Income and Expenditure Accounts Technical Series

    Human Resource Module of the Tourism Satellite Account - A Pilot Study for Ontario

    Appendix D: Methodology

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    Step 1: Benchmark totals
    Step 2: Distribution of Canadian System of National Economic Accounts (CSNEA) data by full- and part-time status
    Step 3: Distribution of industry totals by occupation
    Step 4: Building the occupational time series
    Step 5: Smoothing the Labour Force Survey (LFS) data
    Step 6: Other adjustments

    The basic methodology consists of six steps:

    1. taking totals from the Canadian system of national economic accounts (CSNEA) for jobs, hours worked, and wages and salaries in Ontario
    2. disaggregating these totals, using data from the CSNEA for full-time and part-time jobs
    3. distributing the CSNEA totals for 2000 and 2005 across occupations, gender and age groups, and
    4. immigrant status based on census data
    5. building time series from these benchmarks based on movements in corresponding series from the Labour force survey (LFS)
    6. smoothing the time series for LFS occupations, while keeping the overall industry group totals making limited, final adjustments to data values.

    The following describes the methodology and implicit assumptions in more detail.

    Step 1: Benchmark totals

    The industry group totals for jobs, hours worked, labour income and wages and salaries, including the details by class of worker (employee or self-employed), by full- and part-time status, are from the Canadian Productivity Accounts (CPA) database.

    These data do not exactly meet requirements, however, and a number of adjustments are needed. In particular:

    1. The labour component of mixed income from self-employment is imputed by multiplying the hours worked in self-employment by the average hourly labour income per employee job. This method assumes that the self-employed and paid employees earn the same on average.1 However, the imputation is imposed at the lowest level of the CPA database, resulting in differences in earnings between self-employed and paid employees in tourism industry aggregates.
    2. The CSNEA jobs data follow the CSNEA version of North American Industry Classification System (NAICS), which is simply a special aggregation that defines the working level (W level) industries of the Input-Output Tables. At this level, detail is available only for two parts of accommodation services, traveller accommodation (NAICS 7211) and RV parks, recreational campgrounds and rooming and boarding houses (NAICS 7212 + NAICS 7213 = 721A at the W level). An adjustment is required to remove rooming and boarding houses. This is done using details from Survey of Employment Payroll and Hours (SEPH) on the industry's share of overall jobs, hours and earnings. These shares are used to adjust both employee and self-employment jobs. The same method is used to remove the non-tourism sub-industries of rail transportation (NAICS 4821), automotive equipment rental and leasing (NAICS 5321), food services and drinking places (NAICS 7220), performing arts, spectators and related industries (NAICS 7110) and amusement and recreation industries (NAICS 7131+ NAICS 7132 + NAICS 7139 = 713A at the W level).

    Step 2: Distribution of CSNEA data by full-time and part-time status

    Data from the CPA database in the CSNEA are used to split jobs, hours worked and income by full-time and part-time status.

    Step 3: Distribution of industry totals by occupation

    Information on the occupational distribution of jobs comes from the Census. Step 3 involves using this source to distribute the CSNEA totals by occupation, gender, age group and immigrant status.

    This step relates only to employee jobs, as occupational details are not developed for the self-employed. The Census of Population is used to distribute the industry group totals established in the second step for the years 2000 and 2005 (i.e., the reference years for the 2001 and 2006 Censuses).

    To develop occupational distributors for the industry group totals, special census tabulations are prepared, identifying persons in the tourism industries who had employment income in the reference year and were not self-employed. The selected persons are grouped according to their industry and whether they worked mainly full-time or part-time during the reference year. For each of these groups the distribution of the (weighted) sample by occupation is determined, as well as the distribution of total hours worked and wage and salary income.

    The occupational distributor for hours worked is based on the distribution of total hours (jobs multiplied by average hours worked) across occupations within each industry group.

    The occupational distributor for wages and salaries is based on the distribution of total wages and salaries (jobs multiplied by hours worked multiplied by hourly earnings) across occupations in each industry group.

    Step 4: Building the occupational time series

    Step 4 entails using the corresponding LFS annual average series by occupation, age group and gender to build a time series. Information on immigrant status while available from the LFS was not considered robust enough at the detailed level, and therefore the percentage distribution from the census reference years (2000 and 2005) is used. To take into account the change in the immigrant ratio between the two censuses, a linear interpolation is used. The LFS data are adjusted to the census levels to maintain growth rates between the census years.

    Step 5: Smoothing the LFS data

    Step 5 entails smoothing (using a four-year moving average) to reduce volatility in the occupational time series found in the LFS. It is implemented in a way that preserves the overall industry group totals (from the CSNEA) and the occupational distributions (from the 2001 and 2006 Census).

    A simple moving average is applied to the indicators (discussed in Step 3) used to build the time series on jobs, hours worked and wages and salaries, full-and part-time, by occupation and for each industry. A four-year moving average was judged to provide the best results overall in terms of reasonableness and consistency, reduced volatility, and minimizing the need for manual adjustments.

    Step 6: Other adjustments

    The last step in developing the total industry estimates involves adjustments when the smoothed series appear out of line or generate erratic movements in the implied average annual hours or average hourly earnings. More specifically, adjustments are made if hourly earnings are more than four times higher than the corresponding occupation average or less than half of the Ontario minimum wage or if hours reported are more than 70 hours a week.2 Results indicate that the smoothing and adjustments have little effect on the general pattern of the occupational distributions.


    1. This imputation includes supplementary labour income (SLI). The self-employed do not contribute to the majority of plans/programs included in SLI. The inclusion of SLI as part of labour income for self-employed will be reviewed in the next update.
    2. For details on Ontario minimum wage and standards for hours of work, see Ontario Employment Standards Act, 2000 and regulations 285/01 (sections 4 and 7) and 552/05 (section 2).
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