Trends & Issues
Moving forward with nonprofit labour market information
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Introduction
Since its inception in 2005, the HR Council for the Nonprofit Sector (HR Council) has been working on various labour issues relevant to nonprofits. One key interest of the HR Council is to improve the labour market information (LMI) available on and for nonprofits in Canada. Most recently, this has included a project entitled Developing Labour Market Information for the Nonprofit Sector. This project has led to the development of recommendations and goals for improving LMI for nonprofits. It also included an examination of existing data available on nonprofits and the possibilities for its further use. As with most national statistics and information, the majority of the currently available data comes from Statistics Canada. While finding LMI on nonprofits using business and labour surveys often proves difficult, the Canadian System of National Accounts provides data on these institutions. This report provides an overview of these data and recommendations about moving forward with data development based on the findings of the HR Council’s LMI project and the discussions of a stakeholder panel.
Background
Statistics Canada collects and distributes a wide variety of information on individuals, businesses and the economy as a whole. Despite the wide array of data that are produced, finding information on nonprofits can prove difficult. As nonprofits are distinguished by the type of organization and not the goods produced or the types of workers, they are not easily retrieved from within the larger data frameworks, including the North American Industrial Classification System (NAICS) for industrial data and the National Occupational Classification (NOC) for worker data.
Statistics Canada data on nonprofits stem from various sources. These include business and special surveys, and also the system of national accounts framework. Most prominent amongst these is the Satellite Account of Nonprofit Institutions and Volunteering, part of the Canadian System of National Accounts (CSNA). Within this account, and in line with the international guidelines for national accounts, Statistics Canada compiles information on nonprofit institutions serving households (NPISH). These data offer a potentially valuable source of nonprofit LMI, and were therefore considered worthy of further review and detailed analysis by the HR Council.
Canadian System of National Accounts Satellite Account of Nonprofit Institutions and Volunteering
The CSNA Satellite Account of Nonprofit Institutions and Volunteering was developed in 2001 to enable the CSNA to better track the contributions of nonprofits to the Canadian economy. The Satellite Account provides macro-level economic data for Canada as a whole, but also offers provincial breakdowns. As the system of national accounts and the satellite accounts provide a national portrait of economic activity, they measure gross domestic product (GDP), broken down by NAICS industry code. In addition, they provide information on the number of workers, hours worked and total wage bill that are used to feed Statistics Canada’s productivity estimates.
The Satellite Account offers information on the nonprofit sector as a whole, as well as information on hospitals, universities and colleges and on the core nonprofit sector. Information is also available on a subset of the core known as nonprofit institutions serving households (NPISH). To be included in the NPISH subset, a nonprofit must be:
- Resident in Canada (i.e., not a foreign entity)
- Operating as a nonprofit (i.e., providing no income to those that control them)
- Operating independent of government control (i.e., not owned by government and not directly controlled by the government through legislation, boards of management, etc.)
- Providing goods and/or services to households
- Providing services to households/individuals for free or for nominal rates
If a Canadian nonprofit does not meet one of these tests, it will be classified either to the government sector (if not independent of government control, as in the case of hospitals, nursing homes, colleges and universities) or to the corporate sector (if providing services to organizations or charging non-nominal fees for its goods/services). If the entity is a hospital or college or university, it will be captured in the corresponding category within the CSNA; other organizations will appear as nonprofits not elsewhere classified, or will not be disaggregated from the government sector.
Data organization
Within the CSNA, data on the core nonprofit sector are further subdivided by category based on the International Classification of Non-Profit Organizations (ICNPO). Data on the sector’s income and expenses for Canada as a whole are available on CANSIM, Statistics Canada’s data portal. Breakdowns are also available by subgroup within the Satellite Account. To illustrate the sub-categories available, as well as their relative size, the following table shows GDP for the nonprofit sector by category for 2009, as well as the share of GDP that each category represents.
