The reductions identified in the Government of Canada’s Budget 2025 and the Comprehensive Expenditure Review confirmed Statistics Canada’s need to streamline operations while continuing to deliver the trusted data Canadians rely on. These government-wide measures are intended to reduce spending on operations while protecting priority programs and investing in areas that support Canada’s economic and social well-being.

In response, Statistics Canada entered a workforce adjustment period in January 2026 and has made targeted adjustments to programs to ensure the long-term sustainability of Canada’s national statistical system. Our most critical programs, such as the Census of Population, the Consumer Price Index, gross domestic product, trade, and employment statistics, continue without interruption. These core indicators remain priorities and will continue to be available to governments, businesses, and communities across the country.

Most changes affect how data are collected and produced, rather than the availability of data. To reduce duplication and focus resources where they have the greatest impact, some surveys and statistical programs will be discontinued where the data can be obtained through alternative sources or methods. Statistics Canada will continue to deliver trusted data by increasing the use of administrative data, modelling, automation and artificial intelligence, and by adjusting release frequency or level of detail where appropriate, while maintaining the quality, integrity, and continuity of Canada’s key national indicators.

Throughout this period of change, Statistics Canada remains committed to responsible stewardship of public resources and to fulfilling its mandate under the Statistics Act. Whether we collect administrative, alternative, or survey data, one thing remains certain—Statistics Canada continues to operate in accordance with governing instruments and frameworks, including those guiding the use of automation and artificial intelligence, and our commitment to protecting privacy and safeguarding the confidentiality of data remains unwavering. As Canada’s national statistical agency, Statistics Canada continues to provide high-quality, objective, and trusted data that support informed decision-making and public confidence in official statistics.

The Canadian international merchandise trade program

Introduction

The objective of this text is to provide a general overview of the balance of payments-basis data produced by the Canadian International Merchandise Trade (CIMT) Program, with special reference to concepts and definitions.

Conceptual framework

1. Objectives and coverage: The objective of balance of payments-basis CIMT statistics is to measure the change in economic transactions that involve merchandise trade between residents and non-residents. Information on imports and exports are inputs into the Macroeconomic Accounts, and are used in the formulation of trade and economic policies. Governments, importers, exporters, manufacturers and shipping companies use international merchandise trade statistics to:

• monitor import penetration and export performance;
• monitor commodity price and volume changes; and
• examine transport implications.

2. Trade statistics (customs-basis/balance of payments-basis): Merchandise trade statistics are presented on two different bases: customs and balance of payments.

Statistics for Canada’s imports as well as exports to non-US destinations are compiled from Customs declarations filed with the Canada Border Services Agency (CBSA). Data for Canada’s exports to the United States are derived from the administrative import records of the United States Customs and Border Protection and exchanged under the terms of a memorandum of understanding between Canada and the United States. Statistics developed from these Customs administrative records are commonly referred to as customs-basis trade statistics.

Customs-basis data are adjusted to conform to the National Accounts concepts and definitions. The adjustments to derive balance of payments-basis trade data include adjustments related to trade definition, valuation and timing. The principal difference between the two trade concepts is that customs-basis merchandise trade statistics cover the physical movement of goods as they are reflected in Customs documents while balance of payments-basis data are intended to cover economic transactions that involve merchandise trade between residents and non-residents.

It is possible for the accuracy of customs-basis statistics to be affected by undercoverage and/or country misallocation. Undercoverage occurs when trade is not captured in customs documents. Examples of undercoverage include transactions where the value is below the threshold required for reporting to customs authorities, and the informal or illegal movement of goods across borders. Estimates for undercoverage are included in balance of payments-basis statistics. Country misallocation occurs when the last known destination reported on the customs export documentation does not reflect the ultimate destination for the goods. This occurs most frequently when goods are routed through an intermediary country before continuing to their final destination with the intermediary country being reported as the final destination of the goods.

3. Valuation: For Customs purposes, imports are recorded at values established according to the provisions of the Customs Act, which reflects valuation methods based on the General Agreement on Tariffs and Trade (GATT) Valuation Code System. In general, the value for duty of imported goods must be equivalent to the transaction value or the price actually paid.

