Another key component is that replication and adoption of technological knowledge concerning processes, organizational arrangements, and products are associated with costs and uncertainty linked to the tacit elements involved in technological know-how (Mansfeld et al. 1981; Dosi and Nelson 2009; Maurseth and Svensson 2020). This creates lumpiness, retards the diffusion and application of new technology, and strengthens path dependence. As knowledge about the new technology is accumulated, recipes—that is, coded programs—are increasingly used to implement even newer technologies. Meanwhile, Winter (2016) stresses the importance of including alternative strands of science, e.g., psychology, to better understand how human nature and entrepreneurial behavior can be explained. In particular, entrepreneurial behavior may be less constrained than presumed by the forces of habit and fear of uncertain outcomes and ultimately failure, thereby diminishing the risks that the entrepreneur will be daunted or delayed by path dependence.27

The roots of these insights originate in work by Hayek (1945) and von Mises (1949). They argue that unevenly distributed individual abilities and capacities play a central role in transformative processes and growth. Subsequently, it is important

25 Jovanovic and Rousseau (2005) argue that new frms are more likely to exploit new areas of technology. Small frms also innovate more often in areas where innovation has been unusual (Almeida and Kogut 1997; Almeida 1999).

26Research also shows that a larger number of small and new frms offer dynamic environments that positively affect profts and value (Pastor and Veronesi 2009; Fink et al. 2005).

27See also Sarasvathy (2008) on the effectuation view.

to examine how this dynamic is affected by the institutional framework within which entrepreneurs operate. Nelson and Winter (1982) were the frst to present an evolutionary growth model incorporating several of the features discussed above. One starting point was that frms are generally reluctant to change their operations, which, in combination with endless possibilities for change and a fnite ability to rationally review these possibilities (bounded rationality), creates a need for rules of thumb, or more precisely, routines. Firms are assumed to be continuously involved in a search process either to develop new routines themselves (R&D), which Nelson and Winter call innovation (process innovation), or to imitate other frms. All search behaviors are associated with costs; the probability of discovering an improvement increases as R&D or other search costs increase. Innovation thus requires more resources but can also generate higher returns. Finally, it should be noted that Nelson and Winter assume that the resources invested in searching for new routines depend on a frm's proftability. This tends to lead to the gradually increasing domination of the economy by large frms as they succeed in attaining higher profts.

Nelson and Winter's approach explains both variation and selection and how knowledge is preserved and transferred across periods. Their theory led to extensive research that modifed and further developed variants of their original model.28 Of particular interest is Winter's own (1984) extension of the model to include entrepreneurs and start-ups. Two dominant innovation activities are postulated—one entrepreneurial and one traditional. The former, which is assumed to be more dependent on external knowledge, is dominated by entrepreneurs and newly established frms, while the latter is assumed to be associated with the in-house R&D of existing larger frms.

Other models were to a greater extent based on the dominant general equilibrium paradigm. Jovanovic (1982) presents a model for industrial development based on learning. The model assumes an infnite number of small frms that take price as a given. They have perfect information about the equilibrium structure but are ignorant of their own performance (productivity); however, they learn after market entry. These small frms are at greater risk of failure and are also assumed to have poorer growth opportunities.29

Acs et al. (2004) and Braunerhjelm et al. (2010) take one of Romer's models as their point of departure and show how entrepreneurs who are not involved in research also contribute to innovation and growth. In the model, the business community consists of incumbents that invest in research, as well as entrepreneurs who do not contribute to it. The ability of entrepreneurs to innovate is based on their capacity (unevenly distributed) to draw on previous research investment and to use that knowledge to launch new goods and services. In this way, the entrepreneur becomes an instrument for disseminating knowledge; he or she contributes a

28See Fagerberg (2002), Soete et al. (2010), and OECD (2015) for an overview.

29See also Pakes and Ericson (1995, 1998) and Klette and Kortum (2004) for versions of Jovanovic's model stressing learning and internal resources, respectively.

mechanism for knowledge to be commercialized. In a model that includes entrepreneurs, the opportunities for sustainably higher growth increase.

In a slightly different model, Acs et al. (2005, 2009) show how entrepreneurship can be endogenized on the basis of knowledge investment and institutional conditions (regulations, well-functioning fnancial markets, etc.). Given an environment that promotes entrepreneurship, knowledge investment will result in individuals with different entrepreneurial abilities choosing entrepreneurship over employment. There is thus a complementarity between existing and new frms that leads to the testing and exploitation in the market of a larger proportion of an economy's knowledge base.30

Several of these models seek to incorporate more of the evolutionary elements into a general equilibrium structure, which has occasionally led to drastic assumptions regarding prices, information, transaction costs, distribution of profts, exogeneities, and more. Other models are so complex that it becomes diffcult or impossible to calculate a solution, so that simulation methods must be used instead (this includes Nelson and Winter and their successors).31 In many cases, Schumpeterian creative destruction is not satisfactorily modeled. The more aggregated the data, the more diffcult it becomes to distinguish which components are driving the processes.

Nevertheless, the contribution of these newer models is signifcant. First, they show how variation and selection under competition characterize market economies and are crucial for business sector development. Second, these phenomena take place in dynamically adaptive systems where learning and feedback take place continuously. One conclusion is that change tends to materialize slowly and is dependent on several factors that affect both knowledge building and knowledge dissemination and commercialization. These in turn are affected by institutions and norms. Finally, the evolutionary system is adaptive, complex, and partly selforganizing, while a state of (traditional) equilibrium is usually an exception rather than the rule.

#### **2.3 Small Businesses and Entrepreneurs: The Empirical Picture**

An increasing number of studies point to the importance of new and small frms for the development and commercialization of knowledge, even though they invest relatively modest sums in R&D. Instead, they contribute through their efforts to

30A parallel, and to some extent overlapping, research strand has aimed to integrate neo-Schumpeterian growth models with insights derived from the industrial organization feld. The focus of this research has been how barriers to start-ups, strategic R&D, strategic collaboration, and other factors affect innovation and growth (Laffont and Tirole 1993; Acemoglu et al. 2003; Durnev et al. 2004; Aghion et al. 2004, 2006; Howitt 2007).

31See also Eliasson's (1991, 1996) micro-to-macro simulation model.

apply knowledge. However, according to Cooper's (1964) analysis based on case studies, when small frms undertake R&D, they manage it more effciently than large frms. He suggests two major explanations: (i) smaller frms have an advantage in exploiting employees' abilities and (ii) there are different attitudes as well as more direct communication among R&D personnel in small frms. Acs and Audretsch (1987, 1990), drawing on more extensive data, concluded that even though larger frms accounted for the bulk of R&D investment, smaller ones were signifcantly more innovative in certain industries, such as computers and machine tools, while the reverse was true in the automotive industry. For manufacturing as a whole, the rate of innovation was signifcantly higher in smaller frms. Similar fndings were presented by Baldwin and Johnson (1999) for electronics, instrumentation, medical equipment, steel, and biotechnology. Other studies show that smaller frms are more skilled at producing radically new products. Based on both a theoretical model and an empirical analysis, Michelacci (2003) shows that relatively weak commercialization of research can be explained by too few entrepreneurs.32

Regarding the importance of new and smaller frms for economic development, a number of empirical analyses have also found a positive relationship between small businesses and growth when other factors such as investment, employment, R&D, and internationalization are taken into account. Already in the early 1990s, Levine and Renelt (1992) argued that there was a strong positive relationship between the share of small businesses in an economy and economic growth.33

Haltiwanger et al. (2013) show that it is young frms, rather than small ones, that create a disproportionately large number of jobs. Controlling for age, they fnd that there is no longer any relationship between size and job creation. This has major implications for policy: job creation should be supported by targeting young frms rather than small frms. If the latter are old, they should not be expected to create many jobs. Young frms with superior capabilities and routines move "up" in terms of size and performance, while young ones in which inferior capabilities are discovered are more likely to decline and exit from the market (Huber et al. 2017). Indeed, while the majority of new frms will fold in their frst fve years, the remaining survivors will show considerable growth.

Later studies on both Sweden and the United States confrm these fndings; here, the net contribution of jobs can be disproportionately attributed to young and small frms. On the other hand, productivity seems to have been dominated by larger frms. These differences are explained by the division of labor where low-educated workers can increasingly be found in small and medium-sized enterprises (SMEs) whereas the share of highly educated workers increases with the size of the company. Furthermore, productivity growth is determined in large part by the

32For the importance of entrepreneurs and small businesses for technological development, knowledge, and commercialization, see, for example, Cohen and Klepper (1996), Hopenhayn (1992), Audretsch (1995), Acs (1996), Klepper (1996, 2002), and Almeida (1999).

33 Initially, an infux of smaller frms can lower productivity (Shane 2009). But at the same time, new frms contribute to increasing productivity in existing ones, with a certain time lag (Andersson et al. 2012; Fritsch and Mueller 2004, 2008).

composition of an industry; aggregate productivity growth will be higher if the share of industries where fast-growing and technology-intensive frms are particularly important. As a corollary, this fnding indicates that labor mobility across frms of different sizes is important for the diffusion of knowledge.34 At the same time, the probability of survival is lowest in these frms, especially in technology-intensive industries (Audretsch 1995; Parastuty 2018; Braunerhjelm and Halldin 2022). An infux of new frms and the testing of new ideas—but also their exclusion—is nevertheless a critically important component of dynamic economies.35

To establish a causal relationship between the entry of new frms and aggregate growth implies further diffculties in tracing how different variables interact and whether any actual impact on growth can be identifed. However, all growth models emphasize the role of innovation for growth and given that small, young, and new frms contribute a disproportionate share of innovation, entrepreneurial ventures should have either a direct or indirect effect on growth. Several studies also report a correlation between entrepreneurship and growth, which seems to have been reinforced over time (Thurik 1999; Acs et al. 2004; Salgado-Banda 2005; Block et al. 2009; Braunerhjelm et al. 2010; Galindo and Méndez 2014; Urbano et al. 2019). Klapper et al. (2010) note that entrepreneurship is a necessary condition for a dynamic market and that it leads to both tougher competition and greater growth.

Based on an endogenous growth model that includes entry and exit of frms, Akcigit and Kerr (2018) demonstrate the impact that different types of innovations (explorative versus exploitative) have on economic growth. The classifcation of innovation strategies on explorative and exploitative paths was suggested by March (1991). The former refers to innovation having a more general scope of search whereas exploitative innovation implies prioritizing search depth, i.e., improvement of current products, services, and processes. According to Tushman and Smith (2002), there is a link between these and previous concepts where exploitative innovations can, to a greater extent, be associated with process innovation. In Akcigit and Kerr's model frms invest in explorative R&D to acquire new product lines and in exploitative R&D to improve their existing product lines. They show that explorative R&D does not correspond as strongly with frm size as exploitative R&D, suggesting that smaller and younger frms are important for the latter type of innovations. They also fnd some empirical evidence that new frm entry together with SMEs has relatively higher growth spillover effects.

34See Davis et al. (1996), van Stel and Storey (2004), Baptista et al. (2008), and van Stel and Suddle (2008). Haltiwanger et al. (2013) present an analysis for the U.S., which is replicated for Sweden by Heyman et al. (2019).

35Even though smaller frms generally grow faster than larger ones, the prevailing view since the early 1970s that SMEs accounted for the major share of employment growth has been somewhat modifed and more emphasis is placed on young frms. Gibrat's law—which states that frms grow just as fast regardless of size—has been rejected in a series of studies; see Almus and Nerlinger (2000) for a general overview, and Heshmati (2001) and Daunfeldt and Elert (2013) for the Swedish case.

At the regional level—where the analysis is facilitated by the fact that the formal institutions are the same—there are a large number of studies concluding that entrepreneurship and knowledge levels both contribute strongly to higher growth and prosperity.36 Several studies of U.S. states show that entrepreneurship (approximated by infows and outfows to the market) has a positive effect on productivity and employment. In Europe, similar results have been found, for example, in Spain and Germany (Audretsch and Keilbach 2005; Habersetzer et al. 2021). The results have been interpreted as evidence that international convergence towards more entrepreneurship-led growth is underway, despite differences in institutions and regulations. However, there are still signifcant variations between countries.