Table 1: Gross domestic product of nonprofit institutions, 2009
Category |
GDP ($millions), 2009 |
Share of nonprofit GDP |
| Hospitals | 47,342 |
44% |
| Universities and Colleges | 23,641 |
22% |
| Core Nonprofit Sector | 35,405 |
33% |
|
21,680 |
20% |
|
13,725 |
13% |
| Total nonprofit sector | 106,388 |
100% |
The core nonprofit sector, by GDP, makes up one third of the total nonprofit sector. Of this, approximately two-thirds of organizations fall within the NPISH classification. NPISH organizations represent 20% (by GDP) of nonprofits.
Data availability within NPISH
Statistics Canada has made more detailed data available by NPISH classification code and, by special tabulation, by NAICS industry code. The NPISH classification codes offer data for religious institutions (NP1100), welfare organizations (NP1200), sports and recreation (NP1300), education (NP2000) and organizations not elsewhere classified (NP1900). With the exception of religious institutions, the NPISH codes each cover organizations in a wide array of industries, making detailed analysis by sector difficult in many instances. This is particularly the case for the NP1900 category, which includes 40% of NPISH nonprofits.
The more detailed NAICS breakdowns offer additional industrial detail at the NAICS S- (2 digit), M- (3 digit) and L- (4 digit) levels. The System of National Accounts will also undergo an historic revision in 2012 that will see these data fully disaggregated at the national level by NAICS industry, allowing a wide range of industries to be covered in the data. Of note, these data will be available by special tabulation only, and will be subject to the same suppressions for data confidentiality as other Statistics Canada data. This will improve data clarity and allow for more analysis in industries where there are many nonprofits. Within NPISH, for example, 34% of nonprofit employment is contained within a single NAICS code, namely NAICS 813A - Grant-Making, Civic, and Professional and Similar Organizations (1). Organizations in this category include grant-making institutions, social advocacy institutions, as well as unions. The improved disaggregation will allow for a more detailed and comprehensive analysis than is currently possible with the available data.
Data Utility and Applicability
To determine the value of the information provided by the CSNA and its utility to nonprofit organizations, one must consider both the information itself as well as the needs of end users. The audience for data on nonprofits is varied, including researchers, policy-makers, as well as nonprofit institutions. Each of these groups will have varying levels of expertise in working with data and will want the data for different applications. As such, determining a single “end use” is difficult. These groups do, however, have some shared needs and expectations regarding data on nonprofits that can be used to determine its relevance and value.
The National Survey of Nonprofit and Voluntary Organizations (NSNVO), conducted by Statistics Canada in 2003, has long been considered the benchmark by which the Canadian nonprofit sector is defined and understood. This can be attributed to the gap in data availability filled by the survey as well as the dearth of regularly available information of which end users are aware. While the information from the NSNVO report is now quite dated, the statistics contained therein are still frequently cited and constitute key knowledge about the sector for many. The NSNVO uses a broad definition of the sector, similar to the overall Satellite Account definition. According to the report(2), the sector includes nearly 69,000 organizations with paid employees and nearly 1.2 million workers, or more than 7% of the national labour force.
While data on NPISH are helpful, they are much narrower in scope than the NSNVO. As such, they represent a “partial” view of the nonprofit sector to many sector stakeholders. These data can be combined with the data on hospitals, colleges and universities, but this still leaves 13% of the total nonprofit sector (by GDP), that is one-third of the core nonprofit sector, unaccounted for. This is a sizable share of nonprofits, and represents the majority of nonprofits in some industries (e.g., housing and development). The organizations within this 13% share include nonprofits classified to the corporate sector as well as some nonprofits classified to the government sector, such as residential care facilities.
Chart 1: Total nonprofit sector, by GDP share, 2009
In order for Satellite Account data to be seen as relevant and useful by organizations and individuals within the nonprofit sector, more information needs to be made available on this segment of nonprofits. A detailed breakdown of all the data on nonprofits in the Satellite Account – representing all sectors detailed in the chart on the above – would help to complete the picture of the nonprofit sector and increase the relevance of the data for end users. This could be accomplished by publishing additional data tables on an annual basis and by providing more information about which organizations are covered in the category and which are not. As some nonprofit organizations (e.g., municipal museums, libraries, residential care facilities, etc.) may not be disaggregated from government services, these clarifications are especially important for those who wish to conduct analyses using CSNA data.
