Session Number: 6B
Session Title: Measurement of Government and
                     Other Non-Profit Organizations
Paper Number: 4
Session Organizer: Édith Archambault
Discussant: Jan van Tongeren

Paper prepared for the 26^th General Conference of
The International Association for Research in Income and Wealth
Cracow, Poland, 27 August to 2 September 2000

Extending the Satellite Account for Nonprofit Institutions

Helmut K. Anheier

For additional information please contact:

Helmut K. Anheier
Centre for Civil Society
London School of Economics and Political Science
Houghton Street
London
WC2A 2AE
Email: h.anheier@lse.ac.uk
Fax: +44 (0)20 7905 6039
Tel: +44 (0)20 7905 7360
This paper is placed on the following websites: www.stat.gov.pl
                                                                      www.econ.nyu.edu/dept/iariw

This paper is part of a wider effort to develop a Handbook on Nonprofit Institutions based on the 1993 System of National Accounts (SNA), and builds on the Anheier-Salamon proposal (1998) for a satellite account of nonprofit institutions. The consolidation of nonprofit institutions (NPIs) in a separate institutional sector will allow analysts to explore for the first time the actual importance, structure and development of NPIs within national economies both cross-nationally as well as over time. The various satellite tables that show aggregates and flows involving NPIs are very useful for comparative sector analysis, showing NPIs as a sector next to government, corporations and households. This opens up many questions that will be of great value to economists and policy analysts interested primarily in macro-economic and institutional sector comparisons.

For other analytic and policy-related purposes, however, it may well be necessary to extend the data coverage of the satellite account system beyond monetary representations of economic activity alone, and to include a range of other social and economic indicators. For example, data on employment in NPIs would add useful information for policy analysts interested in employment issues. Moreover, capacity measures for NPIs in fields like health care or education would aid the policy planning process, particularly given the wealth of other information that is part of the SNA and the satellite account.

The purpose of this paper is to present the conceptual outline for such an extension, and to identify major links with other statistical systems that could benefit from a better recognition of NPIs. We will do so in two ways. First, we explore the usefulness of an extended satellite system for the field of third sector research, a inter-disciplinary social science speciality at the intersection of economics, sociology and political science that looks at non-market/non-state organisations. Second, in the theoretical context of third sector studies and the possibilities offered by the satellite account, we suggest a series of data items and tables for further development. The overall aim is to examine how the satellite account can be linked to other data and information in different fields and countries, particularly to international statistical systems.

 The Field of Third Sector / Nonprofit Studies

The field of third, nonprofit or voluntary sector research has gained momentum in recent years (Powell, 1987; Anheier and Seibel, 1990; Ben-Ner and Gui, 1993; Evers and Svetlik, 1993; Salamon and Anheier, 1996). While much has been achieved, the field is really at the beginning of the systematic effort needed to describe and analyze more fully the role third sector organisations currently have in the delivery of education, health care, social services, culture and the arts and well as community development. This also includes the role of the third sector in terms of service provision, advocacy and social cohesion, and more generally, its relation to civil society. Moreover, we need to know how and why the role of nonprofit institutions varies across countries, and what role this set of institutions is likely to play in the future.

But before research can begin in a systematic way, a better conceptual mapping of the areas between the state and the market sectors is needed for the great variety of forms located between household, market and state: membership associations, community groups, clubs, service providers, foundations, self-help groups, and other types of nonprofit organisations. As a start, Salamon and Anheier (1997) suggest to focus on entities that are: (i) organized, i.e. possessing some institutional reality; (ii) private, i.e., institutionally separate from government; (iii) non-profit-distributing, i.e., not returning any profits generated to their owners or directors; (iv) self-governing, i.e., equipped to control their own activities; and (v) voluntary at least in part, i.e., involving some meaningful degree of voluntary participation, either in the agency's activities or management.

This mapping exercise, while usefully started, is by no means completed, and we need to develop better classification schemes and worry about definitional refinements that remain linked to, and compatible with, estabablished SNA classifications. The satellite account will most likely provide new impetus for such efforts as national income account specialists and policy analysts will develop improved procedures for identifying and classifying NPIs.