Given the role attributed to new, young, and small frms in the above-mentioned studies, the recent decline reported in entrepreneurship in several countries is reason for concern (Hathaway and Litan 2014; Decker et al. 2017; Naude 2019; Salgado 2020). This seems to be a trend in most developed countries, Sweden being an exception. According to Heyman et al. (2019), this is due to the reforms introduced in Sweden since the 1980s, in particular in the aftermath of the severe crisis in the early 1990s. This is consistent with new and young frms having played a prominent role in job creation during the period, spurred by labor market reforms such as permitting staffng agencies, the allowance of temporary contracts, informally coordinated wage negotiations, and the Industry Agreement adopted in 1997 (see Chap. 6).

Simultaneously, product markets were deregulated (transportation, education, healthcare, etc.) and a new competition act in 1993 replaced the one from 1925, while the lifting of all foreign exchange controls exposed Swedish frm owners to international competition. As a result, Sweden experienced the highest labor productivity growth rate among the OECD countries between 1995 and 2011 paired with improved allocative effciency and frm-level productivity as the forces of creative destruction were unleashed. This was a huge step away from the interventionist policies pursued in the 1970s and 1980s, an era characterized by lagging productivity and decreased effciency.

#### **2.4 In Sum**

New theoretical and empirical research within the evolutionary approach that we consider to be the most promising shows how a number of institutional factors interact to promote knowledge dissemination and entrepreneurship, thereby paving the way for important innovations. Within this approach, the challenge is much more complex compared to the traditional knowledge-driven growth model, where policy

36See, for example, Reynolds (1999), Audretsch and Fritsch (2002), Callejon and Segarra (1999), Glaeser et al. (1992), Audretsch et al. (2006), Braunerhjelm and Borgman (2004), Feldman (2014), Fritsch and Wyrwich (2017), and Del Del Monte et al. (2022). See Braunerhjelm (2008, 2011) for overviews of the earlier literature.

implications tend to be limited to subsidies or tax breaks for R&D, and measures to expand and prolong formal education. The difference in policy conclusions compared with those derived from endogenous growth models is straightforward: If knowledge and entrepreneurial abilities are decentralized and spread across a large number of actors, policy should be more general and ensure that the measures implemented cover everyone in a non-discriminatory manner and embrace several policy areas. The government should thus refrain from engaging in active "industrial" policies by identifying certain sectors or technological niches.

In the next chapter, we will take a closer, more concrete look at these factors and analyze how their design affects innovation activities.

#### **Appendix: Measuring Entrepreneurship**

Economists have often chosen to measure the degree of entrepreneurship in a country or region as the share of total employment constituted by the self-employed.37 This is a crude simplifcation because the defnition of "entrepreneur" as a selfemployed worker fails to capture all facets of entrepreneurship. In addition, a variety of reasons may lie behind the choice to start one's own business. This is shown in Table 2.2, which presents various motives for entrepreneurship. The term "selfemployed" includes both those who are sole proprietors and those who run their business as a limited liability frm.

Motivations for becoming a self-employed person can include the prospect of a better life or realizing the full entrepreneurial potential of an idea. Often, however, self-employment is a way of circumventing restrictive regulations and obstacles within the company where a person works. Alternatively, the labor market may be too regulated for employees. A third—less agreeable—reason is that selfemployment can increase opportunities for rent seeking and improper tax evasion.

The prevailing conceptual confusion regarding entrepreneurship, where completely different kinds of entrepreneurs are lumped together, sometimes gives inconsistent research results and policy recommendations. According to Schumpeter's (1934) defnition—the one to which we adhere—most new businesspeople and self-employed are *not* entrepreneurs, as they lack the ambition to be innovative or growth-oriented.38 Most self-employed people in Sweden do not have and will never have a single external employee. It is thus important to distinguish between self-employed people as a group and a small number of—often fastgrowing—frms where entrepreneurship is more prominent.39 The latter group accounts for a disproportionately high share of restructuring and job creation in the

37Carree and Thurik (2010) and Wennekers and Thurik (1999).

38This is discussed in detail in Henrekson and Sanandaji (2020).

39High taxes can, for example, lead to more self-employment, if taxes are also high on the alternative (employment) and if self-employed people can more easily avoid taxes (Engström and Holmlund 2009; Hurst et al. 2014). Countries with high taxes do not have fewer self-employed

**Table 2.2** Entrepreneurial and non-entrepreneurial motives for self-employment

*Note*: The table lists the major motives behind self-employment. Intermediate cases also exist. For instance, entrepreneurial self-employment may be partially pursued in search of independence. "First best" means that the choices are both privately and socially optimal. "Second best" implies that the optimal choice is blocked by regulations or some other institutional barrier, but selfemployment may still more or less offset the negative effects that arise *Source*: Developed further from Henrekson (2007)

economy.40 The category of frms with ambition and potential for innovation and rapid growth is signifcantly smaller than the broad group of entrepreneurs and differs markedly from the majority.

It is sometimes claimed that these are all the same kind of frm, and that it is only chance that determines who manages to grow. Of course, there is a large gray area here, for example frms that originally had no ambition to grow but which changed their targets when their growth unexpectedly took off. However, we believe that there are also *ex ante* fundamental differences between different types of entrepreneurs. The overwhelming majority of self-employed people in Sweden state that they do not defne themselves as entrepreneurs based on ambitions to grow, a large number of employees, or innovative ideas. There are other important differences between these separate business owner categories. While self-employed people are similar to wage earners in terms of education, entrepreneurs in the United States who have received venture capital funding are 20 times more likely than the average American to have a doctorate (Bengtsson and Hsu 2010).

We dare say that there is a strong international trend among researchers and experts towards using the terms entrepreneur, entrepreneurial activity, and

people but tend to have fewer exceptionally successful entrepreneurs (Henrekson and Sanandaji 2011, 2014).

40Henrekson and Johansson (2010), Hölzl (2010), and Criscuolo et al. (2017).

entrepreneurship for people, actions, and phenomena where the intention is to create valuable benefts through (growth-oriented) economic activity based on the identifcation and/or creation of new products, processes, and markets. Due to its complexity, this concept is impossible to capture in a single indicator. Those who wish to delve into the problems of measurement are referred to OECD (2008), which offers 18 different indicators of the degree of entrepreneurial activity.

#### **References**

———. 1994. Dynamic of Entrepreneurship, Technology and Institutions. In *The Dynamics of Entrepreneurship*. Crafoord Lectures 5, ed. Erik Dahmén, Leslie Hannah, and Israel M. Kirzner. Lund: Lund University Press.

———. 2020. "Measuring Entrepreneurship: Do Established Metrics Capture Schumpeterian Entrepreneurship?" *Entrepreneurship Theory and Practice* 44(4): 733–760.

Raffaelli, Tiziano. 2003. *Marshall's Evolutionary Legacy*. London: Routledge.

———. 1990. "Endogenous Technical Change." *Journal of Political Economy* 98(5): S71–S102.

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## **Chapter 3 Promoting Entrepreneurship and Innovation: The Institutional Framework**

In the previous chapters, we have consistently emphasized the importance of entrepreneurship for innovation, renewal, growth, and job creation. However, these benefcial forces do not automatically refect the individual entrepreneur's aims. Even if factors such as social recognition and testing one's ideas infuence the desire to become an entrepreneur, the pursuit of proft plays a part that cannot be ignored. When entrepreneurs search for and attempt to create entrepreneurial rents, they are largely governed by the incentives—the reward structure—that prevail in the environment in which they pursue their entrepreneurship. These incentives are essentially determined by the institutional setup of the economic system, which is sometimes called "the rules of the game." Good institutions or favorable rules are prerequisites for encouraging innovation and entrepreneurship and for channeling entrepreneurial effort towards socially productive venturing.

In this chapter, we will identify and analyze the most important institutions and contextual factors involved when discussing the design of policies to promote innovation and productive entrepreneurship in both new and incumbent frms.

#### **3.1 The Rule of Law and Protection of Property Rights**

A market economy, based on voluntary transactions and decentralized decisionmaking with the entrepreneur as its *primus motor*, works best in systems with wellfunctioning institutions in which political freedom thrives. The entrepreneur collects and exploits decentralized information; society's institutions in the broadest sense govern accessibility and opportunities to assimilate, develop, and exploit knowledge. Studies building further on Nobel Laureate Douglass North's research (North 1987, 1990) also fnd strong evidence for the notion that certain basic institutional arrangements are vital to economic growth, of which the rule of law—*de facto*, not only *de jure*—and well-defned and secure property rights seem to be the most

P. Braunerhjelm, M. Henrekson, *Unleashing Society's Innovative Capacity*, International Studies in Entrepreneurship 55, https://doi.org/10.1007/978-3-031-42756-5\_3

important.1 It is also crucial that the state treats citizens equally and impartially, and does not engage in "clientelism," that is, favoring particular groups. The latter easily leads to corruption, which greatly distorts the driving forces of entrepreneurship (Rothstein 2011).

The lack of well-defned property rights may partly explain weak economic growth in the world's poorest countries (de Soto 2000). When properties cannot be mortgaged because they were built without a permit or a legal title, the impact on investment is palpable. Insecure and poorly defned property rights thus undermine the use of assets in prosperity-enhancing productive activities. Kleptocracy can then become a signifcant element of government activities. In a nation governed by the rule of law, fewer resources are wasted on conficts because both citizens and authorities are subject to the law, and the law in turn is rooted in public consciousness. The state is impartial, and enforcement of the law—as well as the imposition of sanctions for violations—is guaranteed by independent courts (Bingham 2011).2

Private ownership is thus central to productive entrepreneurship. By this we mean something more than simply the right to dispose of an asset and to compensation in the event of expropriation. Also crucial are the right to exploit and develop the asset, the right to the return that the asset can generate, the right to transfer all or part of these rights through sale, gift, or rent, and protection against infringements by the government or individuals.

Particularly important in a knowledge-based and innovation-driven economy are the right to ideas and a framework that enables individuals and businesses to transform ideas into new and growing frms. Examples include intellectual property law and patent law. If the protection of property rights is strong, investors can count on retaining the profts they expect from entrepreneurial activities. If legal certainty is high and the legal system is credible, it will be much safer for them to engage in long-term, often risky, projects, as the basic "rules of the game" can be expected to remain stable.

Likewise, risks are lower when entering into agreements and performing transactions with other parties. In a society governed by law with well-defned property rights, there is more room for division of labor. The opportunities are then greatly enhanced for individuals and organizations to acquire specialized skills and form combinations or trade to take advantage of the skills and capabilities of others in addition to their own. Such an environment provides favorable opportunities for entrepreneurs to exploit their ideas by gaining access to external capital and the necessary skills through contracts.

1Rodrik et al. (2004) argue that certain aspects of institutional quality—especially well-defned and secure private property rights—are more important for growth than factors such as trade and geography, e.g., not being landlocked and having access to fertile arable land. See also Acemoglu and Robinson (2012).

2However, Shleifer (2005) notes that even seemingly impartial courts are subject to different kinds of pressure from a variety of groups.

#### **3.2 National Innovation Systems**

In the debate and research on innovations and innovation-promoting institutions, the so-called national innovation systems occupy a central place. A common defnition of such a system is the following (Metcalfe 1995, p. 38):

…that set of distinct institutions which jointly and individually contribute to the development and diffusion of new technologies and which provides the framework within which governments form and implement policies to infuence the innovation process. As such it is a system of interconnected institutions to create, store and transfer the knowledge, skills and artefacts which defne new technologies. The element of nationality follows not only from the domain of technology policy but from elements of shared language and culture which bind the system together, and from the national focus of other policies, laws and regulations which condition the innovative environment.

Similar defnitions are suggested by other leading scholars in the feld. For example, Patel and Pavitt (1994, p. 12) defne a national innovation system as

the national institutions, their incentive structures and their competencies, that determine the rate and direction of technological learning (or the volume and composition of change generating activities) in a country.

