Consumer price indexes

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All (10)

All (10) ((10 results))

  • Articles and reports: 62F0014M2024002
    Description: In collaboration with the Bank of Canada, this research paper focuses on constructing analytical price index series for Canada, using the main owned accommodation measurement concepts proposed by the International Consumer Price Index Manual and adopted by other countries. This analysis explores these alternative treatments of owned accommodation in the Canadian context, examining their impact on the all-items Consumer Price Index. Additionally, it provides an explanation for the gap between perceived inflation and estimated inflation.
    Release date: 2024-03-28

  • Articles and reports: 36-28-0001202300700005
    Description: Increases in grocery prices have outpaced headline consumer inflation since late 2021. While the pace of food inflation has eased recently, prices for many grocery items continue to rise month after month. This article examines data from recent business and household surveys on how Canadians have been adjusting to higher food prices.
    Release date: 2023-07-26

  • Articles and reports: 36-28-0001202300600001
    Description: The Canadian Economic Tracker, released on May 16th 2023, is a new data visualization tool combining selected monthly indicators of economic activity from Statistics Canada’s Common Output Database Repository (CODR) into a unified, customizable interface. The Tracker includes six indicators: business openings and closures, employment and weekly earnings, job vacancies and vacancy rates, gross domestic product, the consumer price index, and the industrial product price index. Each data release for these series is automatically incorporated into the Tracker, ensuring that the statistics remain timely and up to date. This article is the first in a series which will uncover insights that can be collected from the Canadian Economic Tracker.
    Release date: 2023-06-28

  • Articles and reports: 62F0014M2021017
    Description:

    Decisions by economic agents, such as firms and consumers, depend on their views about inflation. Consumers’ views of inflation, are systematically higher than inflation measured by the Consumer Price Index (CPI), and more so for certain demographic groups. While measurement factors can explain part of this gap, behavioral factors appear to play a larger role. This article examines these factors to explain the gap between CPI’s inflation and inflation perceptions in Canada.

    Release date: 2022-01-19

  • Articles and reports: 62F0014M2020001
    Description:

    This paper describes the changes in the methodology for measuring the air transportation index.

    Release date: 2020-01-22

  • Articles and reports: 62F0014M2017002
    Description:

    This document offers information on changes to the Mortgage Interest Cost Index (MICI), which is one of the Consumer Price Index (CPI) components. It describes the new approach for estimating MICI price movements.

    Release date: 2017-11-17

  • Articles and reports: 62F0014M2017001
    Description:

    This article is an overview of the treatment of Shelter in the Canadian Consumer Price Index (CPI). It describes the concepts and methodologies related to the construction of that component and briefly discusses considerations to be taken into account when using the estimates.

    Release date: 2017-09-22

  • Articles and reports: 11-621-M2007057
    Geography: Canada, Province or territory
    Description:

    Using data from the monthly Retail Trade Survey this study examines the sales for the year 2006. This annual review describes sales growth and trends by trade groups such as new motor vehicle dealers, supermarkets and general merchandise stores. This study focuses on provincial sales.

    Release date: 2007-06-27

  • Articles and reports: 12-001-X19990014710
    Description:

    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: 62F0014M1998006
    Geography: Canada
    Description:

    Statistical agencies such as Statistics Canada are investigating the use of scanner data for their own purposes. Interest has grown in the potential uses of this data to improve the quality of price indexes. This paper reports on initial research done in Prices Division. The paper looks at scanner data and the feasibility of its use to produce CPI estimates; evaluates current CPI methodology and procedures; and the impact that use of scanner data would have on the CPI commodity indexes. The main focus of the study, however, is to explore the impact that scanner data would have on the CPI basic commodity indexes covered by scannable items. Since the CPI criterion relates to a limited selection of scanner data, an examination will be made of the impact of gradually relaxing the criteria to include more products and outlets from the scanner data. The initial subset was derived by applying the CPI criteria of volume selling brands and outlets. Each of these changes in criteria yielded a different subset of scanner data. Calculations were performed using these various subsets of scanner data and their results compared to the CPI. An analysis of the results will be used in determining the strengths and limitations of CPI data, detect any deficiencies and provide information for revision of pricing selection.

