Motor vehicle body and trailer manufacturing;Canada;Seasonally adjusted at annual rates;Chained (2017) dollars (v65201344); from Cube 36100434: Gross domestic product (GDP) at basic prices, by industry, monthly

Gross Domestic Product is the unduplicated value of the goods and services produced (by a given industry) in the economic territory of a country or a region during a given period.

Series Attributes:

Unit and Multiplier:

Dollars, Millions

Frequency:

Monthly

Valuation Type:

Basic prices (value at)
The amounts receivable by the producer from the purchaser for a unit of a good or service produced as output minus any product tax payable, and plus any product subsidy receivable, by the producer as a consequence of its production or sale. It excludes any transport charges invoiced separately by the producer.

Seasonal Adjustment:

Seasonally adjusted Monthly GDP
A time series is said to be “seasonally adjusted” when it has been altered to remove predictable seasonal regularities due to normal variations in climate through the year, the schedule of religious, civic and other holidays, established social patterns such as the timing of the school year and other factors of this nature. Seasonally adjusted time series are usually adjusted for calendar effects also, as for example when one month has more working days (Mondays to Fridays) than another. Seasonally adjusted time series are smoother than time series that are not seasonally adjusted. At Statistics Canada most seasonal adjustment is accomplished using X-12-ARIMA method that was developed by the U.S. Census Bureau. Usage of moving averages is one of the basic principles behind the X12-Arima approach. Moving averages can be of different forms (e.g. three by three, three by five, centered). For this vector and for most contained in the monthly GDP table, “short” (i.e. three by three) centered moving averages are used. A shorter moving average, as opposed to a longer one (e.g. three by five), has the advantage of providing an earlier detection of the turning point in a series. However, it generally means that the tail end of the seasonally adjusted time series is prone to larger revisions as there are less data points to calculate the seasonally adjusted results, and therefore each of them has a relatively higher weight. Seasonal adjustment for this vector and for all other monthly GDP vectors is performed up to the last data point available (i.e. concurrent seasonal adjustment) rather than using advanced / projected seasonal factors for the most current periods. While trading day adjustment is also performed with each month’s data, forecasted trading day factors are used within the latest year.

Principal Data Sources:

Industrial Product Price Index (IPPI), Statistics Canada

Monthly Survey of Manufacturing (MSM), Statistics Canada

Methods:

Monthly GDP : Brief overview:

Monthly gross domestic product by industry data provides a current measure of economic growth at the national level for 198 individual industries and 89 aggregates.

For any given industry, the monthly GDP data is benchmarked to the annual supply and use tables (SUT) in volume terms up to the latest available SUT year. For the period following the most recent available SUT, as detailed information on the inputs and, to some extent, on the outputs is not always readily available, monthly GDP by industry can be estimated by holding the relationship between output and GDP by industry in volume terms constant from the latest available SUT year.

Monthly GDP data is compiled at the individual industry level and is estimated using either output projectors (e.g. deflated sales or revenues, deflated sales plus the change in inventories, quantities produced), input projectors (e.g. employment, number of hours worked) or, on occasion, a combination of both.

Monthly GDP: Detailed description of common portion:

Sections a to j below provide a description of the generic steps undertaken to compile GDP by industry for all the vectors, including information about revisions.

Specific methodological information about this vector / industry is provided thereafter.

a) Monthly GDP by industry : General compilation assumption
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Estimating GDP by industry on a monthly basis requires some assumptions, one of which is the following key one regarding the relationship between output and value added (i.e. GDP).

That is, the volume of value added generated from a given volume of output for a specific industry is believed to be constant over short periods of time, as major technological changes usually require some time to change this relationship significantly.