Innovation systems that are organized appropriately have the potential to serve as powerful engines of progress. On the other hand, if poorly organized and fragmented, they may seriously inhibit the process of innovation (Freeman 1987). Metcalfe (2022) interprets innovation systems as a way of organizing labor across universities and industries while testing facilities in search of innovations. As Freeman does, he stresses the need for connectivity, but also structure, between these actors to attain the objectives of new knowledge and innovative outcomes.

Volumes of research and numerous inquiries have also been conducted exploring how such systems should be designed.3 In an overview of research on innovation systems, however, Carlsson (2007) concludes that most of this activity concerns inventions rather than innovation, and a mere two to three percent of the studies Carlsson identifes involve entrepreneurship.4 Policy issues are addressed in about a quarter of these works, but they are almost exclusively focused on technology policy, i.e., technological infrastructure, R&D, patents, private versus public R&D, and collaborations between public and private actors. Incentive structures, which vary between actors in an innovations system (e.g., between research institutes and in

3For Sweden, see, for example, Gergils (2006) and Bager-Sjögren (2011). For an analysis of strength and weaknesses in a particular part (biorefneries) of Swedish innovation systems, see Hellsmark et al. (2016). See especially Lundvall (1992) and Edquist (2005) for an in-depth discussion of innovation systems. As pointed out by Carlsson (2007), these approaches are mainly descriptive, aggregated, and static—there is no room for dynamism. Magro and Wilson (2013) present a policy analysis of innovations systems. See Elert et al. (2019) for the European Union.

4We have not found any more recent evaluation analysis with a similar degree of detail. Jurickova et al. (2019) evaluate national innovations systems by studying how the number of researchers and R&D expenditure hae affected publication of scientifc journal articles and applied patents during 2006–2016 in the European Union. They document a declining performance.

frms), are entirely overlooked and less than one percent of them concern the issue of fnance.

Even more interesting is the fact that, in the extensive literature on innovation systems, the outcome of these initiatives is almost completely overlooked; less than three percent of the research into innovation systems examines success criteria (productivity, growth, innovation, patents, start-ups, etc.). From our perspective, the fact that the innovation system approach attempts to identify and analyze the mechanisms that cause existing and new knowledge to be transformed into economic growth, while it only to a minor extent includes incentive structures, is problematic in terms of its normative power. This shortcoming makes it practically impossible to analyze the incentives required for various actors and functions to work together to create the most value.

A good example of how an overly partial innovation system analysis can easily lead to erroneous conclusions is the introduction of soft loans for start-ups to stimulate innovation and entrepreneurship. Such loans are often a central component of a country's innovation policy, even though they normally have a dubious or even counterproductive effect (Lerner 2009; Dvoulety 2017; Svensson 2017). The reason is that the underlying analysis used to justify such a measure does not take into account the specifc characteristics of entrepreneurial activity (we will return to these below). Without a detail-oriented and competent provider, there are obvious risks that systems in which one main element is soft government loans will develop into a system of subsidies, where various pressure groups (regional bodies, industry representatives, interest groups) compete against each other around the pork barrel. The result is often less than optimal, despite the good intentions. We have observed this phenomenon in the Swedish innovation system. There are numerous actors (e.g., Vinnova, ALMI, Industrifonden, the AP funds, and several regional funds) at the regional and national level which all provide loans, credit guarantees and investments in sizable amounts earmarked for the promotion of new frms and innovations.5 Their assessed impact seems ambiguous. We need to better comprehend how these bodies interact, compete, and overlap as well as what overall impact they achieve.

It is thus unclear whether and how innovation systems, traditionally defned, lead to more innovation and higher growth. As Fig. 3.1 shows, it is also diffcult to establish a simple positive macro-level relationship between aggregate innovation measures (here measured by the EU innovation index) and the economic growth rate. This observation is in line with Akcigit and Nicholas's (2019, p. 623) observation: "Yet it is perhaps surprising how diffcult it has been to establish a robust empirical link between innovation and growth. To our knowledge, no paper has actually shown that innovation is related to U.S. economic growth over the long run."

For us, this suggests that the innovation system approach does not focus suffciently on incentives and drivers for innovation and entrepreneurship. Hence, even though the literature on national innovation systems is purportedly infuenced by the Schumpeterian tradition, the entrepreneur remains largely absent therein.

5Svensson (2017) and SOU 2020:59.

**Fig. 3.1** The EU innovation index and annual GDP growth per capita, 2014–2021, all EU member countries. *Source*: European Commission (2021), OECD Statistics, and Braunerhjelm (2011).

#### **3.3 Public Support for R&D**

Support for frm R&D is not considered to be in breach of EU state aid rules, despite the fact that the EC Treaty prohibits general state aid for activities which, according to the Treaty, must be subject to free competition.6 This is justifed by the fact that R&D is considered central to achieving economic growth, and that there is reason to believe that the social return on R&D investment is greater than the private return. As long as support is non-discriminatory and potentially available for all frms, it is therefore considered compatible with state aid rules.

As shown in Table 3.1, there is signifcant public support for R&D in wealthy countries. This support can manifest in both direct and indirect form:

6Note that the state aid rules have largely been abolished since 2020 due to the COVID-19 crisis, followed by the war in Ukraine and the energy crisis. There is currently an ongoing debate on the design of future rules.

**Table 3.1** Business enterprise R&D support (BERD) as a share of GDP in 27 countries 2020 (%)

*Note*: Indirectly fnanced BERD consists of indirect government support through R&D tax incentives. Directly fnanced BERD: Iceland 2014, Switzerland 2019. Indirectly fnanced BERD: Finland 2014, Spain 2017, the U.S. 2019. Business enterprise R&D: Switzerland 2019. Countries are ordered based on the share of BERD fnanced by the government

*Source*: Eurostat and OECD

incentives, either through the granting of a deduction that exceeds the actual expenditure (Sweden had such a system in 1973–83) or as a tax rebate such as a reduced payroll tax on the salaries of R&D personnel (which Sweden has had

since 2014).7 However, indirect support presupposes that the expenditure conforms to the R&D requirements set by the authorities, which in itself can affect its composition.

An overwhelming majority of OECD countries use indirect support for R&D in the form of tax incentives.8 Of the 27 countries in Table 3.1, Sweden had the eighth most extensive direct subsidies as a share of GDP, but due to its low level of indirect subsidies, Sweden is well below the median for total R&D subsidies. At the same time, Sweden's business sector R&D as a share of GDP is the fourth highest in the world after South Korea, the United States, and Japan, which means that state support constitutes a relatively small part of the business sector's total R&D (just over fve percent).

Hovdan et al. (2023) concluded in a recent survey article that both indirect and direct support to private R&D have positive input and output effects. According to the authors, the effect is somewhat larger for indirect support than for grants, which is confrmed in an econometric study for Belgium. However, they also stress that public support invariably leads to partial crowding-out as frms substitute state aid for their own R&D expenditures, thereby imposing a welfare loss on society as such. In addition, they argue that knowledge regarding how different policy instruments interact is necessary to avoid suboptimal policy designs.

In recent decades, a new kind of tax incentive has attracted increasing interest the so-called patent boxes (alternatively called innovation boxes to underscore that these are not contingent upon granted or applied patents). This means that profts generated by patents, intellectual assets, or intellectual property rights are taxed at a considerably lower rate than corporate profts in general.

There exists no defnitive evidence regarding the effect of patent boxes on innovation or economic outcomes. The effect, whether positive or negative, hinges on the design of the scheme. It was frst used by some European countries as far back as the 1970s and has spread rapidly to several other countries in recent years. At present, 13 European countries, in addition to several regions, have adopted some form of patent boxes.9 Their popularity seems to have levelled out after the OECD linked it to the Base Erosion and Proft Shifting (BEPS) initiative and imposed several restrictions setting limits on the level of intellectual property income eligible for preferential taxation.

Interpretations of the empirical evidence of how patent boxes affect location, innovation outcomes, and R&D investments are mixed. For instance, Gaessler et al. (2021) and Miller and Pope (2015) fnd negative effects, while Mohnen et al. (2017)

7Government Bill 2013/14:1, section 6.9.

8The number of OECD countries that use some form of tax incentive has increased sharply in recent decades; in 1995, it was only used in 12 OECD countries (OECD 2011, p. 15).

9These are Belgium, Cyprus, France, Hungary, Ireland, Lithuania, Luxembourg, Malta, Netherlands, Poland, Portugal, Slovakia, and Spain (federal, Basque Country, and Navarra). Non-EU countries such as Andorra, San Marino, Switzerland, Turkey, and the United Kingdom have also implemented patent box regimes. *Source*: Bunn (2022).

and Bradley et al. (2021) see positive effects. Obviously, one must acknowledge the vast methodological diffculties in assessing the effects of R&D support (OECD 2011).

Overall, we argue that there are several reasons why governments should be restrictive in supporting private R&D. First, there is always the risk that government support will displace private expenditure, i.e., some of the government-fnanced spending would have occurred in any event. Second, in addition to crowding-out effects, R&D support, in particular tax incentives, always creates distortions in how resources are allocated. These can be costly since:

The government can use additional policy measures to promote innovation, one of these is public procurement. In Sweden, this amounted to SEK 819 billion in 2020 (for the state, municipality, and county councils in total), which was more than one-sixth of GDP (Swedish Competition Authority 2020). Given its size, and the fact that public procurement can be an important part of the innovation process, there is a good reason to consider how innovation can be integrated into the procurement process and how smaller businesses can be involved.

The United States pioneered a system targeting smaller frms—Small Business Innovation Research, SBIR—in which innovation-procuring agencies were obligated to allocate a certain proportion of their funds to smaller frms. Other countries, including the Netherlands and the United Kingdom, have introduced similar systems. This model is based on a two-step procedure, where initial public fnancing is aimed at several potential innovators (frms), and the one that succeeds in producing the most promising prototype receives signifcantly more fnancing in the second step. In the United States, evaluation of the SBIR policy points to positive results for frm R&D, R&D collaborations, frm growth, and start-ups.13

10Kärnä et al. (2020) and Svensson (2024).

11Bhidé (2008) argues convincingly, for example, that the so-called non-codifable/non-scientifc knowledge is of extraordinary importance for transforming knowledge into economic value. Thus, it is often not a result of regular R&D, and it is even less often patentable.

12For example, Martinsson (2012) estimates that implementing the Dutch innovation box system in Sweden would immediately cost SEK 5 billion per year in reduced tax revenues. In the long run, the cost would be even higher once companies adapt to the system. Wilson (2009) studies the effects of U.S. state R&D subsidies to businesses. He fnds that these subsidies are a zero-sum game; activities are relocated as a result of the subsidies, but the aggregate effect at the national level is zero. See also OECD (2011).

13See OECD (2010, pp. 106–107) and Link and Scott (2010).

More generally, public procurement to stimulate innovations is still unevenly adopted across countries and the outcomes at the country level have not yet been analyzed nor understood in depth. Uyarra et al. (2023) argue that in order to become an effcient instrument in enhancing innovation, procurement initiatives need to be integrated into a national and sectoral context and aligned with other policy initiatives.

#### **3.4 National Systems of Entrepreneurship/Entrepreneurial Ecosystems**

The essence of national systems of entrepreneurship (NSE) is defned by Acs et al. (2014, p. 479) as

the dynamic, institutionally embedded interaction between entrepreneurial attitudes, activities, and aspirations, by individuals, which drives the allocation of resources through the creation and operation of new ventures.

The insight that a more effcient allocation of resources, and the concomitant restructuring of an economy, are driven by entrepreneurs is profound and important. It clearly alludes to Schumpeter's view on the role of entrepreneurship and creative destruction but adds rigor and stringency.

Thus, the NSE aims at integrating the country-specifc context in which entrepreneurs (and potential entrepreneurs) are embedded with decisions taken by individuals identifying an entrepreneurial opportunity, where the costs and benefts of such decisions are considered (Acs et al. 2016). The NSE is clearly associated with previous research focusing on the existence of entrepreneurial opportunities (Acs et al. 2009). However, it differs from previous research by stressing reallocation and structural change at a more aggregate level. This is a defnitive step forward in understanding the dynamics of innovation.

