release date: May 24, 2022 Updated: January 25, 2023

In this video, you will learn the answers to the following questions:

  • What are confidence intervals?
  • Why do we use confidence intervals?
  • What factors have an impact on a confidence interval?
Data journey step
Foundation
Data competency
  • Data analysis
  • Data interpretation
Audience
Basic
Suggested prerequisites
Length
10:54
Cost
Free

Watch the video

Statistics 101: Confidence intervals - Transcript

Statistics 101: Confidence intervals - Transcript

(The Statistics Canada symbol and Canada wordmark appear on screen with the title: "Statistics 101 Confidence intervals".)

Statistics 101: Confidence intervals

Have you heard this before…

(Text on screen: 37% of Canadians anticipate working from home for the foreseeable future, based on an online survey of 2,000 Canadian adults, with a margin of error of +/- 2.0 percentage points, 19 times out of 20. Do you know what "a margin of error of +/- 2.0 percentage points, 19 times out of 20" means?  This is an example of a confidence interval.)

You have probably heard on the radio or television or read in the newspaper a statement like this:

37% of Canadians anticipate working from home for the foreseeable future, based on an online survey of 2,000 Canadian adults, with a margin of error of +/- 2.0 percentage points, 19 times out of 20.

But what exactly does it mean and why is the information presented in this way?

Working with statistics involves an element of uncertainty, and in this video we will see how confidence intervals and their underlying concepts help us understand and measure this uncertainty.

The statement above actually presents an example of a confidence interval, even though at first glance it does not look like an interval. The interval in this case is 37% +/- 2.0% - in other words, the interval goes from 35% to 39%.

At the end of this presentation you will be able to read similar statements and understand that they represent confidence intervals. You will also understand what a "margin of error" is, and what is meant by the phrase "19 times out of 20".

As pre-requisite viewing for this video, make sure you've watched our other Statistics 101 videos called "Exploring measures of central tendency" and "Exploring measures of dispersion".

Learning goals

(Text on screen: In this video, you will learn the answers to the following questions: What are confidence intervals? Why do we use confidence intervals? What factors have an impact on a confidence interval?)

By the end of this video you will understand what confidence intervals are, why we use them, and what factors have an impact on them.

Understanding the measures of central tendency and the measures of dispersion before watching this video will help you to understand confidence intervals.

Steps of a data journey

(Text on screen: Supported by a foundation of stewardship, metadata, standards and quality.)

(Diagram of the Steps of the data journey: Step 1 - define, find, gather; Step 2 - explore, clean, describe; Step 3 - analyze, model; Step 4 - tell the story. The data journey is supported by a foundation of stewardship, metadata, standards and quality.)

This diagram is a visual representation of the data journey from collecting the data; to exploring, cleaning, describing and understanding the data; to analyzing the data; and lastly to communicating with others the story the data tell.

Step 2: Explore, clean, and describe; Step 3: Analyze and model; and Step 4: Tell the story

(Diagram of the Steps of the data journey with an emphasis on Step 2: Explore, clean, and describe; Step 3: Analyze and model; and Step 4: Tell the story.)

Confidence intervals are helpful in steps 2, 3 and 4 of the data journey.

What is a Confidence Interval?

(text on screen:

Presents a range of possible values, rather than a single estimated value.

Represents the uncertainty resulting from the use of a sample.

The width of the confidence interval is related to the level of uncertainty.)

(Figure 1 demonstrating an example of confidence interval: the average grade on a math test in a class of 100 students. The estimated value is 70%, the lower bound is at 60% and the upper bound is at 80%. The values included between the lower and the upper bounds represent the confidence interval.)

A confidence interval is a range of possible values for something that we want to estimate – for example, what is the average grade on a math test in a particular class of 100 students. It is typically based on a sample that is representative of the population; however the sample is often small compared to the population. In the example here we have math grades for a sample of 10 students from a class of 100 students.

Since the estimate is based on a sample, there remains some uncertainty about the true value.  The confidence interval accounts for this uncertainty by including a range of values, and not just the estimate itself. The more uncertainty there is, the wider the confidence interval will be.

