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ENTREPRENEURSHIP AND ECONOMIC GROWTH A CROSS-SECTIONAL ANALYSIS PERSPECTIVE

innovation more broadly, to competition and economic dynamism. This paper contributes to the entrepreneurship literature by conducting a cross-sectional analysis of the relationship between entrepreneurship and economic growth. Although no evidence of causal relationship between aggregate entrepreneurship and economic growth is firmly established, empirical evidence suggests that different types of entrepreneurship have different effects across economies. It discovers, in particular, that opportunity-driven entrepreneurship is positively related to growth in developing economies where manufacturing is significant. ABSTRACT Entrepreneurship, or the activity of starting and running a business, is a vital ingredient of economic growth and development. Entrepreneurs contribute to innovation, and they are central to dynamic Schumpeterian competition and broader economic dynamism. In this paper, we contribute to the entrepreneurship literature by performing cross-sectional analysis to examine the link between entrepreneurship and economic growth. We divide total early-stage entrepreneurship into opportunity-driven entrepreneurship versus necessity-driven entrepreneurship, and our sample economies into advanced economies versus developing economies. We do not find evidence of a positive link between aggregate entrepreneurship and economic growth. This is consistent with the hugely heterogenous nature of entrepreneurial activity. At a broader level, our empirical evidence points to the importance of distinguishing between different types of entrepreneurship and different groups of economies. In particular, for developing economies where manufacturing is relatively important, we find that opportunity-driven entrepreneurship is positively linked with growth. Entrepreneurs contribute to innovation and, more broadly, to competition and economic dynamism. This paper contributes to the entrepreneurship literature by conducting a cross-sectional analysis of the relationship between entrepreneurship and economic growth. Although no evidence of causal relationship between aggregate entrepreneurship and economic growth is firmly established, empirical evidence suggests that different types of entrepreneurship have different effects across economies. It discovers, in particular, that opportunity-driven entrepreneurship is positively related to growth in developing economies where manufacturing is significant.


