Regional Level Predictor Variables (Level2 and Level3)

The set of predictor variables at Level2 (regional level) and Level3 (country level) concerns the measurement of the socio-economic framework conditions of the region in which social enterprises in the SELUSI dataset operate. This study may be subject to potential endogeneity which may arise because the growth rates (employment growth, revenue growth and / or social impact growth) of social enterprises per region are likely to be affected by some of the regional variables, for instance changes in the level of GDP per capita or an increase in the poverty rate. This issue will be addressed by lagging the socio-economic and institutional variables at regional and country level by one year.

Determinants of social enterprise growth are differentiated between supply and demand factors: The supply of social entrepreneurship is characterised by the regional socio-economic context. In other words, the capacity of social enterprises to respond to unsolved social needs depends on favourable (economic) conditions in the region which allow social enterprises to draw on essential resources, such as funding, an entrepreneurial culture, social capital and voluntary activities within society (Sharir & Lerner, 2006; Hynes, 2009; Estrin et al., 2011;

Buckingham et al., 2012). In order to capture a culture which encourages entrepreneurship at regional level and national level, the variable commercial entrepreneurship rates in 2008 is introduced (Hypothesis 1). This data collected from GEM is based on the Adult Population

Survey (APS)¹⁰⁰. Moreover, as access to informal capital is essential in the process of social enterprise expansion (Scarlata, 2010), informal capital rates in 2008 at regional and national level are added to the analysis (Hypothesis 2). The source of this term is GEM and it is also based on the APS. Social capital is the network of relationships that underpins economic partnerships and alliances. These networks depend upon a culture of cooperation, fostered by trust (Colemann, 1988; Putnam, 1996). Hence, social capital will be proxied by the indicator social trust at regional level (Hypothesis 3), obtained from The World Values Survey¹⁰¹. In addition, social enterprises require cooperation and voluntary activity to operate. In this context, the supply of voluntary activities, e.g. the dimension of the non-profit sector, plays an important role in the development of social entrepreneurship. Therefore, the size of the non-profit sector is included in the analysis, and is measured as the percentage of GDP generated by non-profit institutions (e.g. associations and charities) in 2008 at country level (Hypothesis 4). This information is provided by Eurostat.

However, it should be stressed at this point that the measurement of the size and economic value of the non-profit sector constititutes a major challenge (Salamon et al., 2011). Based on its role in society and its impact it is clear that voluntary activity makes an essential contribution to an economy’s output. However, this contribution is often overlooked in national statistics. Government statistical offices rarely gather data on the non-profit sector and when they do, they often do not report it separately (Salamon & Anheier, 1996). In 2003, the United Nations Statistics Division introduced a handbook on Non-Profit Institutions (NPI) in the system of national accounts calling on national statistical agencies to incorporate data on volunteer work (United Nations, 2003). So far, 31 countries have agreed to implement the handbook and to develop accounts on non-profit institutions and volunteering.

According to Salamon (2010), one of the initial findings of the United Nations NPI handbook is the fact that the civil society sector accounts on average for 5% of the GDP in the countries covered, and exceeds 7% in some countries, such as Canada and the United States.

100 To be precise, this present study uses commercial entrepreneurship rates which comprise the ‘new business rate’ (business has been paying income, such as salaries or drawings, for more than 3, but not more than 42 months) as well as the ‘established businesses rate’ (business has been paying income for more than 42 months).

101: The variable ‘social trust’ reflects the percentage of respondents who answer that “Most people can be trusted” (alternatives being “Need to be very careful” and “Don’t know”) to the question: “Generally speaking, would you say that most people can be trusted or that you can’t be too careful in dealing with people?”. See:

http://www.wvsevsdb.com/wvs/WVSData.jsp?Idioma=I [Accessed: 14 February 2013].

Eurostat reports the net value added of non-profit institutions to national GDP in the European sector accounts¹⁰². Non-profit transactions are disclosed in the account “Non-Profit Institutions Serving Households” (NPISH). NPISH makes up an institutional sector in the context of national accounts consisting of non-profit institutions which are not mainly financed and controlled by the government and which provide goods or services to households for free or at prices that are not economically significant. Examples include churches and religious societies, sports and other clubs, trade unions and political parties.

NPISH are private, non-market producers which are separate legal entities. Their main resources, apart from those derived from occasional sales, are those from voluntary contributions in cash or in kind from households in their capacity as consumers, from payments made by general governments and from property income. Nevertheless, up to now there is no data available for the sub-national level. Hence, this analysis will only include data at country level.

Demand for social entrepreneurship is determined by a combination of factors, including characteristics of the welfare state and adverse societal conditions. Social enterprises bear the responsibility of responding to social needs by addressing poverty and (potential) social exclusion. Thus, the regional indicator risk of poverty (Hypothesis 5) is used, which corresponds to the sum of citizens whose income was below the annual national at-risk-of poverty threshold in 2008¹⁰³. Often, adverse social conditions emerge as a consequence of diminishing public social services. In this context, recent studies indicate that a smaller state sector creates demand for social entrepreneurship (Leadbeater, 1997; Mair & Marti, 2009;

Estrin et al., 2011). To proxy the size of the public sector the regional factor expenditure of public health (Hypothesis 6) is introduced, derived from Eurostat’s information on governments’ spending on health per capita in 2008. Not only the size of government but also the quality of government, proxied by strong institutions bound by the rule of law, affect social enterprise behaviour. According to the literature, weak institutions create a ‘void’ that social entrepreneurs use as an opportunity to develop their enterprises (Mair & Marti, 2009;

Dacin et al., 2010; Estrin et al., 2011). To test the institutional void theory, the variable rule

102 See: http://epp.eurostat.ec.europa.eu/statistics_explained/index.php/Glossary:Non-profit_institutions_serving_households_(NPISH) [Accessed: 28 January 2013].

103 Eurostat (2010): The annual national at-risk-of poverty threshold is set at 60% of the national median income per equivalent adult.

of law (Hypothesis 7) shall be added to the analysis at regional and country level, which is amassed from The Quality of Government Institute at University of Gothenburg¹⁰⁴.