The regional employment effects of new social firm entry

Who creates jobs? There is broad consensus that particularly young and small firms make important contributions to job creation and growth (e.g., Haltiwanger et al. 2013). This has spurred a massive research interest in startups (new firm entry) and their economic effects, not only to better quantify the nature and conditions of the economic effects but also to inform industrial policies more effectively, for example what type of new firms should be promoted (Audretsch et al. 2007; Birch 1981, 1987; Kirchhoff 1994).

With respect to the type of new firms that delivers particularly strong employment effects, existing research mainly focused on commercial new firms. In contrast, potential employment effects of new social firms are poorly understood. The category of social firms includes organizations of varying age and size, a range of governance arrangements, and social missions ranging from altruistic to environmental. Their common ground is that they are formed around a social mission, economic goals and constraints being secondary concerns (Austin et al. 2012; Dacin et al. 2010; Defourny and Nyssens 2010; Hoogendoorn et al. 2010; Peredo and McLean 2006; Zahra et al. 2009). Conversely, although commercial firms may generate social benefits, these are collateral to their main mission. No prior study has separately investigated the net employment effect of social firms. We therefore undertake the first empirical study of the regional level employment dynamics of new social firms and directly compare their employment effects over time to those of new commercial firms. The research question we address is “How do new social firm entrants contribute to regional employment creation over time, and how does their contribution compare to that of new commercial firms?”

Given that there is no established theoretical framework for the specific case of employment effects of new social firms, we draw on the general job creation literature with its focus on commercial new firms. In this literature, Fritsch and Mueller’s (2004, 2008, see also Fritsch, 2008) model of direct and indirect effects over time has become a leading and influential approach to understanding employment effects of new firms (Andersson and Noseleit, 2011; Arauzo Carod et al. 2008; Acs and Mueller 2008; Baptista et al. 2008; van Stel and Suddle 2008). An important insight from Fritsch and Mueller’s (2004) groundbreaking study was that the employment effect of new firms follows a wave pattern over time with the net result being either positive or negative depending on a combination of effects that are both direct and indirect. We decided to take Fritsch and Mueller’s (2004) model and theorizing as a conceptual starting point for our investigation, in addition to existing knowledge of distinguishing features of social firms, compared to commercial firms (see Austin et al., 2012; Mair and Marti 2006).

Given that Fritsch and Mueller’s (2004) study, and several following studies (e.g., Arauzo Carod et al. 2008; Audretsch and Fritsch 2002; Carree and Thurik 2010; Fritsch and Mueller 2008; Fritsch and Noseleit 2013; van Stel and Storey 2004), also made clear that it is essential to examine longer periods of time to understand and capture employment effects of new firms, we consider a longer time horizon in our study. Specifically, we overcome the dearth of data that has hampered research on the employment effects of new social firms (Barbetta et al. 2018) by using a large-scale, firm level dataset covering 67 local labor markets in Sweden between 1990 and 2014, and using a non-profit legal form not allowed for commercial firms to represent social firms. Although employment effects could in principle be investigated by comparing countries or time periods, we conduct the analysis on the regional level following the practice of prior research and in accordance with most social firms being locally embedded ventures that target local social problems (Clarence and Noya 2009).

An investigation of employment effects of social firm entry is important for at least three major reasons. First, by revealing what is similar and what is not, direct comparison of employment effects of social and commercial entry over time provides a more detailed picture of employment effects of new entry, which can inform interpretation and simulate new ideas regarding the well-established temporal pattern of employment effects of new entry in general. This provides insight into boundary conditions and a basis for theoretical development in this otherwise empirically oriented domain of research. For example, our investigation helps clarifying whether the employment effects of new social firms are consistent with the theorizing on employment effects of new firms in general (e.g., Fritsch and Mueller, 2004). Second, insights from our study provide input to policy-making. Social firms constitute a large and growing sector in many economies and have a significant role in welfare policies around the world (Nicholls 2010; Seelos et al. 2011) including employment policies (Dees 2007; OECD 2013). Among other things, social firms are likely to be disproportionately important for employment in marginalized groups like people with disabilities and long-term unemployed individuals. Third, by focusing on social firms’ employment effects we highlight their economic value and not only their social value with which most previous research was concerned. This can inspire new developments in social entrepreneurship research investigating other aspects of economic value creation by social firms.

