FDI & New Business Startups: Does Financial Development Matter?

: The present paper intends to investigate the relationship of foreign direct investment and new business startups in the presence of ﬁnancial development in EAGLE countries, an annual unbalanced data during the period from 2006 to 2016 is used. We apply system GMM approach to estimate the models. Findings suggest that foreign direct inﬂows boost new business start-ups in emerging countries. Moreover, the two measures of ﬁnancial development, domestic credit to private and ﬁnancial sector have shown a signiﬁcant and positive relationship with FDI. However, the mix results of business regulations and business density is found, in model 1 and 3, the relationship is positive, whereas, in model 2 and 4, the relationship is negative but insigniﬁcant. Essentially, it is also noted that ﬁnancial development facilitates the positive spillovers of FDI on new business startups. Therefore, we advise policymakers to regularize the ﬁnancial market in such a manner that attracts more FDI and eventually augment the new business opportunities.


Introduction
Over the last few decades, substantial progress in the flow of investment has been observed across countries, particularly in foreign direct investment. After the removal of cross-border restrictions, companies started expanding their operations into other countries to maximize profit. This rapid expansion attracted researchers to study the cause and effect of FDI. A vast amount of literature evidence that foreign direct investment not only benefits firm profitability and performance but also affects the productivity of the host country. FDI inflows can have a long-term effect on the economic development, since it has a direct link with investment and production (Fahed, 2013). It assists the economies by providing superior knowledge, managerial know-how, marketing skills, and advanced technologies. Moreover, it also influences the efficient development of domestic markets.
In addition to the significance of foreign direct investment and its role in economic progress, productivity, and business performance, there is also a consensus among policymakers, business professionals, and academicians that new business creation is a salient factor that influences the economic growth. Several studies evident that the entrepreneurial and India have the lowest new business registrations and foreign direct inflows. But the overall trend of EAGLE countries has been increasing throughout the period. Due to its potential, we selected this particular region called EAGLEs and try to examine the impact of FDI on new business startups and also examine whether financial sector development facilitates positive spillovers of FDI or not.