In the NSE framework, bottlenecks, or defciencies, are identifed through crosscountry comparisons. Even though lessons can be learned from other countries, interdependencies and links across policy areas and other institutional characteristics tend to center on a certain country-specifc context. As Acs et al. (2016) note, identifying these relationships and understanding their implications should guide the design of an NSE. Obviously, such interactions consist of a complex web, rendering it an intricate and context-dependent task to design the appropriate policy measures required to strengthen the NSE (Autio and Levie 2015).

Another related and largely overlapping concept under which one can frame the relationship between the individual opportunity and the context within which it operates concerns the entrepreneurial ecosystem approach.14 According to Stam and Van de Ven (2021), this entails a multitude of diverse and interrelated organizations

14Malerba and McKelvey (2020) attempt to integrate these two strands in the literature more seamlessly into a coherent framework.

and institutions that co-exist and co-evolve. The actors either compete or cooperate, depending on their specifc characteristics and the circumstances under which they operate. In a well-designed ecosystem, these organizations, and the ways in which they interact, are claimed to contribute to a dynamic but complex economic environment. In such ecosystems, the different roles played by agencies and institutions are emphasized. Stam and Van de Ven also stress how endowments and access to resources are dependent on both the formal and informal institutional setup.

While these modifed system versions offer valuable insights and add dynamic elements lacking in previous versions, we would argue that critically important variables that determine individual behavior, and the outcome at the aggregate level, are absent. In particular, countries are characterized by their specifc formal and informal prerequisites and bottlenecks, generating direct and indirect effects, which should be analyzed within their specifc context (Audretsch 2015). One of a policymaker's most powerful instruments, taxes, will be discussed in Chap. 5 as one example. In addition, some of the institutional variables used to determine the functioning of an NSE, such as technology absorption, gender equality, R&D spending, and depth of capital markets, seem to be outcomes resulting from the structure of the NSE rather than institutional determinants (Braunerhjelm and Henrekson 2016, p. 101).

We argue that a detailed analysis of each individual economy is required to design appropriate policies. Moreover, importing "best practices" from other countries and making them work under local circumstances is a challenging task, although lessons can certainly be learned from them. This is also highlighted in the critique of national innovation systems (NIS) by NSE proponents. For instance, Autio et al. (2014) argue that the NIS literature studies entrepreneurial activities and performance based on the implicit assumption that observed differences are the outcome of institutional infuences operating in the same way across countries. However, in fact, they feature a range of different formal and informal institutional settings, different cultures, norms and values, and attitudes towards entrepreneurship that affect entrepreneurial performance. Hence, even though the NSE approach provides valuable insights on how countries deviate in terms of entrepreneurial effort and orientation from a cross-country average measure taking institutions into account, an appropriate policy design requires additional disaggregation and attention to detail.

#### **3.5 Growth at the Firm Level: The Collaborative Innovation Bloc**

As we have already noted, it is not enough to create new knowledge, as much new knowledge is not in itself economically valuable. The economy therefore needs "knowledge flters" that distinguish economically relevant knowledge and convert it into economic activity (Carlsson et al. 2009). Moreover, the entrepreneurial process that causes the market order to evolve is inherently collaborative: To pursue their innovative projects, entrepreneurs engage in cooperation with a number of actors, whose complementary skills greatly increase the probability that an innovationbased venture will be successful. The actors are drawn from several skill pools, which together form what we call the *collaborative innovation bloc*. Thus, we recognize that entrepreneurship is crucial, but other actors are as well: early-stage fnanciers, key personnel, inventors, knowledgeable and demanding customers, and later-stage fnanciers. Successful entrepreneurship that generates rapid growth is a function of how well these actors acquire and apply their skills. The opportunities and impetus to do this are largely determined by the institutional framework, or what in everyday speech we call "the rules of the game."

Figure 3.2 schematically captures the phases in which various actors enter the innovation and commercialization process. In the initial stage, the entrepreneur identifes potential proft opportunities; knowledgeable customers often play an important part in this process. Inventors are engaged to solve technical problems, but as the business grows, innovators and key personnel, especially experienced managers but also R&D specialists, are needed to lead more comprehensive development projects. Sometimes the process can be initiated by inventors, whose ideas are then further developed by innovators and entrepreneurs.

The early commercialization phase mainly involves entrepreneurs (possibly also inventors) and, to a lesser extent, other types of skilled labor. In the scale-up phase, professional managers, salespeople, and R&D specialists are activated and skilled labor is then essential. Founders, family and friends, business angels, and venture capital frms fnance development in the early stages, while actors in the secondary market, later-stage fnanciers, enter the picture later. Figure 3.2 is obviously a simplifcation—for example, experienced managers and later-stage fnanciers can be involved much earlier, and different actors can work in parallel with each other, overlapping or lagging each other in different phases. The same person can

**Fig. 3.2** The collaborative innovation bloc. *Source*: Elert and Henrekson (2019, 2020)

sometimes fulfll more than one function, for example that of both an entrepreneur and a manager of the frm when it reaches a more mature stage.15

Later-stage fnanciers potentially fall under a number of different categories: wealthy individuals/families, closed-end investment funds, stock-market activists, institutional investors, buyout frms, stock-picking individual savers, and competitors aiming to take over the frm's operations through a so-called trade sale. Laterstage fnanciers have similar skills and carry out similar functions as venture capitalists, in terms of fnancing and the transmission of knowledge and skills, but this selection occurs at a later stage when entrepreneurs and venture capitalists wish to exit their investments. Hence, these actors evaluate frm performance and assess whether there are potential profts in assuming control, replacing the entrepreneur and top management in the event of sustained inferior performance. An important distinction among later-stage fnanciers is between those who take an active part in a company in which they invest or wholly control its governance, and passive investors, such as pension funds and open-ended stock-market funds as well as physical persons who own listed shares directly.

A trade sale—selling the frm to another one, usually a frm in the same industry—is arguably the most common way of exiting. In this case, full control over the frm is handed over to the buyer, and the entrepreneur/founder leaves the business with substantial fnancial assets. These assets make it possible to start new frms or act as a business angel or venture capitalist. A trade sale is likely an indication that some crucial skill is lacking in the frm in its existing form, making an independent scale-up of its operations unfeasible.

Consumers are the ultimate arbiters of an innovation's success (as such, they make the fnal selection), yet they seldom appear in studies of innovation. The omission is regrettable—the willingness and ability of individual consumers to dare to purchase and effectively use new products, and the openness of intermediate producers to new know-how and products, may be crucial drivers of innovation. Usually, the role of the alert, competent, and interested customer is essential to the supply of innovative products. Especially in the early stages, demanding collaborators function as particularly important sources of information regarding consumer needs and preferences, provided that they are representative of a large group of customers. Sometimes they even act as strategic partners who take an active part in the development and commercialization of products, thus having a decisive infuence on the development and design of new products (Bhidé 2008).

In Fig. 3.3, we present a more detailed version of the collaborative innovation bloc. Here we observe the vital interplay between fnal benefciaries and actors in the early- and later-stage markets of fnancing, as well as the main categories of key personnel and customers. For an innovation to have a high probability of reaching its full potential, the collaborative innovation bloc must acquire suffcient size and depth to reach critical mass, i.e., it must have suffciently large pools of each skill

15The view of collaboration between actors described in Fig. 3.2 was originally developed by Gunnar Eliasson, e.g., Eliasson (1996). See also Johansson (2010) and Elert and Henrekson (2019).

**Fig. 3.3** The collaborative innovation bloc—a detailed overview. *Source*: Elert et al. (2019)

from which actors can be recruited to fulfll each function in the collaborative team. A lack of requisite skills or an important actor category may signifcantly impede or even prevent collaborations from taking place.

As we have stated, part of what it means to be an entrepreneur is to be able to gather skills and productively combine them. This is where economic policy and the institutional framework underpinning the innovation bloc come into play. Whether an innovation bloc can emerge spontaneously, because of the actions of entrepreneurs and other actors, depends on conditions faced by the actors who could potentially comprise the collaborative innovation bloc. Some institutions, such as the rule of law and the protection of private property rights, may be relevant for all actors in the innovation bloc, while others are more specifc, e.g., the removal of bottlenecks that hinder the emergence of a suffcient mass and variety of one or several skills in the structure.

#### **3.6 Financing Expansion**

During its life cycle, a business is dependent on different sources of fnance. In Fig. 3.4, the main phases of a frm's development are described schematically. Above all, the fgure highlights how best to resolve the specifc incentive problems that exist when the entrepreneur/founder lacks the means to fnance the company's

**Fig. 3.4** Central phases in the evolution of an entrepreneurial frm. *Source*: Henrekson and Sanandaji (2016)

development alone. Silicon Valley is the region that has come the furthest in developing contracts and formal and informal institutions to deal with these incentive problems (Ohlsson 2019). In the following, we will therefore draw some inspiration from this area.

For a start-up frm based on a unique and untested idea, the risks are apparent and considerable. Even in cases where the business is a success, some time usually elapses before its products reach the market, and even more to achieve a positive cash fow.

The shared risk is seldom calculable, either by the founders or by external parties, and is thus a matter of genuine uncertainty. This is a common and particularly important problem in entrepreneurial venturing. When investing in public frms, the investor often uses historical experience as a basis for an assessment of expected outcomes. When investing in a new, innovative frm, however, the investor cannot possibly predict the outcome—not even its probability distribution—before the product is fully developed and introduced in the marketplace. Before the product exists in physical form, it is impossible to predict what technical problems will arise, or whether a market even exists. The return on investment in start-ups has an exceptionally high variance, with a very high risk that the entire investment will be lost.16

The fundamental diffculty in creating the right incentives is that it is impossible to establish agreements that cover all eventualities. When the parties cannot draft contracts that are detailed enough to cover all possible outcomes, it is important that

16Three-quarters of VC-backed entrepreneurs in the United States receive zero returns on exit (Hall and Woodward 2010)—a risk profle which, in combination with low liquidity and diffculty in diversifying, means that requirements for private return are high. It is also noteworthy that the rate of return on U.S. VC investments declined substantially for funds raised in the 2000s (Kaplan and Sensoy 2015).

ownership and control in different situations are allocated in advance between those involved. Innovative entrepreneurship is an activity where the uncertainty is particularly great, where the value of assets is relationship-specifc, and where parties with widely differing interests must cooperate. Therefore, the need is particularly great for contracts in which ownership and control are conditioned on unpredictable future outcomes.

Due to transaction costs and non-calculable risks, equity fnancing is often necessary. Debt fnancing is problematic, as frms have neither fxed assets to pledge nor a cash fow to borrow against. This means that banks have little interest in fnancing risky entrepreneurial frms. The problem of asymmetric information about a frm's potential, and the risk of excessive optimism among its entrepreneurs, also make loan fnancing more diffcult. At the same time, few founders have enough capital to fnance the company themselves up to the point where the cash fow is positive or the level of uncertainty has diminished suffciently to enable loan fnancing. Many new frms may therefore disappear prematurely due to a lack of capital for development and expansion. One attempt to solve this problem can be soft loan*s* from public bodies.

However, providing access to soft fnancing, including public risk capital that spurs entrepreneurial success, is a diffcult task and the outcome is often disappointing.17 Lerner (2020) claims that such policies may be successful if conditioned on factors such as independent governance structures, matching funds, and a careful evaluation of effects. Such elaborate policy measures are rare. One reason is that politicians may be tempted, for political reasons, to set up agencies on a regional and industry basis with the authority to issue such loans—something that entails a large number of different and unmanageable conditions, often without properly considered long-term plans.18 The most successful international experience to learn from may be that of Israel.19

Those external fnanciers who are usually most suitable for providing equity for the frst seed phase are the so-called angel investors. These are wealthy individuals with their own experience as entrepreneurs or business leaders, and who have the time, commitment, and capital to invest in promising new business ideas. Through the angel's own network, the company often also has access to additional capital and expertise.20

In the next phase of a company's development, there is more information about the viability of the business concept, which lowers the level of uncertainty. In this situation, the company also becomes interesting to those providing venture capital (VC). Like angel investors, VC frms are not only passive fnanciers, but also

17See Lerner (2009) for a survey of international research. For a Swedish overview, see Svensson (2011), Daunfeldt et al. (2014), and Sandström et al. (2019).