As this is the first study on the topic and there are arguments both for and against the employment effects of new social firms mirroring those of commercial entrants, we refrain from stating specific hypotheses about the employment effects of social firm entry. Instead, we approach the issue in an exploratory manner, using the general model developed by Fritsch and Mueller (2004) for the employment effects of commercial firms as the starting point of our exploration.

The paper is structured as follows. Section 2 outlines our theoretical vantage points, i.e., Fritsch and Mueller’s (2004, 2008) theorizing about three types of effects creating a wave-pattern for new firms’ contribution to regional employment creation over time, and prior knowledge about similarities and differences between commercial and social firms. Section 3 explains the data set, variables, and analysis approaches used in the study. Section 4 presents the results regarding the effects of new social firms on regional employment creation over an extended period of time. The paper ends with a Discussion (Sect. 5) addressing the study’s contributions, implications, and limitations as well as opportunities for future research, and a brief conclusion (Sect. 6). Supplementary, descriptive statistics are provided in appendices.

In contrast to earlier research investigating the numbers of jobs created within new entrants themselves over relatively short time spans, Fritsch and Mueller (2004) applied a true regional perspective, considering also effects on other firms and over a longer period of time. Specifically, they investigated the employment effects of new commercial firms over 10 years through incorporating successive annual lags of start-up rates in their model. They concluded that the regional employment effect of new firms follows a wave pattern over time with the net outcome being either positive or negative (see Fig. 1).

Fritsch and Mueller (2004, 2008, Fritsch, 2008) argued that this net effect depends on a combination of direct and indirect effects. The direct (or immediate) effect is positive and consists of the new employment created by the entrants themselves through initial hiring, retention, and eventual expansion of their work force. The indirect effects fall into two categories: the displacement effect and the supply-side effect.¹ The displacement effect, which is negative, arises from some incumbent firms shrinking or exiting the market (along with the less successful of the recent entrants) as a result of new competition from the (better among the) entrants. Since entry is expected to be productivity-enhancing, this should lead to a negative total effect on employment, which is indeed what is often observed in the medium term.

However, as Fritsch (2008: 3) points out, the market process is not a zero-sum game, in which one economic actor’s gain is completely at the expense of other actors. The supply-side effect, which typically takes longer time to evolve, is a composite of even more dispersed effects on the level of the (industry- and regional level) economic system. One important component is that entry drives improvements in efficiency and productivity. According to Fritsch and Mueller (2004) the entry of new firms can secure efficiency or stimulate productivity through contesting established market positions. Beyond the medium-term displacement of less productive firms, productivity-enhancing entrants lead to more competitive and therefore more profitable firms in the regional economy. This provides a basis for profitable growth (cf. Davidsson et al. 2009), leading to a positive effect on employment in the longer run.

Other components of the supply-side effect include that entry of new firms can accelerate structural change in the market through the turnover of the respective economic units, i.e. entry of new firms and exit of old incumbents (creative destruction). Further, new firms can generate qualitative development of the regional economy through amplified innovation and greater variety of products and problem solutions. Accordingly, the supply-side effect does not only emerge from the survival and success of entrants, but also improvements among incumbent firms in the regional economy more generally. This includes sometimes substantial positive effects of entrants that do not survive but nevertheless stimulate important improvements in other firms (cf. Davidsson, 2016: 12–13).

Depending on the relative size of these direct and indirect effects, the employment effect of new firm entry can be either positive, negative, or neutral. Although direct assessment of the indirect effects is challenging, the wave pattern in Fig. 1 is consistent with direct effects operating immediately and continuing over time; displacement effects becoming pronounced in the medium-term, and supply-side effects taking somewhat longer time before they peak. Results consistent with this wave pattern and interpretation have been reported in a number of studies employing Fritsch and Mueller’s (2004) framework in other contexts (e.g., Acs and Mueller 2008; Baptista et al. 2008; Mueller et al. 2008; van Stel and Suddle 2008).

While this theorization and accompanying empirical support resolve the puzzle of alternating positive and negative employment effects of entry recorded in earlier research, they do not distinguish commercial from social firms. Can we also apply this model to quantify and understand net employment effects of new social firms? What does past research say about the employment creation of social firms and about what characteristics distinguish them from social firms? Does what we know suggest that applying the Fritsch-Mueller logic to new social firms makes sense? This is what we turn to next.

