Self-employment as atypical or autonomous work: diverging effects on political orientations

Self-employment as atypical or autonomous work: diverging effects on political orientations Abstract It is often held that the self-employed are an economically conservative, political right-wing class. Previous studies, however, have primarily dealt with self-employed workers as a relatively monolithic social class with shared interests as entrepreneurs and (potential) employers. But, with its recent rise, self-employment has developed into a heterogeneous employment type, with a growing number of dependent and precarious self-employed. In this article, the political preferences of people in self-employment are compared to the preferences of employees on temporary contracts. In doing so, hypotheses are tested from both classic theories on class voting, as well as theories on job precariousness and labor market vulnerabilities. For this purpose, European Social Survey Round 4 (ESS-4) data on eight West European countries are analyzed. The findings suggest that particular segments of self-employment share the characteristics of other forms of ‘atypical’ work, not only with respect to labor market insecurities, but also regarding the political orientations associated with such insecurities. 1. Introduction Labor market risks and job precariousness are increasingly identified as new lines of political division ( Iversen and Soskice, 2001 ; Mughan, 2007 ; Rehm, 2011 ; Corbetta and Colloca, 2013 ). People on permanent employment contracts are often defined as the ‘insiders’ at the labor market, whereas—together with the unemployed—people in atypical employment are seen as the so-called ‘outsiders’ ( Rueda, 2005 ; Emmenegger, 2009 ). Although all forms of employment relationships deviating from ‘standard’ full-time and permanent employment can be considered ‘non-standard’ or ‘atypical’ (e.g. part-time, fixed-term, agency work or self-employment), most studies concentrate upon the division between permanent and temporary employees. Temporary workers, compared with permanent workers, are often entitled to fewer social and labor rights, while being exposed to higher labor market risks ( Kalleberg, 2000 ). Recent studies addressing the effects on political preferences have therefore suggested that temporary workers are more supportive of redistribution policies and other social benefit programs, and are more likely to support (new) left-wing parties ( Corbetta and Colloca, 2013 ; Marx and Picot, 2013 ; Marx, 2014 ). In this article, I extend the research into the political effects of atypical work by focusing on self-employment. Although self-employment is often seen as a form of atypical work ( Stanworth and Stanworth, 1995 ; Pernicka, 2006 ; Schulze Buschoff and Protsch, 2008 ), two opposing views exist on how self-employment relates to political preferences. The dominant approach to these relationships relies on classic class-based theories that differentiate petty bourgeois/employer classes from employee classes ( Evans, 1999 ; Knutsen, 2006 ; Jansen, 2011 ; Evans and de Graaf, 2013 ). Based on their socioeconomic position, the self-employed are considered to be a relatively homogeneous social class with shared interests as entrepreneurs and (potential) employers. A common feature of class theories is the assumption that self-employment differs from paid-employment because it allows for greater individual autonomy in work, and it increases both the rewards and the costs of working on one’s own account ( Arum and Müller, 2004 , p. 6). They would prefer ‘free markets and a low level of social protection because they depend on flexible labor markets and often on relatively low-paid workers’ ( Iversen and Soskice, 2001 , p. 883). Taking individual responsibility for risks and returns associated with market changes, self-employed are assumed to oppose redistribution policies and collective security arrangements ( Iversen and Soskice, 2001 ; Emmenegger, 2009 ). Hence, class-based studies that treat the self-employment as a social grouping that is distinct from that of paid-employees, usually arrive at the conclusion that the self-employed are an economically conservative, political right-wing class. This general picture is confirmed by the frequencies in Table 1 on right-wing voting behavior in Europe, between 2001 and 2011. These data from the Comparative Study of Electoral Systems (CSES) suggest that in many European countries the tendency to vote right-wing was higher among voters in self-employment relative to voters in wage-employment. Moreover, the frequencies—although to be interpreted with some caution due to relatively low numbers of self-employed in the CSES data—suggest that about two-third or more of all voters in self-employment casted a ballot for a party on the right of the political spectrum. Table 1. Right-wing voting behavior by employment type in Europe, 2001–2011 †   Election  Employed  Self-employed  Austria  2008  51.7 ( N =402)   73.8 ( N =72)   Belgium  2003  65.2 ( N =800)   91.6 ( N =105)   Denmark  2001  61.8 ( N =682)   88.6 ( N =114)   Finland  2011  62.2 ( N =399)   73.5 ( N =44)   France  2007  47.1 ( N =702)   65.9 ( N =63)   Germany  2009  47.4 ( N =661)   65.6 ( N =59)   Greece  2009  37.6 ( N =217)   41.1 ( N =80)   Italy  2006  46.8 ( N =103)   57.7 ( N =32)   Netherlands  2010  46.1 ( N =778)   60.0 ( N =133)   Norway  2009  52.4 ( N =934)   78.4 ( N =97)   Portugal  2002  51.1 ( N =372)   64.6 ( N =78)   Spain  2008  31.4 ( N =1832)   45.5 ( N =176)   Sweden  2006  47.4 ( N =612)   72.2 ( N =72)   Switzerland  2011  56.0 ( N =894)   73.0 ( N =199)   UK  2005  51.9 ( N =281)   53.1 ( N =37)     Election  Employed  Self-employed  Austria  2008  51.7 ( N =402)   73.8 ( N =72)   Belgium  2003  65.2 ( N =800)   91.6 ( N =105)   Denmark  2001  61.8 ( N =682)   88.6 ( N =114)   Finland  2011  62.2 ( N =399)   73.5 ( N =44)   France  2007  47.1 ( N =702)   65.9 ( N =63)   Germany  2009  47.4 ( N =661)   65.6 ( N =59)   Greece  2009  37.6 ( N =217)   41.1 ( N =80)   Italy  2006  46.8 ( N =103)   57.7 ( N =32)   Netherlands  2010  46.1 ( N =778)   60.0 ( N =133)   Norway  2009  52.4 ( N =934)   78.4 ( N =97)   Portugal  2002  51.1 ( N =372)   64.6 ( N =78)   Spain  2008  31.4 ( N =1832)   45.5 ( N =176)   Sweden  2006  47.4 ( N =612)   72.2 ( N =72)   Switzerland  2011  56.0 ( N =894)   73.0 ( N =199)   UK  2005  51.9 ( N =281)   53.1 ( N =37)   † Selection based on respondents in employment who participated in the election and casted a valid vote; demographic and political weights applied (if available). Source:Comparative Study of Electoral Systems (2015a , b , Modules 2, 3); data for Spain are based on the Spanish National Election Study series election survey of 2008 ( CIS, 2008 ), own calculations. Right wing is defined based on the party classification of the Comparative Manifesto Project, i.e. including Liberal, Christian, Conservative, Nationalist and Agrarian parties. View Large Table 1. Right-wing voting behavior by employment type in Europe, 2001–2011 †   Election  Employed  Self-employed  Austria  2008  51.7 ( N =402)   73.8 ( N =72)   Belgium  2003  65.2 ( N =800)   91.6 ( N =105)   Denmark  2001  61.8 ( N =682)   88.6 ( N =114)   Finland  2011  62.2 ( N =399)   73.5 ( N =44)   France  2007  47.1 ( N =702)   65.9 ( N =63)   Germany  2009  47.4 ( N =661)   65.6 ( N =59)   Greece  2009  37.6 ( N =217)   41.1 ( N =80)   Italy  2006  46.8 ( N =103)   57.7 ( N =32)   Netherlands  2010  46.1 ( N =778)   60.0 ( N =133)   Norway  2009  52.4 ( N =934)   78.4 ( N =97)   Portugal  2002  51.1 ( N =372)   64.6 ( N =78)   Spain  2008  31.4 ( N =1832)   45.5 ( N =176)   Sweden  2006  47.4 ( N =612)   72.2 ( N =72)   Switzerland  2011  56.0 ( N =894)   73.0 ( N =199)   UK  2005  51.9 ( N =281)   53.1 ( N =37)     Election  Employed  Self-employed  Austria  2008  51.7 ( N =402)   73.8 ( N =72)   Belgium  2003  65.2 ( N =800)   91.6 ( N =105)   Denmark  2001  61.8 ( N =682)   88.6 ( N =114)   Finland  2011  62.2 ( N =399)   73.5 ( N =44)   France  2007  47.1 ( N =702)   65.9 ( N =63)   Germany  2009  47.4 ( N =661)   65.6 ( N =59)   Greece  2009  37.6 ( N =217)   41.1 ( N =80)   Italy  2006  46.8 ( N =103)   57.7 ( N =32)   Netherlands  2010  46.1 ( N =778)   60.0 ( N =133)   Norway  2009  52.4 ( N =934)   78.4 ( N =97)   Portugal  2002  51.1 ( N =372)   64.6 ( N =78)   Spain  2008  31.4 ( N =1832)   45.5 ( N =176)   Sweden  2006  47.4 ( N =612)   72.2 ( N =72)   Switzerland  2011  56.0 ( N =894)   73.0 ( N =199)   UK  2005  51.9 ( N =281)   53.1 ( N =37)   † Selection based on respondents in employment who participated in the election and casted a valid vote; demographic and political weights applied (if available). Source:Comparative Study of Electoral Systems (2015a , b , Modules 2, 3); data for Spain are based on the Spanish National Election Study series election survey of 2008 ( CIS, 2008 ), own calculations. Right wing is defined based on the party classification of the Comparative Manifesto Project, i.e. including Liberal, Christian, Conservative, Nationalist and Agrarian parties. View Large Yet, an alternative approach to self-employment is emerging. Studies that put self-employment under the umbrella of atypical work generally relate self-employment without employees (or ‘solo’ self-employment) to higher labor market risks and more precarious employment positions. The emphasis is often on the so-called ‘new self-employed’ who are assumed to work on the border of self-employment, dependent-employment and unemployment; a group that is believed to be growing due to the flexibilization of labor markets. The risks of people in solo self-employment are considered to be comparable to the risks of people in temporary employment. Compared with ‘standard employees’, self-employed workers would be exposed to higher risks because they often do not build up pension entitlements, and are underinsured with respect to healthcare, labor disability and professional liability ( Schulze Buschoff and Schmidt, 2009 ; Dekker, 2010 ; Pedersini and Coletto, 2010 ). In this perspective, rather than autonomous, stable and voluntary, self-employment is often dependent, precarious and involuntary, and leads to fundamentally different predictions regarding political preferences than does the traditional class-based approach. To date, however, this alternative perspective of self-employment received little to no attention in studies into political attitudes. Therefore, the contribution of this study is two-fold. First, I will discuss the composition of self-employment in Western Europe using aggregate-level data from Eurostat’s Labor Force Surveys. By mapping recent changes in the occupational and sectoral structure of self-employment, I will emphasize the heterogeneity of this employment type. This section serves to challenge the traditional notion in political sociology of the self-employed as a homogeneous social class. Second, using individual-level data from the fourth round of the European Social Survey ( ESS Round 4, 2008 ), I will compare the effect of solo self-employment on political preferences to the effect of temporary employment. The comparison of temporary employment to self-employment provides a deeper understanding of how labor market risks are associated with political divisions. While both are considered ‘atypical’ forms of employment, they may lead to very different preferences regarding welfare protection and political parties. Therefore, I will study under what conditions self-employment and temporary employment might be associated with similar political preferences. By accounting for the fact that different ‘segments’ of self-employment involve different levels of labor market security and/or autonomy, I test whether the traditional notion of the self-employed as a conservative, political right-wing category holds for self-employment types that are more precarious than class theories maintain. Ultimately, this article aims to answer the following research question: (a) To what extent does solo self-employment have a different effect on political preferences compared temporary employment and (b) to what extent is this effect conditioned by degree of labor market security and autonomy? 2. Self-employment heterogeneity in Europe The traditional class-based approach to self-employment is increasingly problematic to understand political orientations. Bögenhold and Staber (1991) and Arum and Müller (2004) have argued that the notion of petty bourgeois and employer entrepreneurship does not suffice in contemporary labor markets. For large segments of self-employment, it is problematic to perceive their interests in terms of employership because employership is rarely the standard ( Millán et al. , 2014 ; Van Stel et al. , 2014 ). Figure 1 shows the level of self-employment as percentage of total employment in the (former) EU-15, Norway and Switzerland in 2004 and 2014, broken down by self-employment with and without employees. Although the level of self-employment varies considerably among countries (ranging from 6% in Norway to over 30% in Greece), all countries have one feature in common: the majority of people in self-employment generally do not employ others. Moreover, in about half of the countries in Figure 1 , self-employment has increased over the last decade, mainly due to a rise in self-employment without employees. Figure 1. View largeDownload slide Self-employment with and without employees as percentage of total employment in Europe, 2004–2014. Source: Eurostat, EU Labour Force Survey (2004, 2014), own calculations. Figure 1. View largeDownload slide Self-employment with and without employees as percentage of total employment in Europe, 2004–2014. Source: Eurostat, EU Labour Force Survey (2004, 2014), own calculations. The social class perspective tends to overlook the heterogeneity of self-employment ( Arum and Müller, 2004 ; Bögenhold and Fachinger, 2012 ). Research suggests that there has been an erosion of the ‘old’ forms of self-employment. In many advanced economies, formerly prevailing types of self-employment (farmers and the petty bourgeois of small proprietors and shop owners) would have declined since the 1980s ( Arum and Müller, 2004 ). People in these ‘classical’ types would generally sell goods instead of services, and work in economic sectors such as the retail or wholesale industry and in agriculture. Despite this decline, there has been an emergence of (solo) self-employment in new occupational types; causing a ‘partial renaissance’ ( OECD, 2000 , p. 188) of self-employment in various advanced economies. Arum and Müller (2004) show that this growth occurred among low-skilled, but in particular among high-skilled occupations. The changing structure of self-employment therefore follows general processes of occupational upgrading and polarization (cf. Oesch, 2015 ). Contrary to the classical types, people in the ‘new’ types of self-employment would increasingly not sell goods, but instead rely on selling services based on their own labor power, and work in business or other service industries ( Kösters et al., 2013 ). To illustrate the diverse and changing nature of self-employment, Table 2 shows the composition of self-employment in European countries, broken down by five sectors of economic activity 1 over a 20 year period (i.e. 1994/1995, 2004 and 2014). The aggregate statistics for the EU-15 are summarized in Figure 2a . In all countries, there is a downward trend in agricultural self-employment. And in most countries also the share of self-employed working in wholesale or retail and in the hotel and restaurant industry has declined since the 1990s. At the same time, there is a clear increase in self-employment in the service-oriented industries, in particular regarding business services. In countries such as Germany (57%), the UK (58%), the Netherlands (61%) and Luxembourg (67%), the vast majority of the self-employed now works in service industries. Figure 2. View largeDownload slide Self-employment in Europe (EU-15), 1995–2014 (in percentage). (a) By economic activity †a,b‡ . (b) By occupational group §c . † 1995, 2004 NACE Rev.1: Agriculture (sections A, B); Industry (sections C–F); Wholesale/Retail/Hotels (sections G, H); Business Services (sections I–K); Other Services (sections L–Q). ‡ 2014, NACE Rev.1: Agriculture (sections A); Industry (sections B–F); Wholesale/Retail/Hotels (sections G–I); Business Services (sections H–N); Other Services (sections O–U). § ISCO-08: Managers (ISCO 1); Professionals (ISCO 2–3); Low-skilled Non-Manual (ISCO 4–5); High-skilled Manual (ISCO 6–7); Low-skilled Manual (8–9). Source: Eurostat, EU Labour Force Survey (1995, 2004, 2014), own calculations. Figure 2. View largeDownload slide Self-employment in Europe (EU-15), 1995–2014 (in percentage). (a) By economic activity †a,b‡ . (b) By occupational group §c . † 1995, 2004 NACE Rev.1: Agriculture (sections A, B); Industry (sections C–F); Wholesale/Retail/Hotels (sections G, H); Business Services (sections I–K); Other Services (sections L–Q). ‡ 2014, NACE Rev.1: Agriculture (sections A); Industry (sections B–F); Wholesale/Retail/Hotels (sections G–I); Business Services (sections H–N); Other Services (sections O–U). § ISCO-08: Managers (ISCO 1); Professionals (ISCO 2–3); Low-skilled Non-Manual (ISCO 4–5); High-skilled Manual (ISCO 6–7); Low-skilled Manual (8–9). Source: Eurostat, EU Labour Force Survey (1995, 2004, 2014), own calculations. Table 2. Self-employment by economic activity in Europe, 1994–2014 (in percentage)   1994 †  2004 †  2014 ‡    1994 †  2004 †  2014 ‡  Austria        Luxembourg         Agriculture    28.6  23.3  Agriculture  21.9  18.4  12.0   Industry    14.4  13.3  Industry  9.6  13.2  3.6   Wholesale/Retail/Hotels    20.4  20.1  Wholesale/Retail/Hotels  42.5  28.7  15.0   Business Services    20.7  25.8  Business Services  12.3  22.8  41.3   Other Services    16.0  17.4  Other Services  13.7  16.9  28.1  Belgium        Netherlands         Agriculture  11.7  9.4  5.4  Agriculture  18.9  13.0  6.7   Industry  18.0  18.6  19.4  Industry  12.7  16.9  14.6   Wholesale/Retail/Hotels  36.7  33.2  25.2  Wholesale/Retail/Hotels  27.2  21.0  17.8   Business Services  15.4  20.4  29.5  Business Services  19.0  26.2  34.5   Other Services  18.2  18.4  20.5  Other Services  22.2  22.7  26.4  Denmark        Norway         Agriculture  23.9  17.9  11.7  Agriculture    26.4  16.8   Industry  21.1  19.2  18.9  Industry    20.1  20.1   Wholesale/Retail/Hotels  22.7  23.7  18.0  Wholesale/Retail/Hotels    14.1  10.8   Business Services  19.7  22.9  31.4  Business Services    18.9  26.9   Other Services  12.6  16.3  19.9  Other Services    20.5  25.4  Finland        Portugal         Agriculture    25.6  19.2  Agriculture  29.4  28.0  22.4   Industry    18.1  19.8  Industry  21.7  25.6  19.1   Wholesale/Retail/Hotels    18.6  15.3  Wholesale/Retail/Hotels  31.9  29.1  30.2   Business Services    20.7  26.1  Business Services  8.2  9.1  16.4   Other Services    16.9  19.5  Other Services  8.8  8.1  12.0  France        Spain         Agriculture  24.5  21.6  15.0  Agriculture  21.9  14.1  9.6   Industry  20.8  21.4  18.9  Industry  23.3  25.3  18.9   Wholesale/Retail/Hotels  26.4  25.4  21.4  Wholesale/Retail/Hotels  34.9  33.5  36.0   Business Services  12.6  13.2  21.7  Business Services  12.9  18.8  23.4   Other Services  15.7  18.3  23.0  Other Services  7.0  8.3  12.1  Germany        Sweden         Agriculture  10.9  7.5  5.1  Agriculture    12.2  9.1   Industry  22.3  20.3  19.6  Industry    21.2  21.3   Wholesale/Retail/Hotels  46.6  23.7  18.5  Wholesale/Retail/Hotels    23.9  19.7   Business Services  7.2  25.4  31.3  Business Services    28.5  32.6   Other Services  13.0  23.1  25.4  Other Services    14.3  17.3  Greece        Switzerland         Agriculture  33.1  26.8  31.3  Agriculture    16.4  14.3   Industry  19.0  18.4  12.1  Industry    19.5  15.6   Wholesale/Retail/Hotels  29.8  31.6  28.2  Wholesale/Retail/Hotels    18.7  17.4   Business Services  11.6  14.9  18.2  Business Services    23.5  29.6   Other Services  6.5  8.2  10.2  Other Services    21.9  23.2  Ireland        UK         Agriculture  40.6  26.0  21.3  Agriculture  7.5  4.9  3.8   Industry  16.8  25.5  20.7  Industry  33.5  30.0  26.0   Wholesale/Retail/Hotels  22.2  17.9  15.8  Wholesale/Retail/Hotels  22.3  16.7  11.5   Business Services  11.4  18.6  27.3  Business Services  20.9  26.5  33.9   Other Services  9.0  12.0  14.9  Other Services  15.8  21.9  24.7  Italy                 Agriculture  13.3  7.4  6.2           Industry  26.2  25.0  21.7           Wholesale/Retail/Hotels  37.4  31.3  29.8           Business Services  12.6  22.7  27.3           Other Services  10.5  13.7  14.9            1994 †  2004 †  2014 ‡    1994 †  2004 †  2014 ‡  Austria        Luxembourg         Agriculture    28.6  23.3  Agriculture  21.9  18.4  12.0   Industry    14.4  13.3  Industry  9.6  13.2  3.6   Wholesale/Retail/Hotels    20.4  20.1  Wholesale/Retail/Hotels  42.5  28.7  15.0   Business Services    20.7  25.8  Business Services  12.3  22.8  41.3   Other Services    16.0  17.4  Other Services  13.7  16.9  28.1  Belgium        Netherlands         Agriculture  11.7  9.4  5.4  Agriculture  18.9  13.0  6.7   Industry  18.0  18.6  19.4  Industry  12.7  16.9  14.6   Wholesale/Retail/Hotels  36.7  33.2  25.2  Wholesale/Retail/Hotels  27.2  21.0  17.8   Business Services  15.4  20.4  29.5  Business Services  19.0  26.2  34.5   Other Services  18.2  18.4  20.5  Other Services  22.2  22.7  26.4  Denmark        Norway         Agriculture  23.9  17.9  11.7  Agriculture    26.4  16.8   Industry  21.1  19.2  18.9  Industry    20.1  20.1   Wholesale/Retail/Hotels  22.7  23.7  18.0  Wholesale/Retail/Hotels    14.1  10.8   Business Services  19.7  22.9  31.4  Business Services    18.9  26.9   Other Services  12.6  16.3  19.9  Other Services    20.5  25.4  Finland        Portugal         Agriculture    25.6  19.2  Agriculture  29.4  28.0  22.4   Industry    18.1  19.8  Industry  21.7  25.6  19.1   Wholesale/Retail/Hotels    18.6  15.3  Wholesale/Retail/Hotels  31.9  29.1  30.2   Business Services    20.7  26.1  Business Services  8.2  9.1  16.4   Other Services    16.9  19.5  Other Services  8.8  8.1  12.0  France        Spain         Agriculture  24.5  21.6  15.0  Agriculture  21.9  14.1  9.6   Industry  20.8  21.4  18.9  Industry  23.3  25.3  18.9   Wholesale/Retail/Hotels  26.4  25.4  21.4  Wholesale/Retail/Hotels  34.9  33.5  36.0   Business Services  12.6  13.2  21.7  Business Services  12.9  18.8  23.4   Other Services  15.7  18.3  23.0  Other Services  7.0  8.3  12.1  Germany        Sweden         Agriculture  10.9  7.5  5.1  Agriculture    12.2  9.1   Industry  22.3  20.3  19.6  Industry    21.2  21.3   Wholesale/Retail/Hotels  46.6  23.7  18.5  Wholesale/Retail/Hotels    23.9  19.7   Business Services  7.2  25.4  31.3  Business Services    28.5  32.6   Other Services  13.0  23.1  25.4  Other Services    14.3  17.3  Greece        Switzerland         Agriculture  33.1  26.8  31.3  Agriculture    16.4  14.3   Industry  19.0  18.4  12.1  Industry    19.5  15.6   Wholesale/Retail/Hotels  29.8  31.6  28.2  Wholesale/Retail/Hotels    18.7  17.4   Business Services  11.6  14.9  18.2  Business Services    23.5  29.6   Other Services  6.5  8.2  10.2  Other Services    21.9  23.2  Ireland        UK         Agriculture  40.6  26.0  21.3  Agriculture  7.5  4.9  3.8   Industry  16.8  25.5  20.7  Industry  33.5  30.0  26.0   Wholesale/Retail/Hotels  22.2  17.9  15.8  Wholesale/Retail/Hotels  22.3  16.7  11.5   Business Services  11.4  18.6  27.3  Business Services  20.9  26.5  33.9   Other Services  9.0  12.0  14.9  Other Services  15.8  21.9  24.7  Italy                 Agriculture  13.3  7.4  6.2           Industry  26.2  25.0  21.7           Wholesale/Retail/Hotels  37.4  31.3  29.8           Business Services  12.6  22.7  27.3           Other Services  10.5  13.7  14.9          † Nomenclature statistique des Activités économiques dans la Communauté Européenne (NACE) Rev.1: Agriculture (sections A, B); Industry (sections C–F); Wholesale/Retail/Hotels (sections G, H); Business Services (sections I–K); Other Services (sections L–Q). ‡ NACE Rev.1: Agriculture (sections A); Industry (sections B–F); Wholesale/Retail/Hotels (sections G–I); Business Services (sections H–N); Other Services (sections O–U). Source: Eurostat, EU Labour Force Survey (1994, 2004, 2014), own calculations. View Large Table 2. Self-employment by economic activity in Europe, 1994–2014 (in percentage)   1994 †  2004 †  2014 ‡    1994 †  2004 †  2014 ‡  Austria        Luxembourg         Agriculture    28.6  23.3  Agriculture  21.9  18.4  12.0   Industry    14.4  13.3  Industry  9.6  13.2  3.6   Wholesale/Retail/Hotels    20.4  20.1  Wholesale/Retail/Hotels  42.5  28.7  15.0   Business Services    20.7  25.8  Business Services  12.3  22.8  41.3   Other Services    16.0  17.4  Other Services  13.7  16.9  28.1  Belgium        Netherlands         Agriculture  11.7  9.4  5.4  Agriculture  18.9  13.0  6.7   Industry  18.0  18.6  19.4  Industry  12.7  16.9  14.6   Wholesale/Retail/Hotels  36.7  33.2  25.2  Wholesale/Retail/Hotels  27.2  21.0  17.8   Business Services  15.4  20.4  29.5  Business Services  19.0  26.2  34.5   Other Services  18.2  18.4  20.5  Other Services  22.2  22.7  26.4  Denmark        Norway         Agriculture  23.9  17.9  11.7  Agriculture    26.4  16.8   Industry  21.1  19.2  18.9  Industry    20.1  20.1   Wholesale/Retail/Hotels  22.7  23.7  18.0  Wholesale/Retail/Hotels    14.1  10.8   Business Services  19.7  22.9  31.4  Business Services    18.9  26.9   Other Services  12.6  16.3  19.9  Other Services    20.5  25.4  Finland        Portugal         Agriculture    25.6  19.2  Agriculture  29.4  28.0  22.4   Industry    18.1  19.8  Industry  21.7  25.6  19.1   Wholesale/Retail/Hotels    18.6  15.3  Wholesale/Retail/Hotels  31.9  29.1  30.2   Business Services    20.7  26.1  Business Services  8.2  9.1  16.4   Other Services    16.9  19.5  Other Services  8.8  8.1  12.0  France        Spain         Agriculture  24.5  21.6  15.0  Agriculture  21.9  14.1  9.6   Industry  20.8  21.4  18.9  Industry  23.3  25.3  18.9   Wholesale/Retail/Hotels  26.4  25.4  21.4  Wholesale/Retail/Hotels  34.9  33.5  36.0   Business Services  12.6  13.2  21.7  Business Services  12.9  18.8  23.4   Other Services  15.7  18.3  23.0  Other Services  7.0  8.3  12.1  Germany        Sweden         Agriculture  10.9  7.5  5.1  Agriculture    12.2  9.1   Industry  22.3  20.3  19.6  Industry    21.2  21.3   Wholesale/Retail/Hotels  46.6  23.7  18.5  Wholesale/Retail/Hotels    23.9  19.7   Business Services  7.2  25.4  31.3  Business Services    28.5  32.6   Other Services  13.0  23.1  25.4  Other Services    14.3  17.3  Greece        Switzerland         Agriculture  33.1  26.8  31.3  Agriculture    16.4  14.3   Industry  19.0  18.4  12.1  Industry    19.5  15.6   Wholesale/Retail/Hotels  29.8  31.6  28.2  Wholesale/Retail/Hotels    18.7  17.4   Business Services  11.6  14.9  18.2  Business Services    23.5  29.6   Other Services  6.5  8.2  10.2  Other Services    21.9  23.2  Ireland        UK         Agriculture  40.6  26.0  21.3  Agriculture  7.5  4.9  3.8   Industry  16.8  25.5  20.7  Industry  33.5  30.0  26.0   Wholesale/Retail/Hotels  22.2  17.9  15.8  Wholesale/Retail/Hotels  22.3  16.7  11.5   Business Services  11.4  18.6  27.3  Business Services  20.9  26.5  33.9   Other Services  9.0  12.0  14.9  Other Services  15.8  21.9  24.7  Italy                 Agriculture  13.3  7.4  6.2           Industry  26.2  25.0  21.7           Wholesale/Retail/Hotels  37.4  31.3  29.8           Business Services  12.6  22.7  27.3           Other Services  10.5  13.7  14.9            1994 †  2004 †  2014 ‡    1994 †  2004 †  2014 ‡  Austria        Luxembourg         Agriculture    28.6  23.3  Agriculture  21.9  18.4  12.0   Industry    14.4  13.3  Industry  9.6  13.2  3.6   Wholesale/Retail/Hotels    20.4  20.1  Wholesale/Retail/Hotels  42.5  28.7  15.0   Business Services    20.7  25.8  Business Services  12.3  22.8  41.3   Other Services    16.0  17.4  Other Services  13.7  16.9  28.1  Belgium        Netherlands         Agriculture  11.7  9.4  5.4  Agriculture  18.9  13.0  6.7   Industry  18.0  18.6  19.4  Industry  12.7  16.9  14.6   Wholesale/Retail/Hotels  36.7  33.2  25.2  Wholesale/Retail/Hotels  27.2  21.0  17.8   Business Services  15.4  20.4  29.5  Business Services  19.0  26.2  34.5   Other Services  18.2  18.4  20.5  Other Services  22.2  22.7  26.4  Denmark        Norway         Agriculture  23.9  17.9  11.7  Agriculture    26.4  16.8   Industry  21.1  19.2  18.9  Industry    20.1  20.1   Wholesale/Retail/Hotels  22.7  23.7  18.0  Wholesale/Retail/Hotels    14.1  10.8   Business Services  19.7  22.9  31.4  Business Services    18.9  26.9   Other Services  12.6  16.3  19.9  Other Services    20.5  25.4  Finland        Portugal         Agriculture    25.6  19.2  Agriculture  29.4  28.0  22.4   Industry    18.1  19.8  Industry  21.7  25.6  19.1   Wholesale/Retail/Hotels    18.6  15.3  Wholesale/Retail/Hotels  31.9  29.1  30.2   Business Services    20.7  26.1  Business Services  8.2  9.1  16.4   Other Services    16.9  19.5  Other Services  8.8  8.1  12.0  France        Spain         Agriculture  24.5  21.6  15.0  Agriculture  21.9  14.1  9.6   Industry  20.8  21.4  18.9  Industry  23.3  25.3  18.9   Wholesale/Retail/Hotels  26.4  25.4  21.4  Wholesale/Retail/Hotels  34.9  33.5  36.0   Business Services  12.6  13.2  21.7  Business Services  12.9  18.8  23.4   Other Services  15.7  18.3  23.0  Other Services  7.0  8.3  12.1  Germany        Sweden         Agriculture  10.9  7.5  5.1  Agriculture    12.2  9.1   Industry  22.3  20.3  19.6  Industry    21.2  21.3   Wholesale/Retail/Hotels  46.6  23.7  18.5  Wholesale/Retail/Hotels    23.9  19.7   Business Services  7.2  25.4  31.3  Business Services    28.5  32.6   Other Services  13.0  23.1  25.4  Other Services    14.3  17.3  Greece        Switzerland         Agriculture  33.1  26.8  31.3  Agriculture    16.4  14.3   Industry  19.0  18.4  12.1  Industry    19.5  15.6   Wholesale/Retail/Hotels  29.8  31.6  28.2  Wholesale/Retail/Hotels    18.7  17.4   Business Services  11.6  14.9  18.2  Business Services    23.5  29.6   Other Services  6.5  8.2  10.2  Other Services    21.9  23.2  Ireland        UK         Agriculture  40.6  26.0  21.3  Agriculture  7.5  4.9  3.8   Industry  16.8  25.5  20.7  Industry  33.5  30.0  26.0   Wholesale/Retail/Hotels  22.2  17.9  15.8  Wholesale/Retail/Hotels  22.3  16.7  11.5   Business Services  11.4  18.6  27.3  Business Services  20.9  26.5  33.9   Other