Do labour productivity, capital productivity and education influence the technical efficiency of entrepreneurial outcomes? Evidence from europe

Entrepreneurship is the ability to identify and analyse opportunities, taking risks to form and manage a business to take advantage of those opportunities. To measure the level of entrepreneurship, many researchers use the establishment of new companies or the entrepreneurial activity index (Castaño et al. 2015; Rico et al. 2019).

Over the last 15 years, following the 2008 global economic and financial crisis, the Covid-19 pandemic and the war in Ukraine, the Eurozone economy has suffered reduced growth rates (Eurostat 2023b). Thus, throughout Europe, entrepreneurship has played an essential role in the development of the economy (Bosma et al. 2018; Crudu 2019), and a recent study demonstrates that entrepreneurship increases productivity (Ghazy et al. 2022). Another example is the leadership of the European Union in environmental sustainability initiatives, which foster opportunities for entrepreneurship (Ruiz et al. 2023). Exploring Europe holds intrigue due to its heterogeneity, as the diverse cultures across countries significantly shape entrepreneurial intentions (Paul et al. 2017).

Therefore, national and supernational efforts have been made to encourage the creation of companies and support entrepreneurship at an early stage, removing specific existing barriers (Roman et al. 2018). But for this to happen correctly and effectively, it is necessary to understand the factors that influence entrepreneurship in the initial phase since there is an enormous heterogeneity among the different entrepreneurs (Du and O’Connor 2018).

In the literature review carried out and presented in the second section of this study, it can be seen that a set of factors can categorically influence the decision of individuals to become entrepreneurs. Such factors can be related to individual characteristics (Lee et al. 2022), associated with education (Alakaleek et al. 2023), linked to risk tolerance (Hvide and Panos 2014), framed by the institutional structure of a country (Sendra-Pons et al. 2022), affected by employment and unemployment (Fonseca 2022), among other economic and social factors.

The field of entrepreneurship has seen substantial growth in recent years (Braunerhjelm and Lappi 2023; Dileo and García Pereira 2019; Dutta and Sobel 2018; Passaro et al. 2018; Roman et al. 2018; Volery et al. 2013). Dileo and García Pereira (2019) indicate that individuals with higher education are more likely to pursue entrepreneurship, suggesting that education and training policies can shape entrepreneurial competencies. Policy measures, especially those involving regulation, can directly or indirectly affect the level of entrepreneurship by creating opportunities for new businesses (Castaño et al. 2016; Moro et al. 2020). Moro et al. (2020) also highlight that tax incentives play a crucial role in determining the rewards and risks of entrepreneurial activities. Governments increasingly promote entrepreneurship as a means to spur economic and social growth and recognize the necessity of fostering more entrepreneurial societies (Sendra-Pons et al. 2022). Public policies aim to leverage the essential role of entrepreneurs in economic expansion, particularly those who are innovative and capable of transforming new technologies and business opportunities into profitable ventures (Hahn et al. 2020). Entrepreneurship is crucial for driving innovation and technological progress, which are key to economic growth (Fotopoulos and Storey 2019; Martínez-Rodriguez et al. 2020). For instance, Kostakis and Tsagarakis (2022) argue that the European Union can achieve progressive circularity by encouraging entrepreneurial opportunities to tackle contemporary challenges like climate change and resource scarcity. During crises, entrepreneurial activities have been used as a strategy to manage economic shocks (Krishnan et al. 2022). Meyer and De Jongh (2018) found that in the EU, entrepreneurship mitigates economic disruptions. González-Pernia et al. (2018) observed that entrepreneurship in Spain mirrored the economic recession of 2007–2010, reflecting a lower perception of opportunities during the global crisis. Galindo-Martín et al. (2021) noted that while entrepreneurship promotes sustainable development, it suffered setbacks during the Covid-19 pandemic. Parker and Van Alstyne (2012) found that economic recovery and booms often follow increases in entrepreneurship, highlighting a bidirectional relationship between entrepreneurship and economic cycles. For example, initial periods of crises see greater entrepreneurial challenges, while need-based entrepreneurship tends to rise significantly post-crisis (Martínez-Rodriguez et al. 2020). However, it is crucial to consider the specific nature of each crisis (Lee et al. 2023).