Once NPIs have been identified and grouped according to the conceptual and operational definition laid out in the satellite account, we can begin to explore some of the fundamental research problems with new rigour. Table 1 lists three questions that are central to the field of third sector research. Each can be addressed at the level of organisations, industries and economies:

• In terms of institutional choice, we need to know why nonprofit or third-sector institutions exist in the first place and what form they take in different countries. What are the rationales for such the choice of form, and how do theoretical expectations relate to reality?

• How do nonprofit institutions compare to alternative providers and forms in terms of efficiency, client base, and other aspects of organisational behavior?

• What are the implications and consequences of nonprofit forms in terms of equity and other distributional characteristics?

A number of theories have been proposed that explore at least some aspects of the “why” and “how” on nonprofit provision in general and in specific fields such as education, health and social services. In the past, lack of data has prevented fuller tests of these theories; however, with the satellite account in place, greater data availability will over time offer more and more systematic opportunities for theory testing in this field (see Salamon and Anheier, 1998):

• the heterogeneity theory, associated with the work of Weisbrod (1977; 1988) suggests that unsatisfied demand for services in situations of demand heterogeneity is related to the presence of nonprofit health providers. Countries with heterogeneous demand would have a larger nonprofit sector than countries with a more homogeneous demand.

The heterogeneity theory would suggest that the satellite account be extended to include information on the composition of the relevant population in terms of ethnic, religious, linguistic etc heterogeneity. Moreover, data are needed to estimate median and non-median demand for different types of public goods, and how the provision of these goods is reflected in public budget allocations and layouts.

• A variation of the heterogeneity argument, the supply-side theory, has been developed by James (1987), who suggests that ideologues and religious and social entrepreneurs use nonprofit establishments to maximize non monetary return. Accordingly, the greater ideological and religious competition in a country, the larger the third sector.

In additional to the data needed for the heterogeneity theory, the supply-side theory would require better information on ideological and religious competition as well as data on “occupational groups” such as clergy, politicians, fund-raisers or activists.

• The trust theory (Hansmann, 1980; 1987; 1996) and related to it, the stakeholder theory developed by Ben-Ner and Van Hommissen (1993) suggests that trust goods like services involve serious information asymmetries to the potential detriment of the customer. Third sector organisations are one solution to this problem, their nondistribution constraint and governance structure suggests “trustworthiness” (Hansmann, 1996).

The trust theories have high data requirements. Not only are measures needed to gauge levels of trust relative to different institutional options, the theory also requires measures of information asymmetry across different types of services. Finally, the theory leads us to look for legal indications of the nondistribution constraint.

• The interdependence theory formulated by Salamon (1987) sees the third sector not as the antithesis to government action; rather it states a complementary relationship between both sectors. Synergetic effects develop over time in the sense that both sectors can complement each other’s strengths and weaknesses.

The interdependence theory requires data on organisational founding and development over time, relative to changes in public budget allocations. Furthermore, the theory needs data on institutional synergies, i.e., welfare effects that arise from public-private partnerships.

• Finally, the social origins theory developed by Salamon and Anheier (1998) argues that the size, role and financing of the nonprofit sector depends on the type of welfare regime in a country. The nonprofit sector is seen as highly “path dependent” and part of a complex set of relationships among social classes, party politics, government regulations, and the influence of interest groups.

The social origins theory has the greatest data demand among the approaches introduced here. In addition to the data needed for the heterogeneity, supply-side and interdependence theories, it requires, at a minimum, information of social class compositions and strength, political mobilization, and public spending and revenue figures over time.