The transaction value of imported goods includes all transportation and associated costs incurred up to the point of direct shipment to Canada. Therefore, Canada's imports are valued Free on Board (FOB), place of direct shipment to Canada. It excludes freight and insurance costs in bringing the goods to Canada from the point of direct shipment.

Exports are recorded at the value declared on Customs documents, which reflect the transaction value (i.e., actual selling price or, in the case of a non-arm's length transaction, the transfer price used for company accounting purposes). Canada's exports are valued at FOB port of exit from Canada, including domestic freight charges to that point but net of discounts and allowances.

4. Statistical period: In theory, the statistical period for balance of payments-basis trade statistics reflects the month during which change of ownership occurred. Since this can be difficult to determine, in practice, the statistical period for balance of payments-basis statistics reflects the month during which the goods cleared Customs. The closing of the statistical month for imports and exports is defined as the last calendar day of the month based on the date of clearance from Customs. Documents received too late for incorporation in the current month are assigned to the month the transaction took place and are published the following statistical month.

5. Trading partner attribution (country of origin/destination): On a custom basis, imports are attributed to the country of origin, that is the country in which the goods were grown, extracted or manufactured in accordance with the rules of origin administered by the CBSA. On a balance of payments-basis, imports are attributed to the country of export instead of the country of origin to reflect the change in ownership of the goods.

Both customs- and balance of payments-basis exports are attributed to the country that is the last known destination of the goods at the time of export. 

6. Principal Trading Partners (PTPs): The list of PTPs is based on their annual share of total trade — merchandise imports plus exports — with Canada in 2012. The countries included in the list of PTPs are the following:

List of Canada's Principal Trading Partners

• United States
• European Union
  • Germany
  • Netherlands
  • France
  • Italy
  • Belgium
  • Spain
• China
• United Kingdom
• Mexico
• Japan
• South Korea
• Hong Kong
• Brazil
• Algeria
• Norway
• India
• Switzerland
• Saudi Arabia
• Turkey
• Taiwan
• Peru
• Australia
• Iraq
• Indonesia
• Singapore
• Russian Federation
• Other OECD countries
• All other countries

7. Legal framework: Import and export statistics with countries other than the United States are derived from information contained in administrative records collected by the CBSA under the Customs Act. Copies of these documents (or information therefrom) are sent to Statistics Canada in accordance with Section 25 of the Statistics Act. It follows that the disclosure of trade statistics is governed by both the Customs Act and the Statistics Act and is subject to the provisions of Section 17(2)(a) of the latter. Disclosure of statistics for trade with the United States is governed by a memorandum of understanding that provides for the exchange of detailed import statistics between Canada and the United States.

Contact information

Telephone: 1-800-263-1136 
Facsimile: 1-877-287-4369
Email: infostats@statcan.gc.ca

Statement outlining results, risks and significant changes in operations, personnel and program

B) Highlights of fiscal quarter and fiscal year-to-date results

This section highlights the significant items that contributed to the net increase in resources available for the year, as well as actual expenditures for the quarter ended December 31. 

Chart 1 outlines the gross budgetary authorities, which represent the resources available for use for the year as of December 31.

Significant changes to authorities

Total authorities available for 2025-26 have increased by $91.2 million, or 10.3%, from the previous year, from $887.8 million to $979 million (Chart 1). The net increase is mostly the result of the following:

• An increase of $86 million in funding received to cover the advanced planning and intensifying production activities related to the ramping up of the 2026 Census of Population program;
• An increase of $12.2 million for the Employee Benefit Plan adjustments and for the carry forward from the previous year. The agency leverages the operating budget carry-forward mechanism to manage the cyclical nature of program operations and investments in the agency's strategic plan;
• An increase of $11.4 million in funding related to compensation following the ratification of collective agreements;
• A decrease of $34.4 million for various initiatives including the Canadian Dental Care Plan and the transfer of certain cloud operations functions to Shared Services Canada;
• An increase of $12.5 million for various initiatives including Canada’s Action Plan on Combatting Hate, the Clean Technology Data Strategy as well as funding to modernize and enhance the collection and dissemination of housing data, supporting Canada’s Housing Plan.

