Canadian Composite Leading Indicator (CI)
Detailed information for March 2005
Status:
Inactive
Frequency:
Monthly
Record number:
1601
The Canadian Composite Leading Indicator is comprised of ten components which lead cyclical activity in the economy and together represent all major categories of Gross Domestic Product (GDP). It thus reflects the variety of mechanisms that can cause business cycles.
Data release - April 19, 2005
Description
The Canadian Composite Leading Indicator is comprised of ten components which lead cyclical activity in the economy and together represent all major categories of Gross Domestic Product (GDP). It thus reflects the variety of mechanisms that can cause business cycles. Eight components are available from 1952 to 1965, 9 from 1966 to 1971 and 10 from 1972. Average lead times can be highly variable, and the leading index will always be more volatile than GDP since the components are specifically selected as representing very sensitive indicators of total demand and output.
Statistical activity
The Canadian System of National Accounts (CSNA) provides a conceptually integrated statistical framework for studying the state and behavior of the Canadian economy. The accounts are centered on the measurement of activities associated with the production of goods and services, the sales of goods and services in final markets, the supporting financial transactions, and the resulting wealth positions.
To produce financial statistics, the CSNA measures the economic dimensions of the public sector of Canada, including the financial inter-relationships among the thousands of entities that make up the three levels of government in Canada (federal, provincial and territorial, and local). In order to carry out this program, the CSNA maintains a universe of all public sector entities including their complex inter-relationships.
Subjects
- Economic accounts
- Leading indicators
Data sources and methodology
Target population
The Canadian economy.
Instrument design
This methodology does not apply.
Sampling
This methodology does not apply.
Data sources
Data are extracted from administrative files and derived from other Statistics Canada surveys and/or other sources.
Four of the 10 indicators come from sources outside of Statistics Canada. They are the Housing Index whose source is the "Multiple Listing Services"; the TSE 300 Stock Price Index; the M1 Money Supply from the Bank of Canada; and the US Conference Board Leading Indicator.
Error detection
This methodology type does not apply to this statistical program.
Imputation
This methodology does not apply.
Estimation
The components of the Canadian Leading Indicator were selected to reflect the variety of mechanisms that can cause business cycles. All major categories of Gross Domestic Product are represented in the leading index by component leading indicators that are associated with the expenditure category. The component indicators must also be available in a timely fashion (i.e. no more than 2 months after the end of the reference month).
The composite index is the simple, unweighted average of the standardized components. It has been found both here and in the United States that experiments in assigning different weights to the components do not significantly improve the results.
The composite index is then standardized so that its mean and standard deviation of its growth rate are equal to those of real GDP and its components, respectively. This is done to give the leading index the same trend as GDP, and facilitates comparisons of the two. Finally, the composite is converted to a 1992=100 index.
To take advantage of all available information, we assemble all the components for the latest month available. This implies that January data for five of the components will be combined with the December value of the US leading indicator and the November data on manufacturing and retail trade. This new composite index, which will be published for the first time in February, would be called the composite index for January since the most components refer to this month. These components include the Toronto stock exchange, the money supply, employment in personal and business services, the average workweek in manufacturing from the labour force survey, and housing starts (the average workweek will be benchmarked to the data from the survey of employment, payrolls and hours after two months when this date becomes available, while the housing index will be revised to incorporate house sales when this data is published one month later).
The composite leading indicator and its ten components are smoothed so as to reduce erratic movements. Statistics Canada uses a 5-month moving average to reduce irregular fluctuations in the leading index. This smoothing allows users to better judge the true underlying signal of the course the economy is likely to take. Smoothing also reduces the effect of revisions that are inevitably made to most of the source data.
Quality evaluation
Data are analyzed for time series consistency and linked to current economic events.
Disclosure control
Statistics Canada is prohibited by law from releasing any information it collects that could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.
In order to prevent any data disclosure, confidentiality analysis is done using the Statistics Canada Generalized Disclosure Control System (G-Confid). G-Confid is used for primary suppression (direct disclosure) as well as for secondary suppression (residual disclosure). Direct disclosure occurs when the value in a tabulation cell is composed of or dominated by few enterprises while residual disclosure occurs when confidential information can be derived indirectly by piecing together information from different sources or data series.
Revisions and seasonal adjustment
Data for the five months preceding the reference month are subject to revision.
Data accuracy
The statistical accuracy of the indicators corresponds to the one of the source data and is considered by the users as highly reliable.
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