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Canadian Classification of the Functions of Government (CCOFOG) Methodology

Universe

CCOFOG data are presented for all general government sectors: the federal general government sector, the provincial general and territorial government sector, the local general government sector, the colleges and universities sector, and the health, school board and Canada and Quebec Pension Plan sectors. Canadian Classification of the Functions of Government (CCOFOG) coding is applied at the program level for the general ledger accounts, specified purpose accounts, special funds, and income statements of specific entities, such as colleges and universities.

For the province of Nova Scotia, program expenses were estimated from the provincial general government budget documents. This is similar to the methodology used in the previous Financial Management System (FMS) framework.

Data composition

The published CCOFOG data represent only expenses, with the exception of the consumption of fixed capital. They also exclude acquisitions of non-financial assets. The CCOFOG data are currently available for the period 2008 to 2012.

Data reliability

CCOFOG provisional data are being released for the first time in November 2014. This provisional qualifier signals to users that although the data are fit for use, they are subject to revisions. Over the next year these data will be integrated into the rest of the Canadian System of Macroeconomic Accounts (the National Accounts, Balance of Payments, International Investment Position, Input-Output Tables) resulting in revisions as data, concepts and methods are reconciled and aligned within the national accounts framework.

Data limitations

A CCOFOG-based analysis must be limited exclusively to a chronological analysis of a single jurisdiction in a single government sector. Transfers among jurisdictions and among government sectors are not consolidated, which means that, in practice, if the health and education sectors, for example, are added to the general provincial government sector, we are over-estimating expenses as a result of the double-counting of the value of the transfers.

Inter-provincial comparisons are also strictly impossible because the non-reconciliation of transfers means that we cannot compare a government sector that has different responsibilities in two provinces. For example, Ontario delegated a majority of its social housing responsibilities to the local government sector, but British Columbia did not. Thus, comparing CCOFOG data from division 710 – Social Protection, for the general government sector for these two provinces is statistically invalid.

Coding process

The CCOFOG classification has three levels. The highest level is referred to as the division and has 10 separate categories. The second level is referred to as the group and the lowest level is referred to as the class. In this initial CCOFOG release the data are presented at the division level and exclude amortization of non-financial assets expenditures. In November 2015, the data will be presented at the group level.

The primary mandate of a government's program, together with additional information provided by the Canadian Government Finance Statistics (CGFS) coding, is used to assign the CCOFOG classification. When a program has multiple mandates requiring multiple CCOFOG codes, available financial documents are used to determine the main proportion of the observed expense. The total value of the government's program is then assigned to that CCOFOG code.

In general, special funds usually have a single function and thus a single CCOFOG code is assigned. For example, a social housing authority would have all expenses coded to 71069 – Housing.

The assignment is always at the lowest level of CCOFOG detail, which is the class level.

General assignment principles

The 2014 Government Finance Statistics Manual, published by the International Monetary Fund, provides an overview of the COFOG assignment rules in Chapter 6 and its annex. Canada rigorously adheres to the guidelines described in the manual but has introduced certain nuances that more accurately reflect the Canadian reality. The “Detailed assignment decisions” section explains these nuances by class and/or function.

When a program significantly impacts a number of different classes in the same group, or if there wasn't enough detail, an aggregate was sometimes created. For example, aggregate 70459 – Transport n.e.c. was created to represent the sum of transport expenses that could not be specifically allocated to the Road Transport, Water Transport, Railway Transport, Air Transport and Pipelines and other transport systems classes.

Detailed assignment decisions

Division 701- General public services

Centralized services such as Access Ontario are classified under 70133 – Other general services. Services shared by certain departments, such as information technology and human resources, are deemed to be “centralized” if they cover more than two departments.

Government research institutes are generally classified under Basic research (70149); most other research institutes are assigned to applied research or experimental development in their area of expertise (health, agriculture, etc.).

All negotiations of territorial treaties with Aboriginal bands are included in class 70169 – General public services.

All expenses identified under the CGFS classification as interest expense, are classified under 70179 – Public debt transactions.

