Social Impact Investing

SOCIAL IMPACT INVESTMENT: BUILDING THE EVIDENCE BASE
Box 6.4. Satellite Account on Non-Profit Institutions
The Satellite Account on Non-Profit Institutions (NPIs) was introduced to respond to a growing non-profit sector
that was not taken into account in the agreed System of National Accounts (SNA 1993). The Handbook (UN, 2003)
provides guidance regarding the identification of all NPIs, in particular through a clear definition of NPI, the valuation of
volunteer work and by introducing a classification system for NPIs based on their function. The need for improved data
coverage — insofar as there were no incentives for NSOs to collect data on NPIs — and the increased policy
relevance, were also key motives for developing this system.
There are a number of distinctive characteristics in NPIs that required a specific statistical approach, different
than the applied to corporations and governmental units. Some of these characteristics, such as the revenue structure,
capital sources or tax treatment, can also be found in SII. By classifying NPIs into 12 group types (see Table A.6.1,
Annex) and providing a system for categorising revenues and expenses as well as volunteer work, donations, as well
as non-market output, the Satellite Account for NPIs provides a harmonised framework for mapping the NPI sector.
Also, it provides data on the extent to which foundations fund other parts of the non-profit sector such as health or
research
For the case of SII, it would be important to highlight the measurement of non-market output. While the traditional
SNA measures output through sales revenue. For the case of some NPIs and SII, part of the output will not be
measured this way and output will be undervalued. This is particularly the case if an organisation has a significant
portion of its revenue coming from donations and other non-sales types of revenue. The measurement approach does
not attempt to value non-market output. Instead, the valuation of non-market output is based on the difference between
costs and sales. If negative the non-market output will be zero, if positive it will be equal to the difference between
sales and costs. Even though this approach is not optimal, it provides a practical solution to the measurement issue.
Source: UN (2003).
6.4.3. Surveys
6.46 The most direct source of data is to conduct surveys of key actors in the market. Surveys can be
very resource-intensive, but provide extremely rich information if well designed and implemented. The
first step in a survey process is to identify key SII players — social enterprises, investors or intermediaries,
depending on the SII component under analysis. This is challenging, since depending on the type of survey
respondent, greater detail and data granularity can be achieved.
6.47 Recently, the OECD carried out a survey of Social Economy Organisations (SEOs), understood
as organisations with non-profit objectives, operating in 14 different regions, corresponding to 8 countries
(OECD 2013g). The geographical scope was limited, but the results insightful. The survey was answered
by 655 SEOs and revealed that, on average, SEOs finance themselves mostly through internal resources —
i.e. their “profit”\cash generating ability — (31.8%) and subsidies (30.6%). In addition, as the level of
detail increases, so do survey costs. 28
6.48 Second, survey design is crucial for efficiently and effectively achieving the objectives of the
analysis. In designing surveys, it is important to reach the right balance between the amount of information
requested and simplicity — i.e. respondents may feel less encouraged to complete the survey if it becomes
too complex and time consuming. Also it is important to consider sampling frames to be able to know what
part of the population is being surveyed (ensure representativeness). To date, most surveys on SII have
focused on selected networks of key market players in certain geographies and therefore it is not clear
whether the data is representative of the population.
28 . Sample size varied by region (between 16 and 145 SEOs). Response rates where unknown in many regions
due to lack of information on the number of surveys distributed. Where available, response rates varied
between 6.4% and 17.7%.
94 © OECD 2015