Services  9.0  12.0  14.9  Other Services  15.8  21.9  24.7  Italy                 Agriculture  13.3  7.4  6.2           Industry  26.2  25.0  21.7           Wholesale/Retail/Hotels  37.4  31.3  29.8           Business Services  12.6  22.7  27.3           Other Services  10.5  13.7  14.9          † Nomenclature statistique des Activités économiques dans la Communauté Européenne (NACE) Rev.1: Agriculture (sections A, B); Industry (sections C–F); Wholesale/Retail/Hotels (sections G, H); Business Services (sections I–K); Other Services (sections L–Q). ‡ NACE Rev.1: Agriculture (sections A); Industry (sections B–F); Wholesale/Retail/Hotels (sections G–I); Business Services (sections H–N); Other Services (sections O–U). Source: Eurostat, EU Labour Force Survey (1994, 2004, 2014), own calculations. View Large A similar picture emerges from Table 3 and Figure 2b , reporting on the occupational heterogeneity of self-employment in Europe. On the basis of 1-digit International Standard Classification of Occupations (ISCO)-08 classifications, I distinguish five occupational categories. Generally, self-employment has declined between 1994/1995 and 2014 in two of these categories: first, decline occurs in the group of ‘High-skilled Manual’ workers, which mainly contains skilled agricultural workers and craft and trades workers. Obviously, this decline reflects the sectoral developments in Figure 2a , depicting a decline in the agricultural industry, wholesale and retail. Second, and perhaps somewhat surprising, there is in most countries also a sharp decline in the share of self-employed managers. Arum and Müller (2004 , p. 23) suggest that in labor force surveys, whether a self-employed persons is classified as a manager depends not only on whether they employ others, but also depending on how they report their occupation. The decline of the managerial group, therefore, may have two sources; first, with the rise of solo self-employment there may be relatively fewer self-employed managers, and second, fewer people may report their occupation as manager or owner. Table 3. Self-employment by occupational group † in Europe, 1994–2014 (in percentage)   1994  2004  2014    1994  2004  2014  Austria        Luxembourg         Managers    22.5  7.8  Managers  51.0  50.0  8.8   Professionals    34.4  40.0  Professionals  21.2  35.5  65.9   Low-skilled Non-Manual    5.2  13.8  Low-skilled Non-Manual  6.0  0.0  11.0   High-skilled Manual    35.0  34.0  High-skilled Manual  21.9  14.5  14.3   Low-skilled Manual    3.0  4.5  Low-skilled Manual  0.0  0.0  0.0  Belgium        Netherlands         Managers  36.5  39.6  19.5  Managers  47.8  35.1  13.1   Professionals  24.2  28.1  37.9  Professionals  26.5  37.4  43.8   Low-skilled Non-Manual  9.0  7.0  16.7  Low-skilled Non-Manual  10.1  9.5  19.0   High-skilled Manual  26.9  24.3  22.0  High-skilled Manual  9.6  12.8  18.8   Low-skilled Manual  3.3  1.1  3.8  Low-skilled Manual  5.9  5.2  5.3  Denmark        Norway         Managers  29.8  32.1  3.9  Managers    5.7  6.8   Professionals  21.2  22.2  45.2  Professionals    26.7  37.3   Low-skilled Non-Manual  5.0  5.0  17.1  Low-skilled Non-Manual    13.4  13.0   High-skilled Manual  38.0  32.3  25.0  High-skilled Manual    45.5  31.8   Low-skilled Manual  6.0  8.4  8.8  Low-skilled Manual    8.6  11.1  Finland        Portugal         Managers    27.2  3.6  Managers  34.1  35.0  25.1   Professionals    20.4  31.5  Professionals  7.3  8.1  18.6   Low-skilled Non-Manual    10.2  19.0  Low-skilled Non-Manual  10.0  7.7  15.7   High-skilled Manual    34.5  34.9  High-skilled Manual  42.0  42.2  35.7   Low-skilled Manual    7.7  10.9  Low-skilled Manual  6.6  7.0  5.0  France        Spain         Managers  16.2  30.3  9.8  Managers  29.6  34.2  12.3   Professionals  18.7  22.4  34.2  Professionals  10.0  17.2  24.4   Low-skilled Non-Manual  16.0  2.8  18.3  Low-skilled Non-Manual  6.9  7.7  30.8   High-skilled Manual  46.9  44.5  34.3  High-skilled Manual  41.4  31.2  25.4   Low-skilled Manual  2.2  0.0  3.5  Low-skilled Manual  12.0  9.8  7.1  Germany        Sweden         Managers  30.1  25.1  12.7  Managers    14.6  10.8   Professionals  33.1  41.2  51.0  Professionals    34.5  38.9   Low-skilled Non-Manual  8.2  7.9  16.8  Low-skilled Non-Manual    13.9  15.5   High-skilled Manual  25.0  22.6  16.5  High-skilled Manual    27.7  25.0   Low-skilled Manual  3.6  3.3  3.0  Low-skilled Manual    9.2  9.7  Greece        Switzerland         Managers  25.9  30.3  8.9  Managers    8.5  11.8   Professionals  10.6  15.4  20.7  Professionals    39.8  44.3   Low-skilled Non-Manual  6.5  5.3  21.0  Low-skilled Non-Manual    14.0  14.9   High-skilled Manual  49.8  41.9  42.9  High-skilled Manual    33.6  25.9   Low-skilled Manual  7.2  7.0  6.5  Low-skilled Manual    4.1  3.0  Ireland        UK         Managers  9.5  45.3  16.8  Managers  19.7  17.9  13.8   Professionals  13.6  18.3  24.8  Professionals  24.8  28.8  31.9   Low-skilled Non-Manual  15.0  5.9  10.4  Low-skilled Non-Manual  7.2  10.0  15.0   High-skilled Manual  52.0  21.0  38.1  High-skilled Manual  35.1  30.1  26.6   Low-skilled Manual  9.9  9.5  10.0  Low-skilled Manual  13.2  13.3  12.7  Italy                 Managers  5.6  27.3  11.6           Professionals  20.0  31.0  36.6           Low-skilled Non-Manual  28.0  8.4  20.4           High-skilled Manual  36.2  25.6  24.8           Low-skilled Manual  10.1  7.7  6.7            1994  2004  2014    1994  2004  2014  Austria        Luxembourg         Managers    22.5  7.8  Managers  51.0  50.0  8.8   Professionals    34.4  40.0  Professionals  21.2  35.5  65.9   Low-skilled Non-Manual    5.2  13.8  Low-skilled Non-Manual  6.0  0.0  11.0   High-skilled Manual    35.0  34.0  High-skilled Manual  21.9  14.5  14.3   Low-skilled Manual    3.0  4.5  Low-skilled Manual  0.0  0.0  0.0  Belgium        Netherlands         Managers  36.5  39.6  19.5  Managers  47.8  35.1  13.1   Professionals  24.2  28.1  37.9  Professionals  26.5  37.4  43.8   Low-skilled Non-Manual  9.0  7.0  16.7  Low-skilled Non-Manual  10.1  9.5  19.0   High-skilled Manual  26.9  24.3  22.0  High-skilled Manual  9.6  12.8  18.8   Low-skilled Manual  3.3  1.1  3.8  Low-skilled Manual  5.9  5.2  5.3  Denmark        Norway         Managers  29.8  32.1  3.9  Managers    5.7  6.8   Professionals  21.2  22.2  45.2  Professionals    26.7  37.3   Low-skilled Non-Manual  5.0  5.0  17.1  Low-skilled Non-Manual    13.4  13.0   High-skilled Manual  38.0  32.3  25.0  High-skilled Manual    45.5  31.8   Low-skilled Manual  6.0  8.4  8.8  Low-skilled Manual    8.6  11.1  Finland        Portugal         Managers    27.2  3.6  Managers  34.1  35.0  25.1   Professionals    20.4  31.5  Professionals  7.3  8.1  18.6   Low-skilled Non-Manual    10.2  19.0  Low-skilled Non-Manual  10.0  7.7  15.7   High-skilled Manual    34.5  34.9  High-skilled Manual  42.0  42.2  35.7   Low-skilled Manual    7.7  10.9  Low-skilled Manual  6.6  7.0  5.0  France        Spain         Managers  16.2  30.3  9.8  Managers  29.6  34.2  12.3   Professionals  18.7  22.4  34.2  Professionals  10.0  17.2  24.4   Low-skilled Non-Manual  16.0  2.8  18.3  Low-skilled Non-Manual  6.9  7.7  30.8   High-skilled Manual  46.9  44.5  34.3  High-skilled Manual  41.4  31.2  25.4   Low-skilled Manual  2.2  0.0  3.5  Low-skilled Manual  12.0  9.8  7.1  Germany        Sweden         Managers  30.1  25.1  12.7  Managers    14.6  10.8   Professionals  33.1  41.2  51.0  Professionals    34.5  38.9   Low-skilled Non-Manual  8.2  7.9  16.8  Low-skilled Non-Manual    13.9  15.5   High-skilled Manual  25.0  22.6  16.5  High-skilled Manual    27.7  25.0   Low-skilled Manual  3.6  3.3  3.0  Low-skilled Manual    9.2  9.7  Greece        Switzerland         Managers  25.9  30.3  8.9  Managers    8.5  11.8   Professionals  10.6  15.4  20.7  Professionals    39.8  44.3   Low-skilled Non-Manual  6.5  5.3  21.0  Low-skilled Non-Manual    14.0  14.9   High-skilled Manual  49.8  41.9  42.9  High-skilled Manual    33.6  25.9   Low-skilled Manual  7.2  7.0  6.5  Low-skilled Manual    4.1  3.0  Ireland        UK         Managers  9.5  45.3  16.8  Managers  19.7  17.9  13.8   Professionals  13.6  18.3  24.8  Professionals  24.8  28.8  31.9   Low-skilled Non-Manual  15.0  5.9  10.4  Low-skilled Non-Manual  7.2  10.0  15.0   High-skilled Manual  52.0  21.0  38.1  High-skilled Manual  35.1  30.1  26.6   Low-skilled Manual  9.9  9.5  10.0  Low-skilled Manual  13.2  13.3  12.7  Italy                 Managers  5.6  27.3  11.6           Professionals  20.0  31.0  36.6           Low-skilled Non-Manual  28.0  8.4  20.4           High-skilled Manual  36.2  25.6  24.8           Low-skilled Manual  10.1  7.7  6.7          † ISCO-08: Managers (ISCO 1); Professionals (ISCO 2–3); Low-skilled Non-Manual (ISCO 4–5); High-skilled0 Manual (ISCO 6–7); Low-skilled Manual (8–9). Source: Eurostat, EU Labour Force Survey (1994, 2004, 2014), own calculations. View Large Table 3. Self-employment by occupational group † in Europe, 1994–2014 (in percentage)   1994  2004  2014    1994  2004  2014  Austria        Luxembourg         Managers    22.5  7.8  Managers  51.0  50.0  8.8   Professionals    34.4  40.0  Professionals  21.2  35.5  65.9   Low-skilled Non-Manual    5.2  13.8  Low-skilled Non-Manual  6.0  0.0  11.0   High-skilled Manual    35.0  34.0  High-skilled Manual  21.9  14.5  14.3   Low-skilled Manual    3.0  4.5  Low-skilled Manual  0.0  0.0  0.0  Belgium        Netherlands         Managers  36.5  39.6  19.5  Managers  47.8  35.1  13.1   Professionals  24.2  28.1  37.9  Professionals  26.5  37.4  43.8   Low-skilled Non-Manual  9.0  7.0  16.7  Low-skilled Non-Manual  10.1  9.5  19.0   High-skilled Manual  26.9  24.3  22.0  High-skilled Manual  9.6  12.8  18.8   Low-skilled Manual  3.3  1.1  3.8  Low-skilled Manual  5.9  5.2  5.3  Denmark        Norway         Managers  29.8  32.1  3.9  Managers    5.7  6.8   Professionals  21.2  22.2  45.2  Professionals    26.7  37.3   Low-skilled Non-Manual  5.0  5.0  17.1  Low-skilled Non-Manual    13.4  13.0   High-skilled Manual  38.0  32.3  25.0  High-skilled Manual    45.5  31.8   Low-skilled Manual  6.0  8.4  8.8  Low-skilled Manual    8.6  11.1  Finland        Portugal         Managers    27.2  3.6  Managers  34.1  35.0  25.1   Professionals    20.4  31.5  Professionals  7.3  8.1  18.6   Low-skilled Non-Manual    10.2  19.0  Low-skilled Non-Manual  10.0  7.7  15.7   High-skilled Manual    34.5  34.9  High-skilled Manual  42.0  42.2  35.7   Low-skilled Manual    7.7  10.9  Low-skilled Manual  6.6  7.0  5.0  France        Spain         Managers  16.2  30.3  9.8  Managers  29.6  34.2  12.3   Professionals  18.7  22.4  34.2  Professionals  10.0  17.2  24.4   Low-skilled Non-Manual  16.0  2.8  18.3  Low-skilled Non-Manual  6.9  7.7  30.8   High-skilled Manual  46.9  44.5  34.3  High-skilled Manual  41.4  31.2  25.4   Low-skilled Manual  2.2  0.0  3.5  Low-skilled Manual  12.0  9.8  7.1  Germany        Sweden         Managers  30.1  25.1  12.7  Managers    14.6  10.8   Professionals  33.1  41.2  51.0  Professionals    34.5  38.9   Low-skilled Non-Manual  8.2  7.9  16.8  Low-skilled Non-Manual    13.9  15.5   High-skilled Manual  25.0  22.6  16.5  High-skilled Manual    27.7  25.0   Low-skilled Manual  3.6  3.3  3.0  Low-skilled Manual    9.2  9.7  Greece        Switzerland         Managers  25.9  30.3  8.9  Managers    8.5  11.8   Professionals  10.6  15.4  20.7  Professionals    39.8  44.3   Low-skilled Non-Manual  6.5  5.3  21.0  Low-skilled Non-Manual    14.0  14.9   High-skilled Manual  49.8  41.9  42.9  High-skilled Manual    33.6  25.9   Low-skilled Manual  7.2  7.0  6.5  Low-skilled Manual    4.1  3.0  Ireland        UK         Managers  9.5  45.3  16.8  Managers  19.7  17.9  13.8   Professionals  13.6  18.3  24.8  Professionals  24.8  28.8  31.9   Low-skilled Non-Manual  15.0  5.9  10.4  Low-skilled Non-Manual  7.2  10.0  15.0   High-skilled Manual  52.0  21.0  38.1  High-skilled Manual  35.1  30.1  26.6   Low-skilled Manual  9.9  9.5  10.0  Low-skilled Manual  13.2  13.3  12.7  Italy                 Managers  5.6  27.3  11.6           Professionals  20.0  31.0  36.6           Low-skilled Non-Manual  28.0  8.4  20.4           High-skilled Manual  36.2  25.6  24.8           Low-skilled Manual  10.1  7.7  6.7            1994  2004  2014    1994  2004  2014  Austria        Luxembourg         Managers    22.5  7.8  Managers  51.0  50.0  8.8   Professionals    34.4  40.0  Professionals  21.2  35.5  65.9   Low-skilled Non-Manual    5.2  13.8  Low-skilled Non-Manual  6.0  0.0  11.0   High-skilled Manual    35.0  34.0  High-skilled Manual  21.9  14.5  14.3   Low-skilled Manual    3.0  4.5  Low-skilled Manual  0.0  0.0  0.0  Belgium        Netherlands         Managers  36.5  39.6  19.5  Managers  47.8  35.1  13.1   Professionals  24.2  28.1  37.9  Professionals  26.5  37.4  43.8   Low-skilled Non-Manual  9.0  7.0  16.7  Low-skilled Non-Manual  10.1  9.5  19.0   High-skilled Manual  26.9  24.3  22.0  High-skilled Manual  9.6  12.8  18.8   Low-skilled Manual  3.3  1.1  3.8  Low-skilled Manual  5.9  5.2  5.3  Denmark        Norway         Managers  29.8  32.1  3.9  Managers    5.7  6.8   Professionals  21.2  22.2  45.2  Professionals    26.7  37.3   Low-skilled Non-Manual  5.0  5.0  17.1  Low-skilled Non-Manual    13.4  13.0   High-skilled Manual  38.0  32.3  25.0  High-skilled Manual    45.5  31.8   Low-skilled Manual  6.0  8.4  8.8  Low-skilled Manual    8.6  11.1  Finland        Portugal         Managers    27.2  3.6  Managers  34.1  35.0  25.1   Professionals    20.4  31.5  Professionals  7.3  8.1  18.6   Low-skilled Non-Manual    10.2  19.0  Low-skilled Non-Manual  10.0  7.7  15.7   High-skilled Manual    34.5  34.9  High-skilled Manual  42.0  42.2  35.7   Low-skilled Manual    7.7  10.9  Low-skilled Manual  6.6  7.0  5.0  France        Spain         Managers  16.2  30.3  9.8  Managers  29.6  34.2  12.3   Professionals  18.7  22.4  34.2  Professionals  10.0  17.2  24.4   Low-skilled Non-Manual  16.0  2.8  18.3  Low-skilled Non-Manual  6.9  7.7  30.8   High-skilled Manual  46.9  44.5  34.3  High-skilled Manual  41.4  31.2  25.4   Low-skilled Manual  2.2  0.0  3.5  Low-skilled Manual  12.0  9.8  7.1  Germany        Sweden         Managers  30.1  25.1  12.7  Managers    14.6  10.8   Professionals  33.1  41.2  51.0  Professionals    34.5  38.9   Low-skilled Non-Manual  8.2  7.9  16.8  Low-skilled Non-Manual    13.9  15.5   High-skilled Manual  25.0  22.6  16.5  High-skilled Manual    27.7  25.0   Low-skilled Manual  3.6  3.3  3.0  Low-skilled Manual    9.2  9.7  Greece        Switzerland         Managers  25.9  30.3  8.9  Managers    8.5  11.8   Professionals  10.6  15.4  20.7  Professionals    39.8  44.3   Low-skilled Non-Manual  6.5  5.3  21.0  Low-skilled Non-Manual    14.0  14.9   High-skilled Manual  49.8  41.9  42.9  High-skilled Manual    33.6  25.9   Low-skilled Manual  7.2  7.0  6.5  Low-skilled Manual    4.1  3.0  Ireland        UK         Managers  9.5  45.3  16.8  Managers  19.7  17.9  13.8   Professionals  13.6  18.3  24.8  Professionals  24.8  28.8  31.9   Low-skilled Non-Manual  15.0  5.9  10.4  Low-skilled Non-Manual  7.2  10.0  15.0   High-skilled Manual  52.0  21.0  38.1  High-skilled Manual  35.1  30.1  26.6   Low-skilled Manual  9.9  9.5  10.0  Low-skilled Manual  13.2  13.3  12.7  Italy                 Managers  5.6  27.3  11.6           Professionals  20.0  31.0  36.6           Low-skilled Non-Manual  28.0  8.4  20.4           High-skilled Manual  36.2  25.6  24.8           Low-skilled Manual  10.1  7.7  6.7          † ISCO-08: Managers (ISCO 1); Professionals (ISCO 2–3); Low-skilled Non-Manual (ISCO 4–5); High-skilled0 Manual (ISCO 6–7); Low-skilled Manual (8–9). Source: Eurostat, EU Labour Force Survey (1994, 2004, 2014), own calculations. View Large Table 3 also supports the notion that with its recent rise, self-employment has also become increasingly polarized. In the majority of countries, self-employment has grown among both high-skilled professionals (including technicians and associate professionals) as well as low-skilled occupations, such as clerks and other service and sales workers. Again, these developments match the shifts in Table 2 toward self-employment activities in service-oriented industries. In particular, the share of professionals increased remarkably and is now the largest category of self-employment in more than halve of the countries in Table 2 . In Germany (51%) and Luxembourg (65%), the majority of self-employed even works within this occupational category. 3. Solo self-employment: autonomous or atypical? 2 3 .1 Differences with temporary employees Based on the traditional distinction between self-employment and paid-employment, especially temporary employees should differ sharply from self-employed persons with respect to their political orientations. Not only do their positions diverge, people in self-employment and temporary employment may also have conflicting labor market interests. As (potential) employers, people in self-employment would consider temporary workers as an important source of flexible labor. The ability to hire (and easily fire) fixed-term personnel reduces the entrepreneurial risks associated with changes in demand and supply, by partially transferring those market risks to employees on temporary contracts. Flexible markets, and a low level of social protection help entrepreneurial freedom of people in self-employment, but harm the position of temporary employees, and vice versa. Unlike the self-employed, temporary employees are therefore assumed to be more supportive of parties and policies supporting welfare protection ( Corbetta and Colloca, 2013 ; Marx and Picot, 2013 ; Marx, 2014 ). The first hypothesis of this study will explicitly test whether differences in, and conflict of interest over labor market risks between (temporary) employees and people in self-employment lead to distinct patterns of political orientation. Hypothesis 1: Comparedwithpermanent employees, (a) temporary workers have a more left-wing political orientation and (b) solo self-employed have a more right-wing political orientation. 3.2 Similarities with temporary employees Arum and Müller (2004) have argued that because ‘self-employment is no longer simply dominated by petty bourgeois self-employment, this social grouping can no longer be understood as a politically conservative force’ (2004, p. 453). The heterogeneity among the self-employed suggests that there are considerable differences in labor market risks. As self-employment increasingly consists of quasi-independent subcontractors, freelancing professionals and others in semi-autonomous work arrangements, the boundaries blur between self-employment and wage-employment ( Muehlberger, 2007 ; Barbieri and Scherer, 2009 ). ‘New’ types of self-employment are more and more seen as atypical work relationships, similar to temporary employment, with higher labor market risks than for traditional ‘petty bourgeois’ entrepreneurs ( Schulze Buschoff and Schmidt, 2009 ; Standing, 2011 ). In this study, I examine whether more precarious labor market positions for solo self-employed are associated with political preferences that are similar to the preferences of paid-employees in atypical work relationships. In doing so, I account for two conditions that may moderate the relationship between employment type and political orientation: the degree of job autonomy and the degree of economic insecurity . 3.3 Job autonomy Autonomy in the workplace may affect workers value-orientations ( Kohn, 1995 ). Kitschelt and Rehm, 2014 ) suggest that ‘people who enjoy discretion and autonomy in their professional life generalize these experiences of an individualistic, universalistic mode of accountability and action to other spheres of life as well’ (pp.1674–1675). With respect to political and economic attitudes, a larger degree of job autonomy can be associated with economic conservatism, i.e.: opposition to redistribution and other government interventions, which might limit individual freedom ( De Witte, 1999 ; Kitschelt and Rehm, 2014 ). The right-wing political orientations of self-employed workers are often attributed to the fact that they have discretion over business activities and take individual responsibility for rewards and costs associated with market pressures. Due to their autonomous positions, people in self-employment would advocate individual freedom, initiative and responsibility, and therefore reject redistribution policies and collective security arrangements. Conversely, also the left-wing political orientation of temporary employees can be related to job autonomy. Temporary workers, generally enjoy lower job discretion and job autonomy than permanent employees ( Gallie et al. , 1998 ). A lack of autonomy in the workplace can strengthen economic progressive, left-wing preferences ( De Witte, 1999 ; Kitschelt and Rehm, 2014 ). The increased heterogeneity of self-employment to some extent obscured the ideal-typical image of self-employment as autonomous employment type, or one that is very distinct from wage-employment ( Stanworth and Stanworth, 1995 ; Pernicka, 2006 ; Schulze Buschoff and Protsch, 2008 ). It has become apparent that not all self-employed workers enjoy greater autonomy compared with paid-employees. There is a growing group of so-called ‘dependent self-employed’, workers who are formally in self-employment but work in hierarchical subordination to a single firm on which they are economically dependent ( Muehlberger, 2007 ). Hiring quasi-independent subcontractors, or others in semi-autonomous forms of self-employment, is sometimes used as a way to evade employment protection legislation ( Román et al. 2011 ). For people in self-employment, lower levels of job autonomy are associated with higher labor market risks. As they are ‘dependent on others for allocating them tasks over which they have little control’ ( Standing, 2011 , p. 16) dependent self-employed workers bear the entrepreneurial risk without entrepreneurial independence. Self-employed who enjoy lower autonomy in their professional life may adopt a less individualistic perception of accountability and responsibility with respect to redistribution policies, collective security arrangements and other government interventions. I therefore expect that the degree of job autonomy moderates the relationship between employment type and political orientation and that—both for temporary workers and self-employed workers—greater job autonomy is related to right-wing attitudes, and lower autonomy to left-wing attitudes. Hence, expanding on the first general hypothesis, I formulate: Hypothesis 2a: The left-wing political orientation of temporary workers is weaker as they have more autonomy over their job. Hypothesis 2b: The right-wing political orientation of solo self-employed workers is stronger as they have more autonomy over their job. 3.4 Economic insecurity Theories on job or economic insecurity and political divisions suggest that labor market vulnerabilities are generally associated with support for leftist parties and pro-welfare policies ( Corbetta and Colloca, 2013 ; Marx and Picot, 2013 ; Marx, 2014 ). People on temporary contracts would be left-leaning because there are exposed to greater risks than permanent employees. Conversely, high job security is often mentioned as one of the driving forces for traditional self-employed to support right-wing parties ( Nieuwbeerta and De Graaf, 1999 ). Again, it can be argued that the rise of ‘new’ forms of self-employment blurred the boundaries between self-employment and temporary employment ( Barbieri and Scherer, 2009 ). Contrary to the archetypical image of stable and secure self-employment, risks are assumed to be high instead of low for particular types of solo self-employment. For one, greater risks arise from the instability of self-employment careers; being self-employed is more and more a temporary situation; compared with those in more traditional types of self-employment (e.g. farmers and shop owners), ‘new’ self-employed are more often former employees, and they are less likely to stay self-employed ( Arum and Müller, 2004 ), and have a higher risk of exiting to unemployment ( Schulze Buschoff and Protsch 2008 ). Moreover, risks may be high due to uncertainty of income. People working on their own account without employees are often reliant on more irregular, potentially lower income, with less capacity for savings, insurance and pensions ( Schulze Buschoff and Schmidt, 2009 ; Dekker, 2010 ; Pedersini and Coletto, 2010 ). Especially unskilled self-employment is generally instable and most poorly paid ( McManus, 2000 ; Lofstrom, 2013 ). Dekker (2010) shows that among self-employed persons, employment-related risks can be related to support for collectivist welfare schemes. For future studies, he suggests that different types of self-employed workers, with disparate risk perceptions, might be related to different attitudes toward welfare state support (2010, p. 781). Hence, instead of politically right-wing, self-employed workers in a more precarious situation (e.g. unstable work, irregular income, underinsured) might be more to the left, i.e. more close to the preferences of paid-employees in atypical work relationships. I therefore expect that the degree of economic insecurity moderates the relationship between employment type and political orientation, and that—both for temporary workers and solo self-employed workers—greater economic security is related to right-wing attitudes, and lower security to left-wing attitudes. Therefore, I formulate: Hypothesis 3a: The left-wing political orientation of temporary workers is stronger as their economic insecurities are higher Hypothesis 3b: The right-wing political orientation of solo self-employed workers is weaker as their economic insecurities are higher 3.5 Data and measurements To test the hypotheses, I use the integrated file of the fourth wave of the ESS. This file is chosen for three reasons. First, disentangling the political alignments of various groups of self-employed workers requires a sufficiently large sample size. In Europe, with average self-employment rates around 10–15%, national political surveys often contain too few cases to differentiate among types of self-employment. Therefore, despite the drawbacks, a pooled dataset is needed to study the political attitudes of a large group of people in self-employment. Second, the ESS is the only large- N datasets that contains information on both atypical employment (i.e. temporary work) and political attitudes ( Kitschelt and Rehm, 2014 ; Marx, 2014 ). And third, the ESS-4 of 2008 not only provides an extensive set of items to measure welfare attitudes, but also includes indicators of job insecurity and job control. To make the analysis as comparable as possible, I only include Western European countries with a more or less similar political party structure, including the presence of both old- and new-left political parties. These countries are: Austria, Belgium, Denmark, France, Germany, the Netherlands, Norway and Switzerland. Moreover, I only included respondents of working age (15–64) in employment (wage-employment or self-employment) and without missing information on relevant variables. Ultimately, the analysis is based on 7186 respondents, of which there are 852 self-employed (i.e. 347 with and 505 without employees). Below I discuss the key variables in more detail; descriptive statistics are presented in Appendix Table A1 . 3.6 Dependent variables To examine the political orientations I use two kinds of variables, attitudes on welfare policies and political party preferences . First, attitudes on welfare policies are measured using five items on what the responsibilities of governments should or should not be. Respondents were asked to rate on an 11-point scale whether the government should ‘not be responsible at all’ (0) or should be ‘entirely responsible’(10) for particular tasks, i.e.: ensure (a) a job for everyone who wants one, (b) adequate health care for the sick, (c) a reasonable standard of living for the old, (d) a reasonable standard of living for the unemployed and (e) provide paid leave from work for people who temporarily have to care for sick family members. A reliability analysis confirmed that the items constitute an adequately reliable scale (Cronbach’s alpha = 0.76). A scale is constructed on the basis of the mean value over the five items, coded in such a way that a higher value indicates a more pro-welfare attitude. 3 Second, following Marx (2014) , political party preferences are primarily measured using party identification rather than voting behavior. Because vote choice is reported retrospectively in the ESS, Marx (2014 , p. 11) argues that the gap between the last election and the time of data collection may cause problems regarding temporary employees with short-duration contracts. Especially for this group, he argues, the ESS provides no reliable information about respondents’ labor market status at the time of last election. The same, I can add, may hold for people in new self-employment, for whom being self-employed is more often a temporary situation. Only for respondents who report no closer attachment to any particular party than all other parties, vote choice is used to proxy their political orientation. Political orientation is measured in three-party categories using the party family classification on the Manifesto Project Database ( Volkens et al. , 2013 ), i.e.: new-left parties (ecology parties), old-left parties (combining (former) communist and social democratic parties), right-wing (combing liberal parties, Christian democrats, conservative, agrarian parties and nationalist parties). 4 3.7 Job characteristics The main independent variables are related to characteristics of the respondent’s job, i.e.: employment type, job autonomy, and economic insecurity . The variable for employment type distinguishes between four employment groups: (a) employees with a permanent contract, (b) temporary employees (with a fixed-term or no contract), (c) people in solo self-employment (without employees) and (d) employers (self-employed with employees). The degree of economic insecurity is measured used two separate items, employment insecurity and income insecurity . Respondents were asked to rate on a 4-point scale how likely it is that during the next 12 months they would (a) be unemployed and looking for work, and (b) not have enough money to cover household necessities. Both variables are recoded into a 3-point scale by collapsing the upper two categories (i.e. ‘[very] likely’), so that a high score relates to a more insecure situation. To measure job autonomy two items were used: Respondents were asked to rate on a 10-point scale how much influence they had (a) to decide how daily work is organized and (b) on policy decision about the organization’s activity. An index was constructed by taking the product of the two variables divided by hundred. This index ranges between 0 ‘no job autonomy’ and 1 ‘full job autonomy’. 