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. 2.7k Downloads.AbstractWhile entrepreneurship researchers agree that institutions ‘matter’ for entrepreneurship, they also have a rather encompassing understanding of institutions as almost any external factor that influences entrepreneurship. Ultimately, this literature thus comes up with a long list of institutional factors that may explain entrepreneurial differences between countries. But which institutions are most influential? How do these institutions relate to different types of entrepreneurship? And to what extent are institutions complementary to each other in the way they sustain different entrepreneurship types? The literature on ‘Varieties-of-Capitalism’ (VoC) offers a parsimonious theoretical framework to address these questions.
Based on the VoC literature, we theoretically derive a consistent set of institutional indicators that can explain differences in entrepreneurship types between countries. Based on principal component and cluster analyses, we illustrate how 21 Western developed economies cluster around four distinct institutional settings. Furthermore, we use simple OLS regressions to show how these institutional constellations are related to different types of entrepreneurship. Download free software bollettini postali pdf da compilare dietetico.
We conclude that four different ‘Varieties of Entrepreneurship’ can be identified across the Western world. The main implication of our findings is that a ‘perfect’ institutional constellation, equally facilitating different types of entrepreneurship, does not exist. Policy-makers seeking to stimulate entrepreneurship are thus faced with the trade-off of targeting policy reforms to that entrepreneurship type they intend to promote—at the expense of other types of entrepreneurship and the broader societal consequences such reforms will have. Having identified those institutions that are presumably most influential for entrepreneurship, the question arises as to how these institutions relate to each other. Again, the VoC literature offers advice by arguing that institutions are complementary, so that the presence of one increases the efficiency of the other (Hall and Soskice: 17).
Amable (: 6) offers a useful example: “Flexible labour markets may be more efficient when financial markets allow for a rapid mobilization of resources and creation of new businesses that in return sustain labour demand. Conversely, a more stable employment relationship may be more efficient when a specific pattern of monitoring is implemented in the context of a close relationship between a firm and a bank.” Translating the idea of institutional complementarity to the development of different forms of entrepreneurship, we expect that. CMEsLMEsEMEsMMEsAustriaIrelandCzech RepublicFranceBelgiumThe UKHungaryItalyDenmarkThe USPolandPortugalFinlandSlovakiaSpainGermanySloveniaThe NetherlandsNorwaySwedenSwitzerland3.2 Data—operationalization of institutions and entrepreneurshipWe operationalize the institutions that the VoC and entrepreneurship literature consider to be relevant for entrepreneurship as follows:With regard to finance-related institutions, we measure the different corporate governance rights between countries using the indicator ‘protection of minority interests’ from the World Bank’s Doing Business database. The indicator focuses on equity investors and, more precisely, on minority shareholders who have a share in losses and profits and a stake that is large enough to allow them to vote on important decisions, but not large enough to allow them to control the company. More concretely, the indicator captures shareholders’ rights in corporate governance by distinguishing three dimensions of ‘good governance’ and three of ‘bad governance’.
Higher values on this ‘protection of minority’ index indicate a more direct involvement of shareholders in corporate governance (without the intermediation of a supervisory board)—and consequently, increased rights to hold managers directly accountable.We measure differences in the minimum capital requirements between countries using the indicator ‘paid-in minimum capital’ from the World Bank’s Doing Business database. This measure captures the amount that the entrepreneur needs to deposit in a bank or with a notary in order to open up a limited liability company (or its legal equivalent). If there is more than one type of limited liability company in the economy, that limited liability form is chosen which is most common among domestic firms. This paid-in capital is recorded as a percentage of the economy’s income per capita. We rescaled this indicator so that a higher score indicates lower minimum capital requirements, and vice versa.The impact of different institutions on the availability of venture capital is measured using the indicator ‘venture capital investments in start-up and seed companies’ compiled by INVEST Europe and made available by Eurostat.