Transfers to governments for infrastructure expenses are coded under group 7018 – Transfers of a general character between different levels of government. Code 70181 was created to identify transfers to the federal government, while code 70182 identifies transfers to provincial governments and code 70183, transfers to local governments.

Division 702- Defence

Military defence is exclusively a federal government jurisdiction – these expenses will not be found at the provincial/territorial or local level.

Division 703- Public order and safety

In Canada, probation and parole monitoring programs are the responsibility of prison administrations and not the courts as recommended by the Government Finance Statistics Manual. To preserve the comparability of international data, we have left these programs under the courts, but we have set them apart by identifying them by a specific code, 70331. This code will make it easier to transfer the program when Canada publishes its public order and safety expenses under its Justice framework.

Similarly, two key Public order and safety programs in Canada also received their own unique codes: 70332 for legal aid and 70333 for administrative tribunals.

704- Economic affairs

Expenses related to status of women boards and other gender equality initiatives are included in 70412- General labour affairs because, historically, the employment component was the initial focus of these programs.

A CCOFOG group was created to integrate the expenses of programs involving immigration and citizenship, namely, 70413 – Citizenship and immigration.

As mentioned earlier, a special aggregation was created to combine transport expenses when there is not enough detail to identify a specific class: 70459 – Transport n.e.c.

705 – Environmental protection

At the local government level, it is sometimes difficult to separate water supply (70639) and waste water management (70529) expenses; in these instances, a new CCOFOG classification was created to aggregate the two types of expenses (70631).

706 – Housing and community amenities

At the local government level, it is sometimes difficult to separate water supply (70639) and waste water management (70529) expenses; in these instances, a new CCOFOG classification was created to aggregate the two types of expenses (70631).

707 – Health

708 – Recreation, culture and religion

709 – Education

The level of available detail in our source data on education expenses does not allow us to estimate pre-elementary and elementary data or the first and second cycles at the secondary level. We have therefore grouped these classes together in a new aggregated category, 70929 – Elementary and secondary education.

We are also unable at this time to separate non-doctoral higher education (70941) from doctoral (70942); we have therefore combined these two classes into a new aggregated category University education (70949).

Furthermore, when there was not sufficient detail to distinguish college education (70939) from university education (70949), the default choice was to classify this expense under university education (70949).

Internships and apprenticeships were included in division 709 – Education only when such hours were essential to obtain credits toward the degree or diploma. Otherwise, internships and apprenticeships are included in division 704 – Economic affairs under group 70412 – General labour affairs.

710 – Social protection

To accommodate the requirements of public order and safety expenses, under group 7107 – Social exclusion n.e.c. a new class was created 71071 – Victims of crime.

Figure 1 Public Sector Universe

Figure 1 Public Sector Universe
Description for Figure 1

The hierarchy of the public sector along with its subcomponents.

Public sector:

  • General governments
    • Federal general government
      • Government
        • Ministries and departments, non-autonomous funds and organizations
        • Autonomous funds and organizations
      • Federal non-autonomous pension plans
    • Social Security FundsFootnote 1
      • Canada Pension Plan
      • Quebec Pension Plan
    • Provincial and territorial general government
      • Government
        • Ministries and departments, non-autonomous funds and organizations
        • Autonomous funds and organizations
      • Provincial non-autonomous pension plans
      • Universities and colleges
      • Health and social service institutions
    • Local general government
      • Government
        • Municipalities and quasi-municipalities, non-autonomous funds and organizations
        • Autonomous funds and organizations
      • School boardsFootnote 2,Footnote 3
    • Aboriginal general government
      • Government
        • Aboriginal governments
  • Government business enterprises
    • Federal government business enterprises
    • Provincial and territorial government business enterprises
    • Local government business enterprises

Footnotes

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North American Product Classification System (NAPCS) Canada 2012 Version 1.1

Introduction

NAPCS Canada 2012 Version 1.1 updates NAPCS Canada 2012 Version 1.0. In total, there are 271 changes between the two versions. Some categories were split, and others were merged. New categories were incorporated, and some were deleted, for a net addition of 65 product categories at different levels, providing better alignment with survey data collection and publication. In some instances, these modifications created the need to renumber codes. These changes account for about half of the update. The remaining changes relate to editing of class titles adding precision to their formulations. The detailed list of changes can be obtained from Standards Division at standards-normes@statcan.gc.ca.