It becomes clear that the satellite account would provide the core data needed for theory testing in terms of size and structure. Indeed, the satellite account would offer the measures for the “dependent variable” or explanandum of each theory; yet, at the same time, more information is needed for the independent variables or explanans of each theory. To a large extent, these data requirements refer to

• Indicators of population characteristics (social composition, religion, ethnicity, voting, socio-economic status etc)
• Public budgets
• Information asymmetries
• Trust, and
• Social mobilisation

Of course, this list of theories is not exhaustive (see Anheier and Ben-Ner, 1997, for overview). Moreover, we need to keep in mind that very different conceptions of the third sector exist across countries. In Europe for example, there is the French notion of économie sociale, which brings the sector much closer to cooperatives and the communal economy (Archambault, 1996); the German concept of subsidiarity which emphasizes private social service provision and political decentralization (Anheier and Seibel, 2000; Zimmer, 1997; Rauschenberg et al, 1995); the Italian concept of associationalism (Barbetta, 1997); and the Swedish concept of broad-based movements which refers to local organising, community building and democratic inclusion (Lundstroem and Wijkstroem, 1997). Behind these concepts are specific state-society and third sector-economy relations and traditions (often in the sense of path dependencies) that need to be understood if we want to get a deeper understanding of institutional choice processes. For example, why do some countries respond to old and new challenges such as AIDS, unemployment or the environment by establishing public agencies, others quasi-public institutions, while others opt for private sector solutions, and others yet do not seem to respond at all?

It is here that data gaps matter most for future developments, both theoretically and in terms of policy analysis. Why is this the case? There are several reasons for this:

First, from a comparative, cross-national point of view, we find that third sector organisations are linked to strikingly different ideological orientations. For example, in the United States and Britain, the third sector is widely seen as an expression of individualism, whereas in Europe, particularly in the French tradition, this set of organisations is seen as a combined social force producing social solidarity and “sociability.” How can it be that the same type of organisation, providing similar services, produces different effects and social outcomes in the end? Moreover, general ideological currents in some countries, such as the United States traditionally and Britain in the 1980s particularly, posit a deep-seated opposition between the third sector and the state. By contrast, in countries like Germany, Sweden, Austria or the Netherlands, both government and nonprofit sector are seen more in symbiotic relationship with each other. What does it mean for the contributions of the third sector in a comparative perspective, when it is alternatively positioned in opposition to, or in close vicinity of, the state? Obviously, there is a need to explore the cultural and political embeddedness or context of third sector organisations.

Second, in trying to explain the existence and behaviors of nonprofit organisations, theories frequently identify characteristics that are attributes of both the input side and the output side of this set of organisations. For example, trust in nonprofit providers is treated as both an input and an output characteristic: people chose nonprofit organisations, because they are more trustworthy under conditions of information asymmetry than other providers (Hansmann, 1996), and nonprofit organisations produce trust in the course of their operations (Fukuyama, 1994; Putnam, 1993). Likewise, third sector organisations are both reflections and producers of heterogeneity (James, 1987) and diversity (Taylor, Langan and Hoggett, 1995), and the consumers and producers of social capital (Edwards and Foley, 1997). The major point is that the rationales for the existence and comparative advantage of third sector organisations involve both input and output characteristics. Available data, however, are largely limited to the input side. This makes it difficult to test theories more fully, and points to a need to collect data on outputs and their impacts more generally. Thus more and better data are needed on the “output side” generally.

Third, beyond comparative advantages associated with the nonprofit form, the literature frequently speaks of “unique characteristics” of nonprofit organisations--attributes and functions that neither government nor businesses can fulfil (Salamon et al, 2000; Kramer, 1987). Similarly, work on the role of nongovernmental organisations (NGOs) in the development process and in humanitarian assistance attributes several “unique” characteristics to nonprofit organisations (see Lewis, 1999). NGOs are assumed to be more in tune with indigenous cultures, and closer to the grass roots. They are seen as representatives of the powerless, engaged in community building, thereby enhancing the developmental capacities of third world societies (Fowler, 1997). By contrast, we also find attributions that see nonprofit organisations as elitist, inefficient, dilettante, premodern and otherwise “suboptimal” or “second-best” institutions when compared to the market and the state (see Seibel, 1993; 1996).

To what extent do these positive and negative characteristics attributed to third sector organisations apply generally, and to what extent do they vary across economies, societies and cultures that differ in their level of economic and social development? Thus there is a need to test the assumption that nonprofit organisations have “unique characteristics” and certain comparative advantages and disadvantages in a broad cross-section of settings. In this respect, the satellite account will make it possible to address the topic of third sector output, performance and impact with the help of three major questions:

Characteristics: Do third sector organisations have unique characteristics and make unique contributions to economy and society?