There are a few descriptive studies of aggregate data suggesting that the expansion of the social sector is associated with employment increase (e.g., Casey 2016; Sivesind 2017; Enjolras and Strømsnes 2018). Although this could be an effect of growth in other sectors rather than an independent source of employment growth, data also suggest that the social sector has grown faster than other sectors in some countries. In Salamon and Sokolowski’s (2018) study within the European Union, the social sector’s annual employment growth rate was 3.4%, 0.6 percentage higher than the employment growth of the economy as a whole. Similarly, Salamon (2012) reported that during 2000 to 2010, employment in the nonprofit social sector in the US grew by 2.1% annually, whereas employment in commercial firms shrank by 0.6% in the same period. This suggests that the social sector’s unique employment contribution is not just a reflection of growth in other sectors.

We know little, however, about the employment creation dynamics of the social sector. Studies on the entry and exit of social firms are few, often non-empirical, and largely focused on topics other than employment dynamics, such as explaining the fundamental origin of and rationale for the social sector (Archambault et al. 2014; Andersson and Ford 2016; Hansmann 1980, 1987; Kachlami et al. 2018; Lecy and Van Slyke 2013; Twombly 2003; Weisbrod 1977). Some have focused on specific behaviors of social firms (e.g., Harrison and Laincz 2008; Harrison and Thornton 2014; Barbetta et al. 2018), but none has investigated the employment effects over time of social firm entry.

Research has established differences between social and commercial firms and their founders which may influence their employment effects of commercial start-ups. Apart from their central mission, social and commercial firms differ also in other regards, such as the demographic and socio-economic characteristics of founders (Harding and Cowling 2006; Bacq et al. 2013; Kachlami et al., 2018; Parker 2018), and how they approach resource mobilization (Austin et al., 2012; Mair and Marti 2006). These and other differences may influence their direct and indirect employment creation prowess.

Further, one could argue that social firms typically enter far-from-saturated “markets” of social needs and that they do not compete with each other (or with commercial firms) to the same extent as is the case in commercial markets. This would reduce any productivity-based mechanism fueling indirect job creation. At the same time, this argument also goes against negative job effects via displacements. It can also be argued that social firm entrants are usually small, poorly resourced, and relying to a great extent on volunteer work. This would suggest low levels of direct job creation effects by the entrants themselves. On the other hand, commercial entrants are similarly dominated by a “modest majority” of low-ambition, low-potential businesses (Davidsson and Gordon 2012) that create few jobs directly on a per capita basis. Few commercial entrants are backed up by significant financial capital and may neither be aiming nor suited for substantial growth (Aldrich and Ruef, 2018; Wiklund et al., 2003). Thus, starting (and staying) small and resource-poor may not distinguish social firm entrants from commercial ones.

This is only one aspect of how differences between social and commercial ventures are sometimes exaggerated. For example, social firms’ revenue generation is not as different as many observers may think. In fact, a very small share consists of charitable contributions and a significant share of earned income (Salamon and Sokolowski 2018). Within Europe, donations and charitable contributions account for only 9% of social firms’ revenue, while earned income from products, services and membership fees amount to a much larger share of their revenue (Salamon and Sokolowski 2018). For some social firms like Work Integration Social Enterprises (WISE), earned income reaches 80% of their revenue (Vidal 2005). Recent developments in social entrepreneurship and increased emphasis on market solutions for social problems has even made the dual mission of social value creation and financial sustainability the defining characteristics of social firms (Garrow and Hasenfeld 2014). As a result, social firms have increasingly entered into competition with other actors in the market. Empirical studies confirm this competition (Fauchart and Gruber 2011; Harrison and Laincz 2008; Kachlami 2016, 2017).

Thus, while there are undeniable differences between social and commercial firms, they do not point unambiguously in one direction, especially considering the combination of direct and indirect effects over time. At the same time, it seems likely that all the effects discussed by Fritsch and Mueller (2004, 2008) would operate to some degree, albeit to different extents--and possibly different timing—compared to commercial entrants. Therefore, we think it is informative to apply the Fritsch-Mueller framework to investigate the unknown territory of employment effect of social firms and to compare them to those of commercial firms. Research on the young field of social entrepreneurship has traditionally borrowed from the closely related field of commercial entrepreneurship. According to Henry et al. (2013) research into social entrepreneurship can progress more quickly if the knowledge acquired from commercial entrepreneurship studies is applied.