18 IVA (2011).

19See Avnimelech and Teubal (2006) for a description of the structure and evolution of the Israeli support system.

20For a more detailed discussion of small business fnancing by angel investors and their other contributions, see Landström (2007), Kerr et al. (2010), and Henrekson and Sanandaji (2018).

contribute to the development of new businesses and the commercialization of their ideas.21

#### *3.6.1 Stock Options Help to Build Firms*

The problem of asymmetric information is best remedied by the investor entering as a partner in the frm and thus gaining more insight into its workings. Otherwise, the investor will initially be reluctant to invest a large amount, as the information asymmetry cannot be signifcantly reduced until they have become a partner. Over time, however, uncertainty about the frm's technical and commercial potential decreases, as experience is gained and more information becomes available. Agreements have therefore been developed in the market where external investors pay out fnancial support in several rounds (staged fnancing), so that there is enough, but just enough, funding available for the business to reach a certain milestone in its development. This creates many opportunities to evaluate the results at each stage—as well as to exit the investment if the frm's performance fails to meet investor expectations.

Even if external fnanciers contribute a number of key competencies, the entrepreneur or founder is normally crucial to the frm's development for several years. Still, of course, the business can arrive at a point at which it would develop better under new management, for example if the founder's strength is in the start-up phase itself but he or she is less suited to leading a growing frm. External fnanciers will want a substantial ownership share in order to receive a substantial part of the value they expect to be created, but the ownership share should not be so large that the entrepreneur has insuffcient incentive to contribute their unique expertise. At the same time, external investors will want an opportunity to replace the founder and/or close down the frm to minimize losses if predictions about its success are not suffciently positive.

Normally, neither the entrepreneur nor his or her close associates have the skills or fnancial resources required to cope with the more capital-intensive development phase. External fnanciers must therefore quickly contribute a large amount of equity relative to what the founder can invest. This means the founder loses control of his or her frm, which weakens their incentives to contribute further to its development. Thus arises a dilemma.

The solution, which began to be used with great success in the United States in the 1980s, is *stock options*. 22 External investors take control of the frm, but the

21Hellman and Puri (2002) have shown that North American venture capitalists can infuence an entrepreneurial frm's strategy choices, for example by ensuring that start-ups pursue active personnel policies and marketing. They have also found that frms supported by VC more quickly commercialize new products. Bottazzi et al. (2004) fnd similar evidence for European VC frms.

22For more details regarding the functioning of stock options and the incentive problems they are used to solve, the reader is referred to Bengtsson and Hand (2013), Chang et al. (2015), and Cumming (2012).

founder (and other key employees) receives inexpensive stock options that guarantee they will regain substantial ownership in the future, provided that a number of stipulated "milestones" are attained. Many frms offer options with a low exercise price, similar to (free) shares. Such agreements are usually also designed with "vesting," i.e., the purchaser may only buy shares if he or she remains in the frm and continues to contribute expertise.

The option instrument is therefore an elegant way of giving the founder and other key employees with limited or zero personal wealth a share in the future value of the frm, the creation of which presupposes their participation. A well-designed options program makes the founder/entrepreneur behave as if she herself were still the owner of the project. In practice, it is diffcult to harmonize the interests of the founder and the frm by using stock options, but it is often possible to achieve a much better correspondence between the interests of the two parties than before. This solution also inhibits wage claims from those who receive the options.

#### *3.6.2 Exit Routes*

When an entrepreneurial frm's cash fow becomes more stable and predictable, the fnancial risk also becomes increasingly calculable. Then it is possible to make forecasts of future growth opportunities and proftability. Once the frm is on stable ground, it is time for early-stage fnanciers to relinquish their ownership role. Such an exit can be made in several ways. Provided that the frm has developed satisfactorily, founders and other key employees who have received options are now able to exchange these for common stock and become major owners in the frm.

A frst exit route is an initial public offering (IPO). For this to succeed, it is usually necessary, after the listing, that there be one main owner who has the motivation and ability to take responsibility and lead the frm in the medium term. An IPO can be implemented more easily if the management, normally the founder, has been granted suffcient stock options to become a major shareholder in the frm if it becomes successful. Stock options also give the founder strong incentives to remain in the frm and contribute to its development, since, in addition to securing ownership of a large part of the value created, he or she now also has the chance to become the controlling owner of a listed company.

Two other exit strategies bear mentioning. A second route is a *trade sale*, which means that the entrepreneur/founder leaves the business, but with fnancial assets that enable them to start a new business or become an angel investor and/or venture capitalist. This is often the most proftable alternative from the acquirer's perspective, because in addition to utilizing the assets they buy, the buyer also wants to prevent competing frms from gaining access to them (Cunningham et al. 2021; Norbäck and Persson 2009). A third possibility, if the frm is performing very well, is that the founder and other senior executives buy out the VC frm in a loan-fnanced management buyout (MBO), possibly in collaboration with long-term private co-fnanciers.

In many cases, the frm will not develop in line with the business plan, which may be due to the business idea having less potential, the competition being tougher than expected, or the management—usually the founder—not performing as expected. The VC frm can then take measures such as removing the management or closing down the business to recover as much as possible of their investment. In the United States, this is achieved by the VC frm owning preferred stock or having priority loans; management instead has common stocks, or options on them, which are usually worthless if the frm is closed down (Metrick and Yasuda 2011; Bengtsson and Sensoy 2011).

The fact that the venture capitalists by and large have the power to decide whether to close down the frm or replace the management team if certain milestones are not met entails a risk that they will behave opportunistically. However, there are a number of mechanisms and forms of agreement to prevent such opportunism (i.e., alleviate the hold-up problem; Black and Gilson 1998).23 These contracts are complex, which refects the fact that the market is characterized by high transaction costs and great uncertainty. Such agreements stipulate the distribution of cash fow, control over board membership and voting rights, under what conditions fnanciers have the right to liquidate the frm and how the remaining assets and other rights are distributed in such a scenario. The outcome is conditioned on the frm's performance, and stock options are consistently an important component of these agreements. An additional mechanism that protects the founder(s) from being held up by the investor is that the VC frm cares not only about its reputation for competence but also as a reliable business partner.24

In turn, the open control protects the founder(s) from being held up by investors since outside board members are unlikely to vote to replace the founder unless performance is truly inferior (Kaplan and Strömberg 2003). A reverse hold-up problem may also arise in cases where the frm is particularly dependent on the skill of the original founder(s). To mitigate this problem, it is common for VCs to include noncompete and vesting provisions that make it more expensive for the entrepreneur to leave the frm prematurely (Kaplan and Strömberg 2003).

#### **3.7 Human Capital and Academic Entrepreneurship**

We have established that entrepreneurs are important, that information is decentralized and fragmented, that a focus on "innovation systems" is too narrow, and that fnancing of entrepreneurial activities entails particular complexities. We now want to broaden the perspective to the supply of entrepreneurial skills and the incentives

23Kaplan and Strömberg (2003, 2004) analyze in detail the forms of agreement that have emerged in the United States between venture capitalists and entrepreneurs.

24Results from experimental economics suggest that making investments observable is a good way to remedy the hold-up problem as it enhances the investor's incentive to adhere to social preferences of fairness (Yang 2021).

to develop and exercise such skills productively. For individuals to acquire valuable skills, it is important to have the right incentives at all levels. We know from the United States that truly successful entrepreneurs are usually more highly educated than average, and that their success hinges on their ability to recruit competent and exceptionally motivated people to build their frms.25 Potential entrepreneurs face educational and career choices several times during their lives, not least in their youth. With the wrong incentives and unclear signals, there are many instances in which an individual risks making choices that inhibit the acquisition of the knowledge that can deliver a good fnancial return in a successful business.

Figure 3.5 outlines the main steps in the creation of a knowledge base that can be translated into commercial activity.

The frst strategic choice the individual encounters is in high school when he or she must decide whether to start gainful employment after graduation or to advance to college. Once she has opted for college, the next decision will be whether to pursue a degree in science and technology or the humanities and social sciences. After having received a bachelor's degree, the graduate must choose between fnding employment or further studies. If the latter is chosen, the subsequent choice is between a university career or leaving academia for work outside it.

Successful scientifc or technical research-based entrepreneurial activities consequently depend on academically educated and highly motivated individuals. When university professors and researchers are actively involved in spin-offs and start-ups on campus, this phenomenon is referred to as academic entrepreneurship (Shane 2009).26 In addition, there are other important sources for recruitment to scientifc and/or technically based entrepreneurship, such as the pool of individuals with an academic degree as well as people with an academic background who work in other frms. Finally, as pointed out by Arora et al. (2021), the diffusion of knowledge, breakthrough innovations, and general purpose technologies (GPTs) requires close interaction between academia and industry. Such interaction is also likely to spur university spin-offs. Currently, the trend seems to be in the opposite direction, characterized by an increased division of labor between university researchers (basic research) and corporate research (applied research).27

Academic entrepreneurship has increased substantially over the last decades (Caputo et al. 2022). For example, 3,376 university spin-offs were documented in the United States between 1980 and 2000, another 2,885 between 2001 and 2007, and 4,539 more between 2008 and 2014. These numbers probably underestimate the true extent of academic entrepreneurship since not all instances are disclosed to universities. Moreover, faculty members may start businesses that are not based on

25See Henrekson and Sanandaji (2014, 2020) and references in those studies.

26Sometimes the term "spin-out" is used instead. Some advocate using the term "spin-off" when the university retains equity, and "spin-out" when the university receives nothing (Walter et al. 2014).

27Arora et al. (2021, p. 94) conclude that although frms make greater use of scientifc knowledge, they are "less willing to produce such knowledge, preferring to shift attention and resources from upstream research to downstream development."

**Fig. 3.5** From educational choice to knowledge-based entrepreneurship. *Source*: Henrekson and Rosenberg (2001)

university intellectual property rights. This development is not confned to the United States; similar patterns can be observed in other countries (Åstebro 2016). Still, the licensing of university patents to established companies strongly dominates over spin-offs as a form of technology transfer (Åstebro et al. 2019).

U.S. universities were long seen as role models for commercializing universitybased inventions and for academic entrepreneurship. The reason for their superiority was typically attributed to the Bayh–Dole Act instituted in 1980. It transferred all intellectual property rights for inventions to the university, provided that it had funded the underlying research. This reform was originally claimed to have contributed to the overall surge in innovation in the United States (Merrill and Mazza 2010; Mowery and Sampat 2005). Others were more skeptical, arguing that the Bayh– Dole Act coincided with a number of other major policy changes said to be instrumental in improving commercialization of university-based research, notably tax reforms, increased federal resources to university research, and more fexible investment policies for pension funds (Kenney and Patton 2009; Lissoni et al. 2009).

Around ten years ago, and simultaneously as the effects of the Bayh–Dole Act became increasingly questioned in the United States, several countries decided to implement a similar intellectual property rights (IPR) regime (e.g., Germany, Belgium, Denmark, Japan, Norway, Finland, and China). These changes were introduced with the aim to increase technology transfer and innovations, thereby strengthening the competitiveness of frms in the respective country. However, according to the evaluations of these reforms, the results are rather bleak. In fact, relatively recent and remarkably consistent evidence from several countries (e.g., Denmark, Germany, and Norway) indicates that implementing a Bayh–Dole system appears to have been detrimental to technology commercialization, or, at best, have had no effect at all. Scholars in Europe thus seem to have applied for patents to the same extent as their U.S. colleagues and to interact as much with industry, despite the previous "Professor's Privilege" (where IP rights remain with the inventor in academia). Czarnitzki et al. (2015) fnd that the volume of university citationweighed patents decreased by 27% (19% unweighted) in Belgium. In the most extreme case of Norway, there was an approximate 50% decline in the rate of new venture creation and patenting by university-based researchers after the reform. The quality of university start-ups and patents also appears to have declined (Hvide and Jones 2018).

