Consumer price indexes
Key indicators
Selected geographical area: Canada
-
2.9%
(12-month change) -
1.9%
(12-month change)
More consumer price indexes indicators
Selected geographical area: Canada
-
6.5%
(12-month change)
-
3.0%
(12-month change)
-
157.13.9%
(annual change)
-
$239.308.1%
(year-over-year change)
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Survey or statistical program
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All (8)
All (8) ((8 results))
- Articles and reports: 62F0014M2023008Description: An interactive timeline of the modernization of the CPI and related programs with dates, links, and summary of key developments.Release date: 2024-02-20
- Articles and reports: 62F0014M2022009Description:
This paper describes the composition of the Consumer Price Index (CPI) basket and the changes introduced with the 2022 basket update, based on 2021 expenditure weights.
Release date: 2022-06-15 - Surveys and statistical programs – Documentation: 11-522-X201700014751Description:
Practically all major retailers use scanners to record the information on their transactions with clients (consumers). These data normally include the product code, a brief description, the price and the quantity sold. This is an extremely relevant data source for statistical programs such as Statistics Canada’s Consumer Price Index (CPI), one of Canada’s most important economic indicators. Using scanner data could improve the quality of the CPI by increasing the number of prices used in calculations, expanding geographic coverage and including the quantities sold, among other things, while lowering data collection costs. However, using these data presents many challenges. An examination of scanner data from a first retailer revealed a high rate of change in product identification codes over a one-year period. The effects of these changes pose challenges from a product classification and estimate quality perspective. This article focuses on the issues associated with acquiring, classifying and examining these data to assess their quality for use in the CPI.
Release date: 2016-03-24 - 4. New Motor Vehicle Sales: 2007 in Review ArchivedArticles and reports: 11-621-M2008069Geography: Canada, Province or territoryDescription:
This study examines new motor vehicle sales in 2007. It looks at the evolution of sales in the last 10 years with respect to the origin of the vehicle (North American-built or overseas-built). It also offers analysis of sales of cars and trucks by province in 2007.
Release date: 2008-04-23 - Articles and reports: 12-001-X20060029554Description:
Survey sampling to estimate a Consumer Price Index (CPI) is quite complicated, generally requiring a combination of data from at least two surveys: one giving prices, one giving expenditure weights. Fundamentally different approaches to the sampling process - probability sampling and purposive sampling - have each been strongly advocated and are used by different countries in the collection of price data. By constructing a small "world" of purchases and prices from scanner data on cereal and then simulating various sampling and estimation techniques, we compare the results of two design and estimation approaches: the probability approach of the United States and the purposive approach of the United Kingdom. For the same amount of information collected, but given the use of different estimators, the United Kingdom's methods appear to offer better overall accuracy in targeting a population superlative consumer price index.
Release date: 2006-12-21 - Articles and reports: 12-001-X19990014710Description:
Most statistical offices select the sample of commodities of which prices are collected for their Consumer Price Indexes with non-probability techniques. In the Netherlands, and in many other countries as well, those judgemental sampling methods come close to some kind of cut-off selection, in which a large part of the population (usually the items with the lowest expenditures) is deliberately left unobserved. This method obviously yields biased price index numbers. The question arises whether probability sampling would lead to better results in terms of the mean square error. We have considered simple random sampling, stratified sampling and systematic sampling proportional to expenditure. Monte Carlo simulations using scanner data on coffee, baby's napkins and toilet paper were carried out to assess the performance of the four sampling designs. Surprisingly perhaps, cut-off selection is shown to be a successful strategy for item sampling in the consumer price index.
Release date: 1999-10-08 - Articles and reports: 62F0014M19970103362Geography: CanadaDescription:
The debate on the measurement of bias in the CPI has been around for decades. However, given the size of government budgetary deficits, the issue of overestimating inflation and therefore payments in social benefits has triggered the interest in the measurement of the CPI bias. The final report of the U.S. Advisory Commission to Study the Consumer Price Index, chaired by Michael Boskin, states that the U.S. CPI has been overestimated by 1.1% per year since 1996. Following the release of the report, many interested groups have asked the question as to the magnitude of the bias for Canada's CPI. This result raised the question whether the bias in the Canadian CPI was of the same magnitude. This paper begins by presenting the bias issue in the context of the Canadian CPI and then outlines some of the plans Statistics Canada intends to undertake in the near future to improve the measurement of the CPI. The paper concludes that, although the Canadian CPI may suffer from the same potential problems as the U.S. CPI, the overall effect of these biases is less notable because Statistics Canada started to apply an appropriate methodology earlier. In fact, in recent studies Crawford (1993 and 1997) tried to estimate an overall bias and concluded that given the generous judgement incorporated in the estimate, it is likely that the bias is, on average smaller than 0.5%.
Release date: 1997-10-02 - Articles and reports: 62F0014M1997010Geography: CanadaDescription:
The debate on the measurement bias in the Consumer Price Index (CPI) arising from the U.S. "Advisory Commission to Study the Consumer Price Index", better known as the Boskin report, is not new and has been around for a number of decades. However, several circumstances made the current debate special.
This publication, Bias in the CPI: experiences from five OECD countries, presents the experience and point of view of five different countries relative to the measurement bias in the CPI. While most statistical agencies recognise that their CPIs are not perfect measures of inflation, some agencies of the Organisation for Economic Co-operation and Development (OECD) countries have consistently developed research agendas designed to improve its measurement.