In addition to the appropriations allocated to the agency through the Main Estimates, Statistics Canada also has vote net authority within Vote 1, which entitles the agency to spend revenues collected from other federal government departments, agencies, and external clients to provide statistical services. The vote netting authority is stable at $120 million when comparing the third quarter of fiscal years 2024-2025 and 2025-2026.

Significant changes to expenditures

Year-to-date net expenditures recorded to the end of the third quarter increased by $37.7 million, or 7% from the previous year, from $536.7 million to $574.4 million (see Table A: Variation in Departmental Expenditures by Standard Object).

Statistics Canada spent approximately 66.9% of its authorities by the end of the third quarter, compared with 69.9% in the same quarter of 2024-2025.

Table A: Variation in Departmental Expenditures by Standard Object (unaudited)

This table displays the variance of departmental expenditures by standard object between fiscal 2024-2025 and 2025-2026. The variance is calculated for year to date expenditures as at the end of the third quarter. The row headers provide information by standard object. The column headers provide information in thousands of dollars and percentage variance for the year to date variation.

Departmental Expenditures Variation by Standard Object:	Q3 year-to-date variation between fiscal year   2024-2025 and 2025-2026
	$'000	%
(01) Personnel	20,232	3.7
(02) Transportation and communications	1,434	12.3
(03) Information	5,188	100.6
(04) Professional and special services	-3,350	-18.5
(05) Rentals	4,784	18.4
(06) Repair and maintenance	49	12.1
(07) Utilities, materials and supplies	1,604	225.3
(08) Acquisition of land, buildings and works	-23	-63.9
(09) Acquisition of machinery and equipment	-940	-40.8
(10) Transfer payments	-	-
(12) Other subsidies and payments	132	36.6
Total gross budgetary expenditures	29,109	4.8
Less revenues netted against expenditures:
Revenues	-8,641	-12.1
Total net budgetary expenditures	37,750	7.0
Note: Explanations are provided for variances of more than $1 million.

Personnel: The increase is primarily due to salary price increases and costs related to the employee benefit plan. To accommodate the cyclical nature of some of Statistics Canada’s programs, including the Census of Population program, resources have been reallocated within the agency.

Transportation and communications: The increase is mainly due to timing differences in invoicing compared to last fiscal year in relation to the connectivity and telecommunications support provided by Shared Services Canada for the 2026 Census of Population.  

Information: The increase is mainly due to advertisement and printing costs for 2026 Census of Population materials such as questionnaires, envelopes, and letters. 

Professional and special services: The decrease is attributable to the salaries of workers hired under the Statistics Act to operate the Census Help Line and to undertake data collection work during the Census Test, which began and ended in 2024. These operations will commence shortly for the 2026 Census. Also contributing is a reduction in IT consultant costs. Additionally, there has been timing differences in invoicing compared to last year. 

Rentals: The increase is mainly due to additional costs for logistical requirements for the 2026 Census of Population, as well as timing differences in invoicing compared to last year. 

Utilities, materials and supplies: The increase is mainly due to additional costs for office supplies needed for the 2026 Census of Population.

Revenues: The increase is mainly due to timing differences in invoicing compared to last year.

Overview

The Consumer Price Index (CPI) plays a key role in the Bank of Canada's conduct of monetary policy.

In 1991, the Bank of Canada and the Government of Canada jointly established an inflation-targeting framework for the conduct of monetary policy. This framework is reviewed every five years, with the most recent renewal occurring in October 2016. Based on this framework, the Bank of Canada conducts monetary policy aimed at keeping inflation, as measured by the change in the All-items CPI, at 2 per cent, the midpoint of an inflation-control range of 1 to 3 per cent.