INTRODUCTION
Entrepreneurship, or the activity of starting and running a business, is a vital ingredient of economic growth and development. Entrepreneurs contribute greatly to innovation, and they are central to dynamic Schumpeterian competition and economic dynamism. Innovative entrepreneurs are the principal agents of the never-ending Schumpeterian process of new products, services, technologies, firms, and industries replacing existing products, services, technologies, firms, and industries. Fortune 100 is replete with new companies that are using new technologies to produce and sell new products. Just as Fortune 100 of 1970 is unrecognizable today, today's Fortune 100 will be unrecognizable in 2070. Behind the constant emergence of new companies with new technologies and new products are visionary, game-changing, risk-taking entrepreneurs such as Steve Jobs who started Apple with his friends in the garage of a suburban California home. Competition forces even mundane, ordinary entrepreneurs such as street food vendors to innovate. Therefore, the contribution of entrepreneurship to the economy is not confined to transformational entrepreneurs.
Despite their significant contribution to innovation and economic growth, entrepreneurship was a relatively under-researched and under-appreciated. This is partly because of lack of data until recent years when the Global Entrepreneurship Monitor (GEM) and other entrepreneurship databases were developed. At a broader level, the lack of research and appreciation reflects the innate difficulty of quantifying entrepreneurship and the factors which motivate entrepreneurs to become entrepreneurs. Further, entrepreneurship is difficult to explain as a rational endeavor because most new businesses fail. Becoming an entrepreneur thus requires irrational exuberance or optimism. Yet another possible reason for why economists tended to neglect entrepreneurship is its tremendous diversity. Entrepreneurs range from street food vendors to transformational innovators such as Elon Musk, making it difficult to clearly conceptualize entrepreneurship. While mundane entrepreneurs contribute a lot to the economy, game-changing entrepreneurs contribute disproportionately to innovation, productivity growth, and economic dynamism.
Transformational entrepreneurs are often the first to take risk and seize unrecognized opportunities despite the low probability of success. Bold visionary creative entrepreneurs think outside the box and create new products, services, and industries. For instance, Ted Turner created a cable TV network that broadcast news 24 hours a day and 7 days a week at a time when most people only watched the news on TV on evenings. Yet four decades later, 24/7 news channels have become a part of daily life. Entrepreneurs are adept at commercializing new technology into products and services that are useful for consumers.
Commercially successful applications of the internet such as Amazon and Google are classic examples. While the public sector played a big role in the development of the basic internet technology, entrepreneurs were responsible for the bulk of its myriad commercial applications. In addition to products that consumers find useful, entrepreneurs produce products that address humanity's most urgent challenges. One prominent example is the coronavirus disease  vaccine produced by the German biotech start-up BioNTech founded by two innovative entrepreneurs, Dr. Ugur Sahin and Dr. Ozlem Tureci.
By fostering knowledge spillovers and radical innovations, innovative entrepreneurs contribute greatly to economic growth, employment creation, productivity, and social welfare in economies of all income and development levels (Kritikos 2014). The distinction between everyday entrepreneurs and innovative entrepreneurs is not always clear-cut. For instance, creative street food vendors who invent uniquely delicious dishes become influential restaurateurs. Nevertheless, a relatively small group of highly productive entrepreneurs account for the lion's share of entrepreneurship's contribution to the economy. Digital technology is not a panacea for lack of entrepreneurship because the level of entrepreneurial activity in a society is influenced by a multitude of factors. To become an entrepreneur or not is fundamentally an individual decision. Talented individuals who become game-changing innovative entrepreneurs have plenty of opportunities as highly paid workers. Their risky decision to start their own business instead is shaped by not only their own values but formal and informal institutions, social norms, and the overall business environment (Baumol andStrom 2008, Acs et al. 2008). The same is true for everyday entrepreneurs. The enabling entrepreneurial ecosystem is constantly evolving. In recent years, organizational innovations such as venture accelerators and crowdfunding improved the entrepreneurial climate. Technological innovations such as the emergence of 5G also affect the climate. While it is difficult to pin down why some individuals start a business while others do not, what is certain is that the decision to become an entrepreneur is inherently a complex, multidimensional process.
The rest of this paper is organized as follows. Section II reviews the literature on entrepreneurship and economic growth. Section III discusses data and empirical framework, and section IV reports and discusses the empirical results. Finally, section V concludes.  Schumpeter (1942) and Baumol (1990) Baumol (1990) pointed out that some kinds of entrepreneurship are socially more productive than others. He emphasized that the overall entrepreneurial environment was a major factor in determining what kind of entrepreneurial activity will dominate in an economy. Acs (2006) argues that economic development depends on combination of successful entrepreneurs and successful corporations. Using cross-sectional time series panel of economy-specific measures of entrepreneurship, Acs et al. (2005) find that entrepreneurial activity makes a positive contribution to economic growth. They conclude that this is consistent with the notion that entrepreneurship serves as a conduit for the knowledge spillovers which foster productivity growth. Using a Schumpeterian approach to link gross domestic product (GDP), innovation, and entrepreneurship, Galindo and Méndez (2013)  Economic activity promotes entrepreneurship and innovation, which, in turn, promote economic activity.