Current and constant price estimates of GDP by industry are derived annually within the framework of the SUT tables. For the years and months following the most recent SUT table, as detailed information by commodity on the outputs and inputs for all industries is not readily available, real GDP by industry can be estimated by holding the relationship between real gross output and real valued added constant.

b) Monthly GDP by industry : Industry concordance
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The monthly GDP estimates are currently prepared using the North American Industrial Classification System. The compilation of monthly GDP estimates is performed for 198 individual industries whereas it is done for 240 industries in the detailed annual SUT. Although both programs cover the entire economy, the monthly GDP program uses a slightly different level of industry in its process. Aggregating some industries together in the monthly GDP program is required given their relative small size and / or for the lack of reliable monthly information. An industry concordance between the monthly GDP program and the detailed Supply and Use tables exists.

c) Monthly GDP by industry : Market and non-market components
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Industries presented in the monthly GDP program contain a market and / or a non-market component. The market component is often referred to as the business sector whereas the non-market component is often called the non-business sector.

Market producers are establishments, all or most of whose output is market output. In contrast, non-market producers are establishments owned by government units or non-profit institutions serving households that supply goods or services free, or at prices that are not economically significant to households or the community as a whole. These producers may also have some sales of secondary market output whose prices are intended to cover their costs or earn a surplus: for example, sales of reproductions by non-market museums. Though governments and non-profit institutions serving households may have establishments undertaking market production, most of their activity will be undertaken on a non-market basis.

Though most industries presented in the monthly GDP program comprise establishments entirely belonging either to the market or the non-market component, a few industries include establishments from both. Examples are the “radio and television broadcasting industry”, the “education” industry and the “health and social assistance” industry.

d) Monthly GDP by industry : The projectors
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Monthly estimates of GDP by industry are projections, derived from a variety of output and/or input indicators. This projector-based approach is necessary because complete monthly information on outputs and intermediate inputs is not available. Constructing GDP as the difference between intermediate inputs and outputs requires data that are collected only by annual surveys, thus, the derivation of monthly value added must rely on a less comprehensive data base, usually provided by monthly surveys and/or administrative sources. Monthly surveys do not cover all commodities produced by a certain industry nor all producers of a certain commodity, and usually collect only scarce information on intermediate inputs. Nevertheless, monthly surveys and/or administrative sources do provide sufficient data on each industry to serve as suitable indicators of the monthly movement in outputs or inputs.

As stated above, the basic assumption underlying the projector method is that changes in outputs or inputs acceptably reflect growth rates in GDP. In volume terms, this assumption is reasonable since technological advances which permit a different amount of output to be produced from the same amount of inputs normally occur slowly.

The most frequently used projector/indicator is output. Generally, estimating changes in GDP in volume terms using output as indicator yields a close approximation to the change in GDP. Although the use of output as a single projector/indicator may lead to revised results if intermediate inputs in volume terms do not change in the same proportion as output in volume terms, in the absence of monthly information on intermediate inputs it has proven to be an acceptable method of estimating GDP in volume terms.

The output in volume terms can be based on deflated value of nominal output, that is nominal value deflated by one or more appropriate price indexes. This deflation type is used in the majority of the manufacturing, retail and wholesale industries. A more direct measure of volume of output is also used when available, that is physical quantity multiplied by a base year price. This approach is often used in the mining industries where sub-annual information on physical quantity produced / extracted is readily available. Approximately 63% of total GDP is derived based on indicators of output.

In some instances, labour input is chosen as an alternative projector/indicator (for example in industries where data on output might not be available or is of insufficient quality). Labour input is either the number of hours worked or the number of employees in the industry. For the most part, approximating changes in GDP by changes in labour input is subject to the same sort of assumptions and limitations that apply to using output as an indicator. Approximately 32% of total GDP is estimated based on labour input. It should be noted that, for a few industries, both output and labour input indicators are used in conjunction.

In a very few cases, an indirect approach is applied instead of a direct measurement of either outputs or inputs. An example is the truck transportation industry. Output by this industry is estimated based on gross revenues received from direct purchases of freight services by industries for intermediate use. Such expenditure by businesses is projected based on the movement in output of the consuming industries. The assumption is that the amount paid for truck transport is a fixed proportion of an industry's output. For a few exceptional cases where monthly information is scarce, related or general indicators are used. These various types of indicators account for approximately 5% of total GDP.

e) Monthly GDP by industry : Seasonal adjustment
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Please see section entitled “seasonal adjustment” for a description of the seasonal adjustment method (located above in this Web page)

f) Monthly GDP by industry : Annual benchmarks
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Estimates of GDP by industry in volume (real) terms provide a measure of economic growth of industries with the effect of price variations removed. Although the annual Supply and Use tables (SUT) and monthly estimates of GDP by industry are based on the same concepts, definitions and classification schemes, the methodologies underlying the two sets of statistics use different data sources and techniques.