3.8 Control variables Next to the main variables a number of control variables are included in the analysis: first, I control for occupation . This variable was measured on the basis 1-digit ISCO-88 classifications. The same five occupational groups are distinguished as in the aggregate statistics presented earlier: Managers (ISCO 1), Professionals (ISCO 2–3), Low-skilled Non-Manual (ISCO 4–5), High-skilled Manual (ISCO 6–7) and Low-skilled Manual (8–9). Moreover, control variables are included for income (measured as total net household income in deciles), part-time work (i.e. less than 30 hours a week = 1), and gender (female = 1). Finally, variables are included for age (15 = 0) and the level of education : based on harmonized International Standard Classification of Education (ISCED) categories, distinguishing between a ‘low-level education’ (ISCED 0–2), ‘medium-level education’ (ISCED 3–4) and ‘high-level education’ (ISCED 5–6). 4. Analyses and results 4.1 Attitudes on welfare policies I start with a regression analysis for pro-welfare attitudes, see Table 4 . The coefficients ( b ) denote the unstandardized coefficients for respondents of attributing a higher responsibility to the government in providing welfare tasks. The standard errors (SEs) are adjusted for clustering in countries. Moreover, country-dummy variables are added to capture national differences in welfare support (not shown for reasons of space), and population size and ESS design weights are applied. 5 Table 4. Regression analysis for pro-welfare attitudes (robust SEs in parentheses)   Model 1   Model 2     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  0.129 **  (0.04)  0.129 **  (0.04)   Solo self-employed  −0.227 ***  (0.05)  −0.296 ***  (0.06)   Employer  −0.207  (0.18)  −0.260  (0.19)  Perceived income insecurity      0.159 **  (0.06)  Perceived employment insecurity      −0.034  (0.06)  Perceived job autonomy      0.128 ***  (0.02)  Income  −0.053 ***  (0.01)  −0.046 ***  (0.01)  Occupation (professionals = ref)  –  –  –  –   Managers  −0.263 ***  (0.04)  −0.291 ***  (0.03)   Low-skilled Non-Manual  −0.049  (0.05)  −0.042  (0.05)   High-skilled Manual  0.099 **  (0.04)  0.098 **  (0.03)   Low-skilled Manual  0.128  (0.08)  0.134*  (0.06)  Part-time  −0.032  (0.15)  −0.035  (0.15)  Age  0.008 **  (0.00)  0.008 **  (0.00)  Female  0.165  (0.11)  0.162  (0.11)  Education (middle = ref)  –  –  –  –   Lower  −0.163 **  (0.07)  −0.162 **  (0.06)   Higher  −0.104 *  (0.04)  −0.091 *  (0.04)  Constant  8.000 ***  (0.13)  7.779 ***  0.04    Model 1   Model 2     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  0.129 **  (0.04)  0.129 **  (0.04)   Solo self-employed  −0.227 ***  (0.05)  −0.296 ***  (0.06)   Employer  −0.207  (0.18)  −0.260  (0.19)  Perceived income insecurity      0.159 **  (0.06)  Perceived employment insecurity      −0.034  (0.06)  Perceived job autonomy      0.128 ***  (0.02)  Income  −0.053 ***  (0.01)  −0.046 ***  (0.01)  Occupation (professionals = ref)  –  –  –  –   Managers  −0.263 ***  (0.04)  −0.291 ***  (0.03)   Low-skilled Non-Manual  −0.049  (0.05)  −0.042  (0.05)   High-skilled Manual  0.099 **  (0.04)  0.098 **  (0.03)   Low-skilled Manual  0.128  (0.08)  0.134*  (0.06)  Part-time  −0.032  (0.15)  −0.035  (0.15)  Age  0.008 **  (0.00)  0.008 **  (0.00)  Female  0.165  (0.11)  0.162  (0.11)  Education (middle = ref)  –  –  –  –   Lower  −0.163 **  (0.07)  −0.162 **  (0.06)   Higher  −0.104 *  (0.04)  −0.091 *  (0.04)  Constant  8.000 ***  (0.13)  7.779 ***  0.04  Notes: * P  < 0.1; ** P  < 0.05; *** P  < 0.01 (two-tailed test); robust SEs for country-clustering. Population size and design weights applied. Not shown: country dummy variables. View Large Table 4. Regression analysis for pro-welfare attitudes (robust SEs in parentheses)   Model 1   Model 2     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  0.129 **  (0.04)  0.129 **  (0.04)   Solo self-employed  −0.227 ***  (0.05)  −0.296 ***  (0.06)   Employer  −0.207  (0.18)  −0.260  (0.19)  Perceived income insecurity      0.159 **  (0.06)  Perceived employment insecurity      −0.034  (0.06)  Perceived job autonomy      0.128 ***  (0.02)  Income  −0.053 ***  (0.01)  −0.046 ***  (0.01)  Occupation (professionals = ref)  –  –  –  –   Managers  −0.263 ***  (0.04)  −0.291 ***  (0.03)   Low-skilled Non-Manual  −0.049  (0.05)  −0.042  (0.05)   High-skilled Manual  0.099 **  (0.04)  0.098 **  (0.03)   Low-skilled Manual  0.128  (0.08)  0.134*  (0.06)  Part-time  −0.032  (0.15)  −0.035  (0.15)  Age  0.008 **  (0.00)  0.008 **  (0.00)  Female  0.165  (0.11)  0.162  (0.11)  Education (middle = ref)  –  –  –  –   Lower  −0.163 **  (0.07)  −0.162 **  (0.06)   Higher  −0.104 *  (0.04)  −0.091 *  (0.04)  Constant  8.000 ***  (0.13)  7.779 ***  0.04    Model 1   Model 2     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  0.129 **  (0.04)  0.129 **  (0.04)   Solo self-employed  −0.227 ***  (0.05)  −0.296 ***  (0.06)   Employer  −0.207  (0.18)  −0.260  (0.19)  Perceived income insecurity      0.159 **  (0.06)  Perceived employment insecurity      −0.034  (0.06)  Perceived job autonomy      0.128 ***  (0.02)  Income  −0.053 ***  (0.01)  −0.046 ***  (0.01)  Occupation (professionals = ref)  –  –  –  –   Managers  −0.263 ***  (0.04)  −0.291 ***  (0.03)   Low-skilled Non-Manual  −0.049  (0.05)  −0.042  (0.05)   High-skilled Manual  0.099 **  (0.04)  0.098 **  (0.03)   Low-skilled Manual  0.128  (0.08)  0.134*  (0.06)  Part-time  −0.032  (0.15)  −0.035  (0.15)  Age  0.008 **  (0.00)  0.008 **  (0.00)  Female  0.165  (0.11)  0.162  (0.11)  Education (middle = ref)  –  –  –  –   Lower  −0.163 **  (0.07)  −0.162 **  (0.06)   Higher  −0.104 *  (0.04)  −0.091 *  (0.04)  Constant  8.000 ***  (0.13)  7.779 ***  0.04  Notes: * P  < 0.1; ** P  < 0.05; *** P  < 0.01 (two-tailed test); robust SEs for country-clustering. Population size and design weights applied. Not shown: country dummy variables. View Large In Model 1, I run a model with only employment type and the control variables. I test the general hypothesis that people in solo self-employment are, everything else held equal, politically more to the right (i.e. oppose government responsibility in the domain of social welfare) and temporary employees are politically more to the left (i.e. support government responsibility in providing social welfare). The reference category in this model is formed by people on permanent employment contracts. For the hypothesis to hold, I would have to find a negative effect of solo self-employment, and a positive effect of temporary employment. The model shows that there is indeed a positive effect of temporary employment (0.129) and a negative effect of solo self-employment (−0.227). Hence, these results provide support for hypothesis 1: compared with permanent employees, temporary workers have a somewhat more leftist political orientation, and self-employed have a more right-wing political orientation. In Model 2, I add indicators for perceived employment insecurity, income insecurity and job autonomy. Before testing whether the aforementioned-effects of temporary employment and solo self-employment are moderated by such characteristics related to precariousness and/or job control, I first assess the direct effects of these variables. The model shows that welfare state support is stronger for respondents perceiving their income as insecure (0.159), and for respondents with greater job autonomy (0.128). As expected, labor market vulnerabilities (i.e. insecurities of income) are generally associated with support for pro-welfare policies. For perceived employment insecurity, however, this effect is not found. Moreover, contrarily to the expectation greater autonomy at the workplace seems to correlate positively instead of negatively with pro-welfare attitudes. In Table 5 interaction effects are introduced between employment type on the one hand and on the other hand income insecurity (Model 3), employment insecurity (Model 4) and job autonomy (Model 5). This way, I can test the hypotheses that the left-wing, pro-welfare attitudes of temporary workers are weaker as they have more autonomy over their job, and stronger as their economic insecurities are higher (hypothesis 2a and 3a, respectively). The results in Table 5 , however, generally do not support hypothesis 2a and 3a; there appears to be no significant interaction between temporary employment and income insecurity (Model 3), employment insecurity (Model 4) or job autonomy (Model 5). Hence, pro-welfare orientation of temporary workers is not stronger as their economic insecurities are higher, nor weaker as they have more autonomy over their job. Table 5. Interaction effects for pro-welfare attitudes (robust SEs in parentheses)   Model 3     ( b )   SE  Employment (permanent employee = ref)  –  –   Temporary employee  0.201 **  (0.07)   Solo self-employed  −0.222 ***  (0.04)   Employer  −0.405 **  (0.14)  Perceived income insecurity  0.165 **  (0.05)   ×Temporary employee  −0.072  (0.06)   × Solo self-employed  −0.086  (0.07)   × Employer  0.256 *  (0.13)      Model 4     ( b )   SE    Employment (permanent employee = ref)  –  –   Temporary employee  0.173 **  (0.06)   Solo self-employed  −0.429 ***  (0.08)   Employer  −0.418  (0.23)  Perceived employment insecurity  −0.056  (0.06)   ×Temporary employee  −0.030  (0.02)   × Solo self-employed  0.201 ***  (0.05)   × Employer  0.408 **  (0.12)      Model 5     ( b )   SE    Employment (permanent employee = ref)  –  –   Temporary employee  0.155 *  (0.07)   Solo self-employed  0.131  (0.21)   Employer  −0.486 ***  (0.13)  Perceived job autonomy  0.179 ***  (0.02)   ×Temporary employee  −0.085  (0.14)   × Solo self-employed  −0.546 **  (0.22)   × Employer  0.216  (0.27)    Model 3     ( b )   SE  Employment (permanent employee = ref)  –  –   Temporary employee  0.201 **  (0.07)   Solo self-employed  −0.222 ***  (0.04)   Employer  −0.405 **  (0.14)  Perceived income insecurity  0.165 **  (0.05)   ×Temporary employee  −0.072  (0.06)   × Solo self-employed  −0.086  (0.07)   × Employer  0.256 *  (0.13)      Model 4     ( b )   SE    Employment (permanent employee = ref)  –  –   Temporary employee  0.173 **  (0.06)   Solo self-employed  −0.429 ***  (0.08)   Employer  −0.418  (0.23)  Perceived employment insecurity  −0.056  (0.06)   ×Temporary employee  −0.030  (0.02)   × Solo self-employed  0.201 ***  (0.05)   × Employer  0.408 **  (0.12)      Model 5     ( b )   SE    Employment (permanent employee = ref)  –  –   Temporary employee  0.155 *  (0.07)   Solo self-employed  0.131  (0.21)   Employer  −0.486 ***  (0.13)  Perceived job autonomy  0.179 ***  (0.02)   ×Temporary employee  −0.085  (0.14)   × Solo self-employed  −0.546 **  (0.22)   × Employer  0.216  (0.27)  Notes: * P  < 0.1; ** P  < 0.05; *** P  < 0.01 (two-tailed test); robust SEs for country-clustering. Population size and design weights applied. All models controlled for income, occupational class, part-time, age, gender, education and country-dummies (see Table 1 ). View Large Table 5. Interaction effects for pro-welfare attitudes (robust SEs in parentheses)   Model 3     ( b )   SE  Employment (permanent employee = ref)  –  –   Temporary employee  0.201 **  (0.07)   Solo self-employed  −0.222 ***  (0.04)   Employer  −0.405 **  (0.14)  Perceived income insecurity  0.165 **  (0.05)   ×Temporary employee  −0.072  (0.06)   × Solo self-employed  −0.086  (0.07)   × Employer  0.256 *  (0.13)      Model 4     ( b )   SE    Employment (permanent employee = ref)  –  –   Temporary employee  0.173 **  (0.06)   Solo self-employed  −0.429 ***  (0.08)   Employer  −0.418  (0.23)  Perceived employment insecurity  −0.056  (0.06)   ×Temporary employee  −0.030  (0.02)   × Solo self-employed  0.201 ***  (0.05)   × Employer  0.408 **  (0.12)      Model 5     ( b )   SE    Employment (permanent employee = ref)  –  –   Temporary employee  0.155 *  (0.07)   Solo self-employed  0.131  (0.21)   Employer  −0.486 ***  (0.13)  Perceived job autonomy  0.179 ***  (0.02)   ×Temporary employee  −0.085  (0.14)   × Solo self-employed  −0.546 **  (0.22)   × Employer  0.216  (0.27)    Model 3     ( b )   SE  Employment (permanent employee = ref)  –  –   Temporary employee  0.201 **  (0.07)   Solo self-employed  −0.222 ***  (0.04)   Employer  −0.405 **  (0.14)  Perceived income insecurity  0.165 **  (0.05)   ×Temporary employee  −0.072  (0.06)   × Solo self-employed  −0.086  (0.07)   × Employer  0.256 *  (0.13)      Model 4     ( b )   SE    Employment (permanent employee = ref)  –  –   Temporary employee  0.173 **  (0.06)   Solo self-employed  −0.429 ***  (0.08)   Employer  −0.418  (0.23)  Perceived employment insecurity  −0.056  (0.06)   ×Temporary employee  −0.030  (0.02)   × Solo self-employed  0.201 ***  (0.05)   × Employer  0.408 **  (0.12)      Model 5     ( b )   SE    Employment (permanent employee = ref)  –  –   Temporary employee  0.155 *  (0.07)   Solo self-employed  0.131  (0.21)   Employer  −0.486 ***  (0.13)  Perceived job autonomy  0.179 ***  (0.02)   ×Temporary employee  −0.085  (0.14)   × Solo self-employed  −0.546 **  (0.22)   × Employer  0.216  (0.27)  Notes: * P  < 0.1; ** P  < 0.05; *** P  < 0.01 (two-tailed test); robust SEs for country-clustering. Population size and design weights applied. All models controlled for income, occupational class, part-time, age, gender, education and country-dummies (see Table 1 ). View Large Next, Models 4 and 5 may be used to test whether the right-wing political orientation of solo self-employed workers is stronger as they have more autonomy over their job, and weaker as their economic insecurities are higher (hypothesis 2b and 3b, respectively). Model 4 shows a negative main-effect of solo self-employment on pro-welfare attitudes (−0.429), and a significant positive interaction effect between self-employment and employment insecurity (0.201). As expected, this result indicates that people in solo self-employment, compared with permanent employees, are more likely to support welfare policies as they are more insecure with respect to their employment position. To ease interpretation, I have plotted this effect in Figure 3b . Model 5 shows the interaction between self-employment and job autonomy. Here I find a negative main-effect (−0,486) combined with a negative interaction-effect (−0,546), indicating that people in solo self-employment, compared with permanent employees, are even less likely to support welfare policies as they are more autonomous with respect to their job. This effect is plotted in Figure 3c . In general these results seem to support hypothesis 2b and 3b. Figure 2b and c indicates that self-employed workers are more left-wing orientated as their employment insecurities are higher, and more right-wing orientated as they are more autonomous. Yet, a reservation applies: unlike employment insecurity, income insecurity does not moderate the effect of solo self-employment on welfare attitudes ( Figure 3a ). Figure 3. View largeDownload slide Interaction effects on pro-welfare attitudes (predicted values) † . † Confidence intervals (95%) for the solo self-employed and permanent wage-employees. Figure 3. View largeDownload slide Interaction effects on pro-welfare attitudes (predicted values) † . † Confidence intervals (95%) for the solo self-employed and permanent wage-employees. 4.2 Political party preferences So far, I examined political orientations by looking at welfare attitudes, specifically with respect to the role of governments. Next, I will shift the focus to party preferences. For this purpose, I use a multinomial logit model with three outcome categories, i.e.: new-left, old-left, and right-wing parties, see Table 6 . The reference outcome category is formed by the right-wing parties. Again, the SEs are adjusted for country-clustering, country-dummy variables are added, and population and design weights are applied. Table 6. Multinomial logit regression for party preference (robust SEs in parentheses)   Model 1     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.107  (0.16)  −0.012  (0.19)   Solo self-employed  −0.605 **  (0.24)  0.288 **  (0.12)   Employer  −0.853 ***  (0.15)  −0.413 **  (0.18)  Perceived income insecurity  0.225 ***  (0.04)  0.046  (0.08)  Perceived employment insecurity  −0.009  (0.02)  0.055  (0.09)  Perceived job autonomy  −0.319 *  (0.19)  −0.076  (0.06)  Income  −0.087 ***  (0.02)  −0.099 ***  (0.02)  Occupation (Professionals = ref)  –  –  –  –   Managers  −0.599 *  (0.34)  −0.619 **  (0.31)   Low-skilled Non-Manual  −0.467 ***  (0.16)  −0.656 ***  (0.21)   High-skilled Manual  −0.243  (0.15)  −0.905 *  (0.54)   Low-skilled Manual  0.113  (0.16)  −0.411  (0.48)  Part-time  0.185 *  (0.10)  0.466 ***  (0.11)  Age  0.012 ***  (0.00)  −0.002  (0.00)  Female  0.229 ***  (0.06)  0.199  (0.14)  Education (lower = ref)  –  –  –  –   Middle  0.071  (0.12)  −0.222  (0.19)   High  0.199  (0.12)  0.704 ***  (0.07)  Constant  0.252 *  (0.15)  −3.224 ***  (0.34)    Model 1     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.107  (0.16)  −0.012  (0.19)   Solo self-employed  −0.605 **  (0.24)  0.288 **  (0.12)   Employer  −0.853 ***  (0.15)  −0.413 **  (0.18)  Perceived income insecurity  0.225 ***  (0.04)  0.046  (0.08)  Perceived employment insecurity  −0.009  (0.02)  0.055  (0.09)  Perceived job autonomy  −0.319 *  (0.19)  −0.076  (0.06)  Income  −0.087 ***  (0.02)  −0.099 ***  (0.02)  Occupation (Professionals = ref)  –  –  –  –   Managers  −0.599 *  (0.34)  −0.619 **  (0.31)   Low-skilled Non-Manual  −0.467 ***  (0.16)  −0.656 ***  (0.21)   High-skilled Manual  −0.243  (0.15)  −0.905 *  (0.54)   Low-skilled Manual  0.113  (0.16)  −0.411  (0.48)  Part-time  0.185 *  (0.10)  0.466 ***  (0.11)  Age  0.012 ***  (0.00)  −0.002  (0.00)  Female  0.229 ***  (0.06)  0.199  (0.14)  Education (lower = ref)  –  –  –  –   Middle  0.071  (0.12)  −0.222  (0.19)   High  0.199  (0.12)  0.704 ***  (0.07)  Constant  0.252 *  (0.15)  −3.224 ***  (0.34)  Notes: * P  < 0.1; ** P  < 0.05; *** P  < 0.01 (two-tailed test); robust SEs for country-clustering. Population size and design weights applied. Not shown: country-dummy variables. View Large Table 6. Multinomial logit regression for party preference (robust SEs in parentheses)   Model 1     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.107  (0.16)  −0.012  (0.19)   Solo self-employed  −0.605 **  (0.24)  0.288 **  (0.12)   Employer  −0.853 ***  (0.15)  −0.413 **  (0.18)  Perceived income insecurity  0.225 ***  (0.04)  0.046  (0.08)  Perceived employment insecurity  −0.009  (0.02)  0.055  (0.09)  Perceived job autonomy  −0.319 *  (0.19)  −0.076  (0.06)  Income  −0.087 ***  (0.02)  −0.099 ***  (0.02)  Occupation (Professionals = ref)  –  –  –  –   Managers  −0.599 *  (0.34)  −0.619 **  (0.31)   Low-skilled Non-Manual  −0.467 ***  (0.16)  −0.656 ***  (0.21)   High-skilled Manual  −0.243  (0.15)  −0.905 *  (0.54)   Low-skilled Manual  0.113  (0.16)  −0.411  (0.48)  Part-time  0.185 *  (0.10)  0.466 ***  (0.11)  Age  0.012 ***  (0.00)  −0.002  (0.00)  Female  0.229 ***  (0.06)  0.199  (0.14)  Education (lower = ref)  –  –  –  –   Middle  0.071  (0.12)  −0.222  (0.19)   High  0.199  (0.12)  0.704 ***  (0.07)  Constant  0.252 *  (0.15)  −3.224 ***  (0.34)    Model 1     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.107  (0.16)  −0.012  (0.19)   Solo self-employed  −0.605 **  (0.24)  0.288 **  (0.12)   Employer  −0.853 ***  (0.15)  −0.413 **  (0.18)  Perceived income insecurity  0.225 ***  (0.04)  0.046  (0.08)  Perceived employment insecurity  −0.009  (0.02)  0.055  (0.09)  Perceived job autonomy  −0.319 *  (0.19)  −0.076  (0.06)  Income  −0.087 ***  (0.02)  −0.099 ***  (0.02)  Occupation (Professionals = ref)  –  –  –  –   Managers  −0.599 *  (0.34)  −0.619 **  (0.31)   Low-skilled Non-Manual  −0.467 ***  (0.16)  −0.656 ***  (0.21)   High-skilled Manual  −0.243  (0.15)  −0.905 *  (0.54)   Low-skilled Manual  0.113  (0.16)  −0.411  (0.48)  Part-time  0.185 *  (0.10)  0.466 ***  (0.11)  Age  0.012 ***  (0.00)  −0.002  (0.00)  Female  0.229 ***  (0.06)  0.199  (0.14)  Education (lower = ref)  –  –  –  –   Middle  0.071  (0.12)  −0.222  (0.19)   High  0.199  (0.12)  0.704 ***  (0.07)  Constant  0.252 *  (0.15)  −3.224 ***  (0.34)  Notes: * P  < 0.1; ** P  < 0.05; *** P  < 0.01 (two-tailed test); robust SEs for country-clustering. Population size and design weights applied. Not shown: country-dummy variables. View Large In Model 1, the general expectation is tested that temporary employees are, everything else held equal, politically more to the left (i.e. are more likely to support old- or new-left parties) and self-employed workers are politically more to the right (i.e. less likely to support old- or new-left parties). People working on permanent employment contracts function as the reference group. Model 1 shows that people in solo self-employment are indeed less likely (−0.605) to prefer an old-left party. Support for the old-left is lowest for employers, that is, for self-employed with personnel (−0.853). Yet, with respect to new-left versus right-wing parties the effect of solo self-employment is even positive (0.288). Surprisingly, solo self-employed workers are even more strongly oriented toward new-left parties, compared with permanent employees. Moreover, contrarily the expectation, there are no significant effects for temporary employment. Compared with employees on permanent contracts, temporary workers neither have a stronger preference for old-left parties, nor for new-left parties. To assess whether the effects of employment type are moderated by income insecurity, employment insecurity and job autonomy, interactions should be introduced. Before adding these interaction effects, I first examine the direct effects of these variables on party preference. Model 1 shows that income insecurity (0.225) is positively related to an old-left party orientation (vs. an orientation toward right-wing parties). People whose income is more insecure more often prefer old-left versus right-wing parties. Moreover, job autonomy shows a negative association with old-left party preferences (−0.319), indicating that people with greater autonomy at the workplace are less likely to prefer old-left parties. With respect to new-left party preferences, however, I find no direct effects of income insecurity and job autonomy. New-left party preferences seem unrelated to perceived insecurities in income and/or the degree of autonomy at the workplace. In Table 7 interaction effects are estimated between employment types on the one hand, and on the other hand income insecurity (Model 2), employment insecurity (Model 3) and job autonomy (Model 4). Let me first assess the moderating effect of income insecurity: with respect to supporting the old-left, Model 2 shows significant and positive interactions for temporary employment (0.505) and the solo self-employment (0.235). These effects indicate that, temporary workers and self-employed workers have a stronger preference for old-left parties when their income situation is more insecure. To ease interpretation, I have plotted these effects in Figure 4 . The other way around, Figure 4 also shows that right-wing party support among temporary employees and self-employed declines when income insecurity is higher; although for self-employed workers this effect seems surrounded with relatively high levels of uncertainty. What appears from both the table and the plots, it that new-left party orientations are not strongly moderated by income insecurity. Neither temporary employees, nor self-employed are more included to prefer new-left parties under greater uncertainty of income. Figure 4. View largeDownload slide Interaction effects with perceived income insecurity (predicted probabilities) † . † Confidence intervals (95%) for the solo self-employed and permanent wage-employees. Figure 4. View largeDownload slide Interaction effects with perceived income insecurity (predicted probabilities) † . † Confidence intervals (95%) for the solo self-employed and permanent wage-employees. Table 7. Interaction effects for party preference based on multinomial logit regression (robust SEs in parentheses)   Model 2     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.595 *  (0.31)  0.033  (0.33)   Solo self-employed  −0.806 ***  (0.22)  0.277 **  (0.11)   Employer  −0.891 ***  (0.16)  −0.815 ***  (0.29)  Perceived income insecurity  0.150 ***  (0.04)  0.028  (0.09)   ×Temporary employee  0.505 ***  (0.18)  −0.057  (0.23)   × Solo self-employed  0.235 ***  (0.06)  0.018  (0.20)   × Employer  0.046  (0.12)  0.729 **  (0.31)      Model 3     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE    Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.515 **  (0.25)  −0.037  (0.26)   Solo self-employed  −0.772 ***  (0.26)  −0.325 ***  (0.12)   Employer  −0.933 ***  (0.26)  −0.681 ***  (0.18)  Perceived employment insecurity  −0.093 ***  (0.03)  −0.077  (0.06)   ×Temporary employee  0.385 ***  (0.08)  0.072  (0.10)   × Solo self-employed  0.283 ***  (0.07)  0.879 ***  (0.32)   × Employer  0.170  (0.37)  0.589 ***  (0.11)      Model 4     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE    Employment (permanent employee = ref)  –  –  –  –   Temporary employee  0.057  (0.15)  −0.390  (0.29)   Solo self-employed  0.049  (0.41)  0.679  (0.43)   Employer  −2.511 **  (1.00)  1.156 **  (0.49)  Perceived job autonomy  −0.195  (0.19)  −0.138  (0.08)   ×Temporary employee  −0.604 **  (0.24)  1.116 ***  (0.32)   × Solo self-employed  −0.874  (0.65)  −0.423  (0.47)   × Employer  1.705  (1.15)  −1.730 **  (0.74)    Model 2     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.595 *  (0.31)  0.033  (0.33)   Solo self-employed  −0.806 ***  (0.22)  0.277 **  (0.11)   Employer  −0.891 ***  (0.16)  −0.815 ***  (0.29)  Perceived income insecurity  0.150 ***  (0.04)  0.028  (0.09)   ×Temporary employee  0.505 ***  (0.18)  −0.057  (0.23)   × Solo self-employed  0.235 ***  (0.06)  0.018  (0.20)   × Employer  0.046  (0.12)  0.729 **  (0.31)      Model 3     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE    Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.515 **  (0.25)  −0.037  (0.26)   Solo self-employed  −0.772 ***  (0.26)  −0.325 ***  (0.12)   Employer  −0.933 ***  (0.26)  −0.681 ***  (0.18)  Perceived employment insecurity  −0.093 ***  (0.03)  −0.077  (0.06)   ×Temporary employee  0.385 ***  (0.08)  0.072  (0.10)   × Solo self-employed  0.283 ***  (0.07)  0.879 ***  (0.32)   × Employer  0.170  (0.37)  0.589 ***  (0.11)      Model 4     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE    Employment (permanent employee = ref)  –  –  –  –   Temporary employee  0.057  (0.15)  −0.390  (0.29)   Solo self-employed  0.049  (0.41)  0.679  (0.43)   Employer  −2.511 **  (1.00)  1.156 **  (0.49)  Perceived job autonomy  −0.195  (0.19)  −0.138  (0.08)   ×Temporary employee  −0.604 **  (0.24)  1.116 ***  (0.32)   × Solo self-employed  −0.874  (0.65)  −0.423  (0.47)   × Employer  1.705  (1.15)  −1.730 **  (0.74)  Notes: * P  < 0.1; ** P  < 0.05; *** P  < 0.01 (two-tailed test); robust SEs for country-clustering. Population size and design weights applied. All models controlled for income, occupational class, part-time, age, gender, education, and country-dummies (see Table 4 ). View Large Table 7. Interaction effects for party preference based on multinomial logit regression (robust SEs in parentheses)   Model 2     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.595 *  (0.31)  0.033  (0.33)   Solo self-employed  −0.806 ***  (0.22)  0.277 **  (0.11)   Employer  −0.891 ***  (0.16)  −0.815 ***  (0.29)  Perceived income insecurity  0.150 ***  (0.04)  0.028  (0.09)   ×Temporary employee  0.505 ***  (0.18)  −0.057  (0.23)   × Solo self-employed  0.235 ***  (0.06)  0.018  (0.20)   × Employer  0.046  (0.12)  0.729 **  (0.31)      Model 3     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE    Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.515 **  (0.25)  −0.037  (0.26)   Solo self-employed  −0.772 ***  (0.26)  −0.325 ***  (0.12)   Employer  −0.933 ***  (0.26)  −0.681 ***  (0.18)  Perceived employment insecurity  −0.093 ***  (0.03)  −0.077  (0.06)   ×Temporary employee  0.385 ***  (0.08)  0.072  (0.10)   × Solo self-employed  0.283 ***  (0.07)  0.879 ***  (0.32)   × Employer  0.170  (0.37)  0.589 ***  (0.11)      Model 4     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE    Employment (permanent employee = ref)  –  –  –  –   Temporary employee  0.057  (0.15)  −0.390  (0.29)   Solo self-employed  0.049  (0.41)  0.679  (0.43)   Employer  −2.511 **  (1.00)  1.156 **  (0.49)  Perceived job autonomy  −0.195  (0.19)  −0.138  (0.08)   ×Temporary employee  −0.604 **  (0.24)  1.116 ***  (0.32)   × Solo self-employed  −0.874  (0.65)  −0.423  (0.47)   × Employer  1.705  (1.15)  −1.730 **  (0.74)    Model 2     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.595 *  (0.31)  0.033  (0.33)   Solo self-employed  −0.806 ***  (0.22)  0.277 **  (0.11)   Employer  −0.891 ***  (0.16)  −0.815 ***  (0.29)  Perceived income insecurity  0.150 ***  (0.04)  0.028  (0.09)   ×Temporary employee  0.505 ***  (0.18)  −0.057  (0.23)   × Solo self-employed  0.235 ***  (0.06)  0.018  (0.20)   × Employer  0.046  (0.12)  0.729 **  (0.31)      Model 3     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE    Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.515 **  (0.25)  −0.037  (0.26)   Solo self-employed  −0.772 ***  (0.26)  −0.325 ***  (0.12)   Employer  −0.933 ***  (0.26)  −0.681 ***  (0.18)  Perceived employment insecurity  −0.093 ***  (0.03)  −0.077  (0.06)   ×Temporary employee  0.385 ***  (0.08)  0.072  (0.10)   × Solo self-employed  0.283 ***  (0.07)  0.879 ***  (0.32)   × Employer  0.170  (0.37)  0.589 ***  (0.11)      Model 4     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE    Employment (permanent employee = ref)  –  –  –  –   Temporary employee  0.057  (0.15)  −0.390  (0.29)   Solo self-employed  0.049  (0.41)  0.679  (0.43)   Employer  −2.511 **  (1.00)  1.156 **  (0.49)  Perceived job autonomy  −0.195  (0.19)  −0.138  (0.08)   ×Temporary employee  −0.604 **  (0.24)  1.116 ***  (0.32)   × Solo self-employed  −0.874  (0.65)  −0.423  (0.47)   × Employer  1.705  (1.15)  −1.730 **  (0.74)  Notes: * P  < 0.1; ** P  < 0.05; *** P  < 0.01 (two-tailed test); robust SEs for country-clustering. Population size and design weights applied. All models controlled for income, occupational class, part-time, age, gender, education, and country-dummies (see Table 4 ). View Large Next, in Model 3 interactions are included with employment insecurity. Again, I find positive interactions for temporary employees (0.385) and solo self-employed (0.283) in case of the old-left/right-wing contrast. Figure 5 shows that temporary workers are more strongly orientated toward old-left parties when their employment is more insecure. For people in solo self-employment job insecurity seems associated (albeit with some uncertainty) with a weaker right-wing orientation, but not necessarily with a stronger orientation toward the old-left. Instead, as an alternative for right-wing parties, insecure self-employed workers tend to support new-left parties. All in all, there seems support for hypotheses 3a and 3b: Not only the left-wing political orientation of temporary workers is stronger as their economic insecurities are higher, but also the left-wing orientation of solo self-employed workers. Figure 5. View largeDownload slide Interaction effects with perceived employment insecurity (predicted probabilities) † . † Confidence intervals (95%) for the solo self-employed and permanent wage-employees. Figure 5. View largeDownload slide Interaction effects with perceived employment insecurity (predicted probabilities) † . † Confidence intervals (95%) for the solo self-employed and permanent wage-employees. Finally, Model 4 includes interaction effects between employment type and job autonomy. For solo self-employment these interaction do not reach significance, indicating that for self-employed workers their degree of job autonomy does not moderate their party orientation. Hence, these results do not corroborate hypothesis 2b, the right-wing political orientation of self-employed workers is not stronger as they have more autonomy over their job. For temporary workers, however, I find a significant negative interaction effect with job autonomy regarding old-left versus right-wing parties (−0.604) and a positive interaction effect regarding new-left versus right-wing parties (1.116). The plots in Figure 6 suggest that greater job autonomy strengthens in particular new-left orientations, rather than right-wing orientations. As far as the old-left is concerned, the plots indicate that the moderating effect of job autonomy is surrounded with relatively high levels of uncertainty. The results therefore provide little to no support for the hypothesis that left-wing political orientation of temporary workers is weaker as they have more autonomy over their job (hypothesis 2a). Figure 6. View largeDownload slide Interaction effects with job autonomy (predicted probabilities) † . † Confidence intervals (95%). Figure 6. View largeDownload slide Interaction effects with job autonomy (predicted probabilities) † . † Confidence intervals (95%). 