Standard classification structure

The standard classification structure of NAPCS Canada 2012 comprises four levels: group, class, subclass, and detail. The table below outlines the nomenclature and provides the number of categories within each level of NAPCS Canada 2012 versions 1.1 and 1.0.

Standard classification structure of NAPCS Canada 2012
Level Coding Number of categories NAPCS 2012 Version 1.1 Number of categories NAPCS 2012 Version 1.0
Group 3-digit codes 158 158
Class 5-digit codes 511 510
Subclass 6-digit codes 1,402 1,398
Detail 7-digit codes 2,694 2,648
Table source: Statistics Canada, NAPCS.

Classification variants

Along with NAPCS Canada 2012 Version 1.1, two new regrouping variants are made available: one for the Industrial Product Price Index (IPPI) and one for the Raw Materials Price Index (RMPI). These variants add one level (section) above the standard classification structure; this new level is defined in terms of standard groups (three-digit). The tables below illustrate the nomenclature of the IPPI and RMPI variants and provide the number of categories within each level.

Levels for IPPI variant
Levels for IPPI variant Coding Number of categories
Section 3-character alphanumeric codes 21
Group 3-digit standard codes, and 4-character alphanumeric codes 79
Class 5-digit standard codes, and 6-character alphanumeric codes 241
Subclass 6-digit standard codes 665
Detail 7-digit standard codes 1,190
Table source: Statistics Canada, NAPCS.
Levels for RMPI variant
Levels for RMPI variant Coding Number of categories
Section 3-character alphanumeric codes 6
Group 3-digit standard codes, and 4-character alphanumeric codes 21
Class 5-digit standard codes, and 6-character alphanumeric codes 44
Subclass 6-digit standard codes 90
Detail 7-digit standard codes 197
Table source: Statistics Canada, NAPCS.

At the time of publishing this note, the plan is to create two regrouping variants for capital expenditures and one extension variant for agricultural products.

Status

This standard was approved as a departmental standard on January 16, 2007.

2006 version of the SGC

The Standard Geographical Classification (SGC) is Statistics Canada's official classification of geographic areas in Canada. The SGC provides unique numeric codes for three types of geographic areas: provinces and territories, census divisions (counties, regional municipalities), and census subdivisions (municipalities). The three geographic areas are hierarchically related; a seven-digit code is used to show this relationship. In addition to the SGC units, metropolitan areas with their component census subdivisions and economic regions with their component census divisions are included.

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Concordances and documentation on changes

Other geographical entities

Changes to SGC 2006

Reference Maps

The Standard Geographical Classification (SGC) is Statistics Canada's official classification of geographic areas in Canada. The SGC provides unique numeric codes for three types of geographic areas: provinces and territories, census divisions (counties, regional municipalities), and census subdivisions (municipalities). The three geographic areas are hierarchically related; a seven-digit code is used to show this relationship. In addition to the SGC units, metropolitan areas with their component census subdivisions are included.

More information

Five-Year Survival Estimates for Cancer using the Cohort Approach – Key Methodological Points

Survival after a diagnosis of cancer is affected by a variety of individual, tumour and healthcare system factors. Individual factors include sex, age at diagnosis, comorbidity, socioeconomic status and lifestyle; tumour-related factors include histological subtype, aggressiveness of the tumour, and spread of disease at diagnosis; and, healthcare system factors include the availability and quality of early detection, diagnostic and treatment services. Examined across cancer types and regions, survival estimates can be used to establish priority areas for improving prognosis.Note 1 Examined over time, and in conjunction with incidence and mortality trends, survival estimates can be used to monitor progress in cancer control.Note 2 Because of the importance of cancer survival, the Canadian Cancer Registry (CCR) regularly produces survival estimates using the cohort approach. Key aspects of the methodology employed are detailed below.