To help it achieve this target, the Bank of Canada uses a set of measures of core inflation. The purpose of these measures is to capture persistent price movements by eliminating transitory or sector-specific fluctuations in some components of the CPI. From 2001 until the most recent renewal of the inflation control target, the Bank of Canada's focal measure of core inflation was the All-items CPI excluding eight of its most volatile components (as defined by the Bank of Canada) as well as the effect of changes in indirect taxes on the remaining components (CPIX). For more information, see the Bank of Canada Review article (Macklem (2001)).

As discussed in the Renewal of the Inflation-Control Target – Background Information, the Bank of Canada has identified three preferred measures of core inflation to help assess underlying inflation in Canada.^Note 1 The Bank of Canada chose these three measures based primarily on analysis conducted in 2015 by its researchers (Khan, Morel and Sabourin (2015)). While the Bank's emphasis will be on these three measures, Statistics Canada will continue to calculate and publish CPIX.

Although no measure of core inflation was superior across all the evaluation criteria, three measures showed the best performance. Based on the results of this analysis, the Bank of Canada decided to change its approach by jointly using all three measures: i) a measure based on the trimmed mean (CPI-trim); ii) a measure based on the weighted median (CPI-median); and, iii) a measure based on the common component (CPI-common). For more information on how the three measures were chosen, see the background document on the renewal of the inflation-control target (Bank of Canada (2016)). In the rest of this document, we will present detailed information on the methodologies and data used to produce these measures of core inflation.^Note 2

Reference period

These measures are expressed as a year-over-year percentage change (i.e., comparing any month in a given year to the same month in the previous year). Accordingly, they are not available in the form of an index level and do not have a reference period (e.g., 2002=100).

Data sources and methodologies

The three preferred measures of core inflation are computed by Statistics Canada using data from the CPI Survey. For more information on the data sources, error detection, imputation rules, estimation and calculation of price indexes, quality evaluation of the data collected, and data disclosure control for the CPI survey, see the description of this survey. Below, we will describe the CPI data used and the methods for calculating these three measures of core inflation.

The three measures require historical series of consumer price indexes based on the disaggregation of the All-items CPI into a fixed number of components. These components are exhaustive and mutually exclusive. Therefore, the sum of their respective weights in the CPI basket is equal to 100. These measures are based on a 55-component disaggregation of the CPI basket; a complete list of these components is provided in Table A1 in the appendix of this document. These historical series are available on a monthly basis. Owing to data limitations, these 55 components are calculated since January 1989.^Note 3 Since we use price indexes calculated at the national level, the three measures are only calculated at that level of detail.

The consumer price indexes of the 55 components are first adjusted to remove the effect of changes in indirect taxes.

Measure of core inflation based on the trimmed mean (CPI-trim)

CPI-trim excludes from the 55 components those whose monthly rates of change in the CPI are located in the tails of the distribution of the monthly rates of change of all the price indexes in a given month. This measure is calculated as a weighted arithmetic average of the price changes of the non-excluded components. The weight of a component corresponds to its weight in the CPI basket at the basket link month. The procedure for calculating CPI-trim every month can be described as follows.

Step 1: The historical series of price indexes for the 55 components, adjusted to remove the effect of changes in indirect taxes, are seasonally adjusted. For more information on the seasonal adjustment methodology, see the "Revisions and seasonal adjustment" section below.

Step 2: We obtain the distribution of all monthly inflation rates calculated for the 55 components based on the percentage changes in price indexes for the current month versus those for the previous month. These monthly inflation rates are then sorted in ascending order (i.e., from lowest to highest). By ranking all the components' weights and monthly inflation rates together in this order, components with the lowest inflation rates are excluded, which accounts for 20 per cent^Note 4 of the total CPI basket. The same process is used to exclude components with the highest inflation rates, up to 20 per cent^Note 5 of the basket.

Step 3: We calculate a monthly trimmed inflation rate, ${\text{CPI-trim}}_t^{m/m}$, defined as the weighted arithmetic average of monthly inflation rates for components not excluded in Step 2, which make up 60 per cent of the total CPI basket. The weight of the excluded components will always be 40 per cent of the total CPI basket, but the excluded components are not necessarily the same from month to month.