5. Conclusion The main aim of the current study was to extend the research into the political effects of atypical work by comparing the political orientations of self-employed workers to those of people in temporary employment. The growth of temporary work in Europe and the revival of self-employment are both considered to be processes related to the flexibilization of labor markets. These processes are generally assumed to have weakened the position of workers vis-à-vis employers by partially transferring market risks to ‘atypical’ workers by short-term hiring and outsourcing to freelancers. New political divisions would arise between those with and without secure labor market positions. The novelty of this study was to compare the effect of self-employment on policy and party preferences to the effect of temporary employment. The self-employed are worthwhile examining because of their ‘Janus face’ in the labor market literature ( Mevissen and Van der Berg, 2011 ), i.e.: on the one hand belonging to the insiders of the labor market as a group of independent entrepreneurs, while on the other hand belonging to the labor market outsiders as precarious workers in quasi-autonomous employment relationships (see also Barbieri and Scherer, 2009 ). The findings from this study suggest that in general people in solo self-employment are more strongly orientated toward rightist positions regarding welfare policies and that in terms of party support, they more often prefer right-wing parties over ‘old’ left-wing parties, such as the social democrats and (former) communists. Interestingly, when it comes to their orientation toward new-left parties, solo self-employed workers are even more supportive of this type of parties compared with paid-employees. Temporary employees, on the other hand, are generally somewhat more to the left, in particular with respect to welfare state support—but not necessarily with respect to party preferences. By and large, these finding would indicate that self-employed workers have a distinct pattern of political orientation, one that is very different from the attitudes of people in (temporary) paid-employment. Yet, another major goal of the current study was to determine whether the political orientations of people in self-employment would be more toward the left—and therefore more close toward the views of (temporary) employees, as they have a more precarious position on the labor market. For this purpose, I examined how employment insecurity and income insecurity moderate the effect of self-employment on policy and party orientations. Taken together, the results suggest that people in solo self-employment are generally more likely to support welfare policies and (new)left parties—and oppose right-wing parties—as they are more insecure with respect to their income and/or job. This study therefore is the first to show that economic vulnerabilities might challenge the archetypical image of people in self-employment as an economic conservative, political right-wing class. This observation suggests that particular segments of self-employment may share the characteristics of other forms of ‘atypical’ work, not only with respect to labor market insecurities, but also regarding the political orientations associated with such insecurities (c.f. Corbetta and Colloca, 2013 ; Marx and Picot, 2013 ; Marx, 2014 ). In fact, with respect to party preferences, this study shows that vulnerability affects self-employed workers and temporary employees in more or less similar fashion: greater insecurities strengthen left-wing political orientations and weaken right-wing political orientations. The second condition in this study to moderate the relationship between employment type and political orientations was the degree of job autonomy. In this respect, the results were less clear. With respect to pro-welfare attitudes, there is some evidence that job autonomy strengthens right-wing orientation among people in solo self-employment. With respect to party orientations, however, job autonomy only to some extent impacts the effect of temporary employment—but not self-employment: greater job autonomy to some extent strengthens new-left party orientations, but no clear patterns were found for old-left or right-wing party support. This finding does not support the observation that a lack of autonomy in the workplace can strengthen economic progressive, traditional left-wing preferences ( De Witte, 1999 ; Kitschelt and Rehm, 2014 ), even though temporary workers generally enjoy lower job discretion and job autonomy than permanent employees ( Gallie et al. , 1998 ). All in all, this study provides some indication for the notion that politically the self-employment are more heterogeneous than traditional class-based theories assume. Contrary to the image of (free market) right-wing entrepreneurship, there seems to be at least a section of the self-employed workers in Europe that, driven by rather precarious working conditions, are less strongly attached to rightist politics. This observation may have implications not only for the scientific study of self-employment, but also for politicians and policy-makers seeking to adapt labor laws and social protection policies aimed at self-employed persons without personnel ( Schulze Buschoff and Schmidt, 2009 ; Dekker, 2010 ). Especially for those who do not fit the ‘ideal-type’ entrepreneur, more targeted policies may be necessary. In spite of general individualistic approach to responsibility and accountability among self-employed, this study shows that the support for more collectivist and inclusive policies and parties is greater among self-employed persons that work under greater uncertainty and strain. The patterns emerging from this study, however, are not conclusive. A few limitations need to be considered. First, by using 2008 data only, this study is unable to address changes in the relationship between atypical work and political orientations. Longitudinal data would be required to study the long-term political consequences of heterogenization of self-employment since 1980s. Moreover, the pooled analysis of eight West European countries, obviously obscured country-to-country differences in this relationship, and ignores that the economic and institutional context of countries could moderate the relationship between perceived insecurities and political preferences ( Gingrich and Ansell, 2012 ). Future studies should address whether the political effects of self-employment are conditioned by a country’s degree of market competitiveness, and/or the legislative context regarding self-employment. Also larger national samples of self-employed workers, and specific self-employment surveys would help us to establish a greater degree of accuracy on this matter. Next, the current study had to rely on a party family categorization to measure party choice. Future research, however, may not only aim at more detailed measures of party orientations, but may also pursuit better measurements of political values and policy preferences. The relevance, for example, of ‘new-left’ parties taps into a second political value dimension (e.g. post-materialist vs. materialist values, or libertarian vs. authoritarian value) that is related to ‘new’ class politics (cf. Güveli et al. , 2007 ; Oesch, 2008 ). From this perspective, one finding from this study that needs further attention is the interaction between self-employment and perceived insecurity on the likelihood of voting for the new-left. It seems plausible that the support for new-left (and green) parties is strongest among particular segments of self-employed professionals, such as freelancers in social and cultural occupations (e.g. authors, journalists and other creative and cultural workers). Although highly educated, some of these professionals work in very competitive markets, where low entry barriers put pressure on tariffs and earnings. A programmatic blend combining an economic centrist agenda with cultural progressive issues and concerns for the environment (such as D’66 in the Netherlands or the Grünliberale in Switzerland), may be attractive to this group. Yet, whether liberal moral values intersect with economic vulnerabilities to function as a driving force of the political orientations among self-employed social–cultural professionals requires a level of detail beyond the scope of this study. Future research may look deeper into the relationship between atypical work and ‘new’ political dimensions, including also the support for populist right-wing parties (cf. Standing, 2011 ). Finally, in the current study precariousness is limited to insecurities about income, employment and job autonomy. In particular, the measure for employment insecurity is sub-optimal. For self-employed workers, this measure ignores risks more specifically associated with self-employment, such as unstable work through irregular orders, and low financial buffers to survive periods when little orders and money are coming in. Also for temporary employees, the question used here (i.e. ‘how likely it is that one will be unemployed and looking for work during the next 12 months’) is sub-optimal to measure employment risks, as it ignores the remaining contract duration. Future studies might investigate other aspects that link self-employment to ‘atypical work arrangements’, i.e. the extent to which someone is dependent on (structural) orders of a single client, or whether self-employment is a voluntary decision. Against the backdrop of the lack of this type of data (at least in the domain of political surveys) the present study serves as a valuable first step to examine the political implications of the risks associated with being self-employed in modern labor markets. Funding This research was supported by the Netherlands Organization for Scientific Research (NWO), grant 451-13-027. 1 The sector classification is derived from a Eurofound report on self-employment (1997) . In this classification, the hotel and restaurant industry is merged with the trade industries (wholesale and retail), not with the business sector or other services. In doing so, I follow Arum and Muller (2004) who consider restaurateurs to belong to the ‘traditional’ forms of self-employment. Hence, this distinction allows to better map the structural changes in self-employment, i.e., the decrease of the traditional forms vis-à-vis the rise of self-employment in ‘new’ sectors. 2 This phrase is borrowed from Celia and John Stanworth’s article (1995) ‘The self-employed without employees: autonomous or atypical’. 3 A principal axis factor analysis confirmed that these items relate to one dimension, also when conducted separately for each country. A sixth item, however, was excluded, i.e.: on the government’s responsibility for sufficient child care services for working parents. Including this item resulted in different factor solutions for different countries. To avoid unnecessarily loss of information, instead of using the factor scores to compute the dependent variable, I used the mean value over the items while allowing 2 missing values for each respondent. The mean-index score and the factor scores correlate very highly, and the results of this study do not substantially change when using the factor scores. 4 Two issues should be considered. First, the classification of the Manifesto Project Database is used with a few exceptions: Following Marx (2014) the Danish and Norwegian Socialist People’s Parties were classified as ‘new-left’ instead of ‘old-left’. Following Jansen et al. (2011), D’66 in the Netherlands is classified as ‘new-left’ instead of old-left. Second, the decision to use retrospective party choice, instead of party attachment, for respondents with no party attachment, is based on the assumption that—when recoded into three party categories—the two items do not substantially diverge. This assumption is supported by a relatively strong association between party attachment and retrospective vote choice among respondents with valid information on both items. The Cramers’ V based on the pooled sample is 0.82, indicating a fairly strong association between party attachment and vote choice. Moderately to very strong associations are also found for most countries, i.e.: Austria (0.90), Belgium (0.51), Switzerland (0.83), Germany (0.80), Denmark (0.89), France (0.74), Netherlands (0.85) and Norway (0.75). 5 To be able to generalize whether the results from a pooled analysis are indicative of a general European trend population weights are applied. In doing so, I follow a modeling strategy similar to the study of Marx (2014) on the political preferences of temporary workers. These weights correct for the fact that countries in the ESS data have different population sizes but similar sample sizes. References Arum R. Müller W. ( 2004 ). The Reemergence of Self-Employment: A Comparative Study of Self-Employment Dynamics and Social Inequality  , New Jersey , Princeton University Press . Barbieri P. Scherer S. ( 2009 ). ‘Labour Market Flexibilization and Its Consequences in Italy’ , European Sociological Review  , 25 , 677 – 692 . Google Scholar CrossRef Search ADS   Bögenhold D. Fachinger U. ( 2012 ). ‘How Diverse is Entrepreneurship? Observations on the Social Heterogeneity of Self-Employment in Germany’ . In Bonnet, J., Desjardin, M. and Madrid-Guijarro, A. (eds) The Shift to the Entrepreneurial Society: A Built Economy in Education, Sustainability and Regulation  , Cheltenhem, UK, Edward Elger, p. 227 . Bögenhold D. Staber U. ( 1991 ). ‘The Decline and Rise of Self-Employment’ , Work, Employment & Society  , 5 , 223 – 239 . Google Scholar CrossRef Search ADS   CIS (2008). ‘Spanish National Election Survey 2008’. [dataset]. Madrid, Centro de Investigaciones Sociológicas. Corbetta P. Colloca P. ( 2013 ). ‘Job Precariousness and Political Orientations: The Case of Italy’, South European Society and Politics  , 18 , 333 – 354 . Google Scholar CrossRef Search ADS   Dekker F. ( 2010 ). ‘Self‐Employed without Employees: Managing Risks in Modern Capitalism’, Politics & Policy  , 38 , 765 – 788 . Google Scholar CrossRef Search ADS   De Witte H. ( 1999 ). ‘On the Occupational Roots of Conservatism: Expanding Middendorp’s Analysis with the Concepts of Rotter and Kohn’ . In De Witte H. Scheepers P. (eds) Ideology in the Low Countries. Trends, Models and Lacunae  , van Gorcum , Assen , pp. 69 – 89 . Emmenegger P. ( 2009 ). ‘Barriers to Entry: Insider/Outsider Politics and the Political Determinants of Job Security Regulations’ , Journal of European Social Policy  , 19 , 131 – 146 . Google Scholar CrossRef Search ADS   Evans G. (ed.) ( 1999 ). The End of Class Politics? Class Voting in Comparative Context  , Oxford , Oxford University Press . Evans G. de Graaf N. D. (eds) ( 2013 ). Political Choice Matters: Explaining the Strength of Class and Religious Cleavages in Cross-National Perspective  , Oxford , Oxford University Press . ESS Round 4 ( 2008 ). European Social Survey Round 4. Data file edition 4.3. Norwegian Social Science Data Services, Norway – Data Archive and distributor of ESS data for ESS ERIC. Eurofound ( 1997 ). The Working Conditions of the Self-Employed in the European Union , Dublin, European Foundation for the Improvement of Living and Working Conditions. Eurostat ( 2014 ). European Labor Force Surveys. LFS Series – Detailed Annual Survey Results, 1994, 1995, 2004, 2014 [Database]. accessed at http://ec.europa.eu/eurostat/web/lfs/data/data-base on January 11, 2016. Gallie D. White M. Cheng Y Tomlinson M. ( 1998 ). Restructuring the Employment Relationship  , Oxford , Oxford University Press . Gingrich J. Ansell B. ( 2012 ). ‘Preferences in Context. Micro Preferences, Macro Contexts, and the Demand for Social Policy’, Comparative Political Studies  , 45 , 1624 – 1654 . Google Scholar CrossRef Search ADS   Güveli A. Need A. De Graaf N. D. ( 2007 ). ‘The Rise of “New” Social Classes within the Service Class in The Netherlands. Political Orientation of Social and Cultural Specialists and Technocrats between 1970 and 2003’ . Acta Sociologica  , 50 , 129 – 146 . Google Scholar CrossRef Search ADS   Iversen T. Soskice D. ( 2001 ). ‘An Asset Theory of Social Policy Preferences’ , American Political Science Review  , 95 , 875 – 894 . Jansen G. ( 2011 ). Social Cleavages and Political Choices: Large Scale Comparisons of Social Class, Religion and Voting Behaviour in Western Democracies , ICS Dissertation, Nijmegen, Radboud University. Jansen G. De Graaf N. D. Need A. ( 2011 ). ‘Class Voting, Social Changes and Political Changes in the Netherlands 1971–2006’, Electoral Studies  , 30 , 510 – 524 . Google Scholar CrossRef Search ADS   Kalleberg A. L. ( 2000 ). Nonstandard Employment Relations: Part-Time, Temporary and Contract Work, Annual review of sociology  , 26 , 341 – 365 . Google Scholar CrossRef Search ADS   Kitschelt H. Rehm P. ( 2014 ). ‘Occupations as a Site of Political Preference Formation’ , Comparative Political Studies  , 47 , 1670 – 1706 . Google Scholar CrossRef Search ADS   Knutsen O. ( 2006 ). Class Voting in Western Europe: a Comparative Longitudinal Study  , Oxford , Lexington Books . Kohn M. L. ( 1995 ). ‘Social Structure and Personality through Time and Space’ . In: Moen P. Elder G. Lüscher K.E. (eds) Examining Lives in Context: Perspectives on the Ecology of Human Development  . Washington, DC: American Psychological Association , pp. 141 – 168 . Kösters L. Smits W. de Vries R. ( 2013 ). ‘De ene zzp’er is de andere niet’. In van Gaalen, R., Goudswaard, A., Sanders, J. and Smits, W. (eds) Dynamiek op de Nederlandse arbeidsmarkt. De focus op flexibilisering , Den Haag/Heerlen, CBS/TNO, 139 – 153 . Lofstrom M. ( 2013 ). ‘Does Self-Employment Increase the Economic Well-Being of Low-Skilled Workers?’ Small Business Economics  , 40 , 933 – 952 . Google Scholar CrossRef Search ADS   Marx P. ( 2014 ). ‘Labour Market Risks and Political Preferences: The Case of Temporary Employment’, European Journal of Political Research  , 53 , 136 – 159 . Google Scholar CrossRef Search ADS   Marx P. Picot G. ( 2013 ). ‘The Party Preferences of Atypical Workers in Germany’, Journal of European Social Policy  , 23 , 164 – 178 . Google Scholar CrossRef Search ADS   McManus P. A. ( 2000 ). ‘Market, State, and the Quality of new Self-Employment Jobs among Men in the US and Western Germany’, Social forces  , 78 , 865 – 905 . Google Scholar CrossRef Search ADS   Mevissen J. Van der Berg N ( 2011 ). ‘De januskop van de zzp’er : De zelfstandige zonder personeel: ondernemer of eigenlijk een werknemer?’, Tijdschrift voor Arbeidsvraagstukken  , 27 , 264 – 280 . Millán J. M. Congregado E. Román C. ( 2014 ). Persistence in Entrepreneurship and Its Implications for the European Entrepreneurial Promotion Policy’, Journal of Policy Modeling  , 36 , 83 – 106 . Google Scholar CrossRef Search ADS   Muehlberger U. ( 2007 ). Dependent Self-Employment: Workers on the Border between Employment and Self Employment  , New York , Palgrave Macmillan . Mughan A. ( 2007 ). ‘Economic Insecurity and Welfare Preferences: A Micro-Level Analysis’ , Comparative Politics  , 39 , 293 – 310 . Nieuwbeerta P. De Graaf N. D. ( 1999 ). ‘Traditional Class Voting in Twenty Postwar Societies’. In Evans G. (ed.) The End of Class Politics  , Oxford , Oxford university Press , pp. 23 – 56 . OECD . 2000 . ‘The Partial Renaissance of Self-Employment’. In OECD Economic Outlook , Paris, Organisation for Economic Co-operation and Development. Oesch D. ( 2008 ). ‘The Changing Shape of Class Voting: An Individual-Level Analysis of Party Support in Britain, Germany and Switzerland’, European Societies  , 10 , 329 – 355 . Google Scholar CrossRef Search ADS   Oesch D. ( 2015 ). ‘Occupational Structure and Labor Market Change in Western Europe Since 1990’ . In Beramendi P. Häusermann S. Kitschelt H. Kriesi H. (eds) The Politics of Advanced Capitalism  , Cambridge, Cambridge University Press , pp. 112 – 132 . Pedersini R. Coletto D. ( 2010 ). Self-Employed Workers: Industrial Relations and Working Conditions , Dublin, European Foundation for the Improvement of Living and Working Conditions. Pernicka S. ( 2006 ). ‘Organizing the Self-Employed: Theoretical Considerations and Empirical Findings’, European Journal of Industrial Relations  , 12 , 125 – 142 . Google Scholar CrossRef Search ADS   Rehm P. ( 2011 ). ‘Social Policy by Popular Demand’, World Politics  , 63 , 271 – 299 . Google Scholar CrossRef Search ADS   Román C. Congregado E. Millán J. M. ( 2011 ). ‘Dependent Self-Employment as a Way to Evade Employment Protection Legislation’, Small Business Economics  , 37 , 363 – 392 . Google Scholar CrossRef Search ADS   Rueda D. ( 2005 ). ‘Insider–Outsider Politics in Industrialized Democracies: the Challenge to Social Democratic Parties’ , American Political Science Review  , 99 , 61 – 74 . Google Scholar CrossRef Search ADS   Schulze Buschoff K. S. Protsch P. ( 2008 ). ‘(A‐) Typical and (in‐) Secure? Social Protection and ‘Non‐Standard’ Forms of Employment in Europe’ , International Social Security Review  , 61 , 51 – 73 . Google Scholar CrossRef Search ADS   Schulze Buschoff K. S. Schmidt C. ( 2009 ). ‘Adapting Labour Law and Social Security to the Needs of the “New Self-Employed”—Comparing the UK, Germany and the Netherlands’, Journal of European Social Policy  , 19 , 147 – 159 . Google Scholar CrossRef Search ADS   Standing G. ( 2011 ). The Precariat: The New Dangerous Class  , London, Bloomsbury Publishing . Stanworth C. Stanworth J. ( 1995 ). ‘The Self‐Employed without Employees. Autonomous or Atypical?’, Industrial Relations Journal  , 26 , 221 – 229 . Google Scholar CrossRef Search ADS   The Comparative Study of Electoral Systems ( 2015a ) ( www.cses.org ). CSES MODULE 2 FULL RELEASE [dataset]. December 15, 2015 version. doi:10.7804/cses.module2.2015-12-15 The Comparative Study of Electoral Systems ( 2015b ) ( www.cses.org ). CSES MODULE 3 FULL RELEASE [dataset]. December 15, 2015 version. doi:10.7804/cses.module3.2015-12-15 Van Stel A. J. Wennekers S. Scholman G. ( 2014 ). Solo Self-employed versus Employer Entrepreneurs: Determinants and Macro-economic Effects in OECD Countries , Vol. 201212. Zoetermeer, EIM Research Report. Volkens A. Lehmann P. Merz N. Regel S. Werner A. Lacewell O.P. Schultze H. ( 2013 ). The Manifesto Data Collection. Manifesto Project (MRG/CMP/MARPOR). Version 2013b  , Berlin , Wissenschaftszentrum Berlin für Sozialforschung (WZB ). Appendix Table A1. Descriptive statistics ( N  = 7186)   Min.  Max.  Mean  SD  Dependent Variables          Pro-welfare attitudes  0.00  10.00  7.02  1.42  Party Preference (N = 5564)           New-left  0.00  1.00  0.14  0.34   Old-left  0.00  1.00  0.39  0.49   Right-wing  0.00  1.00  0.47  0.50  Independent Variables          Permanent employee  0.00  1.00  0.76  0.43  temporary employee  0.00  1.00  0.12  0.33  Solo self-employed  0.00  1.00  0.07  0.26  Employer  0.00  1.00  0.05  0.21  Perceived income insecurity  0.00  2.00  0.74  0.66  Perceived employment insecurity  0.00  2.00  0.67  0.69  Perceived job autonomy  0.00  1.00  0.39  0.34  Managers  0.00  1.00  0.08  0.27  Professionals  0.00  1.00  0.44  0.50  Low-skilled Non-Manual  0.00  1.00  0.24  0.43  High-skilled Manual  0.00  1.00  0.13  0.33  Low-skilled Manual  0.00  1.00  0.12  0.32  Income  1.00  10.00  6.39  2.58  Part-time  0.00  1.00  0.16  0.37  Age (15 = 0)  0.00  49.00  27.32  10.89  Female  0.00  1.00  0.46  0.50  Low-level education  0.00  1.00  0.13  0.34  Medium-level education  0.00  1.00  0.50  0.50  High-level education  0.00  1.00  0.37  0.48    Min.  Max.  Mean  SD  Dependent Variables          Pro-welfare attitudes  0.00  10.00  7.02  1.42  Party Preference (N = 5564)           New-left  0.00  1.00  0.14  0.34   Old-left  0.00  1.00  0.39  0.49   Right-wing  0.00  1.00  0.47  0.50  Independent Variables          Permanent employee  0.00  1.00  0.76  0.43  temporary employee  0.00  1.00  0.12  0.33  Solo self-employed  0.00  1.00  0.07  0.26  Employer  0.00  1.00  0.05  0.21  Perceived income insecurity  0.00  2.00  0.74  0.66  Perceived employment insecurity  0.00  2.00  0.67  0.69  Perceived job autonomy  0.00  1.00  0.39  0.34  Managers  0.00  1.00  0.08  0.27  Professionals  0.00  1.00  0.44  0.50  Low-skilled Non-Manual  0.00  1.00  0.24  0.43  High-skilled Manual  0.00  1.00  0.13  0.33  Low-skilled Manual  0.00  1.00  0.12  0.32  Income  1.00  10.00  6.39  2.58  Part-time  0.00  1.00  0.16  0.37  Age (15 = 0)  0.00  49.00  27.32  10.89  Female  0.00  1.00  0.46  0.50  Low-level education  0.00  1.00  0.13  0.34  Medium-level education  0.00  1.00  0.50  0.50  High-level education  0.00  1.00  0.37  0.48  Notes: Population size and design weights applied. View Large Table A1. Descriptive statistics ( N  = 7186)   Min.  Max.  Mean  SD  Dependent Variables          Pro-welfare attitudes  0.00  10.00  7.02  1.42  Party Preference (N = 5564)           New-left  0.00  1.00  0.14  0.34   Old-left  0.00  1.00  0.39  0.49   Right-wing  0.00  1.00  0.47  0.50  Independent Variables          Permanent employee  0.00  1.00  0.76  0.43  temporary employee  0.00  1.00  0.12  0.33  Solo self-employed  0.00  1.00  0.07  0.26  Employer  0.00  1.00  0.05  0.21  Perceived income insecurity  0.00  2.00  0.74  0.66  Perceived employment insecurity  0.00  2.00  0.67  0.69  Perceived job autonomy  0.00  1.00  0.39  0.34  Managers  0.00  1.00  0.08  0.27  Professionals  0.00  1.00  0.44  0.50  Low-skilled Non-Manual  0.00  1.00  0.24  0.43  High-skilled Manual  0.00  1.00  0.13  0.33  Low-skilled Manual  0.00  1.00  0.12  0.32  Income  1.00  10.00  6.39  2.58  Part-time  0.00  1.00  0.16  0.37  Age (15 = 0)  0.00  49.00  27.32  10.89  Female  0.00  1.00  0.46  0.50  Low-level education  0.00  1.00  0.13  0.34  Medium-level education  0.00  1.00  0.50  0.50  High-level education  0.00  1.00  0.37  0.48    Min.  Max.  Mean  SD  Dependent Variables          Pro-welfare attitudes  0.00  10.00  7.02  1.42  Party Preference (N = 5564)           New-left  0.00  1.00  0.14  0.34   Old-left  0.00  1.00  0.39  0.49   Right-wing  0.00  1.00  0.47  0.50  Independent Variables          Permanent employee  0.00  1.00  0.76  0.43  temporary employee  0.00  1.00  0.12  0.33  Solo self-employed  0.00  1.00  0.07  0.26  Employer  0.00  1.00  0.05  0.21  Perceived income insecurity  0.00  2.00  0.74  0.66  Perceived employment insecurity  0.00  2.00  0.67  0.69  Perceived job autonomy  0.00  1.00  0.39  0.34  Managers  0.00  1.00  0.08  0.27  Professionals  0.00  1.00  0.44  0.50  Low-skilled Non-Manual  0.00  1.00  0.24  0.43  High-skilled Manual  0.00  1.00  0.13  0.33  Low-skilled Manual  0.00  1.00  0.12  0.32  Income  1.00  10.00  6.39  2.58  Part-time  0.00  1.00  0.16  0.37  Age (15 = 0)  0.00  49.00  27.32  10.89  Female  0.00  1.00  0.46  0.50  Low-level education  0.00  1.00  0.13  0.34  Medium-level education  0.00  1.00  0.50  0.50  High-level education  0.00  1.00  0.37  0.48  Notes: Population size and design weights applied. View Large © The Author 2016. Published by Oxford University Press and the Society for the Advancement of Socio-Economics. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/ ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Socio-Economic Review Oxford University Press

Self-employment as atypical or autonomous work: diverging effects on political orientations

Socio-Economic Review , Volume Advance Article – Sep 15, 2016

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Oxford University Press
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© The Author 2016. Published by Oxford University Press and the Society for the Advancement of Socio-Economics.