Thus, a cyclical study of entrepreneurship is needed to better assess the scope of the most recent crises (Galindo-Martín et al. 2021). Analysing entrepreneurial behaviour in homogeneous periods will support decision-making to promote entrepreneurship and consequent economic growth (Martínez-Rodriguez et al. 2020). This argument suggests the pertinence of an analysis of the influencing factors of entrepreneurial activities and the creation of new companies in periods of crisis and after these crises. A study of this kind will aim to clarify which determinants impact these entrepreneurship outcomes. Hence, the need for this study arises from the significant role that entrepreneurship plays in the European economy, especially in times of economic downturns and crises. Besides the crises, it is also important to mention the economic rise of Asia, especially China and other Asian countries, over the past 10 years, which has posed strong competition for European companies in various sectors (Ciani and Mau 2023). Therefore, a longitudinal study of the past 10 years can provide a comprehensive and detailed insight into entrepreneurship in Europe. This is particularly relevant because, in today’s economy, the ability to adapt to rapid changes, with an emphasis on innovation and entrepreneurship, is crucial for success (Badri and Badri 2020).

Bearing this in mind, this article aimed to evaluate the results of entrepreneurial activity based on the performance of 26 EU-27 countries and measured by Total Entrepreneurial Activity (TEA) and Birth Rate of enterprise in the reference period. These outcomes are the result of economic determinants such as unemployment, technology, investment and human capital. This supports the suggestion of Silva et al. (2022) that future studies should incorporate more than an indicator of entrepreneurship beyond TEA, thereby giving rise to a distinctive investigation. Moreover, this study also differs from others by focusing on assessing the impacts of various socio-economic variables on entrepreneurship specifically in the European context, particularly during crisis periods and in the post-crisis period, supporting Galindo-Martín et al.’s (2021) suggestion. Given the diversity of cultures and economic conditions across European countries, the contribution to the literature reviewed is based on a proposal concerning a theoretical framework which develops the assumptions of the relationship between entrepreneurship, unemployment, and the determinants of economic growth. This proposal is based on models of economic growth, and their determinants including the employment-unemployment pairing and their entrepreneurship linkage.

Thus, following this theoretical framework, whose proposed equations will be considered by applying in the first approach, the study used the non-parametric frontier through Data Envelopment Analysis (DEA), which presented technical efficiency scores for each European country considered a Decision-Making Unit (DMU). In a second approach, the study used the stochastic frontier function (SFA) analysis technique, equally considering the two outcomes and the same inputs used in the DEA approach.

Consequently, this article aimed to answer the following questions: (i) How different or how similar are the technical efficiency scores in the two different approaches in terms of the positioning of European countries? (ii) What are the average scoring differentials for European countries in the sub-periods of the sample, particularly in the period of the 2008–2010 global crisis, in the period of the 2011–2014 sovereign crisis and after this last crisis that is 2015–2019?

The originality of this study lies in three contributions: first, it presents an overview of the performance of entrepreneurial activities and the creation of new firms in Europe during the crisis periods and in the post-crisis period 2015–2019. Second, it assesses the impact of socioeconomic variables on entrepreneurial activities and firms’ creation. Specifically, the present investigation uses a heterogeneous sample, with different European countries and respective different levels of Human Capital and Labour Market. This justifies the application of both the SFA and the DEA to make a comparative analysis of the results of entrepreneurship activities and newly created companies obtained by these two methodologies. Therefore, the use of these two methods can be complementary. The DEA makes it possible to deal with size heterogeneity between European countries. In contrast, the SFA is more adapted to possible sampling errors. It should be remembered that there are different countries and data from various business contexts, so the information had to be processed to ensure minimum or maximum harmonisation. Third, through the examination of a heterogeneous sample of European countries with varying levels in the indicators used, this analysis provides a more comprehensive understanding of the determinants of entrepreneurship in Europe and suggests possible areas of policy intervention to promote economic growth and innovation. Thus, based on these three contributions, this study represents an opportunity to provide valuable insights for stakeholders and incentive policymakers, including self-employment policies to increase entrepreneurial activity and/or the creation of successful new firms.

The remainder of the article is structured as follows. The “Literature review” section provides an overview of the theoretical framework and research model. The “Theoretical framework” section presents the theoretical framework, while the “Data and methodology” section details the data, variables, and methodologies employed. The results are presented in the “Results” section, followed by a discussion and implications in the “Discussion of findings” section. Lastly, the “Conclusions, limitations, and future studies” section offers the main conclusions, discusses limitations, and provides suggestions for future studies.