Granting intellectual property rights to the university may work in the United States where universities are generally independent institutions that operate in a highly competitive environment. By contrast, in most European countries, universities are part of the government sector and less exposed to competition. This makes it far less likely that universities in Europe will do their utmost to make sure that the intellectual property rights they have been granted will be exploited commercially (Henrekson and Rosenberg 2001). Here is yet another example of the diffculties encountered when adopting institutions from other countries.

Figure 3.5 shows that several links must be present and considered suffciently attractive for the right persons to create an environment where scientifc researchbased entrepreneurship can fourish:

The overarching condition is that it must be proftable to acquire productive knowledge and to use it intensively. Income taxes, pay differences, and a wellfunctioning service sector that enables specialization are important components. Social insurance systems are also crucial—they must not weaken incentives to change jobs but rather offer an equivalent safety net under this transfer. In addition, they should not entail a high opportunity cost in the form of lost pension rights and other amenities when one switches to an employer who offers higher expected social value creation. The tax system and social insurance system interact, and their effects need to be jointly analyzed. In Chap. 4, we will explore how this interaction manifests in practice in the Swedish case.

#### **3.8 Dynamics in Tax-Financed Welfare Services**

Innovations and entrepreneurship are essential for growth and development not only in the goods-producing sector. They play at least as important a role in the service sector, in order to develop new services, streamline organizations, and reduce costs. How service production is organized—not least how competition works in these markets—is of great importance in this respect. Regulations, procurement, and monitoring affect the impetus and opportunities for entrepreneurs to attempt new ways of doing things and to experiment and innovate in the service sector.

The leading European welfare states made a strategic choice in the twentieth century: to rely primarily on tax fnancing and government production of healthcare, education, and social care. The public sector was then still small, the overall tax burden was low, and these services were relatively inexpensive. Welfare services were considered too important to the cohesion of society to be kept under government control and not be subject to the vagaries of market forces. Distributional aspects and positive externalities could be invoked to justify both government production and fnancing, especially in education and healthcare. At the time, neither the effciency of government production, nor whether taxes were the most appropriate form of fnance, were discussed.

As Table 3.2 shows, government spending as a share of GDP on education and care services is now sizable in major OECD countries. Cross-country variation around the average of 14.3% is surprisingly small, despite sometimes sizable differences within subcategories. There is also large additional private spending on several services, notably in the United States, where total spending on education and care is well above 25% of GDP.

As incomes rise, the demand for services such as education, healthcare, and social care tends to rise even faster, i.e., the income elasticity of demand is larger than one. At the same time, these services are particularly labor-intensive, and in most cases, it is not possible to reduce staff without reducing quality. Machines

**Table 3.2** Government spending on education and care as a percentage of GDP in selected OECD countries (latest available year)

*Source*: OECD

cannot replace people in this area as they can in manufacturing. This makes it more diffcult to achieve increases in productivity, although there are exceptions (mainly due to IT and development of artifcial intelligence, AI). The relative cost of welfare services therefore tends to rise, especially if citizens demand that quality be raised in tandem with real incomes. Healthcare, education, and social care are therefore becoming increasingly expensive in comparison to food, travel, or mobile phones. We have already mentioned Baumol's Cost Disease.28 However, there is some potential for rationalization due to the fact that a larger proportion of total working hours can be devoted to producing the service (teaching, patient care, and the like) if activities are organized effciently.

In a modern knowledge society, education becomes increasingly important. Both the quality of education and the time spent pursuing it need to increase. With rising incomes, the expectations of quality in child and elderly care are also heightened, at the same time as demographic development further increases the demand for the latter. Increased incomes create a rapidly increasing demand for healthcare, while technological advances make it possible to offer increasingly more treatments and interventions for conditions that were previously untreatable. New medical breakthroughs (more powerful medicines, joint replacements, keyhole surgeries, etc.) can entail lower costs for specifc procedures. At the same time, however, demand rises for these services as they become available to more people—while the demand for quality rises inexorably. The overall effect is increased costs (Smith et al. 2022).29

This combination of rising costs and the fact that most Western countries have reached a point at which further tax increases are not possible presents a signifcant challenge. There is only one solution to this dilemma: innovation. To this end, competition needs to be allowed between government and private (non-proft and forproft) providers by establishing the so-called quasi-markets (Le Grand 2009), where consumer choice is combined with government fnancing. However, in order for quasi-markets to fulfll the potential of their innovative promise, the regulatory framework must be properly designed (and continually revised). Currently, the production of welfare services is surrounded by a wide range of restrictions—on funding, procurement, quality, and governance—which severely limits the framework for what can be done. Several of these restrictions need to be recast to allow for more entrepreneurship; at the same time, competence in monitoring and governing these services requires improvement (see Chap. 4).

28Named after William Baumol, who pointed out that a string quartet cannot increase its productivity by playing Beethoven faster. On the other hand, technological advances, for example in the distribution of the string quartet's performances—formerly radio and records, now downloads or streaming—may mean that increasingly more people have the opportunity to listen to the performance at low or even no cost.

29For an extensive discussion of this issue, see Eliasson (2009).

#### **3.9 Urbanization, Agglomeration, and Innovation**

How we live, work, and travel have a crucial, and sometimes overlooked, role among the mechanisms for disseminating knowledge. We therefore wish to conclude this chapter with a section on urbanization, agglomeration, and regional labor markets—factors that are becoming increasingly important driving forces for societies that aspire to be entrepreneurial and innovative.

Since the early 1990s, urbanization has gained momentum in Sweden and other nations in the Western world. Historically, population growth has been concentrated in the larger cities, while it has declined in many medium-sized towns. In the OECD, half of the population live in cities, while roughly one-quarter live in towns and semi-dense areas and one-quarter in rural areas (OECD 2022).30 The share of the population living in cities is expected to continue to increase. In 2000, 84% of the Swedish population lived in urban areas (defned as towns with at least 200 inhabitants), which had increased to 88% in 2020. Even though population growth seems to have levelled out in some cities, notably Stockholm, at the municipality level growth continues in all the larger cities in Sweden.31 Most forecasts indicate that this trend will continue, even though the current shift towards a larger share of employees working remotely at least part of the week may alter previous forecasts.

The main reason for urbanization is that higher population density provides not only economic benefts but also social and living amenities. Specialization and increased division of labor is one source of prosperity and higher wages, often referred to as the urban premium. Until the early 1970s, specialization and rising prosperity were primarily driven by increased standardization and mass production, aided by technology and specialized capital equipment. In step with the growth of the service sector, digitalization, and increased specialization, production of services is becoming the most important source of job creation and development, often concentrated to cities.32

In any event, the service sector in all developed industrial countries is today signifcantly larger than the goods-producing sector. At the same time, the boundaries between the various sectors have become more fuid. Physical products contain components of services to an increasing extent, while many services are now produced in industrial processes. A customer who buys a truck from Scania or Volvo,

30Cities are defned as local units where at least half of the population lives in clusters of densely populated grid cells with at least 50,000 inhabitants plus adjacent local units with high levels of commuting (travel-to-work fows) towards the cities.

31 In 2021, only one of the 50 largest municipalities in Sweden had any sizable population decline (≈ 0.5%).

32The production of hardware also continues to grow through new advanced implementation of automation, robotization, and 3D technologies. A parallel development that has recently intensifed revolves around new and more sophisticated versions of artifcial intelligence (AI) and machine learning (e.g., Open AI's GPT4 and Google's Bard). However, whether these technological developments will result in a net loss of jobs is an open question, as previous alarmist predictions have so far not materialized (Frey and Osborne 2013; Arntz et al. 2019; Frey 2020).

or for that matter a Tesla, not only buys a vehicle but a transport service, including repairs and software that are continually updated. Traditional service frms such as banks and insurers conduct their business using powerful computers, just as in manufacturing.

#### *3.9.1 Agglomerations and Cluster Formation*

Increased specialization in the production of services does not have to mean that an individual's tasks become simplifed or more monotonous. On the contrary, the work can instead be characterized by more collaboration, continuous skill development, and high fexibility. Densely populated environments then become attractive, partly because they provide entrepreneurial opportunity due to knowledge fows and proximity to markets and customers. They also become attractive because clusters tend to emerge in dense, agglomerated areas where companies of a similar nature can collaborate, compete, and learn from each other—and beneft from the dynamic labor market for specialists typical for such clusters.33

There is an extensive literature on existing clusters and agglomeration forces. Normally these are categorized as either Marshallian or Jacobian types of agglomerations, related to whether agglomeration effects occur within an industry (intraindustry) or are spread across industries (interindustry). The underlying mechanisms refer to the type and extent of spillovers, which are categorized as either knowledge or pecuniary spillovers. The latter refers to different types of linkages predominantly between customers and suppliers of goods or services. Some of these issues are more peripheral to our analysis, e.g., the causes and effects of agglomeration in a broader sense.34

Our main focus is how clusters and agglomerations infuence innovations associated with different types of microlevel interactions and spillovers. This is a dimension of clusters and agglomeration where research is relatively scarce (Combes and Gobillon 2015). There are some exceptions, such as Carlino and Kerr (2016), who also stress the importance of pursuing more research covering this perspective. Using a spatial panel data analysis, Kosfeld and Mitze (2023) fnd that R&Dintensive regional clusters in Germany have contributed to higher productivity within the region. They also conclude that it is not cluster diversity that matters for productivity growth but rather cluster strength. However, they did not use specifc innovation data.

33Agglomeration means that similar or related economic activities by frms and other institutions, interconnected through various channels, are located in more or less immediate geographical proximity to each other. The defnition of clusters is overlapping, even though clusters may refer to a more distinct industry or economic activity.

34These broader issues are thoroughly surveyed by, for instance, Combes and Gobillon (2015) and Hennig et al. (2016).

The improved availability of microlevel data that allows the identifcation of inventors, mobility, and networks has expanded the possibilities for such research. One crucial issue that deserves increased attention concerns the resilience and longevity of cores of innovation located in clusters, not least since new clusters emerge that compete with those already in existence. In the United States, innovation centers have shifted between locations such as Austin, Boston, Detroit, and Silicon Valley. In recent decades, Tel Aviv and Bangalore have also emerged as strong innovation nodes.

Sorenson (2018) addresses this issue from a different angle. He fnds that entrepreneurial activity and innovation are strongly embedded in socially and spatially bounded relationships. By combining insights from sociology, economic geography, and economics, he challenges some of the established views on the microeconomic foundations of spatial formations, knowledge diffusion, and interactions between economic agents. Instead, he emphasizes how more soft ties based on family and the individual's established networks infuence location and agglomerations.35

Overall, policymakers need to be better assisted by research to understand how clusters and agglomerations develop and how policy can strengthen both agglomeration and innovation (Carlino and Kerr 2016). This is a complex task, spanning several policy areas, where there are obvious knowledge gaps. However, these knowledge gaps have not stopped governments from spending billions of dollars in their attempts to promote innovative clusters.

An attempt to provide some insight into the process of emerging clusters was provided by Braunerhjelm and Feldman (2006). They analyzed whether clusters emerge by coincidence or as a result of deliberate policy efforts, and the extent to which entrepreneurs could infuence policy design. They found, that, to a great extent, these can be attributed to chance and entrepreneurial initiative, but after this initial phase, policy has generally been crucial where entrepreneurs also contributed to its design. For instance, there were initially many potential "Hollywoods." That Hollywood became Hollywood was due not only to the climate but also to the fact that policies adapted to the flm industry's needs; the government did not reject the industry as "immoral" but rather encouraged it.

Another example is Israel, which has benefted from the particular combination of a high-quality education system, the immigration of skilled engineers from Eastern Europe, and access to American venture capital. In Israel, several attempts were made to establish a high-tech sector; the big boost came only when it was realized that this required both a knowledge platform and entrepreneurial skills, which

35As a case in point: When William Shockley founded his frm in Mountain View, California instead of in New Jersey, where his former employer Bell Labs was located, he did so not because he aimed to create something like Silicon Valley but because he was nostalgic about his boyhood and wanted to move closer to his mother who suffered from failing health. Furthermore, his failures as a boss were not intended to usher in a host of spin-outs by "the treacherous eight" and the founding of the broader web of collaborative innovation blocs currently known as Silicon Valley (Klepper 2016, pp. 114–120).

generated a supply of ideas (deal fow) that was combined with competent venture capital. The state played a crucial role in building a venture capital market, enlisting the assistance of private investors early in this process.36

Furthermore, as shown by Henrekson et al. (2021) in a study of the emergence of the Silicon Valley venture capital model and the Hollywood flm industry, specialized institutions that regulate these entrepreneurial ecosystems were not designed by policymakers. Instead, they emerged through actions by business entrepreneurs. Thus, Schumpeterian entrepreneurs not only created new companies; they also created new institutions as an integral part of the restructuring process. At times, efforts by identifable entrepreneurs were crucial, while in other instances institutional change resulted from a Hayekian process of emergence fueled by the efforts of business entrepreneurs.

In general terms, the benefts of agglomeration and dense areas can be summarized as follows:

36See Braunerhjelm and Feldman (2006) for a cross-country comparative analysis of emerging clusters in biotech as well as in information and communication technologies (ICT).

However, there are also forces working in the opposite direction. The advances made in digital technologies such as artifcial intelligence and advanced machine learning may lead to the demise of advantages related to physical proximity. Still, there is a long way to go before agglomerated and dense areas more generally can be replaced by more remote systems. Production costs will therefore vary with population density.37

There are thus strong forces that propel agglomeration and the co-location of frms/employers and individuals/employees. Every time a new job is created in the competitive sector, more jobs are created in the local service sector. The multiplier effect stems from rising income, which generates demand for salon services, restaurant visits, medical care, and so on. Successes in the competitive sector thus create more jobs in the local service sector. Based on U.S. data, Moretti (2010) fnds that every new job in the competitive sector in a city generates 1.6 new jobs in the service sector in the same city. The higher the skill level, the greater the ratio, i.e., an increase in income generates correspondingly higher and more extensive knowledge spillovers. Moretti and Thulin (2013) conducted a similar study for Sweden and found the same multiplier effect here as well.38

#### **3.10 In Sum**

In this chapter, we have presented some of the necessary institutions and conditions for innovative activities to take place, such as the rule of law and the security of private property rights. We have also surveyed previous research efforts to identify institutional frameworks that are intended to govern innovations, notably national innovation systems and their "progeny," national systems of entrepreneurship and entrepreneurial ecosystem approaches. While these system approaches give valuable insights regarding the shaping and understanding of the innovation landscape, we argue that their microeconomic foundation needs to be reinforced. Finally, we addressed a number of key areas required to promote innovation and entrepreneurship, such as the fnancial market, access to human capital, the organization and production of welfare services, and the importance of dense and knowledgeintensive areas. One important message from this chapter is that we should not be afraid of large, expanding cities. In the next chapter, we will focus more intently on the details in designing policies required to encourage and stimulate innovative endeavors.

37 Jansson (2014) shows that each visit to a health center costs as much as fve to ten times more in upper Norrland than in a medium-sized city such as Linköping. In the same way, the cost per capita for roads, electricity networks, sewage systems, waste management, and other infrastructure will be considerably lower in dense environments with a higher degree of utilization.

38 If Stockholm is included as a separate region, the multiplier effect is exceptionally large—more than three. High-tech industries are associated with higher multiplier effects.

#### **References**

———. 2004. "Characteristics, Contracts, and Actions: Evidence from Venture Capital Analyses." *Journal of Finance* 59(5): 2177–2210.

———. 2024. "Tax Incentives as an Alternative to R&D Subsidies." In *Moonshots and the New Industrial Policy: Questioning the Mission Economy*, ed. Magnus Henrekson, Christian Sandström, and Mikael Stenkula, forthcoming. Cham: Springer.

Swedish Competition Authority. 2020. *Siffror och fakta om offentlig upphandling*. Stockholm: Swedish Competition Authority.

**Open Access** This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

## **Chapter 4 Policies to Stimulate Innovation and Entrepreneurship**

Most advanced industrialized countries today justify their innovation policies on the basis of the dominant knowledge-based growth paradigm—primarily investment in R&D and education, as we saw in Chap. 2. However, in terms of how growth policy should be formulated, this provides an incomplete guide which even borders on the misleading. The reason behind this misguided thinking is simplistic assumptions, both about how an economy functions and about the innovation process itself. Innovation is still seen as an exogenous force that can be stimulated through government funding targeting R&D, start-ups, and small businesses, which will then fuel higher growth and increased prosperity.

We claim that this line of reasoning is also subject to debate in the specifc context we address in at least two respects (Frydman et al. 2019). First, given that we seek to explain the causes of economic growth, a deeper causal understanding is required. Second, the adequacy and precision of policy proposals hinge on a good causal understanding of the growth process and its microeconomic foundations. Innovation is an intricate and complex process involving a multitude of actors with complementary competencies. The willingness to handle uncertainty is key, a feature often attributed to the entrepreneur, but it also involves other important agents in an innovation bloc. Thus, to stimulate innovative processes, policies must encourage risk-taking and increase the willingness of agents to act without certainty of success. Since uncertainty is genuine, there will be failures, and these will negatively infuence those who have been engaged in innovative endeavors. The policymaker can cushion such failures to some extent but, perhaps more importantly, incentivize innovation activities by, for instance, maintaining taxes at reasonable levels should the attempted venture prove successful.

Given that the group of countries doing cutting-edge innovation of great commercial value is no longer restricted to wealthy industrialized countries, this task becomes even more important for the policymaker. The former planned economies have become market economies, millions of new engineers are being herded through universities in China and India, and considerable fortunes are being made thanks to

P. Braunerhjelm, M. Henrekson, *Unleashing Society's Innovative Capacity*, International Studies in Entrepreneurship 55, https://doi.org/10.1007/978-3-031-42756-5\_4

new business models and rapid technological development. Sophisticated new knowledge is being created all over the world and spread through new channels at a furious pace. Even small frms can, with the help of modern information technology, become internationalized and make use of research expertise on the other side of the globe. Still, the so-called born globals are a rare phenomenon and entail considerable risks (Braunerhjelm and Halldin 2019; Ferguson et al. 2021).

Nevertheless, increased trade (including internal trade within frms), rising investment between countries, and increasingly intensive exchanges between universities are some of the mechanisms for disseminating information and knowledge. Economies are linked via sophisticated Internet-based tools that promote crossborder networks and collaborations—as well as commercialization. The result is intensifed global competition, making it increasingly diffcult to obtain a high return over a longer period in the form of high relative prices for advanced products where Swedish companies have traditionally held market power. Some of these links have, however, become weaker due to the present tendencies towards deglobalization and increased geopolitical tensions.

For a small country like Sweden, the frst task in this new landscape will be to *build a globally competitive body of knowledge* based on domestic education and research efforts but also on knowledge acquired from abroad. The second task is to *create effective mechanisms that disseminate knowledge and transform it into societal benefts*, i.e., innovations that lead to new and growing businesses, rising investment, higher value-added and increased employment. Maximum leverage from policy initiatives to boost innovation and entrepreneurship is achieved when such measures are *coordinated* across different policy areas. At the same time, we are well aware that it is not politically feasible to implement all proposed measures simultaneously; whether to implement a specifc policy must be weighed against societal interests other than boosting innovation and entrepreneurship.

Innovation presupposes a long-term perspective, trust, and transparent systems. Existing institutions and regulations strongly infuence the opportunities for entrepreneurs to develop and commercialize innovations. In this chapter and the subsequent one, which deals exclusively with taxation, we review a number of policies and measures that can promote innovation. We will describe in some detail the changes in tax codes, regulation, education, and other policy areas that we consider most important. In the concluding Chap. 6, we will then summarize the proposed measures in the form of an innovation policy framework, inspired by the frameworks for monetary and fscal policy introduced after the 1990s crisis, which created long-term predictability in macroeconomic policy.

#### **4.1 The Need for a Broad Strategy**

Our approach is much broader than the one that dominates the daily political debate on innovation and innovation policy, which still largely revolves around support for R&D investment and capital for start-ups. As discussed in Chap. 3, some basic institutional conditions must be in place for other policies to be effective. Most prominent are the enforcement of the rule of law such that contracts are honored, property rights are well-defned and secure, and corruption is minimal. According to Transparency International, Sweden ranked among the top fve countries with the lowest level of corruption in 2022.1 However, the Swedish score has continually declined since 2012, indicating that corruption is on the rise. According to the ranking of the Heritage Foundation Index of Economic Freedom, Sweden is also among the top global performers, ranked at tenth place out of 163 countries in 2022. The organization states in particular that "the transparent and effcient regulatory and legal environment encourages robust entrepreneurial activity."2 Hence, from an international perspective, Sweden seems well-positioned when it comes to the most basic prerequisites for the emergence of an environment conducive to innovation. Nevertheless, these are merely necessary conditions that must be fulflled to foster innovation. In this chapter, we will present what we deem to be the most important of the remaining and critically important building blocks of an effective innovation policy, excluding tax policy, which will be discussed in the subsequent chapter.

#### *4.1.1 Subsidies to R&D?*

*"Innovation strategies"*—in other words, R&D investment and seed fnancing—are often presented as the solution to future challenges. The OECD launched its innovation strategy in 2010 (OECD 2010), which was updated in 2015 (OECD 2015), and the so-called *Innovation Union* was one of the fagship initiatives in the European Union's Europe 2020 Strategy to strengthen the EU's global competitiveness. The most recent framework program to bolster the EU's R&D, innovation, and competitiveness—Horizon Europe—stretches from 2021 to 2027 and has a budget of EUR 95.5 billion. It builds on three pillars—excellent science, global challenges, and industrial competitiveness—and takes a mission-oriented approach.3

These ambitions are commendable, and the bar is set high. However, the arsenal of means to achieve these goals is not described in suffcient detail. Policymakers often run into obstacles when translating general principles into practical proposals. Strategies developed by international organizations seldom become particularly innovative. Member countries' ministries of industry all too often merely impose their own blueprint on the general measures prescribed, especially if these are kept at a general level, such as "support for R&D"—a proposal that virtually everyone

1 https://www.transparency.org/en/cpi/2021/index/swe

2 https://www.heritage.org/index/country/sweden

3For details, see https://www.catalyze-group.com/horizon-europe-2023/?utm\_ campaign=Horizon%20Europe&utm\_term=Horizon%20Europe%20 funding&gclid=Cj0KCQjwn9CgBhDjARIsAD15h0AaRKeKJVsf7n53IpZCHNzgvVIasoBbgjay JUAqfOkjaCQuPnwkqYaAksEEALw\_wcB

will endorse. But the path to success resides in the specifc and often unique competencies and conditions that are best defned on a much more disaggregated level, information which must be translated into concrete proposals covering a wide range of policy areas.

As we have already discussed, there are a number of evaluations of the effects of R&D support. Table 4.1 summarizes the advantages and disadvantages of subsidies and tax relief, respectively.

In this comparison, tax reliefs are socioeconomically preferable to direct subsidies. Most international studies also identify a positive effect, albeit the magnitude differs and crowding-out effects are present (Hall and Van Reenen 2000; Hovdan et al. 2023). In particular, recent research provides evidence that effectiveness differs sharply across frms of different sizes and between countries, depending on the specifc institutional context in which businesses operate. There are also signs that frms act tactically by increasing the level of R&D just enough to achieve maximum state support. When it comes to large frms—particularly those with multinational operations—they tend to relocate R&D activity to locations with greater R&D tax relief, implying R&D tax incentives could raise R&D domestically but at the expense of R&D in other locations. Hence, tax incentives work as a beggar-thyneighbor instrument, which casts doubt on its ability to increase R&D globally (Knoll et al. 2021). More generally, R&D tax incentives and subsidies seem more effcient for smaller frms (Galindo-Rueda et al. 2020). Further, the OECD (2020) concludes that there are vast differences in returns to companies of different sizes, with most bang-for-the-buck for the smallest frm cohorts. In addition, tax incentives seem better suited for supporting R&D projects closer to the market, while direct government funding—such as grants and R&D procurement—is more effcient when targeting basic research.