End user needs
While the above concerns regarding utility and applicability affect the overall use of the data, the stakeholder panel highlighted some issues that must be considered when determining the utility of the data for users. These concerns should shape the HR Council’s approach to publicizing and communicating the data to end users. In this case, end users may be individual, local nonprofit organizations or local groups supporting nonprofits (e.g., chambers of voluntary organizations, umbrella organizations representing nonprofits). Large, national nonprofits as well as regional groups – such as provincial labour groups, sector councils or governments – could also be included in this category, although these latter groups are likely better equipped than the smaller end users to identify relevant data and analyze and interpret it for their own use.
Detailed analyses
The CSNA Satellite Account of Nonprofit Institutions and Volunteering provides information by industry for Canada as a whole as well as breakdowns by province. These data are available at various levels of aggregation, with data available in five NPISH categories, as well as at the NAICS S- (2 digit), M- (3 digit) and L- (4 digit) levels. While these tables provide data and insight on nonprofits, sector users would find it helpful to have access to interpretation or analysis. The lack of interpretation currently offered presents a challenge for end users in the nonprofit sector, especially for smaller organizations; it also, however, represents an opportunity for researchers and analysts within the sector to work with the data, building and sharing knowledge and also capacity for data analysis with small organizations and new data users. As many nonprofits have little, if any, capacity to analyze data – and often do not use or interpret LMI on a regular basis – the information available is not useful to them.
In order to make the information more useful to the widest variety of end users, it needs additional analysis and interpretation. Ideally, this analysis would include information about how the NPISH and Satellite Account concepts “map” on to other understandings of the sector, such as the NSNVO. Some additional analyses that could be helpful in this respect include:
- comparing nonprofits across sub-industries or types (e.g., comparing nonprofits within specific NAICS codes or groups of codes, such as examining the specific industries that comprise the NP1200 – Welfare Organizations category)
- comparing different types of organizations – nonprofits, government and for-profit enterprises – in specific industries to examine similarities and differences between the organizations (e.g., organizational size, number of workers, average wages, funding sources, changes in these variables over time, etc.)
- examining the share of nonprofits in a given industry/sector over time to highlight trends
- comparing characteristics of the nonprofit sector – including its relative size and the number and size of organizations – by province, region or sub-provincial area if possible – to explore similarities, differences and trends between provinces and across Canada
These analyses could be done by Statistics Canada, by researchers at universities and colleges or by researchers and analysts working within the nonprofit sector. If Statistics Canada will not be conducting and publishing detailed analyses of the information, it is hoped that granular data could be made available to researchers, through Research Data Centres or through custom data tabulations, in order to facilitate the best possible use of the existing data.
Regional disaggregation
While national and provincial level information are useful for researchers and others working at a macro level, it has less applicability for organizations or researchers who wish to make detailed analyses or comparisons. These users would be better served with data at the sub-provincial level wherever possible. Regional data at the sub-provincial level is especially important for local communities and municipalities. At the sub-provincial level, regional data enables analysts to examine trends within provinces and between communities. In provinces with several large population centres, such as Ontario, Québec, British Columbia and Alberta, this would allow comparisons between communities and local detail.
Regional disaggregations would also allow the data set to be compared with granular local data, offering an opportunity for benchmarking and validation across data sources. Although data compatibility could be a concern (e.g., local data may not be organized according to NAICS category; geographic identifiers may be coded differently or not present; definitions of the sector may differ, etc.), the availability of CSNA data for local areas would open up new possibilities for comparisons and could be considered in the design of new research, studies and/or surveys.