The detailed SUT in volume terms, which provide the annual benchmarks for the monthly GDP, are produced using a double-deflation method, that is deflating the output and the intermediate inputs separately. The GDP, or value added, is calculated as the difference between the output and the intermediate inputs. The deflation is done at the goods and services (i.e. commodity) level, as opposed to at the industry level. The SUT in volume terms are calculated at the national level, on an annual basis only. They are available about two and half years after the end of the reference year; this is because of the delay in obtaining the needed source data and by the complex nature of producing such a detailed account. The data sources are typically annual surveys, censuses and / or administrative data.

For two full years and part of the third year following the most recent SUT and also for sub-annual (i.e. monthly) periods, the lack of applicable data, particularly data on intermediate inputs, precludes a detailed GDP calculation. Estimates of GDP in these periods are projections, that are essentially based on proxy indicators such as output, employment-based data or a combination of both. These indicators are usually obtained from monthly surveys and/or monthly administrative sources. As a result of using different data sources and methodologies, the annual volume of GDP from the SUT and the yearly totals from the independently produced monthly estimates are not initially identical.

However, for each of the industry and aggregates, this initial difference between the two sets of estimates is then eliminated by integrating the annual benchmark values into the monthly GDP estimates as soon as the most recent SUT become available. This blending process is called benchmarking. In other words, the monthly GDP estimates are statistically forced to equal to the annual SUT. The technique used to do so is the proportional Denton-Cholette quadratic minimization method. This method adjusts the monthly estimates to the annual values in such a way to preserve, as much as possible, the variation of the original monthly estimates while maintaining the annual constraint.

g) Monthly GDP by industry : Chaining
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Monthly GDP by industry data are chained volume estimates with 2012 as the reference year. This means that data for each industry and each aggregate are obtained from a chained volume index, multiplied by the industry's value added in 2012. As indicated, the monthly data are benchmarked to the annually chained Fisher SUT, up to the latest SUT year. For the period starting with the month after the latest SUT, the monthly GDP data are derived by chaining a fixed-weight Laspeyres volume index to the prior period. The fixed weights are industry prices from the latest SUT. The monthly GDP measure can therefore be seen as a hybrid volume measure, i.e. annually chained Fisher with a Laspeyres tail.

Monthly gross domestic product is also computed and published under the heading “constant prices”. Currently the base year for such constant prices estimates is 2012. This means that the estimates for each industry are obtained from a constant price volume index where the constant prices are from the year 2012. The monthly estimates, while first derived using 2012 fixed weights, are subsequently benchmarked to annually chained Laspeyres volume measures obtained from the supply and use tables in volume terms.

h) Monthly GDP by industry : Balancing adjustments
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On an occasional basis, adjustments to the results stemming directly from the general methodology may be required in order to arrive at the final / published monthly GDP-by-industry estimates. These adjustments are referred to as balancing adjustments. One, or more, of the following situations may warrant the use of an adjustment:

1) the concepts, definitions and coverage of the underlying source data are not in line with those being measured;

2) large variations in the source data cannot be fully explained and / or are not corroborated by related indicators;

3) lower than usual response rates in the source data;

4) known events, such as strike and production difficulties, are not appearing to be properly captured in the source data;

5) where it is strongly believed that the main compilation assumption of the fixed ratio of gross output to value added in volume terms should be modified;

6) for the overall harmonization / reconciliation of the economy-wide quarterly industry GDP measure with the volume measure of the quarterly expenditure-based GDP (see section below for more information).

i) Monthly GDP by industry : Harmonization with the quarterly Income and Expenditure-based GDP
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GDP can be compiled using 3 different approaches: the sum of final incomes (compensation of employees, gross operations surplus of corporations, etc.), the sum of final consumption expenditures (the typical C+G+I+X-M equation consisting of the consumer/household expenditures, government expenditures on goods and services, business and government investment in fixed capital, exports less imports), and the sum of value added by industry (ranging from the goods-producing industries such as agriculture, mining, construction and manufacturing to the service-producing industries such as retail-wholesale trade, finance and insurance, public administration). Although economic theory tells us that such approaches should yield the exact same result, the empirical / statistical situation is otherwise.