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1475-1461
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1475-147X
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Abstract

Abstract It is often held that the self-employed are an economically conservative, political right-wing class. Previous studies, however, have primarily dealt with self-employed workers as a relatively monolithic social class with shared interests as entrepreneurs and (potential) employers. But, with its recent rise, self-employment has developed into a heterogeneous employment type, with a growing number of dependent and precarious self-employed. In this article, the political preferences of people in self-employment are compared to the preferences of employees on temporary contracts. In doing so, hypotheses are tested from both classic theories on class voting, as well as theories on job precariousness and labor market vulnerabilities. For this purpose, European Social Survey Round 4 (ESS-4) data on eight West European countries are analyzed. The findings suggest that particular segments of self-employment share the characteristics of other forms of ‘atypical’ work, not only with respect to labor market insecurities, but also regarding the political orientations associated with such insecurities. 1. Introduction Labor market risks and job precariousness are increasingly identified as new lines of political division ( Iversen and Soskice, 2001 ; Mughan, 2007 ; Rehm, 2011 ; Corbetta and Colloca, 2013 ). People on permanent employment contracts are often defined as the ‘insiders’ at the labor market, whereas—together with the unemployed—people in atypical employment are seen as the so-called ‘outsiders’ ( Rueda, 2005 ; Emmenegger, 2009 ). Although all forms of employment relationships deviating from ‘standard’ full-time and permanent employment can be considered ‘non-standard’ or ‘atypical’ (e.g. part-time, fixed-term, agency work or self-employment), most studies concentrate upon the division between permanent and temporary employees. Temporary workers, compared with permanent workers, are often entitled to fewer social and labor rights, while being exposed to higher labor market risks ( Kalleberg, 2000 ). Recent studies addressing the effects on political preferences have therefore suggested that temporary workers are more supportive of redistribution policies and other social benefit programs, and are more likely to support (new) left-wing parties ( Corbetta and Colloca, 2013 ; Marx and Picot, 2013 ; Marx, 2014 ). In this article, I extend the research into the political effects of atypical work by focusing on self-employment. Although self-employment is often seen as a form of atypical work ( Stanworth and Stanworth, 1995 ; Pernicka, 2006 ; Schulze Buschoff and Protsch, 2008 ), two opposing views exist on how self-employment relates to political preferences. The dominant approach to these relationships relies on classic class-based theories that differentiate petty bourgeois/employer classes from employee classes ( Evans, 1999 ; Knutsen, 2006 ; Jansen, 2011 ; Evans and de Graaf, 2013 ). Based on their socioeconomic position, the self-employed are considered to be a relatively homogeneous social class with shared interests as entrepreneurs and (potential) employers. A common feature of class theories is the assumption that self-employment differs from paid-employment because it allows for greater individual autonomy in work, and it increases both the rewards and the costs of working on one’s own account ( Arum and Müller, 2004 , p. 6). They would prefer ‘free markets and a low level of social protection because they depend on flexible labor markets and often on relatively low-paid workers’ ( Iversen and Soskice, 2001 , p. 883). Taking individual responsibility for risks and returns associated with market changes, self-employed are assumed to oppose redistribution policies and collective security arrangements ( Iversen and Soskice, 2001 ; Emmenegger, 2009 ). Hence, class-based studies that treat the self-employment as a social grouping that is distinct from that of paid-employees, usually arrive at the conclusion that the self-employed are an economically conservative, political right-wing class. This general picture is confirmed by the frequencies in Table 1 on right-wing voting behavior in Europe, between 2001 and 2011. These data from the Comparative Study of Electoral Systems (CSES) suggest that in many European countries the tendency to vote right-wing was higher among voters in self-employment relative to voters in wage-employment. Moreover, the frequencies—although to be interpreted with some caution due to relatively low numbers of self-employed in the CSES data—suggest that about two-third or more of all voters in self-employment casted a ballot for a party on the right of the political spectrum. Table 1. Right-wing voting behavior by employment type in Europe, 2001–2011 †   Election  Employed  Self-employed  Austria  2008  51.7 ( N =402)   73.8 ( N =72)   Belgium  2003  65.2 ( N =800)   91.6 ( N =105)   Denmark  2001  61.8 ( N =682)   88.6 ( N =114)   Finland  2011  62.2 ( N =399)   73.5 ( N =44)   France  2007  47.1 ( N =702)   65.9 ( N =63)   Germany  2009  47.4 ( N =661)   65.6 ( N =59)   Greece  2009  37.6 ( N =217)   41.1 ( N =80)   Italy  2006  46.8 ( N =103)   57.7 ( N =32)   Netherlands  2010  46.1 ( N =778)   60.0 ( N =133)   Norway  2009  52.4 ( N =934)   78.4 ( N =97)   Portugal  2002  51.1 ( N =372)   64.6 ( N =78)   Spain  2008  31.4 ( N =1832)   45.5 ( N =176)   Sweden  2006  47.4 ( N =612)   72.2 ( N =72)   Switzerland  2011  56.0 ( N =894)   73.0 ( N =199)   UK  2005  51.9 ( N =281)   53.1 ( N =37)     Election  Employed  Self-employed  Austria  2008  51.7 ( N =402)   73.8 ( N =72)   Belgium  2003  65.2 ( N =800)   91.6 ( N =105)   Denmark  2001  61.8 ( N =682)   88.6 ( N =114)   Finland  2011  62.2 ( N =399)   73.5 ( N =44)   France  2007  47.1 ( N =702)   65.9 ( N =63)   Germany  2009  47.4 ( N =661)   65.6 ( N =59)   Greece  2009  37.6 ( N =217)   41.1 ( N =80)   Italy  2006  46.8 ( N =103)   57.7 ( N =32)   Netherlands  2010  46.1 ( N =778)   60.0 ( N =133)   Norway  2009  52.4 ( N =934)   78.4 ( N =97)   Portugal  2002  51.1 ( N =372)   64.6 ( N =78)   Spain  2008  31.4 ( N =1832)   45.5 ( N =176)   Sweden  2006  47.4 ( N =612)   72.2 ( N =72)   Switzerland  2011  56.0 ( N =894)   73.0 ( N =199)   UK  2005  51.9 ( N =281)   53.1 ( N =37)   † Selection based on respondents in employment who participated in the election and casted a valid vote; demographic and political weights applied (if available). Source:Comparative Study of Electoral Systems (2015a , b , Modules 2, 3); data for Spain are based on the Spanish National Election Study series election survey of 2008 ( CIS, 2008 ), own calculations. Right wing is defined based on the party classification of the Comparative Manifesto Project, i.e. including Liberal, Christian, Conservative, Nationalist and Agrarian parties. View Large Table 1. Right-wing voting behavior by employment type in Europe, 2001–2011 †   Election  Employed  Self-employed  Austria  2008  51.7 ( N =402)   73.8 ( N =72)   Belgium  2003  65.2 ( N =800)   91.6 ( N =105)   Denmark  2001  61.8 ( N =682)   88.6 ( N =114)   Finland  2011  62.2 ( N =399)   73.5 ( N =44)   France  2007  47.1 ( N =702)   65.9 ( N =63)   Germany  2009  47.4 ( N =661)   65.6 ( N =59)   Greece  2009  37.6 ( N =217)   41.1 ( N =80)   Italy  2006  46.8 ( N =103)   57.7 ( N =32)   Netherlands  2010  46.1 ( N =778)   60.0 ( N =133)   Norway  2009  52.4 ( N =934)   78.4 ( N =97)   Portugal  2002  51.1 ( N =372)   64.6 ( N =78)   Spain  2008  31.4 ( N =1832)   45.5 ( N =176)   Sweden  2006  47.4 ( N =612)   72.2 ( N =72)   Switzerland  2011  56.0 ( N =894)   73.0 ( N =199)   UK  2005  51.9 ( N =281)   53.1 ( N =37)     Election  Employed  Self-employed  Austria  2008  51.7 ( N =402)   73.8 ( N =72)   Belgium  2003  65.2 ( N =800)   91.6 ( N =105)   Denmark  2001  61.8 ( N =682)   88.6 ( N =114)   Finland  2011  62.2 ( N =399)   73.5 ( N =44)   France  2007  47.1 ( N =702)   65.9 ( N =63)   Germany  2009  47.4 ( N =661)   65.6 ( N =59)   Greece  2009  37.6 ( N =217)   41.1 ( N =80)   Italy  2006  46.8 ( N =103)   57.7 ( N =32)   Netherlands  2010  46.1 ( N =778)   60.0 ( N =133)   Norway  2009  52.4 ( N =934)   78.4 ( N =97)   Portugal  2002  51.1 ( N =372)   64.6 ( N =78)   Spain  2008  31.4 ( N =1832)   45.5 ( N =176)   Sweden  2006  47.4 ( N =612)   72.2 ( N =72)   Switzerland  2011  56.0 ( N =894)   73.0 ( N =199)   UK  2005  51.9 ( N =281)   53.1 ( N =37)   † Selection based on respondents in employment who participated in the election and casted a valid vote; demographic and political weights applied (if available). Source:Comparative Study of Electoral Systems (2015a , b , Modules 2, 3); data for Spain are based on the Spanish National Election Study series election survey of 2008 ( CIS, 2008 ), own calculations. Right wing is defined based on the party classification of the Comparative Manifesto Project, i.e. including Liberal, Christian, Conservative, Nationalist and Agrarian parties. View Large Yet, an alternative approach to self-employment is emerging. Studies that put self-employment under the umbrella of atypical work generally relate self-employment without employees (or ‘solo’ self-employment) to higher labor market risks and more precarious employment positions. The emphasis is often on the so-called ‘new self-employed’ who are assumed to work on the border of self-employment, dependent-employment and unemployment; a group that is believed to be growing due to the flexibilization of labor markets. The risks of people in solo self-employment are considered to be comparable to the risks of people in temporary employment. Compared with ‘standard employees’, self-employed workers would be exposed to higher risks because they often do not build up pension entitlements, and are underinsured with respect to healthcare, labor disability and professional liability ( Schulze Buschoff and Schmidt, 2009 ; Dekker, 2010 ; Pedersini and Coletto, 2010 ). In this perspective, rather than autonomous, stable and voluntary, self-employment is often dependent, precarious and involuntary, and leads to fundamentally different predictions regarding political preferences than does the traditional class-based approach. To date, however, this alternative perspective of self-employment received little to no attention in studies into political attitudes. Therefore, the contribution of this study is two-fold. First, I will discuss the composition of self-employment in Western Europe using aggregate-level data from Eurostat’s Labor Force Surveys. By mapping recent changes in the occupational and sectoral structure of self-employment, I will emphasize the heterogeneity of this employment type. This section serves to challenge the traditional notion in political sociology of the self-employed as a homogeneous social class. Second, using individual-level data from the fourth round of the European Social Survey ( ESS Round 4, 2008 ), I will compare the effect of solo self-employment on political preferences to the effect of temporary employment. The comparison of temporary employment to self-employment provides a deeper understanding of how labor market risks are associated with political divisions. While both are considered ‘atypical’ forms of employment, they may lead to very different preferences regarding welfare protection and political parties. Therefore, I will study under what conditions self-employment and temporary employment might be associated with similar political preferences. By accounting for the fact that different ‘segments’ of self-employment involve different levels of labor market security and/or autonomy, I test whether the traditional notion of the self-employed as a conservative, political right-wing category holds for self-employment types that are more precarious than class theories maintain. Ultimately, this article aims to answer the following research question: (a) To what extent does solo self-employment have a different effect on political preferences compared temporary employment and (b) to what extent is this effect conditioned by degree of labor market security and autonomy? 2. Self-employment heterogeneity in Europe The traditional class-based approach to self-employment is increasingly problematic to understand political orientations. Bögenhold and Staber (1991) and Arum and Müller (2004) have argued that the notion of petty bourgeois and employer entrepreneurship does not suffice in contemporary labor markets. For large segments of self-employment, it is problematic to perceive their interests in terms of employership because employership is rarely the standard ( Millán et al. , 2014 ; Van Stel et al. , 2014 ). Figure 1 shows the level of self-employment as percentage of total employment in the (former) EU-15, Norway and Switzerland in 2004 and 2014, broken down by self-employment with and without employees. Although the level of self-employment varies considerably among countries (ranging from 6% in Norway to over 30% in Greece), all countries have one feature in common: the majority of people in self-employment generally do not employ others. Moreover, in about half of the countries in Figure 1 , self-employment has increased over the last decade, mainly due to a rise in self-employment without employees. Figure 1. View largeDownload slide Self-employment with and without employees as percentage of total employment in Europe, 2004–2014. Source: Eurostat, EU Labour Force Survey (2004, 2014), own calculations. Figure 1. View largeDownload slide Self-employment with and without employees as percentage of total employment in Europe, 2004–2014. Source: Eurostat, EU Labour Force Survey (2004, 2014), own calculations. The social class perspective tends to overlook the heterogeneity of self-employment ( Arum and Müller, 2004 ; Bögenhold and Fachinger, 2012 ). Research suggests that there has been an erosion of the ‘old’ forms of self-employment. In many advanced economies, formerly prevailing types of self-employment (farmers and the petty bourgeois of small proprietors and shop owners) would have declined since the 1980s ( Arum and Müller, 2004 ). People in these ‘classical’ types would generally sell goods instead of services, and work in economic sectors such as the retail or wholesale industry and in agriculture. Despite this decline, there has been an emergence of (solo) self-employment in new occupational types; causing a ‘partial renaissance’ ( OECD, 2000 , p. 188) of self-employment in various advanced economies. Arum and Müller (2004) show that this growth occurred among low-skilled, but in particular among high-skilled occupations. The changing structure of self-employment therefore follows general processes of occupational upgrading and polarization (cf. Oesch, 2015 ). Contrary to the classical types, people in the ‘new’ types of self-employment would increasingly not sell goods, but instead rely on selling services based on their own labor power, and work in business or other service industries ( Kösters et al., 2013 ). To illustrate the diverse and changing nature of self-employment, Table 2 shows the composition of self-employment in European countries, broken down by five sectors of economic activity 1 over a 20 year period (i.e. 1994/1995, 2004 and 2014). The aggregate statistics for the EU-15 are summarized in Figure 2a . In all countries, there is a downward trend in agricultural self-employment. And in most countries also the share of self-employed working in wholesale or retail and in the hotel and restaurant industry has declined since the 1990s. At the same time, there is a clear increase in self-employment in the service-oriented industries, in particular regarding business services. In countries such as Germany (57%), the UK (58%), the Netherlands (61%) and Luxembourg (67%), the vast majority of the self-employed now works in service industries. Figure 2. View largeDownload slide Self-employment in Europe (EU-15), 1995–2014 (in percentage). (a) By economic activity †a,b‡ . (b) By occupational group §c . † 1995, 2004 NACE Rev.1: Agriculture (sections A, B); Industry (sections C–F); Wholesale/Retail/Hotels (sections G, H); Business Services (sections I–K); Other Services (sections L–Q). ‡ 2014, NACE Rev.1: Agriculture (sections A); Industry (sections B–F); Wholesale/Retail/Hotels (sections G–I); Business Services (sections H–N); Other Services (sections O–U). § ISCO-08: Managers (ISCO 1); Professionals (ISCO 2–3); Low-skilled Non-Manual (ISCO 4–5); High-skilled Manual (ISCO 6–7); Low-skilled Manual (8–9). Source: Eurostat, EU Labour Force Survey (1995, 2004, 2014), own calculations. Figure 2. View largeDownload slide Self-employment in Europe (EU-15), 1995–2014 (in percentage). (a) By economic activity †a,b‡ . (b) By occupational group §c . † 1995, 2004 NACE Rev.1: Agriculture (sections A, B); Industry (sections C–F); Wholesale/Retail/Hotels (sections G, H); Business Services (sections I–K); Other Services (sections L–Q). ‡ 2014, NACE Rev.1: Agriculture (sections A); Industry (sections B–F); Wholesale/Retail/Hotels (sections G–I); Business Services (sections H–N); Other Services (sections O–U). § ISCO-08: Managers (ISCO 1); Professionals (ISCO 2–3); Low-skilled Non-Manual (ISCO 4–5); High-skilled Manual (ISCO 6–7); Low-skilled Manual (8–9). Source: Eurostat, EU Labour Force Survey (1995, 2004, 2014), own calculations. Table 2. Self-employment by economic activity in Europe, 1994–2014 (in percentage)   1994 †  2004 †  2014 ‡    1994 †  2004 †  2014 ‡  Austria        Luxembourg         Agriculture    28.6  23.3  Agriculture  21.9  18.4  12.0   Industry    14.4  13.3  Industry  9.6  13.2  3.6   Wholesale/Retail/Hotels    20.4  20.1  Wholesale/Retail/Hotels  42.5  28.7  15.0   Business Services    20.7  25.8  Business Services  12.3  22.8  41.3   Other Services    16.0  17.4  Other Services  13.7  16.9  28.1  Belgium        Netherlands         Agriculture  11.7  9.4  5.4  Agriculture  18.9  13.0  6.7   Industry  18.0  18.6  19.4  Industry  12.7  16.9  14.6   Wholesale/Retail/Hotels  36.7  33.2  25.2  Wholesale/Retail/Hotels  27.2  21.0  17.8   Business Services  15.4  20.4  29.5  Business Services  19.0  26.2  34.5   Other Services  18.2  18.4  20.5  Other Services  22.2  22.7  26.4  Denmark        Norway         Agriculture  23.9  17.9  11.7  Agriculture    26.4  16.8   Industry  21.1  19.2  18.9  Industry    20.1  20.1   Wholesale/Retail/Hotels  22.7  23.7  18.0  Wholesale/Retail/Hotels    14.1  10.8   Business Services  19.7  22.9  31.4  Business Services    18.9  26.9   Other Services  12.6  16.3  19.9  Other Services    20.5  25.4  Finland        Portugal         Agriculture    25.6  19.2  Agriculture  29.4  28.0  22.4   Industry    18.1  19.8  Industry  21.7  25.6  19.1   Wholesale/Retail/Hotels    18.6  15.3  Wholesale/Retail/Hotels  31.9  29.1  30.2   Business Services    20.7  26.1  Business Services  8.2  9.1  16.4   Other Services    16.9  19.5  Other Services  8.8  8.1  12.0  France        Spain         Agriculture  24.5  21.6  15.0  Agriculture  21.9  14.1  9.6   Industry  20.8  21.4  18.9  Industry  23.3  25.3  18.9   Wholesale/Retail/Hotels  26.4  25.4  21.4  Wholesale/Retail/Hotels  34.9  33.5  36.0   Business Services  12.6  13.2  21.7  Business Services  12.9  18.8  23.4   Other Services  15.7  18.3  23.0  Other Services  7.0  8.3  12.1  Germany        Sweden         Agriculture  10.9  7.5  5.1  Agriculture    12.2  9.1   Industry  22.3  20.3  19.6  Industry    21.2  21.3   Wholesale/Retail/Hotels  46.6  23.7  18.5  Wholesale/Retail/Hotels    23.9  19.7   Business Services  7.2  25.4  31.3  Business Services    28.5  32.6   Other Services  13.0  23.1  25.4  Other Services    14.3  17.3  Greece        Switzerland         Agriculture  33.1  26.8  31.3  Agriculture    16.4  14.3   Industry  19.0  18.4  12.1  Industry    19.5  15.6   Wholesale/Retail/Hotels  29.8  31.6  28.2  Wholesale/Retail/Hotels    18.7  17.4   Business Services  11.6  14.9  18.2  Business Services    23.5  29.6   Other Services  6.5  8.2  10.2  Other Services    21.9  23.2  Ireland        UK         Agriculture  40.6  26.0  21.3  Agriculture  7.5  4.9  3.8   Industry  16.8  25.5  20.7  Industry  33.5  30.0  26.0   Wholesale/Retail/Hotels  22.2  17.9  15.8  Wholesale/Retail/Hotels  22.3  16.7  11.5   Business Services  11.4  18.6  27.3  Business Services  20.9  26.5  33.9   Other Services  9.0  12.0  14.9  Other Services  15.8  21.9  24.7  Italy                 Agriculture  13.3  7.4  6.2           Industry  26.2  25.0  21.7           Wholesale/Retail/Hotels  37.4  31.3  29.8           Business Services  12.6  22.7  27.3           Other Services  10.5  13.7  14.9            1994 †  2004 †  2014 ‡    1994 †  2004 †  2014 ‡  Austria        Luxembourg         Agriculture    28.6  23.3  Agriculture  21.9  18.4  12.0   Industry    14.4  13.3  Industry  9.6  13.2  3.6   Wholesale/Retail/Hotels    20.4  20.1  Wholesale/Retail/Hotels  42.5  28.7  15.0   Business Services    20.7  25.8  Business Services  12.3  22.8  41.3   Other Services    16.0  17.4  Other Services  13.7  16.9  28.1  Belgium        Netherlands         Agriculture  11.7  9.4  5.4  Agriculture  18.9  13.0  6.7   Industry  18.0  18.6  19.4  Industry  12.7  16.9  14.6   Wholesale/Retail/Hotels  36.7  33.2  25.2  Wholesale/Retail/Hotels  27.2  21.0  17.8   Business Services  15.4  20.4  29.5  Business Services  19.0  26.2  34.5   Other Services  18.2  18.4  20.5  Other Services  22.2  22.7  26.4  Denmark        Norway         Agriculture  23.9  17.9  11.7  Agriculture    26.4  16.8   Industry  21.1  19.2  18.9  Industry    20.1  20.1   Wholesale/Retail/Hotels  22.7  23.7  18.0  Wholesale/Retail/Hotels    14.1  10.8   Business Services  19.7  22.9  31.4  Business Services    18.9  26.9   Other Services  12.6  16.3  19.9  Other Services    20.5  25.4  Finland        Portugal         Agriculture    25.6  19.2  Agriculture  29.4  28.0  22.4   Industry    18.1  19.8  Industry  21.7  25.6  19.1   Wholesale/Retail/Hotels    18.6  15.3  Wholesale/Retail/Hotels  31.9  29.1  30.2   Business Services    20.7  26.1  Business Services  8.2  9.1  16.4   Other Services    16.9  19.5  Other Services  8.8  8.1  12.0  France        Spain         Agriculture  24.5  21.6  15.0  Agriculture  21.9  14.1  9.6   Industry  20.8  21.4  18.9  Industry  23.3  25.3  18.9   Wholesale/Retail/Hotels  26.4  25.4  21.4  Wholesale/Retail/Hotels  34.9  33.5  36.0   Business Services  12.6  13.2  21.7  Business Services  12.9  18.8  23.4   Other Services  15.7  18.3  23.0  Other Services  7.0  8.3  12.1  Germany        Sweden         Agriculture  10.9  7.5  5.1  Agriculture    12.2  9.1   Industry  22.3  20.3  19.6  Industry    21.2  21.3   Wholesale/Retail/Hotels  46.6  23.7  18.5  Wholesale/Retail/Hotels    23.9  19.7   Business Services  7.2  25.4  31.3  Business Services    28.5  32.6   Other Services  13.0  23.1  25.4  Other Services    14.3  17.3  Greece        Switzerland         Agriculture  33.1  26.8  31.3  Agriculture    16.4  14.3   Industry  19.0  18.4  12.1  Industry    19.5  15.6   Wholesale/Retail/Hotels  29.8  31.6  28.2  Wholesale/Retail/Hotels    18.7  17.4   Business Services  11.6  14.9  18.2  Business Services    23.5  29.6   Other Services  6.5  8.2  10.2  Other Services    21.9  23.2  Ireland        UK         Agriculture  40.6  26.0  21.3  Agriculture  7.5  4.9  3.8   Industry  16.8  25.5  20.7  Industry  33.5  30.0  26.0   Wholesale/Retail/Hotels  22.2  17.9  15.8  Wholesale/Retail/Hotels  22.3  16.7  11.5   Business Services  11.4  18.6  27.3  Business Services  20.9  26.5  33.9   Other Services  9.0  12.0  14.9  Other Services  15.8  21.9  24.7  Italy                 Agriculture  13.3  7.4  6.2           Industry  26.2  25.0  21.7           Wholesale/Retail/Hotels  37.4  31.3  29.8           Business Services  12.6  22.7  27.3           Other Services  10.5  13.7  14.9          † Nomenclature statistique des Activités économiques dans la Communauté Européenne (NACE) Rev.1: Agriculture (sections A, B); Industry (sections C–F); Wholesale/Retail/Hotels (sections G, H); Business Services (sections I–K); Other Services (sections L–Q). ‡ NACE Rev.1: Agriculture (sections A); Industry (sections B–F); Wholesale/Retail/Hotels (sections G–I); Business Services (sections H–N); Other Services (sections O–U). Source: Eurostat, EU Labour Force Survey (1994, 2004, 2014), own calculations. View Large Table 2. Self-employment by economic activity in Europe, 1994–2014 (in percentage)   1994 †  2004 †  2014 ‡    1994 †  2004 †  2014 ‡  Austria        Luxembourg         Agriculture    28.6  23.3  Agriculture  21.9  18.4  12.0   Industry    14.4  13.3  Industry  9.6  13.2  3.6   Wholesale/Retail/Hotels    20.4  20.1  Wholesale/Retail/Hotels  42.5  28.7  15.0   Business Services    20.7  25.8  Business Services  12.3  22.8  41.3   Other Services    16.0  17.4  Other Services  13.7  16.9  28.1  Belgium        Netherlands         Agriculture  11.7  9.4  5.4  Agriculture  18.9  13.0  6.7   Industry  18.0  18.6  19.4  Industry  12.7  16.9  14.6   Wholesale/Retail/Hotels  36.7  33.2  25.2  Wholesale/Retail/Hotels  27.2  21.0  17.8   Business Services  15.4  20.4  29.5  Business Services  19.0  26.2  34.5   Other Services  18.2  18.4  20.5  Other Services  22.2  22.7  26.4  Denmark        Norway         Agriculture  23.9  17.9  11.7  Agriculture    26.4  16.8   Industry  21.1  19.2  18.9  Industry    20.1  20.1   Wholesale/Retail/Hotels  22.7  23.7  18.0  Wholesale/Retail/Hotels    14.1  10.8   Business Services  19.7  22.9  31.4  Business Services    18.9  26.9   Other Services  12.6  16.3  19.9  Other Services    20.5  25.4  Finland        Portugal         Agriculture    25.6  19.2  Agriculture  29.4  28.0  22.4   Industry    18.1  19.8  Industry  21.7  25.6  19.1   Wholesale/Retail/Hotels    18.6  15.3  Wholesale/Retail/Hotels  31.9  29.1  30.2   Business Services    20.7  26.1  Business Services  8.2  9.1  16.4   Other Services    16.9  19.5  Other Services  8.8  8.1  12.0  France        Spain         Agriculture  24.5  21.6  15.0  Agriculture  21.9  14.1  9.6   Industry  20.8  21.4  18.9  Industry  23.3  25.3  18.9   Wholesale/Retail/Hotels  26.4  25.4  21.4  Wholesale/Retail/Hotels  34.9  33.5  36.0   Business Services  12.6  13.2  21.7  Business Services  12.9  18.8  23.4   Other Services  15.7  18.3  23.0  Other Services  7.0  8.3  12.1  Germany        Sweden         Agriculture  10.9  7.5  5.1  Agriculture    12.2  9.1   Industry  22.3  20.3  19.6  Industry    21.2  21.3   Wholesale/Retail/Hotels  46.6  23.7  18.5  Wholesale/Retail/Hotels    23.9  19.7   Business Services  7.2  25.4  31.3  Business Services    28.5  32.6   Other Services  13.0  23.1  25.4  Other Services    14.3  17.3  Greece        Switzerland         Agriculture  33.1  26.8  31.3  Agriculture    16.4  14.3   Industry  19.0  18.4  12.1  Industry    19.5  15.6   Wholesale/Retail/Hotels  29.8  31.6  28.2  Wholesale/Retail/Hotels    18.7  17.4   Business Services  11.6  14.9  18.2  Business Services    23.5  29.6   Other Services  6.5  8.2  10.2  Other Services    21.9  23.2  Ireland        UK         Agriculture  40.6  26.0  21.3  Agriculture  7.5  4.9  3.8   Industry  16.8  25.5  20.7  Industry  33.5  30.0  26.0   Wholesale/Retail/Hotels  22.2  17.9  15.8  Wholesale/Retail/Hotels  22.3  16.7  11.5   Business Services  11.4  18.6  27.3  Business Services  20.9  26.5  33.9   Other Services  9.0  12.0  14.9  Other Services  15.8  21.9  24.7  Italy                 Agriculture  13.3  7.4  6.2           Industry  26.2  25.0  21.7           Wholesale/Retail/Hotels  37.4  31.3  29.8           Business Services  12.6  22.7  27.3           Other Services  10.5  13.7  14.9            1994 †  2004 †  2014 ‡    1994 †  2004 †  2014 ‡  Austria        Luxembourg         Agriculture    28.6  23.3  Agriculture  21.9  18.4  12.0   Industry    14.4  13.3  Industry  9.6  13.2  3.6   Wholesale/Retail/Hotels    20.4  20.1  Wholesale/Retail/Hotels  42.5  28.7  15.0   Business Services    20.7  25.8  Business Services  12.3  22.8  41.3   Other Services    16.0  17.4  Other Services  13.7  16.9  28.1  Belgium        Netherlands         Agriculture  11.7  9.4  5.4  Agriculture  18.9  13.0  6.7   Industry  18.0  18.6  19.4  Industry  12.7  16.9  14.6   Wholesale/Retail/Hotels  36.7  33.2  25.2  Wholesale/Retail/Hotels  27.2  21.0  17.8   Business Services  15.4  20.4  29.5  Business Services  19.0  26.2  34.5   Other Services  18.2  18.4  20.5  Other Services  22.2  22.7  26.4  Denmark        Norway         Agriculture  23.9  17.9  11.7  Agriculture    26.4  16.8   Industry  21.1  19.2  18.9  Industry    20.1  20.1   Wholesale/Retail/Hotels  22.7  23.7  18.0  Wholesale/Retail/Hotels    14.1  10.8   Business Services  19.7  22.9  31.4  Business Services    18.9  26.9   Other Services  12.6  16.3  19.9  Other Services    20.5  25.4  Finland        Portugal         Agriculture    25.6  19.2  Agriculture  29.4  28.0  22.4   Industry    18.1  19.8  Industry  21.7  25.6  19.1   Wholesale/Retail/Hotels    18.6  15.3  Wholesale/Retail/Hotels  31.9  29.1  30.2   Business Services    20.7  26.1  Business Services  8.2  9.1  16.4   Other Services    16.9  19.5  Other Services  8.8  8.1  12.0  France        Spain         Agriculture  24.5  21.6  15.0  Agriculture  21.9  14.1  9.6   Industry  20.8  21.4  18.9  Industry  23.3  25.3  18.9   Wholesale/Retail/Hotels  26.4  25.4  21.4  Wholesale/Retail/Hotels  34.9  33.5  36.0   Business Services  12.6  13.2  21.7  Business Services  12.9  18.8  23.4   Other Services  15.7  18.3  23.0  Other Services  7.0  8.3  12.1  Germany        Sweden         Agriculture  10.9  7.5  5.1  Agriculture    12.2  9.1   Industry  22.3  20.3  19.6  Industry    21.2  21.3   Wholesale/Retail/Hotels  46.6  23.7  18.5  Wholesale/Retail/Hotels    23.9  19.7   Business Services  7.2  25.4  31.3  Business Services    28.5  32.6   Other Services  13.0  23.1  25.4  Other Services    14.3  17.3  Greece        Switzerland         Agriculture  33.1  26.8  31.3  Agriculture    16.4  14.3   Industry  19.0  18.4  12.1  Industry    19.5  15.6   Wholesale/Retail/Hotels  29.8  31.6  28.2  Wholesale/Retail/Hotels    18.7  17.4   Business Services  11.6  14.9  18.2  Business Services    23.5  29.6   Other Services  6.5  8.2  10.2  Other Services    21.9  23.2  Ireland        UK         Agriculture  40.6  26.0  21.3  Agriculture  7.5  4.9  3.8   Industry  16.8  25.5  20.7  Industry  33.5  30.0  26.0   Wholesale/Retail/Hotels  22.2  17.9  15.8  Wholesale/Retail/Hotels  22.3  16.7  11.5   Business