II. LITERATURE REVIEW
Valliere and Peterson (2009)  (2020) find that entrepreneurship has a positive effect on economic growth. In particular, their evidence suggests that early-stage and opportunity-driven entrepreneurship promotes growth in the sample economies.
Most of the earlier studies on entrepreneurship and economic growth were centered on developed economies rather than developing economies. Empirically, the effect of entrepreneurship on growth in developing economies remains uncertain and further research is needed. According to the analysis of Stam and van Stel (2011), entrepreneurship does not influence the growth of middle-income economies but contributes to the growth of highincome economies. Lerner and Schoar (2010) note that it is imperative to understand the dynamic interaction between environmental factors such as market regulation and entrepreneurship to better assess the impact of entrepreneurs on growth in developing nations. Acs (2010) observed an S-shaped relationship between entrepreneurship and economic development. In the initial stage of development, entrepreneurship plays a visible role, but its role increases at a decreasing rate as the efficiency stage takes hold. However, as the economy moves from the efficiency-driven stage to the innovation-or knowledgedriven stage, entrepreneurship reassumes a more important role which increases at an increasing rate. According to Acemoglu and Johnson (2005), as institutions are strengthened, more and more entrepreneurial activity is shifted toward productive entrepreneurship, thus promoting economic development. This burst of entrepreneurial activity gains momentum through the efficiency-driven stage and culminates in a high level of innovation when entrepreneurship eventually levels out. Koster and Rai (2008) expect rates of entrepreneurship to decline with economic development which opens employment possibilities, and thus reduces the need to become entrepreneurs out of economic necessity. However, this pattern is not consistent with the Indian experience. Rather, entrepreneurship appears to be an important driver of economic growth. One possible explanation is that India is a service-based economy, which makes it easier for small business to exist. Although the level of entrepreneurship has increased over time, the quality of small firms and the share of registered firms has remained stable. The Henrekson and Sanandaji (2011)].
According to ADB (2020), strong institutions enable innovative entrepreneurs. The quality of entrepreneurship in an economy is more important for innovation than its quantity.
In terms of economic contribution, not all entrepreneurship is created equal. A small group of entrepreneurs known as "gazelles" in the business world account for most of the innovation and job growth, while the majority of entrepreneurs neither innovate nor create jobs. The ability of an economy to breed gazelles is largely determined by its institutional conditions.
According to an analysis of over 36,000 businesses in 17 Asian economies, strong property rights and the rule of law encourage entrepreneurs to formalize their businesses, and greater formalization is associated with greater innovation. Understanding the sector-by-sector potential for growth helps us understand the cumulative impact of innovation and entrepreneurship on overall economic performance.
Research into the phenomenon of innovative high-growth firms is recently gaining traction. These firms account for much of job and output creation in both high-income and developing economies. ADB (2020) and Wong et al. (2005) found out that, among four types of entrepreneurships, only high-growth potential entrepreneurship has a significant impact on economic growth. These findings are consistent with existing studies which find that fast-  (2021) find that small and medium-sized enterprises, which produced radical innovations in the German biotech sector, enjoy superior innovation performance in subsequent periods. Further, firms that cooperate directly with radical innovators enjoy higher innovation performance than firms that do not.

III. DATA AND EMPIRICAL FRAMEWORK
Our paper performs cross-sectional analysis to identify the effect of entrepreneurship on economic growth. In line with existing literature, our key independent variables are total early-stage entrepreneurship (TEA), which consists of opportunity-driven early-stage entrepreneurship (OEA) and necessity-driven early-stage entrepreneurship (NEA; refer to, for example, Wong et al. 2005 andValliere andPeterson 2009). Data on these entrepreneurship variables were collected from the GEM, the most widely used source of entrepreneurship data. 1 The key dependent variables are GDP growth and GDP per capita growth, the two most widely used measures of economic growth. Data on these indicators were taken from the World Bank's World Development Indicators database.
We also divide the economy sample into advanced versus emerging and developing economies. In addition, we consider the economic structure of an economy. More specifically,  Across economies, GDP growth increases with the early-stage entrepreneurship activity rate. GDP = gross domestic product. Notes: Each dot represents annual percentage GDP growth and entrepreneurial activity rate for an economy in a particular year. Observations with GDP growth below the 5% percentile and above the 95% percentile were considered as outliers and removed from the sample. Red dots represent emerging and developing economies, while blue dots represent advanced economies. Total early-stage entrepreneurial activity rate is the percentage of working-age population who are nascent (i.e., those actively involved in starting a new business) or new entrepreneurs/young business owners (i.e., those running a new business that is less than 42 months old). Opportunity-driven early-stage entrepreneurial activity is the percentage of individuals involved in early-stage entrepreneurial activity who claim to be purely or partially driven by opportunity as opposed to having no other options for work. Necessity-driven early-stage entrepreneurial activity is the percentage of individuals involved in early-stage entrepreneurial activity who claim to be motivated by necessity (having no better choice for work) rather than opportunity.  Income per capita increases necessity-driven entrepreneurship. GDP = gross domestic product. Notes: Each dot represents annual percentage GDP per capita growth and entrepreneurial activity rate for an economy in a particular year. Observations with GDP per capita growth below the 5% percentile and above the 95% percentile were considered as outliers and removed from the sample. Red dots represent emerging and developing economies, while blue dots represent advanced economies. Sources: Global Entrepreneurship Monitor database; World Bank. World Development Indicators online database (accessed 25 January 2022).
TEA is one of the main indicators in the GEM database. It is significant because some TEA entrepreneurs contribute to innovation, job creation, and economic development.
GEM defines TEA as the percentage of working age population that is actively involved in starting a new venture and/or managing a business less than 42 months old. TEA thus includes two types of entrepreneurs, namely nascent entrepreneurs and young business owners, who are engaged in new business activity.
GEM distinguishes two types of entrepreneurial activity based on individual entrepreneurial motivation: OEA and NEA. We include these two variables in the analysis since several studies found that the effect of entrepreneurship on economic growth depends on the type of entrepreneurship. Figure 3 looks at the cross-sectional relationship between economic growth and early-stage entrepreneurial activity. The economies are ordered on the basis of the level of entrepreneurship. Figure 3 shows no clear pattern between entrepreneurship and growth. Figure 4 illustrates the trend between the ratio of opportunity to NEA and GDP per capita of an economy. The ratio is a measure of the relative importance of OEA, which tends to be more productive, relative to NEA (Acs et al. 2008). The fitted line shows a positive relationship between GDP per capita and the entrepreneurship ratio. In other words, entrepreneurship is motivated more by opportunity than necessity in richer economies.
Intriguingly, the single-year cross-sectional patterns of 2015 in Figure 3 and  The association between entrepreneurship and capita growth is broadly mixed across economies.  In addition to entrepreneurship, our key independent variable of interest, we included several control variables that can also influence economic growth. These are standard variables drawn from the empirical literature on growth. 2 They include physical investment, which is measured by the ratio of investment to GDP; human capital, which is measured by secondary education enrollment level; population growth; and economic openness. The initial GDP and lag of GDP growth or GDP per capita growth were also included.  Table A2, we summarized the dependent, independent, and control variables used in this study, including their definition and data sources.
The empirical model is 3 yi,t = β1ENTi,t-1 + β2Xi,t + µi,t i: represents the economy and t is time; 2 According to Solow (1956) and Swan (1956), investments in physical capital and labor are the main factors in the growth model. Romer (1986) adds knowledge into the growth model. 3 We have estimated with two sets of dependent variables, GDP growth and GDP per capita growth and the result of GDP per capita growth is presented in Tables A5 and A6 in the Appendix. yi,t : growth of GDP; ENTi,t : the types of entrepreneurships; Xi,t : the control variables; and µi,t : the error term.

