Trust: The Social Virtues and the Creation of Prosperity

Geography and Trade

This paper is an introduction to the special issue from the 3rd Global Entrepreneurship Monitor Research Conference held in Washington, D.C., in 2008. The paper has three objectives. First, to discuss the importance of the three stages of economic development, the factor-driven stage, the efficiency-driven stage and the innovation-driven stage. Second, to examine the empirical evidence on the relationship between stages of economic development and entrepreneurship. Third, to present a summary of the papers in the context of the theory.

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Entrepreneurship, economic development and institutions

National Systems of Entrepreneurship: Measurement issues and policy implications

Social entrepreneurship has recently received greater recognition from the public sector, as well as from scholars. However, the lack of a unifying paradigm in the field has lead to a proliferation of definitions. Moreover, several approaches of the phenomenon, as well as different schools of thought, have emerged in different regions of the world. At first glance, because of different conceptions of capitalism and of the government's role, there seems to be a difference between the American and the European conceptions of social entrepreneurship. The objective of this paper is to clarify the concepts of ‘social entrepreneurship’, ‘social entrepreneur’ and ‘social entrepreneurship organization’ and to examine whether there is a transatlantic divide in the way these are conceived and defined. After having justified the need for a definition, we present the different geographical perspectives. North American and European literatures on social entrepreneurship are critically analysed by means of Gartner's fo...

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The multiple faces of social entrepreneurship: A review of definitional issues based on geographical and thematic criteria

This paper compares two datasets designed to measure entrepreneurship. The Global Entrepreneurship Monitor dataset captures early-stage entrepreneurial activity; the World Bank Group Entrepreneurship Survey dataset captures formal business registration. There are a number of important differences when the data are compared. First, GEM data tend to report significantly greater levels of early-stage entrepreneurship in developing economies than do the World Bank data. The World Bank data tend to be greater than GEM data for developed countries. Second, the magnitude of the difference between the datasets across countries is related to the local institutional and environmental conditions for entrepreneurs, after controlling for levels of economic development. A possible explanation for this is that the World Bank data measure rates of entry in the formal economy, whereas GEM data are reflective of entrepreneurial intent and capture informality of entrepreneurship. This is particularly true for developing countries. Therefore, this discrepancy can be interpreted as the spread between individuals who could potentially operate businesses in the formal sector - and those that actually do so: In other words, GEM data may represent the potential supply of entrepreneurs, whereas the World Bank data may represent the actual rate of entrepreneurship. The findings suggest that entrepreneurs in developed countries have greater ease and incentives to incorporate, both for the benefits of greater access to formal financing and labor contracts, as well as for tax and other purposes not directly related to business activities.

https://papers.ssrn.com/sol3/Delivery.cfm/4667.pdf?abstractid=1233043&mirid=3

What Does 'Entrepreneurship' Data Really Show? A Comparison of the Global Entrepreneurship Monitor and World Bank Group Datasets

Knowledge generated in universities can serve as an important base for the commercialization of innovation. One mechanism for commercialization is the creation of a new company by a scientist. We shed light on this process by examining the role of scientist characteristics, access to resources and key university conditions in driving the likelihood of a scientist to start a company. Our sample comprises 1,899 university scientists across six different scientific fields. We make a methodological contribution by using self-reported data from the scientists themselves, whereas most previous research relied on university or public data. Our consideration of six scientific fields is a substantive contribution and reveals that scientist startups are heterogeneous in nature. Our findings are largely consistent with extant research on the role of individual and university variables in scientist entrepreneurship; in addition, we uncover the novel finding that the type of research field is also a key driver of scientist startup activity.

Scientist entrepreneurship across scientific fields

ICT clusters have attracted much attention because of their rapid growth and their value for other economic activities. Using a nested multi-level model, we examine how conditions at the country level and at the city level affect ICT clustering activity in 227 cities across 22 European countries. We test for the influence of three country regulations (starting a business, registering property, enforcing contracts) and two city conditions (proximity to university, network density) on ICT clustering. We consider heterogeneity within the sector and study two types of ICT activities: ICT product firms and ICT content firms. Our results indicate that country conditions and city conditions each have idiosyncratic implications for ICT clustering, and further, that these can vary by activities in ICT products or ICT content manufacturing.

https://link.springer.com/content/pdf/10.1007%2Fs10961-015-9422-y.pdf

What drives ICT clustering in European Cities

Government size, corruption, and tax policy can influence allocation towards necessity or opportunity-driven entrepreneurship. Using a comparative multi-source sample across 52 countries during 2005–2015, we apply a mixed-process estimation of the simultaneously unrelated system of equations and unpack these heterogeneous and complex effects. Interestingly, our results show that the influence of tax policy and corruption on necessity and opportunity entrepreneurship depends on government size. Our results hold for numerous robustness analyses. Institutions matter for the choice of opportunity and necessity-driven entrepreneurship. Government size, the level of corruption, and tax policy directly affect entrepreneurs’ motivation and incentives. We study 52 countries during 2005–2015 to find out to what extent tax rate, corruption, and a range of government expenditure change the allocation of necessity and opportunity entrepreneurship. Our main implications are for (1) Research: Formal and informal institutions need to be considered when studying entrepreneurship allocation, particularly in an emerging and developing country context. Results suggest that the impact of the same institutional settings and informal institutions such as corruption on necessity and opportunity entrepreneurship is not uniform in size and scope and have different magnitude. The effect of government expenditure on necessity and opportunity entrepreneurship is not ubiquitous. (2) Management: The broader institutional context affects allocation of entrepreneurship, and potential entrepreneurs can consider how corruption in particular can affect them. (3) Policy: Policymakerscan measure the extent to which opportunity and necessity entrepreneurship are likely to change, when they make changes to tax policy, resources for public spending, and take anti-corruption measures.

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Necessity or opportunity? Government size, tax policy, corruption, and implications for entrepreneurship

Entrepreneurship can have important positive effects linked to job creation, wealth and income generation, innovation and industry competitiveness. Scholars and policy-makers around the world have turned to the regulatory environment as a mechanism through which entrepreneurship can be encouraged, grown and its economic benefits harnessed. The effect of regulatory conditions on entrepreneurship however is not well understood, and can be nuanced given the wide range of regulatory tools and possible areas of impact. This paper serves as the introduction to a special issue, which seeks to shed some light on the relationship between regulation, firm dynamics and entrepreneurship. We identify some foundational considerations relevant to this relationship and discuss key questions, followed by a brief overview of each of the papers contained in the special issue.

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Sameeksha Desai

Papers

What Does 'Entrepreneurship' Data Really Show? A Comparison of the Global Entrepreneurship Monitor and World Bank Group Datasets

Scientist entrepreneurship across scientific fields

What drives ICT clustering in European Cities

Necessity or opportunity? Government size, tax policy, corruption, and implications for entrepreneurship

Regulation, firm dynamics and entrepreneurship