Services  11.4  18.6  27.3  Business Services  20.9  26.5  33.9   Other Services  9.0  12.0  14.9  Other Services  15.8  21.9  24.7  Italy                 Agriculture  13.3  7.4  6.2           Industry  26.2  25.0  21.7           Wholesale/Retail/Hotels  37.4  31.3  29.8           Business Services  12.6  22.7  27.3           Other Services  10.5  13.7  14.9          † Nomenclature statistique des Activités économiques dans la Communauté Européenne (NACE) Rev.1: Agriculture (sections A, B); Industry (sections C–F); Wholesale/Retail/Hotels (sections G, H); Business Services (sections I–K); Other Services (sections L–Q). ‡ NACE Rev.1: Agriculture (sections A); Industry (sections B–F); Wholesale/Retail/Hotels (sections G–I); Business Services (sections H–N); Other Services (sections O–U). Source: Eurostat, EU Labour Force Survey (1994, 2004, 2014), own calculations. View Large A similar picture emerges from Table 3 and Figure 2b , reporting on the occupational heterogeneity of self-employment in Europe. On the basis of 1-digit International Standard Classification of Occupations (ISCO)-08 classifications, I distinguish five occupational categories. Generally, self-employment has declined between 1994/1995 and 2014 in two of these categories: first, decline occurs in the group of ‘High-skilled Manual’ workers, which mainly contains skilled agricultural workers and craft and trades workers. Obviously, this decline reflects the sectoral developments in Figure 2a , depicting a decline in the agricultural industry, wholesale and retail. Second, and perhaps somewhat surprising, there is in most countries also a sharp decline in the share of self-employed managers. Arum and Müller (2004 , p. 23) suggest that in labor force surveys, whether a self-employed persons is classified as a manager depends not only on whether they employ others, but also depending on how they report their occupation. The decline of the managerial group, therefore, may have two sources; first, with the rise of solo self-employment there may be relatively fewer self-employed managers, and second, fewer people may report their occupation as manager or owner. Table 3. Self-employment by occupational group † in Europe, 1994–2014 (in percentage)   1994  2004  2014    1994  2004  2014  Austria        Luxembourg         Managers    22.5  7.8  Managers  51.0  50.0  8.8   Professionals    34.4  40.0  Professionals  21.2  35.5  65.9   Low-skilled Non-Manual    5.2  13.8  Low-skilled Non-Manual  6.0  0.0  11.0   High-skilled Manual    35.0  34.0  High-skilled Manual  21.9  14.5  14.3   Low-skilled Manual    3.0  4.5  Low-skilled Manual  0.0  0.0  0.0  Belgium        Netherlands         Managers  36.5  39.6  19.5  Managers  47.8  35.1  13.1   Professionals  24.2  28.1  37.9  Professionals  26.5  37.4  43.8   Low-skilled Non-Manual  9.0  7.0  16.7  Low-skilled Non-Manual  10.1  9.5  19.0   High-skilled Manual  26.9  24.3  22.0  High-skilled Manual  9.6  12.8  18.8   Low-skilled Manual  3.3  1.1  3.8  Low-skilled Manual  5.9  5.2  5.3  Denmark        Norway         Managers  29.8  32.1  3.9  Managers    5.7  6.8   Professionals  21.2  22.2  45.2  Professionals    26.7  37.3   Low-skilled Non-Manual  5.0  5.0  17.1  Low-skilled Non-Manual    13.4  13.0   High-skilled Manual  38.0  32.3  25.0  High-skilled Manual    45.5  31.8   Low-skilled Manual  6.0  8.4  8.8  Low-skilled Manual    8.6  11.1  Finland        Portugal         Managers    27.2  3.6  Managers  34.1  35.0  25.1   Professionals    20.4  31.5  Professionals  7.3  8.1  18.6   Low-skilled Non-Manual    10.2  19.0  Low-skilled Non-Manual  10.0  7.7  15.7   High-skilled Manual    34.5  34.9  High-skilled Manual  42.0  42.2  35.7   Low-skilled Manual    7.7  10.9  Low-skilled Manual  6.6  7.0  5.0  France        Spain         Managers  16.2  30.3  9.8  Managers  29.6  34.2  12.3   Professionals  18.7  22.4  34.2  Professionals  10.0  17.2  24.4   Low-skilled Non-Manual  16.0  2.8  18.3  Low-skilled Non-Manual  6.9  7.7  30.8   High-skilled Manual  46.9  44.5  34.3  High-skilled Manual  41.4  31.2  25.4   Low-skilled Manual  2.2  0.0  3.5  Low-skilled Manual  12.0  9.8  7.1  Germany        Sweden         Managers  30.1  25.1  12.7  Managers    14.6  10.8   Professionals  33.1  41.2  51.0  Professionals    34.5  38.9   Low-skilled Non-Manual  8.2  7.9  16.8  Low-skilled Non-Manual    13.9  15.5   High-skilled Manual  25.0  22.6  16.5  High-skilled Manual    27.7  25.0   Low-skilled Manual  3.6  3.3  3.0  Low-skilled Manual    9.2  9.7  Greece        Switzerland         Managers  25.9  30.3  8.9  Managers    8.5  11.8   Professionals  10.6  15.4  20.7  Professionals    39.8  44.3   Low-skilled Non-Manual  6.5  5.3  21.0  Low-skilled Non-Manual    14.0  14.9   High-skilled Manual  49.8  41.9  42.9  High-skilled Manual    33.6  25.9   Low-skilled Manual  7.2  7.0  6.5  Low-skilled Manual    4.1  3.0  Ireland        UK         Managers  9.5  45.3  16.8  Managers  19.7  17.9  13.8   Professionals  13.6  18.3  24.8  Professionals  24.8  28.8  31.9   Low-skilled Non-Manual  15.0  5.9  10.4  Low-skilled Non-Manual  7.2  10.0  15.0   High-skilled Manual  52.0  21.0  38.1  High-skilled Manual  35.1  30.1  26.6   Low-skilled Manual  9.9  9.5  10.0  Low-skilled Manual  13.2  13.3  12.7  Italy                 Managers  5.6  27.3  11.6           Professionals  20.0  31.0  36.6           Low-skilled Non-Manual  28.0  8.4  20.4           High-skilled Manual  36.2  25.6  24.8           Low-skilled Manual  10.1  7.7  6.7            1994  2004  2014    1994  2004  2014  Austria        Luxembourg         Managers    22.5  7.8  Managers  51.0  50.0  8.8   Professionals    34.4  40.0  Professionals  21.2  35.5  65.9   Low-skilled Non-Manual    5.2  13.8  Low-skilled Non-Manual  6.0  0.0  11.0   High-skilled Manual    35.0  34.0  High-skilled Manual  21.9  14.5  14.3   Low-skilled Manual    3.0  4.5  Low-skilled Manual  0.0  0.0  0.0  Belgium        Netherlands         Managers  36.5  39.6  19.5  Managers  47.8  35.1  13.1   Professionals  24.2  28.1  37.9  Professionals  26.5  37.4  43.8   Low-skilled Non-Manual  9.0  7.0  16.7  Low-skilled Non-Manual  10.1  9.5  19.0   High-skilled Manual  26.9  24.3  22.0  High-skilled Manual  9.6  12.8  18.8   Low-skilled Manual  3.3  1.1  3.8  Low-skilled Manual  5.9  5.2  5.3  Denmark        Norway         Managers  29.8  32.1  3.9  Managers    5.7  6.8   Professionals  21.2  22.2  45.2  Professionals    26.7  37.3   Low-skilled Non-Manual  5.0  5.0  17.1  Low-skilled Non-Manual    13.4  13.0   High-skilled Manual  38.0  32.3  25.0  High-skilled Manual    45.5  31.8   Low-skilled Manual  6.0  8.4  8.8  Low-skilled Manual    8.6  11.1  Finland        Portugal         Managers    27.2  3.6  Managers  34.1  35.0  25.1   Professionals    20.4  31.5  Professionals  7.3  8.1  18.6   Low-skilled Non-Manual    10.2  19.0  Low-skilled Non-Manual  10.0  7.7  15.7   High-skilled Manual    34.5  34.9  High-skilled Manual  42.0  42.2  35.7   Low-skilled Manual    7.7  10.9  Low-skilled Manual  6.6  7.0  5.0  France        Spain         Managers  16.2  30.3  9.8  Managers  29.6  34.2  12.3   Professionals  18.7  22.4  34.2  Professionals  10.0  17.2  24.4   Low-skilled Non-Manual  16.0  2.8  18.3  Low-skilled Non-Manual  6.9  7.7  30.8   High-skilled Manual  46.9  44.5  34.3  High-skilled Manual  41.4  31.2  25.4   Low-skilled Manual  2.2  0.0  3.5  Low-skilled Manual  12.0  9.8  7.1  Germany        Sweden         Managers  30.1  25.1  12.7  Managers    14.6  10.8   Professionals  33.1  41.2  51.0  Professionals    34.5  38.9   Low-skilled Non-Manual  8.2  7.9  16.8  Low-skilled Non-Manual    13.9  15.5   High-skilled Manual  25.0  22.6  16.5  High-skilled Manual    27.7  25.0   Low-skilled Manual  3.6  3.3  3.0  Low-skilled Manual    9.2  9.7  Greece        Switzerland         Managers  25.9  30.3  8.9  Managers    8.5  11.8   Professionals  10.6  15.4  20.7  Professionals    39.8  44.3   Low-skilled Non-Manual  6.5  5.3  21.0  Low-skilled Non-Manual    14.0  14.9   High-skilled Manual  49.8  41.9  42.9  High-skilled Manual    33.6  25.9   Low-skilled Manual  7.2  7.0  6.5  Low-skilled Manual    4.1  3.0  Ireland        UK         Managers  9.5  45.3  16.8  Managers  19.7  17.9  13.8   Professionals  13.6  18.3  24.8  Professionals  24.8  28.8  31.9   Low-skilled Non-Manual  15.0  5.9  10.4  Low-skilled Non-Manual  7.2  10.0  15.0   High-skilled Manual  52.0  21.0  38.1  High-skilled Manual  35.1  30.1  26.6   Low-skilled Manual  9.9  9.5  10.0  Low-skilled Manual  13.2  13.3  12.7  Italy                 Managers  5.6  27.3  11.6           Professionals  20.0  31.0  36.6           Low-skilled Non-Manual  28.0  8.4  20.4           High-skilled Manual  36.2  25.6  24.8           Low-skilled Manual  10.1  7.7  6.7          † ISCO-08: Managers (ISCO 1); Professionals (ISCO 2–3); Low-skilled Non-Manual (ISCO 4–5); High-skilled0 Manual (ISCO 6–7); Low-skilled Manual (8–9). Source: Eurostat, EU Labour Force Survey (1994, 2004, 2014), own calculations. View Large Table 3. Self-employment by occupational group † in Europe, 1994–2014 (in percentage)   1994  2004  2014    1994  2004  2014  Austria        Luxembourg         Managers    22.5  7.8  Managers  51.0  50.0  8.8   Professionals    34.4  40.0  Professionals  21.2  35.5  65.9   Low-skilled Non-Manual    5.2  13.8  Low-skilled Non-Manual  6.0  0.0  11.0   High-skilled Manual    35.0  34.0  High-skilled Manual  21.9  14.5  14.3   Low-skilled Manual    3.0  4.5  Low-skilled Manual  0.0  0.0  0.0  Belgium        Netherlands         Managers  36.5  39.6  19.5  Managers  47.8  35.1  13.1   Professionals  24.2  28.1  37.9  Professionals  26.5  37.4  43.8   Low-skilled Non-Manual  9.0  7.0  16.7  Low-skilled Non-Manual  10.1  9.5  19.0   High-skilled Manual  26.9  24.3  22.0  High-skilled Manual  9.6  12.8  18.8   Low-skilled Manual  3.3  1.1  3.8  Low-skilled Manual  5.9  5.2  5.3  Denmark        Norway         Managers  29.8  32.1  3.9  Managers    5.7  6.8   Professionals  21.2  22.2  45.2  Professionals    26.7  37.3   Low-skilled Non-Manual  5.0  5.0  17.1  Low-skilled Non-Manual    13.4  13.0   High-skilled Manual  38.0  32.3  25.0  High-skilled Manual    45.5  31.8   Low-skilled Manual  6.0  8.4  8.8  Low-skilled Manual    8.6  11.1  Finland        Portugal         Managers    27.2  3.6  Managers  34.1  35.0  25.1   Professionals    20.4  31.5  Professionals  7.3  8.1  18.6   Low-skilled Non-Manual    10.2  19.0  Low-skilled Non-Manual  10.0  7.7  15.7   High-skilled Manual    34.5  34.9  High-skilled Manual  42.0  42.2  35.7   Low-skilled Manual    7.7  10.9  Low-skilled Manual  6.6  7.0  5.0  France        Spain         Managers  16.2  30.3  9.8  Managers  29.6  34.2  12.3   Professionals  18.7  22.4  34.2  Professionals  10.0  17.2  24.4   Low-skilled Non-Manual  16.0  2.8  18.3  Low-skilled Non-Manual  6.9  7.7  30.8   High-skilled Manual  46.9  44.5  34.3  High-skilled Manual  41.4  31.2  25.4   Low-skilled Manual  2.2  0.0  3.5  Low-skilled Manual  12.0  9.8  7.1  Germany        Sweden         Managers  30.1  25.1  12.7  Managers    14.6  10.8   Professionals  33.1  41.2  51.0  Professionals    34.5  38.9   Low-skilled Non-Manual  8.2  7.9  16.8  Low-skilled Non-Manual    13.9  15.5   High-skilled Manual  25.0  22.6  16.5  High-skilled Manual    27.7  25.0   Low-skilled Manual  3.6  3.3  3.0  Low-skilled Manual    9.2  9.7  Greece        Switzerland         Managers  25.9  30.3  8.9  Managers    8.5  11.8   Professionals  10.6  15.4  20.7  Professionals    39.8  44.3   Low-skilled Non-Manual  6.5  5.3  21.0  Low-skilled Non-Manual    14.0  14.9   High-skilled Manual  49.8  41.9  42.9  High-skilled Manual    33.6  25.9   Low-skilled Manual  7.2  7.0  6.5  Low-skilled Manual    4.1  3.0  Ireland        UK         Managers  9.5  45.3  16.8  Managers  19.7  17.9  13.8   Professionals  13.6  18.3  24.8  Professionals  24.8  28.8  31.9   Low-skilled Non-Manual  15.0  5.9  10.4  Low-skilled Non-Manual  7.2  10.0  15.0   High-skilled Manual  52.0  21.0  38.1  High-skilled Manual  35.1  30.1  26.6   Low-skilled Manual  9.9  9.5  10.0  Low-skilled Manual  13.2  13.3  12.7  Italy                 Managers  5.6  27.3  11.6           Professionals  20.0  31.0  36.6           Low-skilled Non-Manual  28.0  8.4  20.4           High-skilled Manual  36.2  25.6  24.8           Low-skilled Manual  10.1  7.7  6.7            1994  2004  2014    1994  2004  2014  Austria        Luxembourg         Managers    22.5  7.8  Managers  51.0  50.0  8.8   Professionals    34.4  40.0  Professionals  21.2  35.5  65.9   Low-skilled Non-Manual    5.2  13.8  Low-skilled Non-Manual  6.0  0.0  11.0   High-skilled Manual    35.0  34.0  High-skilled Manual  21.9  14.5  14.3   Low-skilled Manual    3.0  4.5  Low-skilled Manual  0.0  0.0  0.0  Belgium        Netherlands         Managers  36.5  39.6  19.5  Managers  47.8  35.1  13.1   Professionals  24.2  28.1  37.9  Professionals  26.5  37.4  43.8   Low-skilled Non-Manual  9.0  7.0  16.7  Low-skilled Non-Manual  10.1  9.5  19.0   High-skilled Manual  26.9  24.3  22.0  High-skilled Manual  9.6  12.8  18.8   Low-skilled Manual  3.3  1.1  3.8  Low-skilled Manual  5.9  5.2  5.3  Denmark        Norway         Managers  29.8  32.1  3.9  Managers    5.7  6.8   Professionals  21.2  22.2  45.2  Professionals    26.7  37.3   Low-skilled Non-Manual  5.0  5.0  17.1  Low-skilled Non-Manual    13.4  13.0   High-skilled Manual  38.0  32.3  25.0  High-skilled Manual    45.5  31.8   Low-skilled Manual  6.0  8.4  8.8  Low-skilled Manual    8.6  11.1  Finland        Portugal         Managers    27.2  3.6  Managers  34.1  35.0  25.1   Professionals    20.4  31.5  Professionals  7.3  8.1  18.6   Low-skilled Non-Manual    10.2  19.0  Low-skilled Non-Manual  10.0  7.7  15.7   High-skilled Manual    34.5  34.9  High-skilled Manual  42.0  42.2  35.7   Low-skilled Manual    7.7  10.9  Low-skilled Manual  6.6  7.0  5.0  France        Spain         Managers  16.2  30.3  9.8  Managers  29.6  34.2  12.3   Professionals  18.7  22.4  34.2  Professionals  10.0  17.2  24.4   Low-skilled Non-Manual  16.0  2.8  18.3  Low-skilled Non-Manual  6.9  7.7  30.8   High-skilled Manual  46.9  44.5  34.3  High-skilled Manual  41.4  31.2  25.4   Low-skilled Manual  2.2  0.0  3.5  Low-skilled Manual  12.0  9.8  7.1  Germany        Sweden         Managers  30.1  25.1  12.7  Managers    14.6  10.8   Professionals  33.1  41.2  51.0  Professionals    34.5  38.9   Low-skilled Non-Manual  8.2  7.9  16.8  Low-skilled Non-Manual    13.9  15.5   High-skilled Manual  25.0  22.6  16.5  High-skilled Manual    27.7  25.0   Low-skilled Manual  3.6  3.3  3.0  Low-skilled Manual    9.2  9.7  Greece        Switzerland         Managers  25.9  30.3  8.9  Managers    8.5  11.8   Professionals  10.6  15.4  20.7  Professionals    39.8  44.3   Low-skilled Non-Manual  6.5  5.3  21.0  Low-skilled Non-Manual    14.0  14.9   High-skilled Manual  49.8  41.9  42.9  High-skilled Manual    33.6  25.9   Low-skilled Manual  7.2  7.0  6.5  Low-skilled Manual    4.1  3.0  Ireland        UK         Managers  9.5  45.3  16.8  Managers  19.7  17.9  13.8   Professionals  13.6  18.3  24.8  Professionals  24.8  28.8  31.9   Low-skilled Non-Manual  15.0  5.9  10.4  Low-skilled Non-Manual  7.2  10.0  15.0   High-skilled Manual  52.0  21.0  38.1  High-skilled Manual  35.1  30.1  26.6   Low-skilled Manual  9.9  9.5  10.0  Low-skilled Manual  13.2  13.3  12.7  Italy                 Managers  5.6  27.3  11.6           Professionals  20.0  31.0  36.6           Low-skilled Non-Manual  28.0  8.4  20.4           High-skilled Manual  36.2  25.6  24.8           Low-skilled Manual  10.1  7.7  6.7          † ISCO-08: Managers (ISCO 1); Professionals (ISCO 2–3); Low-skilled Non-Manual (ISCO 4–5); High-skilled0 Manual (ISCO 6–7); Low-skilled Manual (8–9). Source: Eurostat, EU Labour Force Survey (1994, 2004, 2014), own calculations. View Large Table 3 also supports the notion that with its recent rise, self-employment has also become increasingly polarized. In the majority of countries, self-employment has grown among both high-skilled professionals (including technicians and associate professionals) as well as low-skilled occupations, such as clerks and other service and sales workers. Again, these developments match the shifts in Table 2 toward self-employment activities in service-oriented industries. In particular, the share of professionals increased remarkably and is now the largest category of self-employment in more than halve of the countries in Table 2 . In Germany (51%) and Luxembourg (65%), the majority of self-employed even works within this occupational category. 3. Solo self-employment: autonomous or atypical? 2 3 .1 Differences with temporary employees Based on the traditional distinction between self-employment and paid-employment, especially temporary employees should differ sharply from self-employed persons with respect to their political orientations. Not only do their positions diverge, people in self-employment and temporary employment may also have conflicting labor market interests. As (potential) employers, people in self-employment would consider temporary workers as an important source of flexible labor. The ability to hire (and easily fire) fixed-term personnel reduces the entrepreneurial risks associated with changes in demand and supply, by partially transferring those market risks to employees on temporary contracts. Flexible markets, and a low level of social protection help entrepreneurial freedom of people in self-employment, but harm the position of temporary employees, and vice versa. Unlike the self-employed, temporary employees are therefore assumed to be more supportive of parties and policies supporting welfare protection ( Corbetta and Colloca, 2013 ; Marx and Picot, 2013 ; Marx, 2014 ). The first hypothesis of this study will explicitly test whether differences in, and conflict of interest over labor market risks between (temporary) employees and people in self-employment lead to distinct patterns of political orientation. Hypothesis 1: Comparedwithpermanent employees, (a) temporary workers have a more left-wing political orientation and (b) solo self-employed have a more right-wing political orientation. 3.2 Similarities with temporary employees Arum and Müller (2004) have argued that because ‘self-employment is no longer simply dominated by petty bourgeois self-employment, this social grouping can no longer be understood as a politically conservative force’ (2004, p. 453). The heterogeneity among the self-employed suggests that there are considerable differences in labor market risks. As self-employment increasingly consists of quasi-independent subcontractors, freelancing professionals and others in semi-autonomous work arrangements, the boundaries blur between self-employment and wage-employment ( Muehlberger, 2007 ; Barbieri and Scherer, 2009 ). ‘New’ types of self-employment are more and more seen as atypical work relationships, similar to temporary employment, with higher labor market risks than for traditional ‘petty bourgeois’ entrepreneurs ( Schulze Buschoff and Schmidt, 2009 ; Standing, 2011 ). In this study, I examine whether more precarious labor market positions for solo self-employed are associated with political preferences that are similar to the preferences of paid-employees in atypical work relationships. In doing so, I account for two conditions that may moderate the relationship between employment type and political orientation: the degree of job autonomy and the degree of economic insecurity . 3.3 Job autonomy Autonomy in the workplace may affect workers value-orientations ( Kohn, 1995 ). Kitschelt and Rehm, 2014 ) suggest that ‘people who enjoy discretion and autonomy in their professional life generalize these experiences of an individualistic, universalistic mode of accountability and action to other spheres of life as well’ (pp.1674–1675). With respect to political and economic attitudes, a larger degree of job autonomy can be associated with economic conservatism, i.e.: opposition to redistribution and other government interventions, which might limit individual freedom ( De Witte, 1999 ; Kitschelt and Rehm, 2014 ). The right-wing political orientations of self-employed workers are often attributed to the fact that they have discretion over business activities and take individual responsibility for rewards and costs associated with market pressures. Due to their autonomous positions, people in self-employment would advocate individual freedom, initiative and responsibility, and therefore reject redistribution policies and collective security arrangements. Conversely, also the left-wing political orientation of temporary employees can be related to job autonomy. Temporary workers, generally enjoy lower job discretion and job autonomy than permanent employees ( Gallie et al. , 1998 ). A lack of autonomy in the workplace can strengthen economic progressive, left-wing preferences ( De Witte, 1999 ; Kitschelt and Rehm, 2014 ). The increased heterogeneity of self-employment to some extent obscured the ideal-typical image of self-employment as autonomous employment type, or one that is very distinct from wage-employment ( Stanworth and Stanworth, 1995 ; Pernicka, 2006 ; Schulze Buschoff and Protsch, 2008 ). It has become apparent that not all self-employed workers enjoy greater autonomy compared with paid-employees. There is a growing group of so-called ‘dependent self-employed’, workers who are formally in self-employment but work in hierarchical subordination to a single firm on which they are economically dependent ( Muehlberger, 2007 ). Hiring quasi-independent subcontractors, or others in semi-autonomous forms of self-employment, is sometimes used as a way to evade employment protection legislation ( Román et al. 2011 ). For people in self-employment, lower levels of job autonomy are associated with higher labor market risks. As they are ‘dependent on others for allocating them tasks over which they have little control’ ( Standing, 2011 , p. 16) dependent self-employed workers bear the entrepreneurial risk without entrepreneurial independence. Self-employed who enjoy lower autonomy in their professional life may adopt a less individualistic perception of accountability and responsibility with respect to redistribution policies, collective security arrangements and other government interventions. I therefore expect that the degree of job autonomy moderates the relationship between employment type and political orientation and that—both for temporary workers and self-employed workers—greater job autonomy is related to right-wing attitudes, and lower autonomy to left-wing attitudes. Hence, expanding on the first general hypothesis, I formulate: Hypothesis 2a: The left-wing political orientation of temporary workers is weaker as they have more autonomy over their job. Hypothesis 2b: The right-wing political orientation of solo self-employed workers is stronger as they have more autonomy over their job. 3.4 Economic insecurity Theories on job or economic insecurity and political divisions suggest that labor market vulnerabilities are generally associated with support for leftist parties and pro-welfare policies ( Corbetta and Colloca, 2013 ; Marx and Picot, 2013 ; Marx, 2014 ). People on temporary contracts would be left-leaning because there are exposed to greater risks than permanent employees. Conversely, high job security is often mentioned as one of the driving forces for traditional self-employed to support right-wing parties ( Nieuwbeerta and De Graaf, 1999 ). Again, it can be argued that the rise of ‘new’ forms of self-employment blurred the boundaries between self-employment and temporary employment ( Barbieri and Scherer, 2009 ). Contrary to the archetypical image of stable and secure self-employment, risks are assumed to be high instead of low for particular types of solo self-employment. For one, greater risks arise from the instability of self-employment careers; being self-employed is more and more a temporary situation; compared with those in more traditional types of self-employment (e.g. farmers and shop owners), ‘new’ self-employed are more often former employees, and they are less likely to stay self-employed ( Arum and Müller, 2004 ), and have a higher risk of exiting to unemployment ( Schulze Buschoff and Protsch 2008 ). Moreover, risks may be high due to uncertainty of income. People working on their own account without employees are often reliant on more irregular, potentially lower income, with less capacity for savings, insurance and pensions ( Schulze Buschoff and Schmidt, 2009 ; Dekker, 2010 ; Pedersini and Coletto, 2010 ). Especially unskilled self-employment is generally instable and most poorly paid ( McManus, 2000 ; Lofstrom, 2013 ). Dekker (2010) shows that among self-employed persons, employment-related risks can be related to support for collectivist welfare schemes. For future studies, he suggests that different types of self-employed workers, with disparate risk perceptions, might be related to different attitudes toward welfare state support (2010, p. 781). Hence, instead of politically right-wing, self-employed workers in a more precarious situation (e.g. unstable work, irregular income, underinsured) might be more to the left, i.e. more close to the preferences of paid-employees in atypical work relationships. I therefore expect that the degree of economic insecurity moderates the relationship between employment type and political orientation, and that—both for temporary workers and solo self-employed workers—greater economic security is related to right-wing attitudes, and lower security to left-wing attitudes. Therefore, I formulate: Hypothesis 3a: The left-wing political orientation of temporary workers is stronger as their economic insecurities are higher Hypothesis 3b: The right-wing political orientation of solo self-employed workers is weaker as their economic insecurities are higher 3.5 Data and measurements To test the hypotheses, I use the integrated file of the fourth wave of the ESS. This file is chosen for three reasons. First, disentangling the political alignments of various groups of self-employed workers requires a sufficiently large sample size. In Europe, with average self-employment rates around 10–15%, national political surveys often contain too few cases to differentiate among types of self-employment. Therefore, despite the drawbacks, a pooled dataset is needed to study the political attitudes of a large group of people in self-employment. Second, the ESS is the only large- N datasets that contains information on both atypical employment (i.e. temporary work) and political attitudes ( Kitschelt and Rehm, 2014 ; Marx, 2014 ). And third, the ESS-4 of 2008 not only provides an extensive set of items to measure welfare attitudes, but also includes indicators of job insecurity and job control. To make the analysis as comparable as possible, I only include Western European countries with a more or less similar political party structure, including the presence of both old- and new-left political parties. These countries are: Austria, Belgium, Denmark, France, Germany, the Netherlands, Norway and Switzerland. Moreover, I only included respondents of working age (15–64) in employment (wage-employment or self-employment) and without missing information on relevant variables. Ultimately, the analysis is based on 7186 respondents, of which there are 852 self-employed (i.e. 347 with and 505 without employees). Below I discuss the key variables in more detail; descriptive statistics are presented in Appendix Table A1 . 3.6 Dependent variables To examine the political orientations I use two kinds of variables, attitudes on welfare policies and political party preferences . First, attitudes on welfare policies are measured using five items on what the responsibilities of governments should or should not be. Respondents were asked to rate on an 11-point scale whether the government should ‘not be responsible at all’ (0) or should be ‘entirely responsible’(10) for particular tasks, i.e.: ensure (a) a job for everyone who wants one, (b) adequate health care for the sick, (c) a reasonable standard of living for the old, (d) a reasonable standard of living for the unemployed and (e) provide paid leave from work for people who temporarily have to care for sick family members. A reliability analysis confirmed that the items constitute an adequately reliable scale (Cronbach’s alpha = 0.76). A scale is constructed on the basis of the mean value over the five items, coded in such a way that a higher value indicates a more pro-welfare attitude. 3 Second, following Marx (2014) , political party preferences are primarily measured using party identification rather than voting behavior. Because vote choice is reported retrospectively in the ESS, Marx (2014 , p. 11) argues that the gap between the last election and the time of data collection may cause problems regarding temporary employees with short-duration contracts. Especially for this group, he argues, the ESS provides no reliable information about respondents’ labor market status at the time of last election. The same, I can add, may hold for people in new self-employment, for whom being self-employed is more often a temporary situation. Only for respondents who report no closer attachment to any particular party than all other parties, vote choice is used to proxy their political orientation. Political orientation is measured in three-party categories using the party family classification on the Manifesto Project Database ( Volkens et al. , 2013 ), i.e.: new-left parties (ecology parties), old-left parties (combining (former) communist and social democratic parties), right-wing (combing liberal parties, Christian democrats, conservative, agrarian parties and nationalist parties). 4 3.7 Job characteristics The main independent variables are related to characteristics of the respondent’s job, i.e.: employment type, job autonomy, and economic insecurity . The variable for employment type distinguishes between four employment groups: (a) employees with a permanent contract, (b) temporary employees (with a fixed-term or no contract), (c) people in solo self-employment (without employees) and (d) employers (self-employed with employees). The degree of economic insecurity is measured used two separate items, employment insecurity and income insecurity . Respondents were asked to rate on a 4-point scale how likely it is that during the next 12 months they would (a) be unemployed and looking for work, and (b) not have enough money to cover household necessities. Both variables are recoded into a 3-point scale by collapsing the upper two categories (i.e. ‘[very] likely’), so that a high score relates to a more insecure situation. To measure job autonomy two items were used: Respondents were asked to rate on a 10-point scale how much influence they had (a) to decide how daily work is organized and (b) on policy decision about the organization’s activity. An index was constructed by taking the product of the two variables divided by hundred. This index ranges between 0 ‘no job autonomy’ and 1 ‘full job autonomy’. 