IV. EMPIRICAL RESULTS
In this section, we report and discuss the main findings of our empirical analysis.

A. Estimation Result
Our regression results, based on the fixed-effects estimation, of the baseline empirical model in equations (1) and (2) are reported in Tables A5 and A6 of the Appendix.
We reported the regression results of the same models for advanced economies and emerging and developing economies. Additionally, we separately reported the estimation results without control variables in Tables A7 and A8.
In order to address potential reverse causality from economic growth to entrepreneurship activity, we used the lag of entrepreneurship activity rates. Although entrepreneurship can contribute to economic growth, as explained above, growth can also affect entrepreneurship. For instance, there may be more entrepreneurial opportunities when the economy is booming. Further, by including the lag of economic growth as an independent variable, we tried to limit the bias from omitted variables.  (Table A9 of the Appendix). In addition, we report the summary statistics in Table A3 and the correlations in Table A4 of the Appendix.
Overall, for developing economies, our results indicate that the expansion of manufacturing amplifies the positive growth effects of OEA whereas the expansion of services strengthens the positive growth effects of NEA.

Economies
Before we assess economic significance, we conduct a Chow test to compare the subsamples of advanced economies and developing economies, as shown in Table A9. The level of entrepreneurship varies among economies at different stages of economic development. A comparison of the two-economy groups reveals that TEA is higher in emerging and developing economies, possibly because entrepreneurship is expanding faster than in advanced economies, where entrepreneurship is more mature. NEA is also higher in emerging and developing economies (Table A10 and Figure 5). The estimation results in Table A8 imply that an increase in OEA activity rate from the mean level of the developing economies to the mean level of the advanced economies (55.02 -42.68 = 12.34), together with a standard deviation increase in the share of manufacturing's valueadded in GDP (6.62), is associated with 0.005 × 12.34 × 6.62 = 0.41% increase in annual GDP per capita, or 4.1% increase in a decade. C. Level of Entrepreneurship in Different Income Groups of Economies 4 Figure 6 and Table A11 show that TEA rate is higher in middle-income and low-income economies than in high-income economies. On the other hand, OEA is highest in highincome economies while NEA is highest in low-income economies. The relative underdevelopment of OEA in middle-and low-income economies suggests that the expansion of such entrepreneurship may yield potentially large growth gains. 4 The World Bank divides the world's economies into four income groups-low, lower-middle, upper-middle, and high-income economies. The classifications are updated annually on July 1 and are based on previous year's GNI per capita in current United States dollar (using the Atlas method exchange rates). We followed the income classifications of the World Bank in 2021. Low-income economies have incomes of less than $1,046; lower middle-income economies have incomes of $1,046-$4,095; upper middle-income economies have incomes of $4,096-$12,695; and high-income economies have incomes of more than $12,695.