Advantages: Do they have comparative advantages and disadvantages relative to government and business?

Embeddedness: Does the cultural and political embeddedness of nonprofit organisations vary, to what outcome, and why?

For cross-national research, we suggest to approach these questions at the level of output, performance and impact:

Output: Output and capacity of third sector provision relative to government and corporate provision;

Performance: Efficiency and equity of third sector provision relative to government and corporations;

Impact: Distributional aspects of third sector provision; Contributions to solving social problems.

While the three basic questions indicate the theoretical reference of the research, the levels of analysis suggest that each question can be looked at from different aspects. When combined, they yield a conceptual tableau that circumscribes key aspects of a future research strategy on nonprofit sector output, performance and impact (Table 2).

Each cell of the tableau indicates what the main thrust of the research problem would be:

• The Output column describes the phenomena under study (“what”),

• The Performance column addresses the reasons underlying observed variations and commonalties (“why”), and

• The Impact column of Table 2 poses the “so what” question, i.e., the affects and consequences of both the phenomena themselves and those of possible alternatives.

The rows in Table 2 represent the particular theoretical interest that is brought to bear:

• Understanding third sector organisations as a unique form in terms of their output (“Characteristics”),

• Putting nonprofit organisations in contrast to other organisational form within a system of social division of labour that may vary cross-nationally (“Advantages”), and

• Exploring the broader social, cultural and political context in which third sector organisations operate.

Of course, the questions stated in the cells of Table 2 are at a fairly general level, and have to be reformulated in concrete research settings. For example, in a project on the contributions of NPIs to employment growth relative to other sectors, we could ask in Field C2: What is the contribution of NPIs to employment stability? Do NPIs have cyclical swings in employment, and do they dampen, offset, or amplify for-profit labour market cycles? How great are the affects of the nonprofit sector on income inequality?

 Extensions of the NPI Satellite Account

As suggested above, for some analytic and policy-related purposes, it may be useful to extend the data coverage of the satellite account system beyond monetary representations of economic activity alone, and to include a range of other social and economic indicators. The basic idea for the extension of the satellite account is presented in Figure 1. There are four basic “building blocks,” each combining a relatively distinct set of tables, variables and data that can be summarised as Structure, Capacity and Output, Clients and Users, and Impact and Performance. Specifically:

• The first block refers to size information largely in terms of input factors such as employment, volunteers, membership and giving.

• The second block deals with a different look at the size of the NPI sector, and includes data on output and capacity measures, and demand.

• The third block includes information on the client and users of NPI services and entities; and, finally,

• The fourth block has information on NPI impact and performance.

Each block will be initially specified in more detail below, although more work is needed to develop the set of tables and the variables included. Likewise, the full range of links to various tables in the satellite account will have to be worked out more fully. There are three types of links that need to be set up, as applicable:

• From the core NPI accounts to the extension blocks; e.g., from “compensation for employees etc” to employment tables;

• from the extension blocks to other statistical data systems; e.g., in the case of employment tables to ILO statistics;

• among the extension blocks themselves; e.g., from physical output like patient days to some efficiency measure.

Moreover, we need to sort out what data are available in one form or another in statistical systems, and what variables may need additional efforts in terms of data coverage and improved data quality. The initial list of variable topics listed below would ultimately lead to a set of tables that would report the variable for the NPIs as a whole and for the various classification systems like the ICNPO. Also note that the list of variables is not exclusive.