    Release date: 1999-05-13
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Analysis (10)

Analysis (10) ((10 results))

  • Articles and reports: 62F0014M2024002
    Description: In collaboration with the Bank of Canada, this research paper focuses on constructing analytical price index series for Canada, using the main owned accommodation measurement concepts proposed by the International Consumer Price Index Manual and adopted by other countries. This analysis explores these alternative treatments of owned accommodation in the Canadian context, examining their impact on the all-items Consumer Price Index. Additionally, it provides an explanation for the gap between perceived inflation and estimated inflation.
    Release date: 2024-03-28

  • Articles and reports: 36-28-0001202300700005
    Description: Increases in grocery prices have outpaced headline consumer inflation since late 2021. While the pace of food inflation has eased recently, prices for many grocery items continue to rise month after month. This article examines data from recent business and household surveys on how Canadians have been adjusting to higher food prices.
    Release date: 2023-07-26

  • Articles and reports: 36-28-0001202300600001
    Description: The Canadian Economic Tracker, released on May 16th 2023, is a new data visualization tool combining selected monthly indicators of economic activity from Statistics Canada’s Common Output Database Repository (CODR) into a unified, customizable interface. The Tracker includes six indicators: business openings and closures, employment and weekly earnings, job vacancies and vacancy rates, gross domestic product, the consumer price index, and the industrial product price index. Each data release for these series is automatically incorporated into the Tracker, ensuring that the statistics remain timely and up to date. This article is the first in a series which will uncover insights that can be collected from the Canadian Economic Tracker.
    Release date: 2023-06-28

  • Articles and reports: 62F0014M2021017
    Description:

    Decisions by economic agents, such as firms and consumers, depend on their views about inflation. Consumers’ views of inflation, are systematically higher than inflation measured by the Consumer Price Index (CPI), and more so for certain demographic groups. While measurement factors can explain part of this gap, behavioral factors appear to play a larger role. This article examines these factors to explain the gap between CPI’s inflation and inflation perceptions in Canada.

    Release date: 2022-01-19

  • Articles and reports: 62F0014M2020001
    Description:

    This paper describes the changes in the methodology for measuring the air transportation index.

    Release date: 2020-01-22

  • Articles and reports: 62F0014M2017002
    Description:

    This document offers information on changes to the Mortgage Interest Cost Index (MICI), which is one of the Consumer Price Index (CPI) components. It describes the new approach for estimating MICI price movements.

    Release date: 2017-11-17

  • Articles and reports: 62F0014M2017001
    Description:

    This article is an overview of the treatment of Shelter in the Canadian Consumer Price Index (CPI). It describes the concepts and methodologies related to the construction of that component and briefly discusses considerations to be taken into account when using the estimates.

    Release date: 2017-09-22

  • Articles and reports: 11-621-M2007057
    Geography: Canada, Province or territory
    Description:

    Using data from the monthly Retail Trade Survey this study examines the sales for the year 2006. This annual review describes sales growth and trends by trade groups such as new motor vehicle dealers, supermarkets and general merchandise stores. This study focuses on provincial sales.

    Release date: 2007-06-27

  • Articles and reports: 12-001-X19990014710
    Description:

    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: 62F0014M1998006
    Geography: Canada
    Description:

    Statistical agencies such as Statistics Canada are investigating the use of scanner data for their own purposes. Interest has grown in the potential uses of this data to improve the quality of price indexes. This paper reports on initial research done in Prices Division. The paper looks at scanner data and the feasibility of its use to produce CPI estimates; evaluates current CPI methodology and procedures; and the impact that use of scanner data would have on the CPI commodity indexes. The main focus of the study, however, is to explore the impact that scanner data would have on the CPI basic commodity indexes covered by scannable items. Since the CPI criterion relates to a limited selection of scanner data, an examination will be made of the impact of gradually relaxing the criteria to include more products and outlets from the scanner data. The initial subset was derived by applying the CPI criteria of volume selling brands and outlets. Each of these changes in criteria yielded a different subset of scanner data. Calculations were performed using these various subsets of scanner data and their results compared to the CPI. An analysis of the results will be used in determining the strengths and limitations of CPI data, detect any deficiencies and provide information for revision of pricing selection.

    Release date: 1999-05-13
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