Step 4: We produce the annual inflation rate for a given month, ${\text{CPI-trim}}_t^{y/y}$, using the cumulative monthly trimmed inflation rates for the 12-month period ending in the current month. The following formula is used for this purpose:

$${\text{CPI-trim}}_t^{y/y}=\left(\left(1+\frac{{\text{CPI-trim}}_{t-11}^{m/m}}{100}\right)\times \left(1+\frac{{\text{CPI-trim}}_{t-10}^{m/m}}{100}\right)\times \dots \times \left(1+\frac{{\text{CPI-trim}}_t^{m/m}}{100}\right)-1\right)\times 100.$$

In other words, the annual inflation rate, ${\text{CPI-trim}}_t^{y/y}$, measured for a given month $t$ is calculated as the cumulative monthly trimmed inflation rates over the 12-month period ending in month $t$.

Measure of core inflation based on the weighted median (CPI-median)

CPI-median represents, for a given month, the price change corresponding to the 50th percentile (in terms of CPI basket weights) of the distribution of price changes of the 55 components. As with CPI-trim, the weight of a component is represented by its weight in the CPI basket at the basket link month. The method for processing data for the CPI-median is similar to that for CPI-trim. The procedure for calculating CPI-median every month can be described as follows.

Step 1: The historical series of price indexes for the 55 components, adjusted to remove the effect of changes in indirect taxes, are seasonally adjusted. For more information on the seasonal adjustment methodology, see the "Revisions and seasonal adjustment" section below.

Step 2: We obtain the distribution of all monthly inflation rates calculated for the 55 components based on the percentage changes in price indexes for the current month versus those for the previous month. These monthly inflation rates are then sorted in ascending order (i.e., from lowest to highest). By ranking all the components' weights and inflation rates together in this order, we identify the monthly inflation rate located at the 50th percentile^Note 6 (in terms of CPI basket weights) of the distribution of the monthly inflation rates for the 55 components. This value represents the monthly inflation rate based on the weighted median, ${\text{CPI-median}}_t^{m/m}$. The component corresponding to the weighted median value is not necessarily the same from month to month. This approach is similar to that for CPI-trim because it eliminates all the weighted monthly price variations at both the bottom and top of the distribution of price changes in any given month, except the price change for the component that is the midpoint of that distribution.

Step 3: We produce the annual inflation rate, ${\text{CPI-median}}_t^{y/y}$, for a given month, using the cumulative monthly inflation rates based on the weighted median for the 12-month period ending in the current month. The following formula is used for this purpose:

$${\text{CPI-median}}_t^{y/y}=\left(\left(1+\frac{{\text{CPI-median}}_{t-11}^{m/m}}{100}\right)\times \left(1+\frac{{\text{CPI-median}}_{t-10}^{m/m}}{100}\right)\times \dots \times \left(1+\frac{{\text{CPI-median}}_t^{m/m}}{100}\right)-1\right)\times 100.$$

In other words, the value of the annual inflation rate, ${\text{CPI-median}}_t^{y/y}$, in a given month $t$ is calculated as the cumulative monthly inflation rates based on the weighted median over the 12-month period ending in month $t$.

Measure of core inflation based on the common component (CPI-common)

CPI-common is a measure that tracks common price changes across the 55 components in the CPI basket.

As with CPI-trim and CPI-median, the input data for CPI-common are the CPI series for the 55 components adjusted to remove the effect of changes in indirect taxes. In addition, we use the historical series of the All-items CPI adjusted to remove the effect of changes in indirect taxes to scale CPI-common to the inflation rate. Unlike CPI-trim and CPI-median, this measure is based on year-over-year percentage changes in price indexes. Therefore, the price index series are not seasonally adjusted when calculating CPI-common.