In the first step, this study sought to estimate for Europe, during two periods of financial crises and a period after them, the technical efficiency scores of entrepreneurship activities and new firm creation. In the transformation of inputs, and as catalysts of entrepreneurship and creation of new companies, associated variables such as the impulse originated by the unemployment situation, the disposable income to want and be able to undertake new ventures, and the skills and knowledge of academic training with tertiary education held to achieve this transformation were measure by TEA.

Using non-parametric Data Envelopment Analysis (DEA) and parametric Stochastic Frontier Analysis (SFA), the study identified European countries with varying levels of efficiency in entrepreneurship. The analysis revealed that factors like labour productivity, capital productivity, unskilled labour, and educational attainment (primary and secondary levels) significantly impact these efficiency scores.

During and after financial crises, differences in education, career intentions, and student self-efficacy influenced how different workforce segments prepared for entrepreneurial careers. These findings highlight the critical role of education and training in fostering an entrepreneurial mindset, aligning with insights from Ouni and Boujelbene (2023), Boubker et al. (2021), and Paola et al. (2023). Educational institutions, especially universities, are key to developing a multidisciplinary and multicultural outlook, which enhances a country’s entrepreneurial capacity (Paola et al. 2023). Incorporating extracurricular activities can cultivate an entrepreneurial mindset, increasing students’ risk-taking, opportunity recognition, and tolerance (Cui et al. 2021).

The empirical evidence from the first and second stages of this study shows that labour productivity and education significantly influence attitudes toward entrepreneurship and new firm creation. During financial crises, the study found that capital productivity negatively impacts the efficiency of entrepreneurial outcomes. This underscores the interplay between economic conditions and entrepreneurship, where self-employment typically rises during economic booms and falls during recessions (Unel and Upton 2023). The study attributes these findings to reduced EU investments in fixed capital and structural changes in the labour market and education levels, particularly in economically growing countries. It is essential to understand these labour market changes and how different government incentives, such as support for new enterprises or education, can affect entrepreneurial success rates. Effective public policies play a crucial role in fostering entrepreneurship, especially during economic crises or recovery periods (Abdesselam et al. 2018; Castaño et al. 2016; Moro et al. 2020; Veiga and Teixeira 2021). However, generous unemployment benefits, common in developed countries with strong social safety nets, can also discourage entrepreneurship by fostering risk aversion (Bilan and Apostoaie 2023; Leitão and Capucho 2021).

Moreover, the macroeconomic conditions during all the periods of analysis imply incentives for the creation of new companies and stimulate entrepreneurial activities in economies. On the other hand, according to the literature (Boubker et al. 2021; Johnstone et al. 2018; Ouni and Boujelbene 2023; Paola et al. 2023), as the level of education increases, so does labour productivity and investment in fixed capital enabling increases in productivity of capital. In that way, it positively affects competitiveness and stimulates economic growth. So, this research points to increases in labour productivity in the efficiency scores of entrepreneurial outcomes. These results mirror the increase in the total active population in periods when there is economic growth and simultaneously a decrease in unemployment due to the diversion of some proportion of the active population to the creation of new companies and increases in entrepreneurial activities. However, the relationship between unemployment fluctuations and firm creation is complex and varies across countries (Faria et al. 2010). Generally, a higher unemployment rate corresponds to a high rate of self-employment (Payne and Mervar 2017), but this trend occurs mainly in high-performing regions (O'Leary 2022).

In the period after the financial crises, despite the improvement observed over this period in contrast to the period of the financial crises, the period is characterized by the predominance in most EU countries of greater capitalization of the financial system and the reduction in the stock of non-productive workers. These factors may also affect the supply of credit and the difficulty in accessing finance. These levels of leverage may have conditioned the investment capacity and productivity of companies. For instance, during periods of economic recession, high-income families have more resources and thus cope better with the situation enabling them to explore new business opportunities (Albert et al. 2023).

The study reveals that labour productivity and the quality of capital investment significantly impact the technical efficiency of new firm creation. Higher disposable income promotes entrepreneurial activities by facilitating better networking and access to education, which cultivates potential entrepreneurs (Molina 2020; Sharma 2014). Additionally, disposable income boosts consumer demand, creating more business opportunities (Alp and Seven 2019).