3.8 Control variables Next to the main variables a number of control variables are included in the analysis: first, I control for occupation . This variable was measured on the basis 1-digit ISCO-88 classifications. The same five occupational groups are distinguished as in the aggregate statistics presented earlier: Managers (ISCO 1), Professionals (ISCO 2–3), Low-skilled Non-Manual (ISCO 4–5), High-skilled Manual (ISCO 6–7) and Low-skilled Manual (8–9). Moreover, control variables are included for income (measured as total net household income in deciles), part-time work (i.e. less than 30 hours a week = 1), and gender (female = 1). Finally, variables are included for age (15 = 0) and the level of education : based on harmonized International Standard Classification of Education (ISCED) categories, distinguishing between a ‘low-level education’ (ISCED 0–2), ‘medium-level education’ (ISCED 3–4) and ‘high-level education’ (ISCED 5–6). 4. Analyses and results 4.1 Attitudes on welfare policies I start with a regression analysis for pro-welfare attitudes, see Table 4 . The coefficients ( b ) denote the unstandardized coefficients for respondents of attributing a higher responsibility to the government in providing welfare tasks. The standard errors (SEs) are adjusted for clustering in countries. Moreover, country-dummy variables are added to capture national differences in welfare support (not shown for reasons of space), and population size and ESS design weights are applied. 5 Table 4. Regression analysis for pro-welfare attitudes (robust SEs in parentheses)   Model 1   Model 2     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  0.129 **  (0.04)  0.129 **  (0.04)   Solo self-employed  −0.227 ***  (0.05)  −0.296 ***  (0.06)   Employer  −0.207  (0.18)  −0.260  (0.19)  Perceived income insecurity      0.159 **  (0.06)  Perceived employment insecurity      −0.034  (0.06)  Perceived job autonomy      0.128 ***  (0.02)  Income  −0.053 ***  (0.01)  −0.046 ***  (0.01)  Occupation (professionals = ref)  –  –  –  –   Managers  −0.263 ***  (0.04)  −0.291 ***  (0.03)   Low-skilled Non-Manual  −0.049  (0.05)  −0.042  (0.05)   High-skilled Manual  0.099 **  (0.04)  0.098 **  (0.03)   Low-skilled Manual  0.128  (0.08)  0.134*  (0.06)  Part-time  −0.032  (0.15)  −0.035  (0.15)  Age  0.008 **  (0.00)  0.008 **  (0.00)  Female  0.165  (0.11)  0.162  (0.11)  Education (middle = ref)  –  –  –  –   Lower  −0.163 **  (0.07)  −0.162 **  (0.06)   Higher  −0.104 *  (0.04)  −0.091 *  (0.04)  Constant  8.000 ***  (0.13)  7.779 ***  0.04    Model 1   Model 2     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  0.129 **  (0.04)  0.129 **  (0.04)   Solo self-employed  −0.227 ***  (0.05)  −0.296 ***  (0.06)   Employer  −0.207  (0.18)  −0.260  (0.19)  Perceived income insecurity      0.159 **  (0.06)  Perceived employment insecurity      −0.034  (0.06)  Perceived job autonomy      0.128 ***  (0.02)  Income  −0.053 ***  (0.01)  −0.046 ***  (0.01)  Occupation (professionals = ref)  –  –  –  –   Managers  −0.263 ***  (0.04)  −0.291 ***  (0.03)   Low-skilled Non-Manual  −0.049  (0.05)  −0.042  (0.05)   High-skilled Manual  0.099 **  (0.04)  0.098 **  (0.03)   Low-skilled Manual  0.128  (0.08)  0.134*  (0.06)  Part-time  −0.032  (0.15)  −0.035  (0.15)  Age  0.008 **  (0.00)  0.008 **  (0.00)  Female  0.165  (0.11)  0.162  (0.11)  Education (middle = ref)  –  –  –  –   Lower  −0.163 **  (0.07)  −0.162 **  (0.06)   Higher  −0.104 *  (0.04)  −0.091 *  (0.04)  Constant  8.000 ***  (0.13)  7.779 ***  0.04  Notes: * P  < 0.1; ** P  < 0.05; *** P  < 0.01 (two-tailed test); robust SEs for country-clustering. Population size and design weights applied. Not shown: country dummy variables. View Large Table 4. Regression analysis for pro-welfare attitudes (robust SEs in parentheses)   Model 1   Model 2     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  0.129 **  (0.04)  0.129 **  (0.04)   Solo self-employed  −0.227 ***  (0.05)  −0.296 ***  (0.06)   Employer  −0.207  (0.18)  −0.260  (0.19)  Perceived income insecurity      0.159 **  (0.06)  Perceived employment insecurity      −0.034  (0.06)  Perceived job autonomy      0.128 ***  (0.02)  Income  −0.053 ***  (0.01)  −0.046 ***  (0.01)  Occupation (professionals = ref)  –  –  –  –   Managers  −0.263 ***  (0.04)  −0.291 ***  (0.03)   Low-skilled Non-Manual  −0.049  (0.05)  −0.042  (0.05)   High-skilled Manual  0.099 **  (0.04)  0.098 **  (0.03)   Low-skilled Manual  0.128  (0.08)  0.134*  (0.06)  Part-time  −0.032  (0.15)  −0.035  (0.15)  Age  0.008 **  (0.00)  0.008 **  (0.00)  Female  0.165  (0.11)  0.162  (0.11)  Education (middle = ref)  –  –  –  –   Lower  −0.163 **  (0.07)  −0.162 **  (0.06)   Higher  −0.104 *  (0.04)  −0.091 *  (0.04)  Constant  8.000 ***  (0.13)  7.779 ***  0.04    Model 1   Model 2     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  0.129 **  (0.04)  0.129 **  (0.04)   Solo self-employed  −0.227 ***  (0.05)  −0.296 ***  (0.06)   Employer  −0.207  (0.18)  −0.260  (0.19)  Perceived income insecurity      0.159 **  (0.06)  Perceived employment insecurity      −0.034  (0.06)  Perceived job autonomy      0.128 ***  (0.02)  Income  −0.053 ***  (0.01)  −0.046 ***  (0.01)  Occupation (professionals = ref)  –  –  –  –   Managers  −0.263 ***  (0.04)  −0.291 ***  (0.03)   Low-skilled Non-Manual  −0.049  (0.05)  −0.042  (0.05)   High-skilled Manual  0.099 **  (0.04)  0.098 **  (0.03)   Low-skilled Manual  0.128  (0.08)  0.134*  (0.06)  Part-time  −0.032  (0.15)  −0.035  (0.15)  Age  0.008 **  (0.00)  0.008 **  (0.00)  Female  0.165  (0.11)  0.162  (0.11)  Education (middle = ref)  –  –  –  –   Lower  −0.163 **  (0.07)  −0.162 **  (0.06)   Higher  −0.104 *  (0.04)  −0.091 *  (0.04)  Constant  8.000 ***  (0.13)  7.779 ***  0.04  Notes: * P  < 0.1; ** P  < 0.05; *** P  < 0.01 (two-tailed test); robust SEs for country-clustering. Population size and design weights applied. Not shown: country dummy variables. View Large In Model 1, I run a model with only employment type and the control variables. I test the general hypothesis that people in solo self-employment are, everything else held equal, politically more to the right (i.e. oppose government responsibility in the domain of social welfare) and temporary employees are politically more to the left (i.e. support government responsibility in providing social welfare). The reference category in this model is formed by people on permanent employment contracts. For the hypothesis to hold, I would have to find a negative effect of solo self-employment, and a positive effect of temporary employment. The model shows that there is indeed a positive effect of temporary employment (0.129) and a negative effect of solo self-employment (−0.227). Hence, these results provide support for hypothesis 1: compared with permanent employees, temporary workers have a somewhat more leftist political orientation, and self-employed have a more right-wing political orientation. In Model 2, I add indicators for perceived employment insecurity, income insecurity and job autonomy. Before testing whether the aforementioned-effects of temporary employment and solo self-employment are moderated by such characteristics related to precariousness and/or job control, I first assess the direct effects of these variables. The model shows that welfare state support is stronger for respondents perceiving their income as insecure (0.159), and for respondents with greater job autonomy (0.128). As expected, labor market vulnerabilities (i.e. insecurities of income) are generally associated with support for pro-welfare policies. For perceived employment insecurity, however, this effect is not found. Moreover, contrarily to the expectation greater autonomy at the workplace seems to correlate positively instead of negatively with pro-welfare attitudes. In Table 5 interaction effects are introduced between employment type on the one hand and on the other hand income insecurity (Model 3), employment insecurity (Model 4) and job autonomy (Model 5). This way, I can test the hypotheses that the left-wing, pro-welfare attitudes of temporary workers are weaker as they have more autonomy over their job, and stronger as their economic insecurities are higher (hypothesis 2a and 3a, respectively). The results in Table 5 , however, generally do not support hypothesis 2a and 3a; there appears to be no significant interaction between temporary employment and income insecurity (Model 3), employment insecurity (Model 4) or job autonomy (Model 5). Hence, pro-welfare orientation of temporary workers is not stronger as their economic insecurities are higher, nor weaker as they have more autonomy over their job. Table 5. Interaction effects for pro-welfare attitudes (robust SEs in parentheses)   Model 3     ( b )   SE  Employment (permanent employee = ref)  –  –   Temporary employee  0.201 **  (0.07)   Solo self-employed  −0.222 ***  (0.04)   Employer  −0.405 **  (0.14)  Perceived income insecurity  0.165 **  (0.05)   ×Temporary employee  −0.072  (0.06)   × Solo self-employed  −0.086  (0.07)   × Employer  0.256 *  (0.13)      Model 4     ( b )   SE    Employment (permanent employee = ref)  –  –   Temporary employee  0.173 **  (0.06)   Solo self-employed  −0.429 ***  (0.08)   Employer  −0.418  (0.23)  Perceived employment insecurity  −0.056  (0.06)   ×Temporary employee  −0.030  (0.02)   × Solo self-employed  0.201 ***  (0.05)   × Employer  0.408 **  (0.12)      Model 5     ( b )   SE    Employment (permanent employee = ref)  –  –   Temporary employee  0.155 *  (0.07)   Solo self-employed  0.131  (0.21)   Employer  −0.486 ***  (0.13)  Perceived job autonomy  0.179 ***  (0.02)   ×Temporary employee  −0.085  (0.14)   × Solo self-employed  −0.546 **  (0.22)   × Employer  0.216  (0.27)    Model 3     ( b )   SE  Employment (permanent employee = ref)  –  –   Temporary employee  0.201 **  (0.07)   Solo self-employed  −0.222 ***  (0.04)   Employer  −0.405 **  (0.14)  Perceived income insecurity  0.165 **  (0.05)   ×Temporary employee  −0.072  (0.06)   × Solo self-employed  −0.086  (0.07)   × Employer  0.256 *  (0.13)      Model 4     ( b )   SE    Employment (permanent employee = ref)  –  –   Temporary employee  0.173 **  (0.06)   Solo self-employed  −0.429 ***  (0.08)   Employer  −0.418  (0.23)  Perceived employment insecurity  −0.056  (0.06)   ×Temporary employee  −0.030  (0.02)   × Solo self-employed  0.201 ***  (0.05)   × Employer  0.408 **  (0.12)      Model 5     ( b )   SE    Employment (permanent employee = ref)  –  –   Temporary employee  0.155 *  (0.07)   Solo self-employed  0.131  (0.21)   Employer  −0.486 ***  (0.13)  Perceived job autonomy  0.179 ***  (0.02)   ×Temporary employee  −0.085  (0.14)   × Solo self-employed  −0.546 **  (0.22)   × Employer  0.216  (0.27)  Notes: * P  < 0.1; ** P  < 0.05; *** P  < 0.01 (two-tailed test); robust SEs for country-clustering. Population size and design weights applied. All models controlled for income, occupational class, part-time, age, gender, education and country-dummies (see Table 1 ). View Large Table 5. Interaction effects for pro-welfare attitudes (robust SEs in parentheses)   Model 3     ( b )   SE  Employment (permanent employee = ref)  –  –   Temporary employee  0.201 **  (0.07)   Solo self-employed  −0.222 ***  (0.04)   Employer  −0.405 **  (0.14)  Perceived income insecurity  0.165 **  (0.05)   ×Temporary employee  −0.072  (0.06)   × Solo self-employed  −0.086  (0.07)   × Employer  0.256 *  (0.13)      Model 4     ( b )   SE    Employment (permanent employee = ref)  –  –   Temporary employee  0.173 **  (0.06)   Solo self-employed  −0.429 ***  (0.08)   Employer  −0.418  (0.23)  Perceived employment insecurity  −0.056  (0.06)   ×Temporary employee  −0.030  (0.02)   × Solo self-employed  0.201 ***  (0.05)   × Employer  0.408 **  (0.12)      Model 5     ( b )   SE    Employment (permanent employee = ref)  –  –   Temporary employee  0.155 *  (0.07)   Solo self-employed  0.131  (0.21)   Employer  −0.486 ***  (0.13)  Perceived job autonomy  0.179 ***  (0.02)   ×Temporary employee  −0.085  (0.14)   × Solo self-employed  −0.546 **  (0.22)   × Employer  0.216  (0.27)    Model 3     ( b )   SE  Employment (permanent employee = ref)  –  –   Temporary employee  0.201 **  (0.07)   Solo self-employed  −0.222 ***  (0.04)   Employer  −0.405 **  (0.14)  Perceived income insecurity  0.165 **  (0.05)   ×Temporary employee  −0.072  (0.06)   × Solo self-employed  −0.086  (0.07)   × Employer  0.256 *  (0.13)      Model 4     ( b )   SE    Employment (permanent employee = ref)  –  –   Temporary employee  0.173 **  (0.06)   Solo self-employed  −0.429 ***  (0.08)   Employer  −0.418  (0.23)  Perceived employment insecurity  −0.056  (0.06)   ×Temporary employee  −0.030  (0.02)   × Solo self-employed  0.201 ***  (0.05)   × Employer  0.408 **  (0.12)      Model 5     ( b )   SE    Employment (permanent employee = ref)  –  –   Temporary employee  0.155 *  (0.07)   Solo self-employed  0.131  (0.21)   Employer  −0.486 ***  (0.13)  Perceived job autonomy  0.179 ***  (0.02)   ×Temporary employee  −0.085  (0.14)   × Solo self-employed  −0.546 **  (0.22)   × Employer  0.216  (0.27)  Notes: * P  < 0.1; ** P  < 0.05; *** P  < 0.01 (two-tailed test); robust SEs for country-clustering. Population size and design weights applied. All models controlled for income, occupational class, part-time, age, gender, education and country-dummies (see Table 1 ). View Large Next, Models 4 and 5 may be used to test whether the right-wing political orientation of solo self-employed workers is stronger as they have more autonomy over their job, and weaker as their economic insecurities are higher (hypothesis 2b and 3b, respectively). Model 4 shows a negative main-effect of solo self-employment on pro-welfare attitudes (−0.429), and a significant positive interaction effect between self-employment and employment insecurity (0.201). As expected, this result indicates that people in solo self-employment, compared with permanent employees, are more likely to support welfare policies as they are more insecure with respect to their employment position. To ease interpretation, I have plotted this effect in Figure 3b . Model 5 shows the interaction between self-employment and job autonomy. Here I find a negative main-effect (−0,486) combined with a negative interaction-effect (−0,546), indicating that people in solo self-employment, compared with permanent employees, are even less likely to support welfare policies as they are more autonomous with respect to their job. This effect is plotted in Figure 3c . In general these results seem to support hypothesis 2b and 3b. Figure 2b and c indicates that self-employed workers are more left-wing orientated as their employment insecurities are higher, and more right-wing orientated as they are more autonomous. Yet, a reservation applies: unlike employment insecurity, income insecurity does not moderate the effect of solo self-employment on welfare attitudes ( Figure 3a ). Figure 3. View largeDownload slide Interaction effects on pro-welfare attitudes (predicted values) † . † Confidence intervals (95%) for the solo self-employed and permanent wage-employees. Figure 3. View largeDownload slide Interaction effects on pro-welfare attitudes (predicted values) † . † Confidence intervals (95%) for the solo self-employed and permanent wage-employees. 4.2 Political party preferences So far, I examined political orientations by looking at welfare attitudes, specifically with respect to the role of governments. Next, I will shift the focus to party preferences. For this purpose, I use a multinomial logit model with three outcome categories, i.e.: new-left, old-left, and right-wing parties, see Table 6 . The reference outcome category is formed by the right-wing parties. Again, the SEs are adjusted for country-clustering, country-dummy variables are added, and population and design weights are applied. Table 6. Multinomial logit regression for party preference (robust SEs in parentheses)   Model 1     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.107  (0.16)  −0.012  (0.19)   Solo self-employed  −0.605 **  (0.24)  0.288 **  (0.12)   Employer  −0.853 ***  (0.15)  −0.413 **  (0.18)  Perceived income insecurity  0.225 ***  (0.04)  0.046  (0.08)  Perceived employment insecurity  −0.009  (0.02)  0.055  (0.09)  Perceived job autonomy  −0.319 *  (0.19)  −0.076  (0.06)  Income  −0.087 ***  (0.02)  −0.099 ***  (0.02)  Occupation (Professionals = ref)  –  –  –  –   Managers  −0.599 *  (0.34)  −0.619 **  (0.31)   Low-skilled Non-Manual  −0.467 ***  (0.16)  −0.656 ***  (0.21)   High-skilled Manual  −0.243  (0.15)  −0.905 *  (0.54)   Low-skilled Manual  0.113  (0.16)  −0.411  (0.48)  Part-time  0.185 *  (0.10)  0.466 ***  (0.11)  Age  0.012 ***  (0.00)  −0.002  (0.00)  Female  0.229 ***  (0.06)  0.199  (0.14)  Education (lower = ref)  –  –  –  –   Middle  0.071  (0.12)  −0.222  (0.19)   High  0.199  (0.12)  0.704 ***  (0.07)  Constant  0.252 *  (0.15)  −3.224 ***  (0.34)    Model 1     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.107  (0.16)  −0.012  (0.19)   Solo self-employed  −0.605 **  (0.24)  0.288 **  (0.12)   Employer  −0.853 ***  (0.15)  −0.413 **  (0.18)  Perceived income insecurity  0.225 ***  (0.04)  0.046  (0.08)  Perceived employment insecurity  −0.009  (0.02)  0.055  (0.09)  Perceived job autonomy  −0.319 *  (0.19)  −0.076  (0.06)  Income  −0.087 ***  (0.02)  −0.099 ***  (0.02)  Occupation (Professionals = ref)  –  –  –  –   Managers  −0.599 *  (0.34)  −0.619 **  (0.31)   Low-skilled Non-Manual  −0.467 ***  (0.16)  −0.656 ***  (0.21)   High-skilled Manual  −0.243  (0.15)  −0.905 *  (0.54)   Low-skilled Manual  0.113  (0.16)  −0.411  (0.48)  Part-time  0.185 *  (0.10)  0.466 ***  (0.11)  Age  0.012 ***  (0.00)  −0.002  (0.00)  Female  0.229 ***  (0.06)  0.199  (0.14)  Education (lower = ref)  –  –  –  –   Middle  0.071  (0.12)  −0.222  (0.19)   High  0.199  (0.12)  0.704 ***  (0.07)  Constant  0.252 *  (0.15)  −3.224 ***  (0.34)  Notes: * P  < 0.1; ** P  < 0.05; *** P  < 0.01 (two-tailed test); robust SEs for country-clustering. Population size and design weights applied. Not shown: country-dummy variables. View Large Table 6. Multinomial logit regression for party preference (robust SEs in parentheses)   Model 1     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.107  (0.16)  −0.012  (0.19)   Solo self-employed  −0.605 **  (0.24)  0.288 **  (0.12)   Employer  −0.853 ***  (0.15)  −0.413 **  (0.18)  Perceived income insecurity  0.225 ***  (0.04)  0.046  (0.08)  Perceived employment insecurity  −0.009  (0.02)  0.055  (0.09)  Perceived job autonomy  −0.319 *  (0.19)  −0.076  (0.06)  Income  −0.087 ***  (0.02)  −0.099 ***  (0.02)  Occupation (Professionals = ref)  –  –  –  –   Managers  −0.599 *  (0.34)  −0.619 **  (0.31)   Low-skilled Non-Manual  −0.467 ***  (0.16)  −0.656 ***  (0.21)   High-skilled Manual  −0.243  (0.15)  −0.905 *  (0.54)   Low-skilled Manual  0.113  (0.16)  −0.411  (0.48)  Part-time  0.185 *  (0.10)  0.466 ***  (0.11)  Age  0.012 ***  (0.00)  −0.002  (0.00)  Female  0.229 ***  (0.06)  0.199  (0.14)  Education (lower = ref)  –  –  –  –   Middle  0.071  (0.12)  −0.222  (0.19)   High  0.199  (0.12)  0.704 ***  (0.07)  Constant  0.252 *  (0.15)  −3.224 ***  (0.34)    Model 1     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.107  (0.16)  −0.012  (0.19)   Solo self-employed  −0.605 **  (0.24)  0.288 **  (0.12)   Employer  −0.853 ***  (0.15)  −0.413 **  (0.18)  Perceived income insecurity  0.225 ***  (0.04)  0.046  (0.08)  Perceived employment insecurity  −0.009  (0.02)  0.055  (0.09)  Perceived job autonomy  −0.319 *  (0.19)  −0.076  (0.06)  Income  −0.087 ***  (0.02)  −0.099 ***  (0.02)  Occupation (Professionals = ref)  –  –  –  –   Managers  −0.599 *  (0.34)  −0.619 **  (0.31)   Low-skilled Non-Manual  −0.467 ***  (0.16)  −0.656 ***  (0.21)   High-skilled Manual  −0.243  (0.15)  −0.905 *  (0.54)   Low-skilled Manual  0.113  (0.16)  −0.411  (0.48)  Part-time  0.185 *  (0.10)  0.466 ***  (0.11)  Age  0.012 ***  (0.00)  −0.002  (0.00)  Female  0.229 ***  (0.06)  0.199  (0.14)  Education (lower = ref)  –  –  –  –   Middle  0.071  (0.12)  −0.222  (0.19)   High  0.199  (0.12)  0.704 ***  (0.07)  Constant  0.252 *  (0.15)  −3.224 ***  (0.34)  Notes: * P  < 0.1; ** P  < 0.05; *** P  < 0.01 (two-tailed test); robust SEs for country-clustering. Population size and design weights applied. Not shown: country-dummy variables. View Large In Model 1, the general expectation is tested that temporary employees are, everything else held equal, politically more to the left (i.e. are more likely to support old- or new-left parties) and self-employed workers are politically more to the right (i.e. less likely to support old- or new-left parties). People working on permanent employment contracts function as the reference group. Model 1 shows that people in solo self-employment are indeed less likely (−0.605) to prefer an old-left party. Support for the old-left is lowest for employers, that is, for self-employed with personnel (−0.853). Yet, with respect to new-left versus right-wing parties the effect of solo self-employment is even positive (0.288). Surprisingly, solo self-employed workers are even more strongly oriented toward new-left parties, compared with permanent employees. Moreover, contrarily the expectation, there are no significant effects for temporary employment. Compared with employees on permanent contracts, temporary workers neither have a stronger preference for old-left parties, nor for new-left parties. To assess whether the effects of employment type are moderated by income insecurity, employment insecurity and job autonomy, interactions should be introduced. Before adding these interaction effects, I first examine the direct effects of these variables on party preference. Model 1 shows that income insecurity (0.225) is positively related to an old-left party orientation (vs. an orientation toward right-wing parties). People whose income is more insecure more often prefer old-left versus right-wing parties. Moreover, job autonomy shows a negative association with old-left party preferences (−0.319), indicating that people with greater autonomy at the workplace are less likely to prefer old-left parties. With respect to new-left party preferences, however, I find no direct effects of income insecurity and job autonomy. New-left party preferences seem unrelated to perceived insecurities in income and/or the degree of autonomy at the workplace. In Table 7 interaction effects are estimated between employment types on the one hand, and on the other hand income insecurity (Model 2), employment insecurity (Model 3) and job autonomy (Model 4). Let me first assess the moderating effect of income insecurity: with respect to supporting the old-left, Model 2 shows significant and positive interactions for temporary employment (0.505) and the solo self-employment (0.235). These effects indicate that, temporary workers and self-employed workers have a stronger preference for old-left parties when their income situation is more insecure. To ease interpretation, I have plotted these effects in Figure 4 . The other way around, Figure 4 also shows that right-wing party support among temporary employees and self-employed declines when income insecurity is higher; although for self-employed workers this effect seems surrounded with relatively high levels of uncertainty. What appears from both the table and the plots, it that new-left party orientations are not strongly moderated by income insecurity. Neither temporary employees, nor self-employed are more included to prefer new-left parties under greater uncertainty of income. Figure 4. View largeDownload slide Interaction effects with perceived income insecurity (predicted probabilities) † . † Confidence intervals (95%) for the solo self-employed and permanent wage-employees. Figure 4. View largeDownload slide Interaction effects with perceived income insecurity (predicted probabilities) † . † Confidence intervals (95%) for the solo self-employed and permanent wage-employees. Table 7. Interaction effects for party preference based on multinomial logit regression (robust SEs in parentheses)   Model 2     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.595 *  (0.31)  0.033  (0.33)   Solo self-employed  −0.806 ***  (0.22)  0.277 **  (0.11)   Employer  −0.891 ***  (0.16)  −0.815 ***  (0.29)  Perceived income insecurity  0.150 ***  (0.04)  0.028  (0.09)   ×Temporary employee  0.505 ***  (0.18)  −0.057  (0.23)   × Solo self-employed  0.235 ***  (0.06)  0.018  (0.20)   × Employer  0.046  (0.12)  0.729 **  (0.31)      Model 3     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE    Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.515 **  (0.25)  −0.037  (0.26)   Solo self-employed  −0.772 ***  (0.26)  −0.325 ***  (0.12)   Employer  −0.933 ***  (0.26)  −0.681 ***  (0.18)  Perceived employment insecurity  −0.093 ***  (0.03)  −0.077  (0.06)   ×Temporary employee  0.385 ***  (0.08)  0.072  (0.10)   × Solo self-employed  0.283 ***  (0.07)  0.879 ***  (0.32)   × Employer  0.170  (0.37)  0.589 ***  (0.11)      Model 4     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE    Employment (permanent employee = ref)  –  –  –  –   Temporary employee  0.057  (0.15)  −0.390  (0.29)   Solo self-employed  0.049  (0.41)  0.679  (0.43)   Employer  −2.511 **  (1.00)  1.156 **  (0.49)  Perceived job autonomy  −0.195  (0.19)  −0.138  (0.08)   ×Temporary employee  −0.604 **  (0.24)  1.116 ***  (0.32)   × Solo self-employed  −0.874  (0.65)  −0.423  (0.47)   × Employer  1.705  (1.15)  −1.730 **  (0.74)    Model 2     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.595 *  (0.31)  0.033  (0.33)   Solo self-employed  −0.806 ***  (0.22)  0.277 **  (0.11)   Employer  −0.891 ***  (0.16)  −0.815 ***  (0.29)  Perceived income insecurity  0.150 ***  (0.04)  0.028  (0.09)   ×Temporary employee  0.505 ***  (0.18)  −0.057  (0.23)   × Solo self-employed  0.235 ***  (0.06)  0.018  (0.20)   × Employer  0.046  (0.12)  0.729 **  (0.31)      Model 3     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE    Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.515 **  (0.25)  −0.037  (0.26)   Solo self-employed  −0.772 ***  (0.26)  −0.325 ***  (0.12)   Employer  −0.933 ***  (0.26)  −0.681 ***  (0.18)  Perceived employment insecurity  −0.093 ***  (0.03)  −0.077  (0.06)   ×Temporary employee  0.385 ***  (0.08)  0.072  (0.10)   × Solo self-employed  0.283 ***  (0.07)  0.879 ***  (0.32)   × Employer  0.170  (0.37)  0.589 ***  (0.11)      Model 4     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE    Employment (permanent employee = ref)  –  –  –  –   Temporary employee  0.057  (0.15)  −0.390  (0.29)   Solo self-employed  0.049  (0.41)  0.679  (0.43)   Employer  −2.511 **  (1.00)  1.156 **  (0.49)  Perceived job autonomy  −0.195  (0.19)  −0.138  (0.08)   ×Temporary employee  −0.604 **  (0.24)  1.116 ***  (0.32)   × Solo self-employed  −0.874  (0.65)  −0.423  (0.47)   × Employer  1.705  (1.15)  −1.730 **  (0.74)  Notes: * P  < 0.1; ** P  < 0.05; *** P  < 0.01 (two-tailed test); robust SEs for country-clustering. Population size and design weights applied. All models controlled for income, occupational class, part-time, age, gender, education, and country-dummies (see Table 4 ). View Large Table 7. Interaction effects for party preference based on multinomial logit regression (robust SEs in parentheses)   Model 2     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.595 *  (0.31)  0.033  (0.33)   Solo self-employed  −0.806 ***  (0.22)  0.277 **  (0.11)   Employer  −0.891 ***  (0.16)  −0.815 ***  (0.29)  Perceived income insecurity  0.150 ***  (0.04)  0.028  (0.09)   ×Temporary employee  0.505 ***  (0.18)  −0.057  (0.23)   × Solo self-employed  0.235 ***  (0.06)  0.018  (0.20)   × Employer  0.046  (0.12)  0.729 **  (0.31)      Model 3     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE    Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.515 **  (0.25)  −0.037  (0.26)   Solo self-employed  −0.772 ***  (0.26)  −0.325 ***  (0.12)   Employer  −0.933 ***  (0.26)  −0.681 ***  (0.18)  Perceived employment insecurity  −0.093 ***  (0.03)  −0.077  (0.06)   ×Temporary employee  0.385 ***  (0.08)  0.072  (0.10)   × Solo self-employed  0.283 ***  (0.07)  0.879 ***  (0.32)   × Employer  0.170  (0.37)  0.589 ***  (0.11)      Model 4     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE    Employment (permanent employee = ref)  –  –  –  –   Temporary employee  0.057  (0.15)  −0.390  (0.29)   Solo self-employed  0.049  (0.41)  0.679  (0.43)   Employer  −2.511 **  (1.00)  1.156 **  (0.49)  Perceived job autonomy  −0.195  (0.19)  −0.138  (0.08)   ×Temporary employee  −0.604 **  (0.24)  1.116 ***  (0.32)   × Solo self-employed  −0.874  (0.65)  −0.423  (0.47)   × Employer  1.705  (1.15)  −1.730 **  (0.74)    Model 2     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE  Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.595 *  (0.31)  0.033  (0.33)   Solo self-employed  −0.806 ***  (0.22)  0.277 **  (0.11)   Employer  −0.891 ***  (0.16)  −0.815 ***  (0.29)  Perceived income insecurity  0.150 ***  (0.04)  0.028  (0.09)   ×Temporary employee  0.505 ***  (0.18)  −0.057  (0.23)   × Solo self-employed  0.235 ***  (0.06)  0.018  (0.20)   × Employer  0.046  (0.12)  0.729 **  (0.31)      Model 3     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE    Employment (permanent employee = ref)  –  –  –  –   Temporary employee  −0.515 **  (0.25)  −0.037  (0.26)   Solo self-employed  −0.772 ***  (0.26)  −0.325 ***  (0.12)   Employer  −0.933 ***  (0.26)  −0.681 ***  (0.18)  Perceived employment insecurity  −0.093 ***  (0.03)  −0.077  (0.06)   ×Temporary employee  0.385 ***  (0.08)  0.072  (0.10)   × Solo self-employed  0.283 ***  (0.07)  0.879 ***  (0.32)   × Employer  0.170  (0.37)  0.589 ***  (0.11)      Model 4     Old-left versus right   New-left versus right     ( b )   SE  ( b )   SE    Employment (permanent employee = ref)  –  –  –  –   Temporary employee  0.057  (0.15)  −0.390  (0.29)   Solo self-employed  0.049  (0.41)  0.679  (0.43)   Employer  −2.511 **  (1.00)  1.156 **  (0.49)  Perceived job autonomy  −0.195  (0.19)  −0.138  (0.08)   ×Temporary employee  −0.604 **  (0.24)  1.116 ***  (0.32)   × Solo self-employed  −0.874  (0.65)  −0.423  (0.47)   × Employer  1.705  (1.15)  −1.730 **  (0.74)  Notes: * P  < 0.1; ** P  < 0.05; *** P  < 0.01 (two-tailed test); robust SEs for country-clustering. Population size and design weights applied. All models controlled for income, occupational class, part-time, age, gender, education, and country-dummies (see Table 4 ). View Large Next, in Model 3 interactions are included with employment insecurity. Again, I find positive interactions for temporary employees (0.385) and solo self-employed (0.283) in case of the old-left/right-wing contrast. Figure 5 shows that temporary workers are more strongly orientated toward old-left parties when their employment is more insecure. For people in solo self-employment job insecurity seems associated (albeit with some uncertainty) with a weaker right-wing orientation, but not necessarily with a stronger orientation toward the old-left. Instead, as an alternative for right-wing parties, insecure self-employed workers tend to support new-left parties. All in all, there seems support for hypotheses 3a and 3b: Not only the left-wing political orientation of temporary workers is stronger as their economic insecurities are higher, but also the left-wing orientation of solo self-employed workers. Figure 5. View largeDownload slide Interaction effects with perceived employment insecurity (predicted probabilities) † . † Confidence intervals (95%) for the solo self-employed and permanent wage-employees. Figure 5. View largeDownload slide Interaction effects with perceived employment insecurity (predicted probabilities) † . † Confidence intervals (95%) for the solo self-employed and permanent wage-employees. Finally, Model 4 includes interaction effects between employment type and job autonomy. For solo self-employment these interaction do not reach significance, indicating that for self-employed workers their degree of job autonomy does not moderate their party orientation. Hence, these results do not corroborate hypothesis 2b, the right-wing political orientation of self-employed workers is not stronger as they have more autonomy over their job. For temporary workers, however, I find a significant negative interaction effect with job autonomy regarding old-left versus right-wing parties (−0.604) and a positive interaction effect regarding new-left versus right-wing parties (1.116). The plots in Figure 6 suggest that greater job autonomy strengthens in particular new-left orientations, rather than right-wing orientations. As far as the old-left is concerned, the plots indicate that the moderating effect of job autonomy is surrounded with relatively high levels of uncertainty. The results therefore provide little to no support for the hypothesis that left-wing political orientation of temporary workers is weaker as they have more autonomy over their job (hypothesis 2a). Figure 6. View largeDownload slide Interaction effects with job autonomy (predicted probabilities) † . † Confidence intervals (95%). Figure 6. View largeDownload slide Interaction effects with job autonomy (predicted probabilities) † . † Confidence intervals (95%). 