This measure is based on a factor model. Factor models are statistical methods that represent the variation in a set of variables as the sum of one or more factors representing co-movements across variables and an idiosyncratic term capturing the part unexplained by this (those) common factor(s). In the context of estimating core inflation, these models are used to separate the common source underlying the changes in CPI series from idiosyncratic elements that are related to sector-specific events (Khan, Morel and Sabourin (2013)).^Note 7 For each of the 55 components, $i=1,2,\mathrm{...},55$, the model is written as follows (in the case of one common factor):

$${\pi }_{i,t}={\Lambda }_i{F}_t+{\epsilon }_{i,t};i=1,2,\mathrm{...},55;t=1,2,\mathrm{...},T,$$

where $T$ represents the total number of time periods available, ${\pi }_{i,t}$ represents the inflation rate of component $i$ for the period $t$, which is related to the common factor $F_t$ through factor loading ${\Lambda }_i$, and ${\epsilon }_{i,t}$ is an idiosyncratic error term representing sector-specific disturbances that are uncorrelated with the common factor. In this model, the measure of core inflation is then defined as follows:

$${\tilde{\pi }}_t=\Lambda F_t\text{ ,}$$

where $\Lambda$ is the matrix of factor loadings. For more information, see Khan et al. (2013).

In practice, CPI-common is calculated using the entire historical data of price index series and by following the steps below.

Step 1: We calculate annual inflation rates for the 55 components and for the All-items CPI excluding the effect of changes in indirect taxes. In a given month, the annual inflation rate for a given component is defined as the year-over-year percentage change in the price index for that month.

Step 2: The historical series of annual inflation rates for the 55 components are standardized. In other words, the historical series of annual inflation rates for each component is centred with respect to its average and then divided by its standard deviation.

Step 3: A factor model is estimated using data from the 55 historical series of annual standardized inflation rates. The principal components method is used for this purpose (Stock and Watson (2002a, 2002b)). This method involves creating 55 new variables, called principal components, each explaining a fraction of the variation found in all 55-historical series of annual inflation rates. The first principal component, which is associated with the highest eigenvalue, is the one that best explains the variation in the 55 historical series of annual inflation rates over the entire observation period. Only the first principal component is used in calculating CPI-common.^Note 8

Step 4: The final step is to scale the first principal component to the inflation rate. The measure of core inflation based on the common component, CPI-common, is defined and calculated as the series of predicted values from the simple linear regression of the annual inflation rates of the All-items CPI excluding the effect of changes in indirect taxes (obtained in Step 1) on an intercept and on the first principal component calculated in Step 3.

Since CPI-common is based on a factor model, a standardization and a linear regression requiring all data available, the historical values for this measure are subject to revisions. An analysis of the magnitude of the revisions, reported in a Bank of Canada's Staff Working Paper (Khan et al. (2013)), suggests that revisions are relatively negligible.

Revisions and seasonal adjustment

These three measures of core inflation, CPI-trim, CPI-median and CPI-common, are subject to revision. For CPI-median and CPI-trim, this results from the fact that these measures are based on seasonally adjusted price index series. For CPI-common, revisions are due to the statistical technique used as the factor model is estimated over all available historical data.

When Statistics Canada introduces the CPI-trim and CPI-median measures in its November 2016 CPI release, 44 of the 55 historical series will be identified as seasonally adjusted, whereas others do not present any identifiable seasonal pattern. Since the technical parameters for seasonal adjustment are updated once a year, the number of series that are seasonally adjusted may change in the future depending on the historical series available that have (or do not have) an identifiable seasonal pattern. As with other CPI series, the approach used for seasonal adjustment involves each series to be seasonally adjusted separately. For more information, see the section "Revisions and seasonal adjustment" in the CPI detailed information document.

The seasonally adjusted CPI series are subject to revision. With each January data release, seasonally adjusted data are revised back three years.^Note 9 For all other months, revisions apply to one historical month.  However, the models underlying the seasonal adjustment procedure are regularly revisited; as a result, they will be revised and updated when necessary.

Data accuracy

As with the CPI in general, statistical reliability is difficult to evaluate for the three preferred measures of core inflation. First, a statistical reliability indicator is not available for the price index series used as inputs to these measures. In addition, calculating these measures is complex, which makes it more difficult to evaluate their statistical reliability. For more information on the evaluation of the CPI data accuracy, see this Statistics Canada publication. In practice, since the three measures are based on price index series calculated at the national level, their level of accuracy should be relatively comparable to that of All-items CPI.