While detailed data at a local level will not be an option for the territories and for provinces with smaller populations due to data confidentiality issues, additional detail would be welcome wherever possible and would increase the relevance and applicability of the data. Where suppressions and confidentiality become key concerns and severely limit the data, the possibility of making data available to researchers through the Research Data Centres program should be explored. Trade-offs between industrial detail and geographic detail could also be explored. Indeed, some users may be eager to receive data at a regional level even if they are aggregated up to the NAICS 2- or 3-digit level. The possibility of additional breakdowns, and the manner in which they could be accessed and used, requires further exploration.
Additional information
The data on NPISH can answer many questions about the nonprofit sector, but also leave some questions unanswered or in need of clarification. For the CSNA Satellite Account data to be most relevant and useful, it would be important to know the number of organizations represented in the classification, not just the number of employees and the sector’s GDP. Without this information, end users may have difficulty gaining an understanding of the size and scope of NPISH; for most, describing the sector’s size in terms of GDP provides a vague idea of the size and scope of the sector. While the share of GDP can give an outline of the basic size of NPISH, the ratio of GDP to organization size is not necessarily stable across nonprofits; additional measures of size would provide users with a better understanding of the sub-sector. This would also allow researchers and analysts to examine differences in size by number of employees and GDP, and also provide additional insights about the composition of nonprofits in specific areas.
As noted above, additional information on nonprofit institutions classified to the business and government sectors would also be extremely useful. This group, labeled as “Other Core” in the chart on page 4, represents 13% of GDP in the nonprofit sector, and one-third of GDP in the core nonprofit sector. A basic breakdown by industry, including total number of workers, hours and wages, and total number of organizations, would be extremely useful and would give users a better understanding of this group of nonprofits.
Opportunities for further data development
Some of the additional data products offered by Statistics Canada through the Annual Survey of Service Industries could be used as templates for further data development. Two such surveys – examining Heritage Institutions (Publication 87F0002X; CANSIM 361-0008 and 361-0027) and Performing Arts (Publication 87F0003X; CANSIM 361-0009 and 361-0029), provide statistics on nonprofit organizations. These surveys offer breakdowns of operating revenues and expenses, as well as data on the total number of employees and the total wage bill. In addition, a survey of residential care facilities (Publication 83-237-X; CANSIM 107-5501 to 107-5512) examines various characteristics of these facilities and includes some information on nonprofits(3).
These surveys, and other surveys conducted using the same templates, could provide an opportunity to learn more about nonprofits in narrowly defined NAICS categories. This information would be particularly appealing to the segments of the nonprofit sector that would be covered; as the sector is very broad, information targeted to particular sub-sectors may be more relevant to individual organizations than information about the nonprofit sector as a whole, or information on large, aggregated industrial classification groups that may have little in common with an individual organization.
Data development would be particularly welcomed for NAICS categories where there are significant numbers of nonprofits classified to the corporate sector. As nonprofits in these categories are often competing with corporations and businesses, having access to data on the entire industry - demarcated into government, business and nonprofit categories - could provide valuable information on the industry and the role that nonprofits and other types of organizations play in the marketplace. For example, comparisons could be particularly insightful in the areas of child day care (NAICS 624410) and development and housing (NAICS 5311); both of these categories contain significant numbers of nonprofits, but as the nonprofits in both categories tend to charge market rates (or, at a minimum, non-nominal fees) for services, they are considered out-of-scope to NPISH. Both industrial categories also include for-profit organizations and government-run organizations. As such, these data could generate rich comparisons of the similarities and differences between the various types of organizations. As the costs of creating and implementing these surveys are not insignificant and as the level of ongoing demand for these data may be low, Statistics Canada, in collaboration with the HR Council, could examine industries where these comparisons would be most effective. For example, areas of interest would include industries in which nonprofits make up the majority – or a significant proportion – of organizations, or industries in which nonprofits have seen significant growth. For these industries, Statistics Canada might consider adding surveys on an intermittent basis (e.g., bi-annually) if the demand for data is limited.