Literature Review
In the past literature, many studies have been conducted that primarily focused on the determinants of foreign direct investment, its effect on the host economy and productivity (Haskel, Pereira, & Slaughter, 2007;Görg & Strobl, 2003). However, in this paper, we are more focused on two strands of literature. One strand determines the crowd-in and out effect of foreign investment, while, the second strand examines the financial development of the country and its role in explaining the spillover effects of FDI on the economy, more specifically on the entrepreneurship.
Prior to discussing the aforementioned strands of literature, we also review some past studies related to foreign direct investment, financial development, and economic growth. The empirical findings of Pegkas (2015) supported the economic theory that foreign direct investment positively affects economic growth, suggesting that countries ought to create a sustainable environment for FDI by reducing market distortions and enhancing macroeconomic stability. Similarly, positive spillovers of FDI with human development is strongly contribute to economic growth.
In the first strand of contemporary literature, spillover effects (crowd-in/crowd-out) of FDI generally more focused on domestic investment and provided mixed results. According to the literature, there are several channels through which FDI can have a positive or negative spillovers on the new business formation. One of the important channels which positively affects entrepreneurship is the demonstration effect; it occurs when domestic firms adopt similar practices and technologies introduced by foreign firms. Labor mobility is another channel through which transmission of ideas, skills, and technologies occur. Previously employed and trained local workers by foreign firms equipped with their superior skills when they work with local firms. They can also utilize skills in establishing their own business. Furthermore, domestic firms can also seize export opportunities by following the channels established by foreign firms.
Contrary to the above, there are some channels through which FDI can also have a negative spillover on entrepreneurship. Entry of foreign firms in the local market raises the threat of competition for the local firms. Due to this competition, the average fixed cost of starting a new business increases. Foreign firms can also crowd out local businesses by providing better working conditions, facilities, and attractive salaries to local workers relative to their domestic firms, resulting potential worker end up in working foreign enterprise instead of utilizing their skills in starting own business. Another channel through which foreign investment inversely affect domestic business is demand effect. The demand for local intermediate goods from MNCs improves the performance of domestic firms. Competition between foreign firms and domestic firms is based on the factors and product markets. The external pressure from MNCs on domestic firms reduces the price index of finished goods, pushing domestic firms to increase efficiency. Firms, who are unable to be efficient and compete have to exit the market. This process lowers the demand for local intermediate goods and in turn crowd-out foreign investments.
Several studies supported the positive spillovers of foreign direct investment in new business creation. For instance, Smarzynska (2004) corroborated the positive spillover effect of FDI by arguing that diffusion of superior knowledge, skills, and technology provide new entrant opportunity to the indigenous people. As contended by Caves and Caves (1996), foreign firms tend to be more productive than the domestic firms. Kim and Li (2014) noted that foreign direct investment has a positive effect on domestic businesses.
In addition to this, Borensztein, De Gregorio, and Lee (1998) also supported the notion that foreign inflows encourage new business startups, particularly in developing countries. Barrios, Görg, and Strobl (2005) studied the impact of foreign direct investment on the entry of domestic firms in host countries. They found that the positive externality of FDI depends on the efficiency of domestic firms and the large amount of capital transferred through FDI. The rapid adaptation of new competition by domestic firms can also be one of the reasons of a positive externality. On the other hand, Kim and Li (2014) found that FDI crowd-in business creation in economies with low educational attainment and weak infrastructures.
In contrast to the above, negative spillovers of foreign investment can also be found in the past literature. The study of Aitken and Harrison (1999) pointed out the negative externalities of FDI on the host economy. They concluded that foreign firms' entry reduces the productivity and efficiency of domestic firms due to the high competitive pressure. Agosin and Machado (2005) also found that FDI crowd-out local businesses. It is mainly due to the weak institutional environment, which makes domestic firms less competitive against foreign firms (Aidis, Estrin, & Mickiewicz, 2012).
Another study highlighted the reason for negative spillovers of FDI due to the local labor markets (Lipsey & Sjöholm, 2004). De Backer and Sleuwaegen (2003) posit that foreign direct investment and imports both have a crowd-out effect on domestic business on labor and product markets, they both reduce the entry of local firms in the market. Similarly, competition and labor mobility are two important reasons that crowd-out foreign investment in domestic business (Danakol, Estrin, Reynolds, & Weitzel, 2017).
In contrast to the above studies, the informal sector is also an integral part of entrepreneurial activities which strongly contribute to economic growth of the country. Very few researchers have studied the relationship between informal entrepreneurship and other macroeconomic factors. See, for example, Goel, Saunoris, and Zhang (2015) studied whether innovation effects economy through informal entrepreneurship. Results reveal that innovation in the informal sector spurs the informal entrepreneurial activities and hence overall growth. Additionally, Jiménez, Palmero-Cámara, González-Santos, González-Bernal, and Jiménez-Eguizábal (2015) examined the impact of formal education on formal and informal entrepreneurship. They found that formal education increases formal entrepreneurial activities by enhancing human capital and self-confidence. At the same time, it reduces informal sector activities due to awareness of possible negative consequences.
On the other hand, the second strand provides studies related to the interplay between financial market, foreign investment and economic growth (Durham, 2004;Hermes & Lensink, 2003;Alfaro et al., 2004). Past studies find that financial sector development is an important element that enhances the absorptive capacity of the country. As a result, it enables foreign investments to have a positive externality on the growth of the economy.
By reviewing above-mentioned studies, it is concluded that foreign direct investment and financial development both are important determinants of economic growth as a whole. Moreover, the importance of entrepreneurial activity in economic growth is also highlighted in the literature. However, studies investigating the spillovers of foreign direct investment on new business creation in the presence of financial development is missing. To bridge the economic literature gap, we intend to investigate the simultaneous spillovers of FDI and financial sector development on entrepreneurship.