This research underscores the impact of educational qualifications on human capital, particularly in countries with economic constraints. These constraints lead to lower labour productivity and employment challenges, especially during economic downturns like financial and sovereign crises. Acquiring skills to improve business prospects becomes crucial under such conditions (Henderson et al. 2017; Rahmani and Groot 2023).

The study also highlights the dynamics between opportunity-driven and necessity-driven entrepreneurship. During economic crises, high unemployment pushes individuals towards necessity-driven entrepreneurship to generate income. Conversely, economic recoveries foster opportunity-driven entrepreneurship as market opportunities emerge. Education is a key factor in this context; higher education levels are linked to increased productivity and capital investment, facilitating opportunity-driven entrepreneurship.

By examining these dynamics, policymakers and economists can better assess economic resilience. A diverse entrepreneurial landscape, including both necessity-driven and opportunity-driven entrepreneurs, fosters innovation, job creation, and economic growth. Thus, entrepreneurship is crucial for national development, offering insights into how economic factors interact with entrepreneurial activity, especially during economic crises, and suggesting practical implications for policy and management.

This study first presented an overview of the performance of entrepreneurial activities and the creation of new companies in Europe during the crisis period 2008–2014 and in the post-crisis period 2015–2019. Second, it assessed the impact of socioeconomic variables on entrepreneurial activities and firm creation. This study proposed a new framework theoretical for examining the relationship between entrepreneurial activities and their determinants of economic growth. Consequently, this investigation, in the first step, the different scores of technical efficiencies among European countries, which justified the application of both the SFA and the DEA to make a comparative analysis of the results of entrepreneurship activities and newly created companies obtained by these two methodologies. In the second stage, this research examined the impacts of some control variables, including labour productivity, capital productivity, labour with primary and secondary education, and population with primary and secondary education, on the efficiency scores of the entrepreneurial outcomes used.

In terms of technical efficiency, estimated in the first step for the 2008–2010 period, the European countries presenting the maximum score according to the DEA-CRS model are Lithuania, Estonia, and the Netherlands. According to the SFA, the countries presenting the lowest levels of inefficiency are the Netherlands and France. Malta, however, presents the highest level of inefficiency during both of the financial crises, according to the SFA technique. In the second period of the financial crisis, according to the DEA-CRS, Lithuania shows a maximum score for efficiency, while Belgium is the most inefficient. On the other hand, according to the SFA results, Estonia, Lithuania, the Czech Republic, Greece, Denmark, Finland and Hungary show the highest values of efficiency (less inefficiency), while Malta and Cyprus are the most inefficient, with the lowest scores for entrepreneurial outcomes and efficiency. When the results for the DEA-CRS for 2015–2019 are considered, after the financial crisis, Lithuania, Estonia, Latvia, and the Netherlands, show a maximum score for efficiency, while Belgium and Finland present the highest inefficiency. Moreover, looking at the results of the SFA in this period after the crisis, Estonia, Romania, Denmark, and the Netherlands are the most efficient, while Austria, the Czech Republic, Hungary, and Slovenia present the highest inefficiency in terms of entrepreneurial outcomes.

During financial crises, capital productivity negatively impacts the efficiency of entrepreneurial outcomes. This is due to reduced EU investments in fixed capital and structural changes in the labour market and education levels, especially in growing economies. Bootstrap Quantile Regression analysis from 2008–2014 shows that labour productivity for primary and secondary education levels and population percentages at higher quantiles increase, except at the 0.90 quantile. Europe’s diverse cultural, economic, and regulatory factors influence entrepreneurial activities, offering a comprehensive understanding of its entrepreneurial ecosystem.

The present study also has some limitations. First, the study relied on secondary data sources, which may have inherent limitations such as data accuracy, completeness, and consistency. Future studies could benefit from using primary data collection methods to overcome these limitations. Second, the study focused on Europe, and therefore, the findings may not be generalizable to other regions or countries outside of Europe. Future research could explore entrepreneurial activities in different regions to provide a more comprehensive understanding. Third, the study analysed data from two specific periods, namely during and after financial crises. However, entrepreneurial activities may be influenced by various other temporal factors, such as technological advancements, policy changes, and market trends. Future research could consider a longer time frame to capture these dynamics more comprehensively. Another interesting study would be to explore entrepreneurship within specific industries or sectors to understand sector-specific challenges and opportunities for entrepreneurship development.