Why do we use confidence intervals?

(Figure 1 demonstrating a young man wondering why we use confidence intervals.)

In statistics, we often estimate a value for a total population using a sample.

The value derived from the sample is not the true value, but an estimate of it.

Confidence intervals example

(Figure 1 demonstrating a class of 100 students, and a sample of 10 students. Figure 2 demonstrating the confidence interval, with an estimated value of 70%, a lower bound at 60%, an upper bound at 80% and a true value of 73%.)

In this example we have a class of 100 students, each with a percentage grade for a math test. 

The class average for the math test is 73%. However, we are not looking at the marks of everyone in the population, but only those of a sample of 10 people. Taking a random sample we obtain an estimated average grade of 70%, with a confidence interval of + or – 10%. In this example, our estimate of 70% is different from the true average of 73%, but the true average is within the confidence interval.

Confidence intervals example

(Figure 1 demonstrating a class of 100 students, and a sample of 10 students. Figure 2 demonstrating the confidence interval, with an estimated value of 65%, a lower bound at 55%, an upper bound at 75% and a true value of 73%.)

By taking another random sample, we obtain a different estimated average grade of 65%, which is again not equal to the true average of 73%, but the confidence interval of 55% to 75% still contains the true average.

Confidence intervals example

(Figure 1 demonstrating a class of 100 students, and a sample of 10 students. Figure 2 demonstrating the confidence interval, with an estimated value of 78%, a lower bound at 68%, an upper bound at 88% and a true value of 73%.)

A third sample of the same class obtains an estimated average grade of 78%. This estimate again differs from the true average of 73%, but again the confidence interval contains the true average.

Estimated Value

(Figure demonstrating a confidence interval, with the estimated value highlighted in the centre.)

The estimated value from the sample is usually at the centre of the confidence interval.

Estimated Value

(Figure demonstrating a confidence interval, highlighting the lower and upper bounds of the interval at equal distance from the estimated value.)

The upper and lower bounds of the confidence interval are then an equal distance above and below the estimated value.

Estimated Value

(Figure demonstrating a confidence interval, highlighting the margin of error below and above the estimated value.)

The distance from the estimated value to the upper or lower bound is called the margin of error.

The size of the margin of error reflects the uncertainty about the true value. More uncertainty means a larger margin of error.

Factors having an impact on a confidence interval

(Figure demonstrating different coloured people with question marks on their heads.)

There are three factors that determine the width of the confidence interval from a sample survey – the confidence level, the variability within the population, and the size of the sample.

These factors will now be described one by one.

Confidence level

(Figure demonstrating an estimated value and two confidence intervals, a first one with a 95% confidence level and a second one, with a 99% confidence level.)

The confidence level tells us how certain we are that the interval contains the true population value. 

With a 95% confidence level, we are 95% confident that the confidence interval contains the true value. In other words, if we were to repeat the survey many times, the interval would contain the true value 19 times out of 20.

With a 99% confidence level, we are 99% confident that the confidence interval contains the true value.  Note that the higher level of confidence requires a longer confidence interval.

Variability within the population

(Figure demonstrating grades on math test for two different groups, a Regular Math class and an Enriched Math class.)

By variability of a population we mean how different population members are, one from another.

In the example shown here the grades of students in the Enriched Math class are less variable than the grades of students in the Regular Math class. In the Regular Math Class, grades vary from 54% to 87%. In the Enriched Math class, grades vary from 86% to 96% – about one third the variability of the Regular Math class.

If variability is high in the population, then it will be high in the sample. If we had two different random samples from the population, then the difference between the two different estimates would also tend to be larger. So higher variability in the population leads to higher variability in the samples, which leads to higher variability in the estimates. This larger variability for the estimates is reflected in a larger margin of error, so that the confidence interval is wider.

Similarly, if variability is lower in the population, then it will be lower in the sample, and the estimate will have lower variability, leading to a smaller margin of error and a narrower confidence interval.

Size of the sample

(Figure demonstrating a class of 100 students.)

A larger sample will produce more precise estimates – that is, estimates with lower variability. 