• Activity and functional classifications
• Size (turn-over or expenditure, FTE employment, volunteers, members)
• Tax exempt status
• Age of entity

• Activity and functional classifications
• Full-time and part-time, average hours worked
• Skill level (unskilled, semiskilled, skilled, professional, managerial); refer to standard international classification of occupations and professions
• Gender
• Age categories of employees
• Compensation and average wage Ž link to NPI/SNA (satellite account)
• Atypical forms of work
• Job security
• Form of remuneration

• Activity and functional classifications
• Educational standard
• Skill level of background occupation/job (unskilled, semiskilled, skilled, professional, managerial); refer to standard international classification of occupations and professions
• Gender
• Age categories of volunteers
• Combinations of paid and unpaid work
• Replacement wagesŽ  link to NPI/SNA
• Ratio of paid and unpaid work Ž  link to NPI/SNA

• Members and memberships by activity and functional classifications
• Skill level of member occupation/job (unskilled, semiskilled, skilled, professional, managerial); refer to standard international classification of occupations and professions
• Gender
• Age categories of members
• Income categories
• Membership duesŽ link to NPI/SNA

• Individual (more tables on givers by age, gender, class, etc
• Corporate
• Pooled and other (lotteries)
• Foundations
• Cross-border

1. Physical measures

• key output and capacity measures by activity classification etc

1. Share data (share of nonprofit supply/capacity relative to total in economy)

• same as above but across sector comparison; these tables offer information on supply by institutional sector in selected areas.

• comparison of demand and supply indicators for each ICNPO field, as applicable. The basic idea of this set of tables would be to offer information of supply/demand discrepancies. Example: What is the estimated demand for hospital beds, and how many of these will be met by nonprofits?

1. Client and User Profile

• Who are the clients/users of nonprofit services? These tables would report data on selected areas such as specific health and social services, culture and recreation, education etc that allow for meaningful client/user profiles by:

• Social background (income, age)
• Special needs (handicapped)
• etc

• How does the nonprofit client/user profile differ from that for other institutional sectors in the same field?

• Heterogenity measures for upolation and users/clients

• occupational statistics

• trust-related measures

• For the client/user profiles above, how does nonprofit provisions relate to estimated supply? We would select a limited number of fields that allow for useful and meaningful comparisons within ICNPO groups.

• How does the nonprofit demand/supply picture differ from that for other institutional sectors for the selected fields (information asymmetries)?

• The basic idea behind these tables is to report information on the question “Are those you use or receive nonprofit services more involved than those receiving forprofit and public services?”

• Representation
• Financial contribution
• Self-help
• Volunteering
• other

• The basic idea here is to report information on the question “Are those you using, volunteering or working for nonprofit entities more satisfied than those in the business or public sector?”

• Consumer satisfaction
• Employees satisfaction
• Volunteer satisfaction
• Member satisfaction
• Other…

 Impact and Performance

1. Input-output measures (Efficiency)

• Key input/output measures for each ICNPO field; the types of tables, measures and data would depend on what output and capacity measures we can get (see above); link needed to NPS/SNA for enumerator of input/output ratio.

• If possible, we should try to get these ratios also for other institutional sectors as well.

• The basic idea here is the link the input/output data with information of demand/supply ratios of some estimate of NEED. For example: if we have a highly efficient service provision but a significant supply shortfall, we would speak of low effectiveness.

• Redistributional aspects

• giving
• tax
• volunteering
• price discrimination
• etc

• Social inclusion

• groups reached as clients, users, members, volunteers in proportion to population share in selected ICNPO groups
• effects of membership overlap and organisational density across population groups for selected ICNPO fields
• Other…

• What is the share of NPIs in total number innovations in selected ICNPO fields relative to other institutional sectors?

• How fast are innovations adopted by NPIs in selected ICNPO fields relative to other institutional sectors?

• Other

 Next steps

Of course, this paper could do little more than sketch the way forward. The following steps are needed for a fuller development of the satellite account extensions:

1. Define, and expand on, the meaning of variables, indicators etc.
2. Assemble table shells and establish links with NPI satellite account and other statistical systems;
3. Systematic search of statistical systems for data on NPIs (actually reported or potential), e.g., explore the possibility of a global data locator relevant for NPIs;
4. Focus on output and capacity measures in the context of current scholarship and ongoing research activities;
5. Think creatively about Client/User measures and innovation data. These are new areas.
6. Decide on short term and long term priorities in extending the satellite system given the paucity of data on NPIs more generally.

 Table 1: Basic Third Sector Research Questions

 Table 2: Tableau for the Comparative Analysis of NPI Output, Performance and Impact

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