Release date: 1997-10-02
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Analysis (7)
Analysis (7) ((7 results))
- Articles and reports: 62F0014M2023008Description: An interactive timeline of the modernization of the CPI and related programs with dates, links, and summary of key developments.Release date: 2024-02-20
- Articles and reports: 62F0014M2022009Description:
This paper describes the composition of the Consumer Price Index (CPI) basket and the changes introduced with the 2022 basket update, based on 2021 expenditure weights.
Release date: 2022-06-15 - 3. New Motor Vehicle Sales: 2007 in Review ArchivedArticles and reports: 11-621-M2008069Geography: Canada, Province or territoryDescription:
This study examines new motor vehicle sales in 2007. It looks at the evolution of sales in the last 10 years with respect to the origin of the vehicle (North American-built or overseas-built). It also offers analysis of sales of cars and trucks by province in 2007.
Release date: 2008-04-23 - Articles and reports: 12-001-X20060029554Description:
Survey sampling to estimate a Consumer Price Index (CPI) is quite complicated, generally requiring a combination of data from at least two surveys: one giving prices, one giving expenditure weights. Fundamentally different approaches to the sampling process - probability sampling and purposive sampling - have each been strongly advocated and are used by different countries in the collection of price data. By constructing a small "world" of purchases and prices from scanner data on cereal and then simulating various sampling and estimation techniques, we compare the results of two design and estimation approaches: the probability approach of the United States and the purposive approach of the United Kingdom. For the same amount of information collected, but given the use of different estimators, the United Kingdom's methods appear to offer better overall accuracy in targeting a population superlative consumer price index.
Release date: 2006-12-21 - Articles and reports: 12-001-X19990014710Description:
Most statistical offices select the sample of commodities of which prices are collected for their Consumer Price Indexes with non-probability techniques. In the Netherlands, and in many other countries as well, those judgemental sampling methods come close to some kind of cut-off selection, in which a large part of the population (usually the items with the lowest expenditures) is deliberately left unobserved. This method obviously yields biased price index numbers. The question arises whether probability sampling would lead to better results in terms of the mean square error. We have considered simple random sampling, stratified sampling and systematic sampling proportional to expenditure. Monte Carlo simulations using scanner data on coffee, baby's napkins and toilet paper were carried out to assess the performance of the four sampling designs. Surprisingly perhaps, cut-off selection is shown to be a successful strategy for item sampling in the consumer price index.
Release date: 1999-10-08 - Articles and reports: 62F0014M19970103362Geography: CanadaDescription:
The debate on the measurement of bias in the CPI has been around for decades. However, given the size of government budgetary deficits, the issue of overestimating inflation and therefore payments in social benefits has triggered the interest in the measurement of the CPI bias. The final report of the U.S. Advisory Commission to Study the Consumer Price Index, chaired by Michael Boskin, states that the U.S. CPI has been overestimated by 1.1% per year since 1996. Following the release of the report, many interested groups have asked the question as to the magnitude of the bias for Canada's CPI. This result raised the question whether the bias in the Canadian CPI was of the same magnitude. This paper begins by presenting the bias issue in the context of the Canadian CPI and then outlines some of the plans Statistics Canada intends to undertake in the near future to improve the measurement of the CPI. The paper concludes that, although the Canadian CPI may suffer from the same potential problems as the U.S. CPI, the overall effect of these biases is less notable because Statistics Canada started to apply an appropriate methodology earlier. In fact, in recent studies Crawford (1993 and 1997) tried to estimate an overall bias and concluded that given the generous judgement incorporated in the estimate, it is likely that the bias is, on average smaller than 0.5%.
Release date: 1997-10-02 - Articles and reports: 62F0014M1997010Geography: CanadaDescription:
The debate on the measurement bias in the Consumer Price Index (CPI) arising from the U.S. "Advisory Commission to Study the Consumer Price Index", better known as the Boskin report, is not new and has been around for a number of decades. However, several circumstances made the current debate special.
This publication, Bias in the CPI: experiences from five OECD countries, presents the experience and point of view of five different countries relative to the measurement bias in the CPI. While most statistical agencies recognise that their CPIs are not perfect measures of inflation, some agencies of the Organisation for Economic Co-operation and Development (OECD) countries have consistently developed research agendas designed to improve its measurement.
Release date: 1997-10-02
Reference (1)
Reference (1) ((1 result))
- Surveys and statistical programs – Documentation: 11-522-X201700014751Description:
Practically all major retailers use scanners to record the information on their transactions with clients (consumers). These data normally include the product code, a brief description, the price and the quantity sold. This is an extremely relevant data source for statistical programs such as Statistics Canada’s Consumer Price Index (CPI), one of Canada’s most important economic indicators. Using scanner data could improve the quality of the CPI by increasing the number of prices used in calculations, expanding geographic coverage and including the quantities sold, among other things, while lowering data collection costs. However, using these data presents many challenges. An examination of scanner data from a first retailer revealed a high rate of change in product identification codes over a one-year period. The effects of these changes pose challenges from a product classification and estimate quality perspective. This article focuses on the issues associated with acquiring, classifying and examining these data to assess their quality for use in the CPI.
Release date: 2016-03-24
- Date modified: