Trends & Issues
Employment trends in Non Profit Institutions Serving Households, 1997-2009
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Non Profit Institutions Serving Households (NPISH) is a subset of nonprofits that make up 22% of the nonprofit sector by GDP. NPISH includes organizations that do not generate profits for their owners, are independent from government and provide services to individuals for free or for nominal fees. The category does not include organizations in the broader nonprofit sector - hospitals, colleges and universities - and nonprofits that charge market rates for their services. The NPISH classification is used by Statistics Canada and by statistical agencies in other countries to compile information on the nonprofit sector.(1) Statistics Canada’s data show trends in nonprofit employment over time, both nationally and by province. This report examines national employment trends for the sector for the period 1997-2009.
The Canadian nonprofit sector is a key part of the national economy, providing communities and individuals with goods, programs and services, and also employing many individuals. The sector includes workers in health care; social services; education; sports and recreation; arts and entertainment; and religion, among other groups. Nonprofits enrich communities, provide important programs and services and represent an important economic sector.
Figure 1
Total employment, NPISH
Nonprofit employment represents a growing share of total employment in Canada. Using data on total employment for NPISH along with data on total employment in Canada from the Survey of Employment, Payrolls and Hours, we can examine employment trends over time. While the sector represented 2.8% of total employment in 1997, this grew to 3.6% by 2009. In fact, employment growth in the NPISH sector outpaced growth in the total workforce in six of the past ten years. In 1997, the first year for which data are available, there were 324,000 jobs in the Canadian nonprofit sector. By 2009, employment in the sector had grown by nearly two-thirds, to 528,580. Nationally, the sector has seen consistent growth year-over-year, although the pace of that growth varies considerably, from a high of 7.5% in 2003 to just 0.4% through the recession in 2009.
Figure 2
Total employment, SEPH and NPISH, and NPISH employment share
About the data
The data on the nonprofit sector used in this report come from the Income and Expenditure Division of Statistics Canada’s System of National Accounts Branch. The data measure productivity and gross domestic product for a segment of the nonprofit sector called Non Profit Institutions Serving Households (NPISH). Aggregate data on the sector can be found in the annual data release on the Satellite Account for Nonprofit Institutions and Volunteering (Catalogue #13-015-X), as well as in CANSIM table 383-0010.
Readers may notice that the NPISH employment estimates differ significantly from those emerging from the National Survey of Nonprofit and Voluntary Organizations (NSNVO), which was conducted in 2003, as the two sources define the sector differently. NPISH are a subset of nonprofits that make up approximately 22% of the total nonprofit sector by gross domestic product (GDP). This is a smaller share than the “core” nonprofit sector (All nonprofits except hospitals, colleges and universities), on which many past estimates have been based.
In addition to the NPISH data, the share of the total workforce was calculated using data from the Survey of Employment, Payrolls and Hours (SEPH). These data are available as a monthly, seasonally-adjusted series on CANSIM (table 281-0025).
Employment by NPISH category
To better describe the sector, the Statistics Canada data for NPISH are broken down into five subcategories: religious organizations; welfare organizations; arts, entertainment and recreation; other nonprofit; and educational services. Examining these categories allows for a better understanding of the sector’s component parts. Of note, the categories do not match neatly to the North American Industry Classification System (NAICS) codes that are commonly used to classify businesses and organizations in Canadian employment and productivity data; the categories, however, do provide a general breakdown of the sector.
Figure 3
Employment by NPISH category, Canada, 1997-2009
The figure above shows that the subcategories’ shares of total employment remain relatively stable over time. The large “other” category, which includes all nonprofits not elsewhere classified, has experienced consistent growth in the past 12 years and has the largest share of employment in all time periods. Employment is also increasing steadily in NP1200 – Welfare Organizations. In this group, employment more than doubled between 1997 and 2009, rising from 64,170 to 137,620. The following table provides a breakdown of sector employment by each subcategory.
Figure 4
NPISH employment by subcategory
Employment levels in NP1100 - Religious Organizations have fluctuated over the past 12 years. Employment dropped significantly between 2003 and 2005, by more than 7,500 jobs, before rebounding in 2006, adding 8,480 jobs and reaching an all-time high.
Provincial employment trends
While the national data give a broad picture of the nonprofit sector in Canada, regional data shed light on differences in the sector across the country. Nonprofit jobs are not spread equally among the provinces; some provinces have relatively high levels of nonprofit employment, while other provinces have smaller nonprofit sectors. Services that are delivered by nonprofits in some provinces are offered by government agencies or private, for-profit organizations in others. This is especially true in the Territories; nonprofit employment in the north represents only 0.15% of Canada’s nonprofit workers.
Figure 5
Employment by province/region, NPISH
Figure 6
Employment, Canada and Provinces, NPISH
As one might expect, the provinces with the largest nonprofit sectors also have the largest populations: Ontario, Quebec and British Columbia’s nonprofit sectors are all sizable. From the chart above, we can also see that growth in the sector has been uneven, with Ontario, Quebec and British Columbia experiencing more rapid growth than the other provinces. Nonprofits in Alberta have also grown rather quickly, but this growth has fluctuated over the past six years.
In 2003, there was a 7.5% increase in nonprofit employment nationally over the previous year’s levels; this growth was widespread, although Saskatchewan and British Columbia did not see large increases and nonprofit employment in Manitoba and the aggregated Territories fell slightly.
To explore provincial nonprofit employment in more detail, we can also examine regional trends in the share of nonprofit employment, or the percentage of all workers that are employed by NPISH organizations. The following table shows the NPISH share of total employment for Canada and the provinces, calculated as a percentage, using data from the Survey of Employment, Payrolls and Hours to determine the total number of jobs.
Figure 7
Employment share (%), Canada and provinces(2)
In the table, we can see that Manitoba and Saskatchewan, by share, have the largest NPISH sectors of all the provinces. Manitoba’s share has fluctuated over the years, but has hovered around 5% of provincial employment, with Saskatchewan’s just slightly lower, consistently remaining around 4%.
In Alberta, Quebec and the Atlantic provinces, however, the employment share is significantly lower. Alberta’s share remains below 3%, although the share briefly surpassed 3% in 2003. While the employment share in Quebec is one of the lowest, the share has shown consistent growth over the years, as has the employment share in the Atlantic Provinces. Ontario and British Columbia have also seen growth in nonprofit shares; the shares in both provinces increased by just less than 1% between 1997 and 2009.
Wage rates
As the NPISH data include measures for the total number of jobs, as well as hours worked and total compensation, an average nonprofit wage rate can be constructed from these series. The rates reported are an average for all nonprofit employees in the NPISH category and therefore should not be generalized to the wages paid for specific occupations or groups of workers; data subdivided by occupation is needed for these purposes, such as data from the Labour Force Survey or from other surveys capturing wages, benefits and compensation. When examining the wage data, keep in mind that many factors affect wage rates, including the characteristics of local labour markets, living costs, unionization rates, the levels of education and experience required for specific jobs.
Nationally, wage rates have increased steadily. Mirroring national trends in the economy as a whole, average wages are lower in the Atlantic Provinces, Manitoba and Saskatchewan than in the other provinces. Wages in the Alberta are the highest, followed closely by those in British Columbia and Ontario. This is also unsurprising as these provinces are amongst the largest in terms of population and also have higher living costs. In the case of Alberta, the high wage rates also reflect the high demand for skilled workers in the province.
Figure 8
Average wage rates, NPISH
Note that the data for the Atlantic Provinces show some high year-over-year rate fluctuations; these dramatic changes are largely the result of suppressions in the source data. If, for example, data for relatively higher paying jobs are suppressed in certain years, the overall average wage will decrease for that year, but will appear to rebound in years when these data are not suppressed. Aggregated data from the Territories have been excluded from this table because a significant number of suppressions in the source data render any average wage estimate unreliable.
1. For more information on NPISH, please consult Quick Facts on Non Profit Institutions Serving Households below.
2. Of note, data for the Territories are not included in the table as the SEPH data are only published for Yukon and the corresponding NPISH data set contains significant numbers of suppressions, limiting the validity of an estimate.
Quick facts on Non Profit Institutions Serving Households
What are Non Profit Institutions Serving Households?
Non Profit Institutions Serving Households (NPISH) is a classification of nonprofits that comes from Statistics Canada and the Canadian System of National Accounts. NPISH are a subset of nonprofits that provide services to individuals and families. To be included in the NPISH category, organizations must:
- Operate as nonprofits (i.e., not provide income to those that control them);
- Operate independent of government control;
- Provide goods and services to households; and
- Provide services for free or for nominal rates.