5. Conclusion The main aim of the current study was to extend the research into the political effects of atypical work by comparing the political orientations of self-employed workers to those of people in temporary employment. The growth of temporary work in Europe and the revival of self-employment are both considered to be processes related to the flexibilization of labor markets. These processes are generally assumed to have weakened the position of workers vis-à-vis employers by partially transferring market risks to ‘atypical’ workers by short-term hiring and outsourcing to freelancers. New political divisions would arise between those with and without secure labor market positions. The novelty of this study was to compare the effect of self-employment on policy and party preferences to the effect of temporary employment. The self-employed are worthwhile examining because of their ‘Janus face’ in the labor market literature ( Mevissen and Van der Berg, 2011 ), i.e.: on the one hand belonging to the insiders of the labor market as a group of independent entrepreneurs, while on the other hand belonging to the labor market outsiders as precarious workers in quasi-autonomous employment relationships (see also Barbieri and Scherer, 2009 ). The findings from this study suggest that in general people in solo self-employment are more strongly orientated toward rightist positions regarding welfare policies and that in terms of party support, they more often prefer right-wing parties over ‘old’ left-wing parties, such as the social democrats and (former) communists. Interestingly, when it comes to their orientation toward new-left parties, solo self-employed workers are even more supportive of this type of parties compared with paid-employees. Temporary employees, on the other hand, are generally somewhat more to the left, in particular with respect to welfare state support—but not necessarily with respect to party preferences. By and large, these finding would indicate that self-employed workers have a distinct pattern of political orientation, one that is very different from the attitudes of people in (temporary) paid-employment. Yet, another major goal of the current study was to determine whether the political orientations of people in self-employment would be more toward the left—and therefore more close toward the views of (temporary) employees, as they have a more precarious position on the labor market. For this purpose, I examined how employment insecurity and income insecurity moderate the effect of self-employment on policy and party orientations. Taken together, the results suggest that people in solo self-employment are generally more likely to support welfare policies and (new)left parties—and oppose right-wing parties—as they are more insecure with respect to their income and/or job. This study therefore is the first to show that economic vulnerabilities might challenge the archetypical image of people in self-employment as an economic conservative, political right-wing class. This observation suggests that particular segments of self-employment may share the characteristics of other forms of ‘atypical’ work, not only with respect to labor market insecurities, but also regarding the political orientations associated with such insecurities (c.f. Corbetta and Colloca, 2013 ; Marx and Picot, 2013 ; Marx, 2014 ). In fact, with respect to party preferences, this study shows that vulnerability affects self-employed workers and temporary employees in more or less similar fashion: greater insecurities strengthen left-wing political orientations and weaken right-wing political orientations. The second condition in this study to moderate the relationship between employment type and political orientations was the degree of job autonomy. In this respect, the results were less clear. With respect to pro-welfare attitudes, there is some evidence that job autonomy strengthens right-wing orientation among people in solo self-employment. With respect to party orientations, however, job autonomy only to some extent impacts the effect of temporary employment—but not self-employment: greater job autonomy to some extent strengthens new-left party orientations, but no clear patterns were found for old-left or right-wing party support. This finding does not support the observation that a lack of autonomy in the workplace can strengthen economic progressive, traditional left-wing preferences ( De Witte, 1999 ; Kitschelt and Rehm, 2014 ), even though temporary workers generally enjoy lower job discretion and job autonomy than permanent employees ( Gallie et al. , 1998 ). All in all, this study provides some indication for the notion that politically the self-employment are more heterogeneous than traditional class-based theories assume. Contrary to the image of (free market) right-wing entrepreneurship, there seems to be at least a section of the self-employed workers in Europe that, driven by rather precarious working conditions, are less strongly attached to rightist politics. This observation may have implications not only for the scientific study of self-employment, but also for politicians and policy-makers seeking to adapt labor laws and social protection policies aimed at self-employed persons without personnel ( Schulze Buschoff and Schmidt, 2009 ; Dekker, 2010 ). Especially for those who do not fit the ‘ideal-type’ entrepreneur, more targeted policies may be necessary. In spite of general individualistic approach to responsibility and accountability among self-employed, this study shows that the support for more collectivist and inclusive policies and parties is greater among self-employed persons that work under greater uncertainty and strain. The patterns emerging from this study, however, are not conclusive. A few limitations need to be considered. First, by using 2008 data only, this study is unable to address changes in the relationship between atypical work and political orientations. Longitudinal data would be required to study the long-term political consequences of heterogenization of self-employment since 1980s. Moreover, the pooled analysis of eight West European countries, obviously obscured country-to-country differences in this relationship, and ignores that the economic and institutional context of countries could moderate the relationship between perceived insecurities and political preferences ( Gingrich and Ansell, 2012 ). Future studies should address whether the political effects of self-employment are conditioned by a country’s degree of market competitiveness, and/or the legislative context regarding self-employment. Also larger national samples of self-employed workers, and specific self-employment surveys would help us to establish a greater degree of accuracy on this matter. Next, the current study had to rely on a party family categorization to measure party choice. Future research, however, may not only aim at more detailed measures of party orientations, but may also pursuit better measurements of political values and policy preferences. The relevance, for example, of ‘new-left’ parties taps into a second political value dimension (e.g. post-materialist vs. materialist values, or libertarian vs. authoritarian value) that is related to ‘new’ class politics (cf. Güveli et al. , 2007 ; Oesch, 2008 ). From this perspective, one finding from this study that needs further attention is the interaction between self-employment and perceived insecurity on the likelihood of voting for the new-left. It seems plausible that the support for new-left (and green) parties is strongest among particular segments of self-employed professionals, such as freelancers in social and cultural occupations (e.g. authors, journalists and other creative and cultural workers). Although highly educated, some of these professionals work in very competitive markets, where low entry barriers put pressure on tariffs and earnings. A programmatic blend combining an economic centrist agenda with cultural progressive issues and concerns for the environment (such as D’66 in the Netherlands or the Grünliberale in Switzerland), may be attractive to this group. Yet, whether liberal moral values intersect with economic vulnerabilities to function as a driving force of the political orientations among self-employed social–cultural professionals requires a level of detail beyond the scope of this study. Future research may look deeper into the relationship between atypical work and ‘new’ political dimensions, including also the support for populist right-wing parties (cf. Standing, 2011 ). Finally, in the current study precariousness is limited to insecurities about income, employment and job autonomy. In particular, the measure for employment insecurity is sub-optimal. For self-employed workers, this measure ignores risks more specifically associated with self-employment, such as unstable work through irregular orders, and low financial buffers to survive periods when little orders and money are coming in. Also for temporary employees, the question used here (i.e. ‘how likely it is that one will be unemployed and looking for work during the next 12 months’) is sub-optimal to measure employment risks, as it ignores the remaining contract duration. Future studies might investigate other aspects that link self-employment to ‘atypical work arrangements’, i.e. the extent to which someone is dependent on (structural) orders of a single client, or whether self-employment is a voluntary decision. Against the backdrop of the lack of this type of data (at least in the domain of political surveys) the present study serves as a valuable first step to examine the political implications of the risks associated with being self-employed in modern labor markets. Funding This research was supported by the Netherlands Organization for Scientific Research (NWO), grant 451-13-027. 1 The sector classification is derived from a Eurofound report on self-employment (1997) . In this classification, the hotel and restaurant industry is merged with the trade industries (wholesale and retail), not with the business sector or other services. In doing so, I follow Arum and Muller (2004) who consider restaurateurs to belong to the ‘traditional’ forms of self-employment. Hence, this distinction allows to better map the structural changes in self-employment, i.e., the decrease of the traditional forms vis-à-vis the rise of self-employment in ‘new’ sectors. 2 This phrase is borrowed from Celia and John Stanworth’s article (1995) ‘The self-employed without employees: autonomous or atypical’. 3 A principal axis factor analysis confirmed that these items relate to one dimension, also when conducted separately for each country. A sixth item, however, was excluded, i.e.: on the government’s responsibility for sufficient child care services for working parents. Including this item resulted in different factor solutions for different countries. To avoid unnecessarily loss of information, instead of using the factor scores to compute the dependent variable, I used the mean value over the items while allowing 2 missing values for each respondent. The mean-index score and the factor scores correlate very highly, and the results of this study do not substantially change when using the factor scores. 4 Two issues should be considered. First, the classification of the Manifesto Project Database is used with a few exceptions: Following Marx (2014) the Danish and Norwegian Socialist People’s Parties were classified as ‘new-left’ instead of ‘old-left’. Following Jansen et al. (2011), D’66 in the Netherlands is classified as ‘new-left’ instead of old-left. Second, the decision to use retrospective party choice, instead of party attachment, for respondents with no party attachment, is based on the assumption that—when recoded into three party categories—the two items do not substantially diverge. This assumption is supported by a relatively strong association between party attachment and retrospective vote choice among respondents with valid information on both items. The Cramers’ V based on the pooled sample is 0.82, indicating a fairly strong association between party attachment and vote choice. Moderately to very strong associations are also found for most countries, i.e.: Austria (0.90), Belgium (0.51), Switzerland (0.83), Germany (0.80), Denmark (0.89), France (0.74), Netherlands (0.85) and Norway (0.75). 5 To be able to generalize whether the results from a pooled analysis are indicative of a general European trend population weights are applied. In doing so, I follow a modeling strategy similar to the study of Marx (2014) on the political preferences of temporary workers. These weights correct for the fact that countries in the ESS data have different population sizes but similar sample sizes. References Arum R. Müller W. ( 2004 ). The Reemergence of Self-Employment: A Comparative Study of Self-Employment Dynamics and Social Inequality  , New Jersey , Princeton University Press . Barbieri P. Scherer S. ( 2009 ). ‘Labour Market Flexibilization and Its Consequences in Italy’ , European Sociological Review  , 25 , 677 – 692 . Google Scholar CrossRef Search ADS   Bögenhold D. Fachinger U. ( 2012 ). ‘How Diverse is Entrepreneurship? Observations on the Social Heterogeneity of Self-Employment in Germany’ . In Bonnet, J., Desjardin, M. and Madrid-Guijarro, A. (eds) The Shift to the Entrepreneurial Society: A Built Economy in Education, Sustainability and Regulation  , Cheltenhem, UK, Edward Elger, p. 227 . Bögenhold D. Staber U. ( 1991 ). ‘The Decline and Rise of Self-Employment’ , Work, Employment & Society  , 5 , 223 – 239 . Google Scholar CrossRef Search ADS   CIS (2008). ‘Spanish National Election Survey 2008’. [dataset]. Madrid, Centro de Investigaciones Sociológicas. Corbetta P. Colloca P. ( 2013 ). ‘Job Precariousness and Political Orientations: The Case of Italy’, South European Society and Politics  , 18 , 333 – 354 . Google Scholar CrossRef Search ADS   Dekker F. ( 2010 ). ‘Self‐Employed without Employees: Managing Risks in Modern Capitalism’, Politics & Policy  , 38 , 765 – 788 . Google Scholar CrossRef Search ADS   De Witte H. ( 1999 ). ‘On the Occupational Roots of Conservatism: Expanding Middendorp’s Analysis with the Concepts of Rotter and Kohn’ . In De Witte H. Scheepers P. (eds) Ideology in the Low Countries. Trends, Models and Lacunae  , van Gorcum , Assen , pp. 69 – 89 . Emmenegger P. ( 2009 ). ‘Barriers to Entry: Insider/Outsider Politics and the Political Determinants of Job Security Regulations’ , Journal of European Social Policy  , 19 , 131 – 146 . Google Scholar CrossRef Search ADS   Evans G. (ed.) ( 1999 ). The End of Class Politics? Class Voting in Comparative Context  , Oxford , Oxford University Press . Evans G. de Graaf N. D. (eds) ( 2013 ). Political Choice Matters: Explaining the Strength of Class and Religious Cleavages in Cross-National Perspective  , Oxford , Oxford University Press . ESS Round 4 ( 2008 ). European Social Survey Round 4. Data file edition 4.3. Norwegian Social Science Data Services, Norway – Data Archive and distributor of ESS data for ESS ERIC. Eurofound ( 1997 ). The Working Conditions of the Self-Employed in the European Union , Dublin, European Foundation for the Improvement of Living and Working Conditions. Eurostat ( 2014 ). European Labor Force Surveys. LFS Series – Detailed Annual Survey Results, 1994, 1995, 2004, 2014 [Database]. accessed at http://ec.europa.eu/eurostat/web/lfs/data/data-base on January 11, 2016. Gallie D. White M. Cheng Y Tomlinson M. ( 1998 ). Restructuring the Employment Relationship  , Oxford , Oxford University Press . Gingrich J. Ansell B. ( 2012 ). ‘Preferences in Context. Micro Preferences, Macro Contexts, and the Demand for Social Policy’, Comparative Political Studies  , 45 , 1624 – 1654 . Google Scholar CrossRef Search ADS   Güveli A. Need A. De Graaf N. D. ( 2007 ). ‘The Rise of “New” Social Classes within the Service Class in The Netherlands. Political Orientation of Social and Cultural Specialists and Technocrats between 1970 and 2003’ . Acta Sociologica  , 50 , 129 – 146 . Google Scholar CrossRef Search ADS   Iversen T. Soskice D. ( 2001 ). ‘An Asset Theory of Social Policy Preferences’ , American Political Science Review  , 95 , 875 – 894 . Jansen G. ( 2011 ). Social Cleavages and Political Choices: Large Scale Comparisons of Social Class, Religion and Voting Behaviour in Western Democracies , ICS Dissertation, Nijmegen, Radboud University. Jansen G. De Graaf N. D. Need A. ( 2011 ). ‘Class Voting, Social Changes and Political Changes in the Netherlands 1971–2006’, Electoral Studies  , 30 , 510 – 524 . Google Scholar CrossRef Search ADS   Kalleberg A. L. ( 2000 ). Nonstandard Employment Relations: Part-Time, Temporary and Contract Work, Annual review of sociology  , 26 , 341 – 365 . Google Scholar CrossRef Search ADS   Kitschelt H. Rehm P. ( 2014 ). ‘Occupations as a Site of Political Preference Formation’ , Comparative Political Studies  , 47 , 1670 – 1706 . Google Scholar CrossRef Search ADS   Knutsen O. ( 2006 ). Class Voting in Western Europe: a Comparative Longitudinal Study  , Oxford , Lexington Books . Kohn M. L. ( 1995 ). ‘Social Structure and Personality through Time and Space’ . In: Moen P. Elder G. Lüscher K.E. (eds) Examining Lives in Context: Perspectives on the Ecology of Human Development  . Washington, DC: American Psychological Association , pp. 141 – 168 . Kösters L. Smits W. de Vries R. ( 2013 ). ‘De ene zzp’er is de andere niet’. In van Gaalen, R., Goudswaard, A., Sanders, J. and Smits, W. (eds) Dynamiek op de Nederlandse arbeidsmarkt. De focus op flexibilisering , Den Haag/Heerlen, CBS/TNO, 139 – 153 . Lofstrom M. ( 2013 ). ‘Does Self-Employment Increase the Economic Well-Being of Low-Skilled Workers?’ Small Business Economics  , 40 , 933 – 952 . Google Scholar CrossRef Search ADS   Marx P. ( 2014 ). ‘Labour Market Risks and Political Preferences: The Case of Temporary Employment’, European Journal of Political Research  , 53 , 136 – 159 . Google Scholar CrossRef Search ADS   Marx P. Picot G. ( 2013 ). ‘The Party Preferences of Atypical Workers in Germany’, Journal of European Social Policy  , 23 , 164 – 178 . Google Scholar CrossRef Search ADS   McManus P. A. ( 2000 ). ‘Market, State, and the Quality of new Self-Employment Jobs among Men in the US and Western Germany’, Social forces  , 78 , 865 – 905 . Google Scholar CrossRef Search ADS   Mevissen J. Van der Berg N ( 2011 ). ‘De januskop van de zzp’er : De zelfstandige zonder personeel: ondernemer of eigenlijk een werknemer?’, Tijdschrift voor Arbeidsvraagstukken  , 27 , 264 – 280 . Millán J. M. Congregado E. Román C. ( 2014 ). Persistence in Entrepreneurship and Its Implications for the European Entrepreneurial Promotion Policy’, Journal of Policy Modeling  , 36 , 83 – 106 . Google Scholar CrossRef Search ADS   Muehlberger U. ( 2007 ). Dependent Self-Employment: Workers on the Border between Employment and Self Employment  , New York , Palgrave Macmillan . Mughan A. ( 2007 ). ‘Economic Insecurity and Welfare Preferences: A Micro-Level Analysis’ , Comparative Politics  , 39 , 293 – 310 . Nieuwbeerta P. De Graaf N. D. ( 1999 ). ‘Traditional Class Voting in Twenty Postwar Societies’. In Evans G. (ed.) The End of Class Politics  , Oxford , Oxford university Press , pp. 23 – 56 . OECD . 2000 . ‘The Partial Renaissance of Self-Employment’. In OECD Economic Outlook , Paris, Organisation for Economic Co-operation and Development. Oesch D. ( 2008 ). ‘The Changing Shape of Class Voting: An Individual-Level Analysis of Party Support in Britain, Germany and Switzerland’, European Societies  , 10 , 329 – 355 . Google Scholar CrossRef Search ADS   Oesch D. ( 2015 ). ‘Occupational Structure and Labor Market Change in Western Europe Since 1990’ . In Beramendi P. Häusermann S. Kitschelt H. Kriesi H. (eds) The Politics of Advanced Capitalism  , Cambridge, Cambridge University Press , pp. 112 – 132 . Pedersini R. Coletto D. ( 2010 ). Self-Employed Workers: Industrial Relations and Working Conditions , Dublin, European Foundation for the Improvement of Living and Working Conditions. Pernicka S. ( 2006 ). ‘Organizing the Self-Employed: Theoretical Considerations and Empirical Findings’, European Journal of Industrial Relations  , 12 , 125 – 142 . Google Scholar CrossRef Search ADS   Rehm P. ( 2011 ). ‘Social Policy by Popular Demand’, World Politics  , 63 , 271 – 299 . Google Scholar CrossRef Search ADS   Román C. Congregado E. Millán J. M. ( 2011 ). ‘Dependent Self-Employment as a Way to Evade Employment Protection Legislation’, Small Business Economics  , 37 , 363 – 392 . Google Scholar CrossRef Search ADS   Rueda D. ( 2005 ). ‘Insider–Outsider Politics in Industrialized Democracies: the Challenge to Social Democratic Parties’ , American Political Science Review  , 99 , 61 – 74 . Google Scholar CrossRef Search ADS   Schulze Buschoff K. S. Protsch P. ( 2008 ). ‘(A‐) Typical and (in‐) Secure? Social Protection and ‘Non‐Standard’ Forms of Employment in Europe’ , International Social Security Review  , 61 , 51 – 73 . Google Scholar CrossRef Search ADS   Schulze Buschoff K. S. Schmidt C. ( 2009 ). ‘Adapting Labour Law and Social Security to the Needs of the “New Self-Employed”—Comparing the UK, Germany and the Netherlands’, Journal of European Social Policy  , 19 , 147 – 159 . Google Scholar CrossRef Search ADS   Standing G. ( 2011 ). The Precariat: The New Dangerous Class  , London, Bloomsbury Publishing . Stanworth C. Stanworth J. ( 1995 ). ‘The Self‐Employed without Employees. Autonomous or Atypical?’, Industrial Relations Journal  , 26 , 221 – 229 . Google Scholar CrossRef Search ADS   The Comparative Study of Electoral Systems ( 2015a ) ( www.cses.org ). CSES MODULE 2 FULL RELEASE [dataset]. December 15, 2015 version. doi:10.7804/cses.module2.2015-12-15 The Comparative Study of Electoral Systems ( 2015b ) ( www.cses.org ). CSES MODULE 3 FULL RELEASE [dataset]. December 15, 2015 version. doi:10.7804/cses.module3.2015-12-15 Van Stel A. J. Wennekers S. Scholman G. ( 2014 ). Solo Self-employed versus Employer Entrepreneurs: Determinants and Macro-economic Effects in OECD Countries , Vol. 201212. Zoetermeer, EIM Research Report. Volkens A. Lehmann P. Merz N. Regel S. Werner A. Lacewell O.P. Schultze H. ( 2013 ). The Manifesto Data Collection. Manifesto Project (MRG/CMP/MARPOR). Version 2013b  , Berlin , Wissenschaftszentrum Berlin für Sozialforschung (WZB ). Appendix Table A1. Descriptive statistics ( N  = 7186)   Min.  Max.  Mean  SD  Dependent Variables          Pro-welfare attitudes  0.00  10.00  7.02  1.42  Party Preference (N = 5564)           New-left  0.00  1.00  0.14  0.34   Old-left  0.00  1.00  0.39  0.49   Right-wing  0.00  1.00  0.47  0.50  Independent Variables          Permanent employee  0.00  1.00  0.76  0.43  temporary employee  0.00  1.00  0.12  0.33  Solo self-employed  0.00  1.00  0.07  0.26  Employer  0.00  1.00  0.05  0.21  Perceived income insecurity  0.00  2.00  0.74  0.66  Perceived employment insecurity  0.00  2.00  0.67  0.69  Perceived job autonomy  0.00  1.00  0.39  0.34  Managers  0.00  1.00  0.08  0.27  Professionals  0.00  1.00  0.44  0.50  Low-skilled Non-Manual  0.00  1.00  0.24  0.43  High-skilled Manual  0.00  1.00  0.13  0.33  Low-skilled Manual  0.00  1.00  0.12  0.32  Income  1.00  10.00  6.39  2.58  Part-time  0.00  1.00  0.16  0.37  Age (15 = 0)  0.00  49.00  27.32  10.89  Female  0.00  1.00  0.46  0.50  Low-level education  0.00  1.00  0.13  0.34  Medium-level education  0.00  1.00  0.50  0.50  High-level education  0.00  1.00  0.37  0.48    Min.  Max.  Mean  SD  Dependent Variables          Pro-welfare attitudes  0.00  10.00  7.02  1.42  Party Preference (N = 5564)           New-left  0.00  1.00  0.14  0.34   Old-left  0.00  1.00  0.39  0.49   Right-wing  0.00  1.00  0.47  0.50  Independent Variables          Permanent employee  0.00  1.00  0.76  0.43  temporary employee  0.00  1.00  0.12  0.33  Solo self-employed  0.00  1.00  0.07  0.26  Employer  0.00  1.00  0.05  0.21  Perceived income insecurity  0.00  2.00  0.74  0.66  Perceived employment insecurity  0.00  2.00  0.67  0.69  Perceived job autonomy  0.00  1.00  0.39  0.34  Managers  0.00  1.00  0.08  0.27  Professionals  0.00  1.00  0.44  0.50  Low-skilled Non-Manual  0.00  1.00  0.24  0.43  High-skilled Manual  0.00  1.00  0.13  0.33  Low-skilled Manual  0.00  1.00  0.12  0.32  Income  1.00  10.00  6.39  2.58  Part-time  0.00  1.00  0.16  0.37  Age (15 = 0)  0.00  49.00  27.32  10.89  Female  0.00  1.00  0.46  0.50  Low-level education  0.00  1.00  0.13  0.34  Medium-level education  0.00  1.00  0.50  0.50  High-level education  0.00  1.00  0.37  0.48  Notes: Population size and design weights applied. View Large Table A1. Descriptive statistics ( N  = 7186)   Min.  Max.  Mean  SD  Dependent Variables          Pro-welfare attitudes  0.00  10.00  7.02  1.42  Party Preference (N = 5564)           New-left  0.00  1.00  0.14  0.34   Old-left  0.00  1.00  0.39  0.49   Right-wing  0.00  1.00  0.47  0.50  Independent Variables          Permanent employee  0.00  1.00  0.76  0.43  temporary employee  0.00  1.00  0.12  0.33  Solo self-employed  0.00  1.00  0.07  0.26  Employer  0.00  1.00  0.05  0.21  Perceived income insecurity  0.00  2.00  0.74  0.66  Perceived employment insecurity  0.00  2.00  0.67  0.69  Perceived job autonomy  0.00  1.00  0.39  0.34  Managers  0.00  1.00  0.08  0.27  Professionals  0.00  1.00  0.44  0.50  Low-skilled Non-Manual  0.00  1.00  0.24  0.43  High-skilled Manual  0.00  1.00  0.13  0.33  Low-skilled Manual  0.00  1.00  0.12  0.32  Income  1.00  10.00  6.39  2.58  Part-time  0.00  1.00  0.16  0.37  Age (15 = 0)  0.00  49.00  27.32  10.89  Female  0.00  1.00  0.46  0.50  Low-level education  0.00  1.00  0.13  0.34  Medium-level education  0.00  1.00  0.50  0.50  High-level education  0.00  1.00  0.37  0.48    Min.  Max.  Mean  SD  Dependent Variables          Pro-welfare attitudes  0.00  10.00  7.02  1.42  Party Preference (N = 5564)           New-left  0.00  1.00  0.14  0.34   Old-left  0.00  1.00  0.39  0.49   Right-wing  0.00  1.00  0.47  0.50  Independent Variables          Permanent employee  0.00  1.00  0.76  0.43  temporary employee  0.00  1.00  0.12  0.33  Solo self-employed  0.00  1.00  0.07  0.26  Employer  0.00  1.00  0.05  0.21  Perceived income insecurity  0.00  2.00  0.74  0.66  Perceived employment insecurity  0.00  2.00  0.67  0.69  Perceived job autonomy  0.00  1.00  0.39  0.34  Managers  0.00  1.00  0.08  0.27  Professionals  0.00  1.00  0.44  0.50  Low-skilled Non-Manual  0.00  1.00  0.24  0.43  High-skilled Manual  0.00  1.00  0.13  0.33  Low-skilled Manual  0.00  1.00  0.12  0.32  Income  1.00  10.00  6.39  2.58  Part-time  0.00  1.00  0.16  0.37  Age (15 = 0)  0.00  49.00  27.32  10.89  Female  0.00  1.00  0.46  0.50  Low-level education  0.00  1.00  0.13  0.34  Medium-level education  0.00  1.00  0.50  0.50  High-level education  0.00  1.00  0.37  0.48  Notes: Population size and design weights applied. View Large © The Author 2016. Published by Oxford University Press and the Society for the Advancement of Socio-Economics. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/ ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

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