The Swedish experience is mixed. In the 1970s, there was a targeted R&D tax relief scheme that allowed frms to deduct more than 100% of their R&D spending. However, the tax relief accrued long after the spending was incurred, which contributed to the ineffciency of the system. Since the subsidy reduced tax revenues

**Table 4.1** Effects of R&D support

*Source*: Guellec and van Pottelsberghe (2003) and OECD (2010)

without yielding the intended results, it was repealed. Later evaluations have shown that Sweden was among the countries with the highest tax expenditure related to R&D.4 In 2014, a new subsidy was introduced that targeted employees working with R&D. Initially, payroll taxes on frms' R&D staff could be reduced by ten percent of wage costs before taxes with a ceiling of SEK 230,000 per month. This design gave the subsidy a small frm angle, i.e., the relative beneft was largest for smaller frms. Effective from July 1, 2023, the maximum payroll tax reduction for a frm amounts to SEK 1.5 million per month, designed as a reduction of the payroll tax rate by almost two-thirds for R&D workers.5 Overall, evaluation of the subsidy fnds signifcant positive effects on the number and share of scientists. Moreover, the treatment effect of the subsidy does not differ across frms by size or debt ratio but seems to be somewhat higher for labor-intensive frms (Stavlöt and Svensson 2022).

The European Union does not allow general state aid within the internal market.6 Nevertheless, a plethora of national R&D subsidies exists. The reason is that the EU's regulatory framework is more permissible towards supporting R&D as a means of increasing productivity and growth. As stated above, this form of competition is diffcult to avoid completely—virtually all countries engage in it (as do individual states in the United States). We therefore arrive somewhat reluctantly at the conclusion that limited subsidies for R&D can be an innovation policy tool. But our main message is that innovation policy should be well-balanced across different policy areas, where subsidies might be one component but requires careful evaluations before being implemented, and the strategy as a whole should be much broader.

#### *4.1.2 Not Only Start-Ups or Small Businesses*

The emergence of new and growing frms is crucial for the transformation of R&D into production and prosperity. This presupposes favorable conditions for innovative entrepreneurship. Policies to promote it have all too often been equated with measures that favor small and new businesses.7 Our analysis in Chaps. 2 and 3 makes clear that such an approach is too narrow; instead, the focus should be on *more general measures* that facilitate the dynamic transformation of as many frms as possible, and in every sector. These broad-based measures should propel *the*

4See Hall and Van Reenen (2000), Table 1.

5Government Bill 2022/23:79. The payroll tax is reduced by 19.59 percentage points (from 31.42 to 11.83%). In practice, a maximum total reduction for all R&D staff of SEK 1.5 million per month (roughly USD 150,000) means that with a typical monthly salary for an R&D worker, the rebate can apply to as many as 120 employees.

6As mentioned above, EU's state aid rules have been partly abolished, partly modifed, since the beginning of the COVID-19 pandemic.

7Often referred to as SME policy. See, for example, Lundström and Stevenson (2005).

*economy as a whole* towards a new competitive landscape by encouraging entrepreneurial experimentation and business growth *throughout* the economy.

Consequently, policy should encourage renewal and growth, regardless of whether development takes place in start-ups or incumbent frms, large or small. New entrepreneurial initiatives exert competitive pressure on other frms, which requires adjustment and rationalization or, for those entities that fail to cope, closure. When the goal of policy is to facilitate the rapid growth of high-quality frms, the focus shifts from encouraging the establishment of new ones to creating a coherent framework that affects a large number of policy areas and basic institutions. Such a policy should encourage (Hölzl 2010, p. 191):

a heterogeneous pool of entrepreneurs to generate new ideas and ventures, as well as mobilize productive resources by enhancing a society's educated workforce and capacity to generate new knowledge. … it should also provide an undistorted process of competitive selection, in which small frms face equal opportunities and the market spurs the reallocation of resources from exiting frms with low performance to fast growing frms with high performance.

The main differences between small business policy and entrepreneurship policy are summarized in Fig. 4.1. Entrepreneurship policy facilitates productive entrepreneurship activities. Whether such activities involve a high or low proportion of selfemployed individuals or small frms is of minor importance. Instead, the policy focuses on more qualitative aspects, favoring entrepreneurial frms with the potential to become high impact entrepreneurship (HIE).

#### *4.1.3 The Importance of High-Growth Firms*

When companies are compared, it turns out—unsurprisingly—that there are large differences in terms of age, size, growth ambitions, proftability, and growth rate. The small business researcher David Birch coined the term "gazelles" 30 years ago to denote the small group of frms that create the majority of all new jobs in the economy.

In later studies, a distinction has been made between gazelles and high-growth frms (Petersen and Ahmad 2007). High-growth frms are defned as frms with an average annualized growth greater than 20% over a three-year period, where growth

**Fig. 4.1** Small business policy versus entrepreneurship policy

is measured either in terms of employment or turnover.  The defnitions also include the qualifcation that enterprises should have at least ten employees at the start of any observation period.

In their reviews of available studies on high-growth frms, Henrekson and Johansson (2010) and Coad et al. (2014) found that:

Young frms that survive have higher productivity and grow more rapidly than more mature ones, suggesting an "up or out" dynamic. Firms have higher productivity *and* grow more rapidly than incumbents or they fail. Thus, the evidence suggests that high-growth frms, especially those that grow rapidly when young and small, are instrumental to economic growth (Haltiwanger et al. 2013; Heyman et al. 2019).8

Heyman et al. (2021) have examined how the Swedish economy managed during three major crises since the 1990s: the real estate/bank crisis 1991–1994, the IT-bubble 2001–2003, and the fnancial market crisis 2008–2009. Their overall conclusion is that the restructuring of the Swedish economy was relatively smooth, particularly during the two latter crises. Some companies shrunk, some went bankrupt, while others were started. Moreover, the reallocation of labor was quite effcient. The authors attribute this ability to cope with crises to policies that have facilitated mergers and acquisitions of frms, good opportunities for laid-off workers to acquire relevant competencies through retraining programs, and improved channeling of savings to new and young frms. Firms of different types and sizes chose different strategies to adjust to a crisis, but by and large the economy jumped back to its pre-crisis path relatively quickly. Heyman et al. argue that it is preferable to strengthen the crisis resilience of businesses through proactive policies that foster and encourage dynamics rather than providing governmental support when a crisis strikes. However, there is room for improvement regarding insolvency institutions, i.e., transfer of ownership is crucial as are the possibilities for new and young frms to exploit market opportunities and absorb dismissed labor.

8Caballero (2007) estimates that half of aggregate productivity growth results from the reallocation of resources from low- to high-productivity frms *within* an industry and that roughly half of that emanates from start-ups and closures.

One important conclusion from this research is that innovation and entrepreneurship policy should focus on general measures. Instead of focusing exclusively on start-ups, the objective is to create an environment facilitating the further development of potentially fast-growing frms irrespective of size, age, and industry. This means a policy that rewards education, knowledge transfer, competition, entrepreneurship, experimentation, and risk-taking. This is what characterized Swedish policy during the "golden" period 1870–1913 when many of Sweden's large, still extant, multinational frms were founded—companies such as Atlas Copco, Ericsson, Electrolux (a merger of two frms founded in that period), Ericsson, SKF, Asea (now ABB), Scania, and Astra (now AstraZeneca). Moreover, frms grew rapidly and became highly internationalized. These large, innovative frms became important "anchors" and nodes for further industrial development in the form of spin-offs and as a breeding ground for other new and growing frms. However, as described by Bornefalk (2017), after World War II, the Swedish economy gradually became more regulated, interventionist, and sclerotic. As a result, no new large frms emerged and remained domiciled in Sweden after the 1960s. Instead, exceptional entrepreneurs emigrated to countries with more business-friendly institutions (notably IKEA's Ingvar Kamprad and Tetra Pak's Ruben Rausing). Economic dynamism stalled and growth was impaired for several decades.

The structural problems of the Swedish economy became increasingly apparent during the 1980s, and these foibles eventually triggered a market-oriented reform process lasting for roughly 25 years, from the mid-1980s until 2010. This set off a wave of entrepreneurial effort, where numerous new frms attained considerable market value, although there are no examples of such frms achieving global prominence rivalling the level attained by several businesses established before World War I. Instead, several of these frms have been acquired by foreign frms and investors and expanded from bases outside of Sweden. Thus, even if Sweden has become something of a start-up nation, it is far from what could be labelled a scale-up nation. This poses a potential threat, not only to Sweden's future industrial base but also to its future welfare and prosperity. Large growing frms are an essential part of a competitive industrial setting based on heterogenous and complementary competencies. In the remainder of this chapter, we will discuss the most important building blocks of a broad innovation policy (except for tax policy, which we will discuss in the next chapter).

#### **4.2 The Education System**

As mentioned, our strategy has two main pillars: frst, to build knowledge and ensure that it reaches a critical mass, and second, to disseminate and commercialize knowledge. A natural starting point for policy proposals is the frst pillar: knowledge building. Obviously, a precondition for knowledge dissemination is that citizens are endowed with useful knowledge and have the ability to absorb knowledge held by others, i.e., absorption capacity is important (Cohen and Levinthal 1990). As we will see in the next section, the estimated effects of school quality on national economic performance are sizable.

#### *4.2.1 Test Results and National Economic Performance*

What explains economic growth and thus social welfare at the country level? Over time, it became increasingly clear that the share of GDP used for capital investment could explain only a small share of per capita growth, perhaps as little as 10–20 percent. In the 1980s, endogenous growth theory brought human capital to the fore. Human capital is the stock of habits, knowledge, and social and personality attributes (including creativity) constituting the ability to perform labor to produce economic value.

A problem arose when policymakers began to equate human capital with quantitative measures of formal schooling. Large cross-country differences in the average scores in internationally comparable tests among students with the same number of school years provide compelling evidence that, in fact, the quality of the educational system matters.9

Studies focusing on the effect of the average number of years of formal schooling across countries have not been able to establish any robust effect on economic growth.10 In contrast, empirical research shows a strong positive relationship between the results of internationally comparable tests and economic growth. Moreover, the estimated effect is large. Hanushek and Woessmann (2015) estimated the effect for 50 countries during the period 1960–2000, where cognitive skill is measured as the average score on all international test 1964 to 2003 (notably TIMSS and PISA) in math and science. They fnd that an increase of one standard deviation in the average test results in mathematics and science, i.e., 100 points, "is associated with approximately two percentage points higher annual growth in GDP per capita."11 Thus, the fact that the quality of the educational system is what matters rather than the duration of schooling per se is crucial for economic growth. More precisely, the purpose of a high-quality school system is not simply to impart substantial knowledge to students but also to instill noncognitive skills such as

9 International assessments of knowledge and skills in certain subjects began to be developed in the early 1960s. Since the mid-1990s, there have been comparable tests for a large number of countries in mathematics and science, and, since the turn of the millennium, tests to measure levels and trends in students' reading comprehension as well. The two most important tests are the *Trends in International Mathematics and Science Study* (TIMSS), and the *Programme for International Student Assessment* (PISA) of mathematics, science, and reading. TIMSS has been repeated every four years since 1995, and PISA every three years since 2000. TIMSS is conducted in grades 4 and 8, as well as at the secondary level (for a select group), and PISA is conducted with 15-year-old students.

10Krueger and Lindahl (2001) and Gennaioli et al. (2013).

11Hanushek and Woessmann (2015, p. 40). To give an example: the average result in Mathematics 2015 was almost exactly 100 points higher in Sweden than in Oman.