It should be noted that while the industry-based and expenditure-based GDP measures are compiled independently, the two measures share a significant amount of source data which bring an added measure of coherence to the two. It should also be noted that the monthly GDP industry measure is readily converted to a quarterly measure by aggregating the 3 months of any given quarter.

In addition to the statistical imperfections inherent in each program’s respective methodologies and data sources, there are additional reasons behind the difference in the behavior (i.e. variation) of the quarterly expenditure-based and industry-based GDP, including notably

1) Conceptual difference: the expenditure-based measure is valued at market prices while the industry one is valued at basic prices.

2) Statistical / methodological differences:

2a) Seasonal adjustment: most expenditure-based series are done quarterly (exports-imports of goods are the exception as it is performed monthly) while GDP-by-industry data is seasonally adjusted monthly.

2b) Different weights in the deflation process, i.e. previous quarter’s weights for expenditure-based GDP and latest Supply-Use Tables year’s weights for industry GDP.

The comprehensive validation and analysis process that takes place while compiling the industry and expenditure-based GDP will often reveal data inconsistencies and allow an occasion for their remediation. However, even after having addressed these statistical issues, balancing adjustments are, at times, required to bring the two overall measures closer.

j) Monthly GDP by industry : Revisions
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Estimates of monthly GDP by industry are subject to revisions. Revisions arise from updates to projectors (e.g. surveys, administrative sources like taxations statistics, employment), incorporating benchmark data (e.g. the annual supply & use tables), methodology changes / improvements, seasonal adjustment and reconciliation / harmonization with the quarterly measure of the expenditure-based GDP. More comprehensive revisions are also carried out on an occasional basis in order to incorporate new concepts and definitions and, less frequently, to implement a new reference year for the volume estimates. These comprehensive revisions are done in tandem with revisions conducted for the other macroeconomic accounts.

The revision policy for this vector and all the vectors contained in the monthly GDP table is as follows: to revise back to the previous year for the January to August reference months; for the September reference month, back to January of the fourth previous year; and for the October to December reference months, back to January of the current year.

Monthly GDP: MSM & IPPI-based projector:

For this particular industry / vector, the monthly GDP projector is based on output. The value of output in volume (real) terms is obtained as follows:

Manufacturing output in nominal prices for any given month is calculated by adding the monthly shipments together with the change in inventories of the goods in process (GIP) and the change in inventories of the finished products (FP). This information comes from the monthly survey of manufacturing (MSM).

The deflated output is arrived at by taking each component (shipments, change in GIP, change in FP) of the output in nominal prices and dividing it by relevant price indexes (deflators). These price deflators are built using price indexes from Statistics Canada’s Industrial Product Price Indexes (IPPI) program at the commodity level (currently as per the North American Product Classification System). Each commodity-based IPPI is weighted according to the weights calculated in the Supply and Use tables (SUT). Since the SUT are produced on a yearly basis, the weights attached to each IPPI are therefore updated accordingly. The weights are kept constant beyond the latest SUT year, until a new SUT is added. The weighted average of these IPPIs then forms the industry deflator that is used to deflate the shipment component in nominal prices calculated above for this vector. Deflators of closing inventories of GIP and FP are moving averages of the deflator for shipments. Deflators of opening inventories are equal to deflators of closing inventories in the previous month.

The table here shows the specific commodities (IPPs) used for this vector. Given that the list of commodities (and IPPIs used) can be quite long for each vector, we have limited ourselves to show only here the commodities (IPPIs) that, once combined, represent more than 80% of the industry output (the full list is used for compilation purposes)