Model Specification
In this study, we try to examine the effect of foreign direct investment in the new business creation and also explain the role of financial development. After reviewing past studies, we derive the following function that explains the above relationships; Here, N ewBus is the new business density, F DI tests the effect of the foreign direct investment on new business creation. DC is the domestic credits including both financial and private sector, X are the control variables used in the study. Unlike Munemo (2017), we develop four separate models for estimations in order to avoid multicollinearity problem. It is likely to occur when the predictors have a correlation in the model. Multicollinearity inflated standard errors, deflated significance level and hence give biased results. In our case, we use interaction terms of FDI and financial development, if both the predictors are used simultaneously in a model it will distort the results because of high correlation, therefore, we develop four distinct models to avoid multicollinearity. Following are the parametric form of the models; Where N ewBus is the dependent variable used as a proxy for new business startups, lnF DI is the natural logarithm of foreign direct investment used as the main variable. DCP and DCF denote as the domestic credit to the financial sector and private sector, both the variables used as a measure of financial development. Moreover, the interaction terms DCP it * lnF DI and DCF it * lnF DI test the role of the financial market development in explaining the impact of FDI on new business startups. In addition, lnGDP and BR are used as the control variables. lnGDP is the gross domestic product used to measure economic growth. Whereas, BR is the business regulations comprised of three components such as the time required for business, the cost required for business and startup procedures. While, , µ, ζ and n are the error terms and subscripts i and t define the cross-sections and time span.

Data and Estimation Procedure
We employ unbalanced panel data from the period of 2006-2016 of emerging and growth leading economies (EAGLEs). According to BBVA research, there are 15 EAGLE members as of 2016, list of countries is also attached in the appendix. Due to the unavailability of data, we have excluded four countries from the panel such as Iran, Bangladesh, Vietnam, and Egypt. The data structure is unbalanced due to the missing cases in new business density and business regulations. Therefore, some countries have a minimum four-years data and maximum 11 years' data. New business startups (entrepreneurship) is measured by new business density, defined as the total number of newly registered businesses with the limited liability per 1,000 from 15-64 working age population. Also, the new business density data only covers the formal business sector. Though the informal sector is also an inevitable part of entrepreneurship in most of the developing nations, however, it is excluded from the analysis due to the unavailability of data. In addition, we have only used those formal businesses which have limited liability, and the data of re-registered businesses were also excluded in order to avoid the distorted view of entrepreneurship.
Furthermore, business regulations for new startups is used as a control variable because the business regulatory environment of a country is considered an important element of entrepreneurial activity. Following the past studies (Klapper et al., 2006;Klapper & Love, 2010;Djankov, La Porta, Lopez-de Silanes, & Shleifer, 2002), which used three measures of new business regulations such as, cost of business, startup procedures and time required to start a business. By applying principal component analysis, we created an index of business regulations. All the data of new business density and business start-up regulations are obtained from the Doing business site (a project of World Bank). The gross domestic product is another control variable used in the study, measured as the annual growth rate. As noted in earlier studies, business regulations and GDP both directly or indirectly affect new business creation. The good regulatory business environment can have an expected positive relationship with entrepreneurship or vice versa. Whereas, greater economic growth may also open up opportunities for new business.
On the other hand, the main variable FDI is an investment made by foreign investors. It is measured by total net inflows (% of GDP) includes long-term and short-term capital, equity capital, etc.). Domestic credit to the private and financial sector are used as a proxy for financial development and are measured as the percentage of GDP. These measures are more comprehensive than other measures such as domestic credit to the private sector by banks and also widely used by several past researchers (Hermes & Lensink, 2003;Demirgüç-Kunt & Levine, 1996). The data on foreign direct investment and domestic credits to (financial & private) sectors obtained from world development indicators (WDI) World Bank.
In the present study, we use the Arellano and Bover (1995) system GMM approach to estimate the models. This approach is preferred on the basis that conventional techniques, such as fixed effect, OLS, and others give biased results when there is a presence of lagged dependent variable, reverse causality and omission of variables (da Silva & Cerqueira, 2017). In our model, we consider FDI and GDP as endogenous variables as it reacts to the fluctuations in business creation. Therefore, we apply a system GMM approach in order to address all of the above issues. In addition, the study has not applied any prerequisite tests such as unit root, cointegration due to the unbalanced type of data.