Conclusion
The data available through the Satellite Account of Nonprofit Institutions and Volunteering provides welcome insight into the nonprofit sector. As few existing data sources specifically identify nonprofit organizations or workers, any surveys or databases that can provide information on this sector have significant value and should be used to their full potential. Data from the Satellite Account have potential applications for research and are also a source of labour market information. In order to maximize their potential, however, the information and its value will need to be explained and publicized to potential users, including what the data are, how they are produced and how to access the information. In addition, although some analytic work has been completed, in order to ensure its fullest value is realized, the data will require some analysis and contextualization on an ongoing basis to engage users, especially those with little experience working with large-scale data sets; many individuals and small organizations are potential users of LMI, but require assistance in the form of analysis to interpret the information and make it relevant to their place in the sector.
While the CSNA and NPISH data in their current form can fill in part of the LMI picture, the data raise additional questions that can be addressed through changes in data presentation and reporting. First, additional information on nonprofits that are neither included in the NPISH, nor hospital, nor college and university categories would help to contextualize the information available and also fill gaps in knowledge for many nonprofits that are not represented in the existing categories; these nonprofits would thus be placed within the portrait of the larger nonprofit sector and also provided with the same level of data available to NPISH nonprofits. The overall applicability of the information could also be increased by providing information on the number of organizations included in NPISH and the core nonprofit sector; while measuring the sector by the number of workers and GDP do have value, many users will be able to gain a better understanding of the data if this measure is added to the current reporting. Users would also find the data more applicable if sub-provincial breakdowns are provided where possible to improve analysis for local areas within large provinces. Finally, additional analyses could shed light on trends within the nonprofit sector. Outside of the CSNA and NPISH, other Statistics Canada surveys and publications that identify nonprofits could be used as templates for examining specific sectors not well covered in the data currently available, such as child care and housing.
In short, the existing information offered by Statistics Canada, particularly that stemming from the Satellite Account, represents a starting place for developing a better picture of LMI for the nonprofit sector. These data can be built upon, both by Statistics Canada as well as by researchers working within and for the nonprofit sector, in order to expand the availability of data as well as the level of analysis offered to users. The HR Council also has a significant role to play as a catalyst, connecting organizations and end users with the information, as well as the tools – both analysis and support – that are required to use the data effectively. Over time, through both data development and stakeholder engagement, these data could become a strong source of LMI for nonprofits, a key source of information for researchers, and an analytic tool for policy-makers. It is hoped that further development and collaboration between Statistics Canada, the HR Council and the broader nonprofit community will see these data realize their full potential and fill a gap in the existing data framework to better serve the nonprofit sector.
Stakeholder panel
To review the data available on NPISH, examine its value and relevance for the nonprofit sector, and discuss how to incorporate these data into the HR Council’s efforts on LMI, experts within the sector were sought to offer their opinions and guidance. A stakeholder panel was constructed that included many of the core members of the LMI Advisory Committee that was assembled for the earlier phases of this project. Through their involvement with the earlier phases of the HR Council’s LMI work, these individuals have demonstrated both their knowledge of nonprofit LMI and their sensitivity to the LMI needs of nonprofit organizations and the sector in general.
The members included:
- Catherine Crucil – Program Manager, Labour Market Partnership, The Vancouver Foundation
- Peter Elson – Senior Research Associate, Mount Royal University
- Mike Grogan – Vice President, Programs and Operations, Calgary Chamber of Voluntary Organizations
- David Lasby – Director, Research, Imagine Canada
(1) Of note, the category NAICS 813A includes all the industries under NAICS 813 except NAICS 8131 – Religious Organizations, which are represented in their own NPISH category.
(2) Statistics Canada (2003) Cornerstones of Community: Highlights of the National Survey of Nonprofit and Voluntary Organizations. Ottawa: Statistics Canada.(3) Most data are not broken down by facility ownership status (e.g., proprietary, government, nonprofit), but these breakdowns are available as special tabulations by request.