For example, in a class of 100 students, the average of a sample of size 20 would have smaller variability than the average of a sample of size 10. The average of a sample of size 50 would have still smaller variability. 

So the larger the sample size, the smaller the variability of the estimate, the smaller the margin of error, and the shorter the confidence interval.

Let's look at an example…

Example - sample of size 10

(Figure demonstrating a class of 100 students, and a sample of 10 students, with an estimated average grade of 64%, and the true class average of 73%.)

The average class grade is 73%.

The average for the random sample of 10 students is 64%.

Example - sample of size 50

(Figure demonstrating a class of 100 students, and a sample of 50 students, with an estimated average grade of  71%, and the true class average of 73%.)

As we see in this example, with a much larger sample size, the variability of the estimator is much smaller, and it would tend to be much closer to the true value. The confidence interval would then be narrower.  

Knowledge check

Now it's your turn. How would you interpret the following statement:

According to a recent study, adults living in a specific city weighed an average of 75 kg, with a margin of error of -/+ 10 kg, 9 times out of 10.

What is the estimated value? What is the confidence interval? What is the confidence level?

Take a moment to think about all the information included in this sentence.

Answer

First, we can conclude that the estimated value was obtained using a sample of the population. Second, we understand that the estimated average weight is 75 kg, and that the confidence interval ranges from 65 kg to 85 kg. The confidence interval is quite large, which may suggest a small sample size, high variability in the weight of individuals, or even both.

The confidence level is 90%, or 9 times out of 10. This means that if a random sampling were to be repeated many times, the confidence interval would contain the true value 9 times out of 10. A higher confidence level, 95%, as an example, would require an even wider confidence interval.

Recap of key points

To summarize what we learned today: confidence intervals can help understand and measure the uncertainty associated with estimated values from samples; data coming from samples do not provide true values, but estimated values; the length of the confidence interval can vary based on the size of the sample, the variability of the population and the confidence level required.

(The Canada Wordmark appears.)

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Data ethics: An introduction

Catalogue number: 892000062022001

Release date: May 24, 2022

In this video, you will be introduced to data ethics, why they are important, and the 6 guiding principles of data ethics implemented by Statistics Canada, throughout the Data Journey.

Data journey step
Foundation
Data competency
  • Data security and governance
  • Data stewardship
Audience
Basic
Suggested prerequisites
N/A
Length
10:54
Cost
Free

Watch the video

Data ethics: An introduction - Transcript

Data ethics: An introduction - Transcript

(The Statistics Canada symbol and Canada wordmark appear on screen with the title: "Data Ethics An Introduction")

Slide 0: Data Ethics : An Introduction

Gathering, exploring, analyzing and interpreting data are essential steps in producing information that benefits society, the economy and the environment. To properly conduct these processes, data ethics must be upheld in order to ensure the appropriate use of data.

Slide 1: Learning Goals

(Text on screen: By the end of this video, you should have a better understanding of the following:

  • What "data ethics" means
  • Why data ethics are important
  • How Statistics Canada impliments data ethics throughout the data journey)

In this video, you will be introduced to data ethics, why they are important, and the 6 guiding principles of data ethics implemented by Statistics Canada, throughout the Data Journey.

Slide 2: Steps in the data journey

(Text on screen: Supported by a foundation of stewardship, metadata, standards and quality

Diagram of the Steps of the data journey: Step 1 - define, find, gather; Step 2 - explore, clean, describe; Step 3 - analyze, model; Step 4 - tell the story. The data journey is supported by a foundation of stewardship, metadata, standards and quality.)

This diagram is a visual representation of the data journey from collecting the data; to exploring, cleaning, describing and understanding the data; to analyzing the data; and lastly to communicating with others the story the data tell.

Slide 3: Steps in the data journey (Part 2)

Data ethics are relevant throughout all steps of the data journey.

Slide 4: What are data ethics?

So what are data ethics exactly? Data Ethics allow data users to address questions about the appropriate use of data throughout all steps of the data journey.

This field of study is used to ensure collected data always have a specific purpose, and that each new project or data acquisition has the best interests of both society and the individual at heart.