The results of our statistical analysis contain both descriptive statistics and the estimation results. Descriptive statistics are presented in Tables 3, 4, and 5 of Appendices 1 and 2, while the estimation results are presented in Table 1 and Fig. 2 of this section. Appendix 1 provides an overview of the distribution of the important variables of this study, i.e., 2-year employment change, commercial start-up rate and social start-up rate, across time and space. As shown in Table 3, most of the labor markets with the highest average employment growth are located in the southern part of Sweden (except Umeå), while most labor markets with the lowest employment growth are located in the northern part. This largely reflects the overall patterns of population density and population growth in the country, which increase from north to south except for some distinct deviations. Table 3 also shows that Stockholm—the capital—is not among the 10 labor markets with the highest employment growth despite having the highest rate of commercial firm formation. In Table 4, the year 2010 has the highest rate of both social and commercial firm formation and the subsequent year, 2011, has the highest employment growth. The increase of start-ups in 2010 might be partly attributed to the introduction of new immigration policy in 2008 allowing immigrants to acquire permanent residence with only 2 years of self-employment above a certain level of income. It can also be partly attributed to the recovery of the overall economy from the economic crisis of 2008. In Table 5, the high correlation among the lagged start-up rates of commercial firms confirms the regional persistence of commercial entrepreneurship reported by previous studies (e.g., Andersson and Koster 2011); however, such persistence could not be found among social firms. The correlations for annual commercial vs. social entry rates are positively correlated at moderate levels; approx. 0.2–0.3.

Table 1 shows two models: model (a) includes only commercial start-up rates and model (b) includes both commercial and social start-up rates. As can be seen, the inclusion of social start-up rates in model (b) improves the estimation model and increases explanatory power by seven percentage points. That is, a substantial part of the changes in regional employment not explained by new commercial start-ups can be explained by new social firms. In assessing this result, it should be remembered that the social sector represents a much smaller fraction of the total economy compared to the commercial sector.

Figure 2 provides a graphical presentation of the results of model (b) through separate lines showing the employment effects of new social and new commercial firms. As can be seen, the employment effect of new commercial firms follows the wave pattern over time reported by previous research. More importantly, the employment effect of new social firms also follows a wave pattern over time, suggesting that both direct and indirect effects are at play. However, unlike Fritsch and Mueller (2004) but in line with Baptista et al. (2008), the employment effect does not peak within the 8-year time frame. Based on previous studies, it is reasonable to assume that the effect would eventually level off or even turn down rather than the curve continuing upward indefinitely.

Interestingly, except for a dip in year 6 (possibly exaggerated for stochastic reasons), the curve for social firms is markedly above the corresponding curve for commercial firms. This suggests that the positive net effect per entrant on regional employment is greater for social firms than for commercial firms.

The results presented in Table 1 and Fig. 2, however, can suffer from high multicollinearity since the start-up rates of subsequent years are highly correlated making the regression coefficients potentially unreliable (Greene, 2008). As explained above, we employ the Almon method to reduce this problem. Table 2 shows the result of the second, third and fourth order polynomial lags for social firms, holding commercial firms constant at the third order as suggested by prior research (e.g., Fritsch and Mueller 2004; Fritsch and Mueller 2008; Baptista et al. 2008; van Stel and Suddle 2008). Figure 3 provides a graphical representation of the results.

The log likelihood results from Table 2 show improvement from the second to fourth order polynomial lag. The improvement after the third order polynomial, however, is negligible. Thus, similar to commercial firms, we identify the third order polynomial to provide a suitable estimation of the lag structure of the employment effects of new social firms. The third order polynomial lag of new social firms, Fig. 3b, shows a wave pattern with increasing effect in the short-term until t₁, decreasing effect in the mid-term from t₂ to t₅, and an increasing effect in the long-term from t₆ to t₈. Across all time horizons, the estimated effect of social firm entry is positive and overall more so than for commercial firms. Accordingly, a main finding of this first study of the regional level net employment effect of new social firms is that the effect is positive and of substantial magnitude.