The indicator measures the extent of venture capital investments in early-stage seed and start-up companies as a percentage of national GDP. Higher values indicate higher venture capital investments in start-up firms and thus increased opportunities for entrepreneurs to access venture funding.Finally, we use the ‘recovery rate’ indicator from the World Bank’s Doing Business database to measure the extent to which shareholders can defend their interests against creditors in case of corporate insolvency. The recovery rate is calculated based on the time, cost, and outcome of insolvency proceedings in each economy. The calculation takes into account the outcome: whether the business emerges from the proceedings as a going concern or the assets are sold piecemeal. Then, the costs of the proceedings are deducted (1 cent for each percentage point of the value of the debtor’s assets). The cost includes court fees and government levies; fees for insolvency administrators, auctioneers, assessors, and lawyers; and all other fees and costs.
Higher values indicate higher costs for creditors to recover their investment, favouring shareholders in case of corporate insolvency.We use three different indicators to measure the short-term orientation of labour-market institutions: In line with the VoC literature, we use the ‘regular employment protection legislation’ indicator from the OECD employment database in order to measure labour-market flexibility of permanent employment. The indicator focuses on the conditions for terminating employment, including required notification and involvement of third parties (such as courts, labour inspectorates, and workers’ councils), notice periods and severance pay, the conditions under which it is permissible to lay off an employee, and the repercussions if a dismissal is found to be unfair. Furthermore, the indicator also takes into account provisions for collective dismissals. Higher scores indicate more rigid labour market institutions, i.e.
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Stronger protection for permanent employment, indicating greater difficulty in hiring and firing permanent workforces in the short run.To measure the institutionalised flexibility of temporary employment, we use the indicator ‘temporary employment protection legislation’ from the OECD employment database. The indicator measures the strictness of regulation on the use of fixed-term and temporary work agency contracts, including valid cases for the use of fixed-term contracts, the maximum number and cumulated duration of successive fixed-term contracts, the types of work for which temporary work agency (TWA) employment is legal, as well as the restrictions on the number and maximum cumulated duration of renewals of TWA assignments. Higher scores indicate stronger protection for temporary employment, indicating greater difficulty in hiring and firing temporary workforces in the short run.Finally, we take the indicator ‘social spending on start-up incentives’ from the OECD database on ‘labour market programmes’ to measure the extent of programmes that promote entrepreneurship by encouraging the unemployed and target groups to start their own businesses or become self-employed. The indicator is calculated as a percentage of national GDP, so that higher values indicate more developed entrepreneurship programmes.In line with our theoretical reasoning, we use three different indicators to assess how education and training-related institutions influence the extent of scientific knowledge available to entrepreneurial ventures. From the OECD database on education, we take the indicator ‘population with tertiary education’ in order to measure the extent to which national education systems facilitate the acquisition of general skills by future workforces.
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The indicator reports the percentage of the population aged 25–64 years with a tertiary degree, so that higher values indicate a higher share of generally skilled workforces and thus a better skill base for Schumpeterian entrepreneurial ventures.From the OECD database on science and technology indicators, we use the indicator ‘researchers per head’ to assess the extent to which institutions facilitate the availability of scientific knowledge to entrepreneurial ventures. This measure indicates the share of scientists active in research and development activities, expressed per thousand people employed.From the Global Entrepreneurship Monitor (GEM), we employ the indicator ‘R&D transfer’ in order to assess the extent to which national R&D activities lead to new commercial opportunities and are available to SMEs. (1)where Y is our entrepreneurship indicators at time t for country i and α is the constant.
Cluster i represents the dummy variables capturing the membership of country i in a certain cluster considering the varieties in the VoC framework, and underlying clusters created based on its four principal dimensions—namely finance-related institutions, labour, education and inter-firm. To create the dummy variables, we rely on results obtained from the cluster analysis and dendograms. In our regression analyses, we also control for the variables log GDP per capita and labour force participation. 4 Analyses and findings.