Measured by GDP, approximately 22% of nonprofits fit within the NPISH category. If a nonprofit does not fit within these criteria, it will be classified in the System of National Accounts as part of the corporate sector (13% of all nonprofits) or the government sector (65% of nonprofits).
Where do NPISH data come from?
Statistics Canada collects information from businesses and organizations on incomes and expenditures (including organizations’ incomes and expenditures and data on production) for the Canadian System of National Accounts (CSNA). The CSNA is based on an international standard that guides how countries report measures of economic activity. The data collected include information on employment, hours worked and compensation, allowing Statistics Canada to calculate worker productivity.
The CSNA includes a Satellite Account on Nonprofit Institutions and Volunteering that aims to improve our understanding of the value of nonprofit organizations. NPISH data are one set of data used in the Satellite Account. Labour statistics from the account are produced by Statistics Canada and compiled in data table 383-0010 on CANSIM, the agency’s database of socioeconomic statistics.
Why is this information important?
Information on the nonprofit workforce is difficult to find. While Statistics Canada collects a wealth of information on businesses and workers, few studies and surveys specifically mention or identify nonprofits. The existing, well-known measures of employment released by Statistics Canada, including the Labour Force Survey (LFS) and the Survey of Employment, Payrolls and Hours (SEPH), do not differentiate nonprofit organizations from other organizations. While the LFS separates workers into “private” and “public” sectors, nonprofit is not an option. Because these systems do not reflect the nonprofit sector, finding relevant data on nonprofits is more difficult than for other sectors of the economy that are differentiated from one another by the type goods and services produced instead of organizational characteristics.
Why is the NPISH sector so much smaller than previous nonprofit employment estimates?
NPISH employment estimates differ significantly from previous employment estimates for the nonprofit sector, including those emerging from the National Survey of Nonprofit and Voluntary Organizations (NSNVO). This survey, which was conducted in 2003, estimated total nonprofit sector employment for that year at 2,031,744. The Satellite Account NPISH data, on the other hand, show an employment estimate of 438,045 for 2003. These estimates, while vastly different, can both be valid and accurate because the two sources define the sector differently. NPISH are a subset of nonprofits that make up approximately 22% of the total nonprofit sector by GDP. The NSNVO data, on the other hand, include the entire nonprofit sector; taking 22% of this figure gives a rough employment estimate of 446,984, just 2% different from the employment figure in the NPISH data and well within the acceptable margin of error for surveys.
What can we do with the NPISH data?
The NPISH data allow us to learn more about the nonprofit sector. They can help us see changes in the sector’s health in terms of jobs and economic contribution. The data indicate the pace of growth by region and by sub-sector.
NPISH data can also be used to better understand trends in nonprofit employment and wages over time. The data set starts in 1997 and is currently available to 2009, providing 12 years of observations. No other data source offers this span of national data on nonprofits. The data are also broken down provincially and by industry code, allowing for in-depth examinations of the nonprofit sector by region, industry, or both.
The data can be compared with data from the Survey of Employment, Payrolls and Hours (SEPH), Canada’s largest and most well-known business survey. Comparing NPISH and SEPH data allow us to determine how nonprofits are faring vis-à-vis the larger economy. Comparing trends in employment and wages by industry and by province helps to demonstrate the relative health of the sector, make comparisons between provinces and examine conditions over time.
What can’t we do with NPISH data?
NPISH data do not cover all nonprofits. Organizations in the government and corporate sectors are not included. NPISH data do not provide breakdowns beyond the provincial level. Therefore, the data are not helpful for examining conditions in local labour markets or in regions within large provinces.
NPISH data are available at several levels of detail based on industry code. There are three levels available: S-level, M-level and L-level. These levels provide increasing amounts of detail on industries, for example, separating ‘Other Services’ at the S-level into religious organizations; grant-making, civic and professional organizations; and personal and laundry services and private households. These more detailed data, however, may be suppressed to meet Statistics Canada’s confidentiality requirements as outlined in the Statistics Act. While the suppressions are minimal in data for Canada as a whole and for the largest provinces, they severely limit the data available in the smaller provinces.
The NPISH wage data are available by industry, not job or employment classification. Therefore, these data should be interpreted with caution as they do not reflect narrow, well-defined groups of employees, like those seen in the national Labour Force Survey and in wage and benefit surveys.