Survival analyses include all primary cancers, including multiple primaries for the same person. This approach is becoming standard practice.Note 3-5 However, cancers diagnosed through autopsy only or death certificate only (DCO) are excluded from survival analysis because the date of diagnosis, and thus survival time, is unknown. Since the “true” survival of cases registered as DCO is generally poorer than those registered by other means, the common approach of excluding DCOs may bias survival estimates upward, particularly in provinces/territories with proportionally more DCOs. The magnitude of such bias, however, is generally minor.Note 6

The vital status of a person with cancer is determined through linkage with the Canadian Vital Statistics Death Database and information reported by provincial/territorial cancer registries (PTCRs). Deaths reported by PTCRs but not confirmed by linkage are included in survival analyses using the date of death submitted by PTCRs. Survival time is calculated as the number of days between the date of diagnosis and date of death or date of last follow-up (whichever is earliest). For the small percentage of persons missing month and/or day of diagnosis or death, the survival time is estimatedNote 7; however, decedents with an unknown year of death are excluded from survival analyses.

Survival analyses are performed using publicly available SAS programs to which minor adaptations are made.Note 8 The standard five-year observation time for each individual is split into multiple observations, one for each interval of follow-up time. Three month intervals are used for the first year of follow-up and six month intervals for the remaining four years for a total of 12 intervals. Since the employed actuarial life table method assumes deaths are evenly distributed within an interval, more intervals are used in the first year of follow-up because mortality is often highest and most unevenly distributed during the first year after a cancer diagnosis. With the exception of cases previously excluded because they were diagnosed through autopsy only or DCO, persons with the same date of diagnosis and death are assigned one day of survival because the SAS program automatically excludes cases with zero days of survival. Survival estimates are then calculated at discrete points in follow-up by taking the product of the interval-specific (conditional) survival estimates within the follow-up period.

Expected survival proportions are derived from sex- and province/territory-specific annual life tables by applying the Ederer II approach.Note 9 Due to small populations, only abridged life tables are produced for Prince Edward Island and the three territories. Using methods suggested by Dickman et al.Note 10, abridged life tables are expanded to complete life tables using the abridged and complete life tables for Canada. Since abridged life tables only extend to age 99 years, expected survival proportions for age 100 to 109 years are drawn from complete Canadian life tables.

Five-year observed survival is the percentage of people surviving five-years after cancer diagnosis. Five-year relative survival ratios are estimated as the ratio of the observed survival of the group diagnosed with cancer to the expected survival for the corresponding general population of the same age, sex, province of residence, and time period. In theory, relative survival ratios greater than 100% indicate that the observed survival of people with cancer is better than that expected in a comparable group from the general population. In these instances, it could be that the persons diagnosed with cancer experienced lower mortality from other causes of death because of a greater than usual interaction with the healthcare system. However, estimates of relative survival greater than 100% should be interpreted with caution as several other factors may be at play including random variation in the observed number of deaths, failure to register some cancer deaths, and imprecision in the estimation of expected survival.

As an indication of the level of statistical uncertainty in survival estimates, confidence intervals formed from standard errors estimated using Greenwood's methodNote 11 are provided. To avoid implausible lower limits less than zero and/or upper limits greater than one for observed survival estimates, asymmetric confidence intervals based on the log (-log) transformation are constructed. Relative survival ratio confidence limits are then derived by dividing the observed survival limits by the corresponding expected survival proportion.

Because survival estimates vary with age and the age distribution of cancer cases can vary over time and between geographic areas, it is usually preferable to use age-standardized survival estimates to compare survival over time, across provinces, or between a province and Canada as a whole. Age-standardized survival estimates are interpretable as the survival estimate that would have occurred if the age distribution of the cancer group under study had been the same as that of the standard population. Age-standardized estimates are calculated using the direct method. Specifically, age-specific survival estimates for a given cancer are weighted to the age distribution of persons diagnosed with that cancer over a recent, relatively long period with the age categories used in the weighting being dependent on the cancer under study. Such an approach has the advantage of producing age-standardized survival estimates that are similar to non-standardized estimates.Note 12 Specifics regarding the standard population used and age categories employed are generally detailed in the various publications released by Statistics Canada. Confidence intervals for age-standardized relative survival ratios are formed by multiplying the corresponding age-standardized observed survival lower and upper limits by the ratio of the age-standardized relative survival ratio to the age-standardized observed survival.

Notes