Slide 5: There Are Lots Of Ways To Gather Data…

With the rapid growth of data associated with the digital age, data gathering approaches have also evolved.

Along with the more traditional survey-based approach, some alternative data gathering methods include:

  • Earth observation data;
  • Scanner data;
  • Administrative data.

Slide 6: … And Transform Data To Information

These data are then used to create useful information such as statistics, and to train algorithms for artificial intelligence and machine learning. But with big data comes big responsibility…

Slide 7: Responsibility to address ethical challenges such as:

When deciding to embrace such evolving data gathering methods as administrative sourcing, web scraping, apps and crowdsourcing, there is a responsibility to maintain focus on such perennial ethical challenges as:

  • Protecting privacy and confidentiality
  • Balancing privacy intrusion vs public good
  • Recognizing the potentially harmful impacts of using biased data
  • Ensuring data quality to avoid misinformation

Slide 8: Statistics Canada's 6 Guiding Principles of Data Ethics

There are many ways to address these ethical challenges, at Statistics Canada, we use the following 6 guiding principles:

  • Data are used to benefit Canadians
  • Data are used in a secure and private manner
  • Data acquisitions and processing methods are transparent and accountable
  • Data acquisitions and processing methods are trustworthy and sustainable
  • The data themselves are of high quality
  • Any information resulting from the data are reported fairly and do no harm

Let's look at these principles in more detail.

Slide 9: Benefits To Society

Benefits to society means that statistical activities must allow governments, businesses and communities to make informed decisions and manage resources effectively, ultimately aiming to clearly benefit the lives of Canadians.

Slide 10: Benefits To Society - Example

A census of population is fundamental to any country's statistical infrastructure. In Canada, the census is currently the only data source that provides high-quality population and dwelling counts based on common standards and at low levels of geography, as well as consistent and comparable information on various population groups.

Slide 11: Privacy and Security

(Text on screen: It is important to find a balance between respecting privacy and producing information

  • Ensure statistical activities are not intruding into the lives of Canadians any more than necessary
  • Always justify whatever intrusion might be considered necessary

It is also important to consider the practical aspects of security, and how potential breaches may affect the well-being of Canadians).

When statistical activities require personal information, the consideration of both privacy and security is mandatory. The appropriate measures must always be taken in order to protect personal information while still ensuring the data can be used to create meaningful information.

Firstly, there is a fine balance between respecting privacy and producing information. Projects that intrude into the private lives of Canadians must justify why this information is important enough to warrant this intrusion, and be able to explain how using this data will ultimately provide benefits. In other words, we must ensure that our statistical activities are not intruding into the lives of Canadians any more than necessary, and to always justify whatever intrusion we consider necessary.

Furthermore, when designing a data-gathering approach, we have a moral obligation to protect the confidentiality and data of Canadians. Part of the data ethics exercise also consists in ensuring that projects have considered potential security threats and have prepared accordingly.

Slide 12: Privacy and Security – Example

(Text on screen: Study on the sexual orientation of individuals in management positions.

Questions related to gender, marital status and sex are pertinent, even if intrusive.

Questions about salary, criminal antecedents and health conditions are intrusive and not directly tied to the project, so they must be justified.

Strict IT and Information Management measures must be taken during all stages of working with this data, as they are personal and sensitive.)

Let's imagine we are trying to have a better picture of the sexual orientation of individuals in management positions. If we conduct a survey, then questions related to gender, marital status and sex are pertinent, even if intrusive. If we were to ask questions about salary, age and nationality, we would have to justify why these variables are necessary.

To avoid any breach of personal information, strict IT and Information Management measures must be taken during all stages of working with data - the collection, retention, use, disclosure and disposal of information, in order to protect the confidentiality of this vulnerable population as well as the integrity of the project.

Slide 13: Transparency and Accountability

Statistical activities undertaken for the benefit of society have the responsibility to be transparent about where the data come from, how they are used and the steps that are taken to ensure confidentiality.