D. Level of Entrepreneurship in Different Regions
According to the comparison of entrepreneurship of different regions in Figure 7 and  Figure 7). The estimation results of Table A8 imply that an increase in OEA activity rate from the mean level of the East Asia and Pacific

V. CONCLUDING OBSERVATIONS
Entrepreneurship, or the activity of starting and running a business, is a vital ingredient of economic growth and development. Entrepreneurs contribute to innovation, and they are central to dynamic Schumpeterian competition and broader economic dynamism. In this paper, we contribute to the entrepreneurship literature by performing cross-sectional analysis to examine the link between entrepreneurship and economic growth. We divide total early-stage entrepreneurship into opportunity-driven early-stage entrepreneurship versus necessity-driven early-stage entrepreneurship to capture the heterogeneity of entrepreneurship. In addition, we divide our sample economies into advanced economies versus developing economies.
We do not find evidence of a positive link between aggregate entrepreneurship and economic growth. This is consistent with the hugely heterogenous nature of entrepreneurial activity. At a broader level, our empirical evidence points to the importance of distinguishing between different types of entrepreneurship and different groups of economies. In particular, for developing economies where manufacturing is relatively important, we find that opportunity-driven entrepreneurship is positively linked with growth. Intuitively, big technological advances in the manufacturing sector create a lot of opportunities for innovative entrepreneurs whereas other entrepreneurs gradually adapt to the slower pace of technological progress in the services sector.
To sum up, we do not find a statistically significant link between total entrepreneurship and economic growth, but we do find significant links between growth and the interaction of sectoral shares and different types of entrepreneurship. Our results imply that such effects can also be of sufficient magnitude to be economically significant. For instance, an increase in opportunity-driven entrepreneurship activity rate from the mean level of the developing economies to the mean level of advanced economies, together with a standard deviation increase in the share of manufacturing's value-added in GDP, is associated with 0.41% increase in annual GDP per capita or 4.1% increase in a decade.     Table   Variables (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

APPENDIX
(1) Gross domestic product (GDP) growth 1.00 (2) GDP per capita growth 0.90 1.00 (3) Total early-stage entrepreneurial activity rate 0.21 0.09 1.00 (4) Opportunity-driven early-stage entrepreneurship activity -0.08 -0.12 -0.16 1.00  33.20 GDP = gross domestic product. Notes: We report robust standard errors in parentheses and rounded off the numbers to three decimal places. *** , ** and * denote statistically significant at the 1% level, 5% level, and 10% level, respectively. Source: Authors' calculations. Notes: We report robust standard errors in parentheses and rounded off the numbers to three decimal places. *** , ** and * denote statistically significant at the 1% level, 5% level, and 10% level, respectively. Source: Authors' calculations. .20 GDP = gross domestic product. a We report the estimation without control variables: investment (% of GDP), population growth (annual %), education and economic openness (% of GDP). GDP = gross domestic product. Notes: We report robust standard errors in parentheses and rounded off the numbers to three decimal places. *** , ** and * denote statistically significant at the 1% level, 5% level, and 10% level, respectively. Source: Authors' calculations. .20 GDP = gross domestic product. a We report the estimation without control variables: investment (% of GDP),population growth (annual %), education and economic openness (% of GDP). Notes: We report robust standard errors in parentheses and rounded off the numbers to three decimal places. *** , ** and * denote statistically significant at the 1% level, 5% level, and 10% level, respectively. Source: Authors' calculations.  Prob > chi 2 = 0.0001 Prob > chi 2 = 0.000 Prob > chi 2 = 0.000 GDP = gross domestic product. Note: ADV represents advanced economies and EMD represents emerging and developing economies. Ind represents Industry, Mfg represents Manufacturing and Svcs represents Service. Source: Authors' calculations.