Slide 14: Transparency and Accountability - Example

At Statistics Canada's Trust Centre for example, you will find a list of all current surveys and statistical programs, together with their methodologies, goals and data sources. Making these projects available is important not only so that Canadians can consult how statistical activities are conducted to determine if a project is in their best interest, but also so they can keep the agency accountable and point out whenever Statistics Canada ever encroaches upon the limits of its mandate.

Slide 15: Data Quality

The Data Quality principle means that the data used to create statistical information must be as representative and accurate as possible. Maintaining this expectation means ensuring that biases and errors do not compromise the potential benefits of a project or mislead data users.

Slide 16: Data Quality – Example

(Text on screen: Low response rates can lead to biasedestimates or samples too small to meet the information need.

Statistics Canada decides to start using alternative data sources.

If sources are biased, they may lead to uninformed measures and policies.)

When conducting a survey, low response rates can lead to biased estimates or samples too small to meet the information need. Take data surrounding employment among individuals with disabilities for example. If the response rate for survey affects the quality of the estimates, Statistics Canada might decide to start using alternative data sources, such as administrative data acquired from industrial associations or labor unions.

If these new sources are biased, the unreliable information resulting from them may lead to uninformed measures and policies, which may cause more harm than good.

Slide 17: Fairness and Do No Harm

When conducting statistical activities, it is necessary to consider all the potential risks that a statistical activity may pose to the well-being of individuals or specific groups.

Slide 18: Fairness and Do No Harm - Example

When acquiring and linking a large amount of data, detailed descriptions of smaller sub-populations of society might become available for analysis. These detailed clusters can sometimes magnify what is happening at the lowest level of geography. While this may sound harmless, it is important to remember these clusters of data might reveal information such as ethnicity and socio-economic status. Putting any sub-population under a microscope can raise ethical issues. For instance, studies on criminality have to be worded in careful manner so as to not reinforce stereotypes, and results have to be shared with caution to ensure that the information is informative and not taken as an indictment of a specific population group.

Slide 19: Trust and Sustainability

In order to maintain the trust of the public, the use of data for the benefit of society should occur only by implementing such best practises as assuring confidentiality, protecting personal information, producing representative data, and being accountable. By making this our mandate, we can ensure that our statistical activities remain socially acceptable in the eyes of the public. If we have social acceptability, any partnership and any approach we undertake becomes and opportunity to show that we follow our mandate and helps the agency promote its objectives and maintain the trust of the public in the long term.

Slide 20: Trust and Sustainability - Example

To illustrate when trust really matters, imagine we are trying to gather information on recreational cannabis use by Canadian youth, via voluntary crowdsourcing, and that this is happening before cannabis was legalized. One can only expect respondents to provide accurate, reliable data if they trust the institution responsible for guarding their responses and preserving confidentiality. In this case, they must trust their data is not going to be shared with anyone, including peers, parents and even legal authorities.

Slide 21: Recap of Key Points

(Figure 1 showing a table with the 6 guiding principles: Benefits Canadians, Trust and Sustainability, Privacy and Security, Data Quality, Transparency and Accountability and Fairness and Do No Harm)

In summary, Data Ethics is the field of study that addresses questions about the appropriate use of data.

With advances in data gathering techniques comes ethical challenges regarding access to and use of data.

There are 6 guiding principles you can use to address ethical concerns:

  • Benefits to Canadians
  • Privacy and security
  • Transparency and accountability
  • Trust and sustainability
  • Data quality
  • Fairness and do no harm

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Retail Trade Survey (Monthly): CVs for total sales by geography – March 2022

CVs for Total sales by geography
This table displays the results of Retail Trade Survey (monthly): CVs for total sales by geography – March 2022. The information is grouped by Geography (appearing as row headers), Month and Percent (appearing as column headers)
Geography Month
202203
%
Canada 0.6
Newfoundland and Labrador 1.8
Prince Edward Island 0.9
Nova Scotia 1.2
New Brunswick 2.1
Quebec  1.5
Ontario 1.2
Manitoba 1.4
Saskatchewan 2.9
Alberta 1.3
British Columbia 1.7
Yukon Territory 1.0
Northwest Territories 1.3
Nunavut 1.6