Data Analysis
Summary Statistics Table 1 shows the summary statistics of foreign direct investment, new business creation, domestic credits (financial & private), gross domestic product and business regulations of the emerging and growth leading economies (EAGLEs). It is noted that average new business registration with limited liability per 1,000 working-age population (15-64) in the selected emerging economies is 4.75. Moreover, the average domestic credit to the financial sector is 87.95% more than the domestic credit to the private sector, which is just 72.64%. In addition, the average economic growth of these economies is 1.44%, in which 1.04% is due to the foreign investments. On the other hand, startups regulations used in the study are comprised of three components, such as start-up procedures, the time required and cost of business. It is observed that the average start-up procedures to start a business in EAGLE countries is 9 with the minimum of 2 and maximum of 18 procedures. While the average time required to start a business is 23 days with the minimum of 1 day and a maximum of 86 days. However, the average cost of business required is 14% of GNI per capita with the minimum of 0.6% and the maximum of 59%.

System Generalized Method of Moments (SGMM)
We apply the system generalized method of moments (SGMM) to estimate the relationship between considered variables. Within the context of the present study, this approach is preferable over the other dynamic panel approaches such as fixed effect estimator, POLS, one-step difference GMM and others. Unlike system GMM, these techniques are inconsistent when the time span is small (Acemoglu, Johnson, Robinson, & Yared, 2008;Nickell, 1981;Anderson & Hsiao, 1981). In addition, this technique is also useful and give consistent results in the presence of endogeneity problem. To deal with the unbalanced panel data, we followed the methodology of Heid, Langer, and Larch (2012) and applied system GMM approach proposed by Arellano and Bover (1995). Table 2 reports system GMM estimations of all the four models. Model 1 and 2 estimate the individual effect of foreign direct investment and financial development, whereas, model 3 and 4 estimate the interacting effect of both the variables on new business startups. It is noted that foreign direct investment has a positive effect on new business creation, implying that foreign inflows play an inevitable role in the entrepreneurship. Similarly, domestic credit to the private and financial sector also has a positive and significant effect on the new business creation. However, the gross domestic product has an insignificant but a positive effect on the new businesses. Moreover, the mixed effect of business regulations found in all the models. On the other side, it is interestingly found that financial markets play a key role in facilitating foreign inflows and its effect on new business creation. It is hereby noticed that both interaction terms have a positive and highly significant impact on the new business startups.  From the above empirical findings, it is concluded that foreign investment in emerging economies has a crowd-in effect on the entrepreneurship. It is possibly because of the knowledge and skills transfer, diffusion of advanced technologies, etc. Domestic firms exploit the opportunity by following the mechanism set by foreign firms. Therefore, it might be the reason for the positive relationship between foreign direct investment and new business creation. In addition, domestic credit (financial & private sector) both have a positive and significant impact on the new business startups. It is obvious when the access to funds is available in the market, it motivates entrepreneurs to invest more in their new ventures. Interestingly, the effect of the gross domestic product, which is a proxy of economic growth is positive and insignificant, it means, the growth of the economy does have a relationship with entrepreneurship, but there are some other prevalent factors that affect more. Finally, the results reveal the significance of financial markets explaining the role of foreign investment in entrepreneurship. Previous studies have also corroborated these findings and stated that the domestic financial environment is considered as one of the pivotal elements for the new business creation (Alfaro et al., 2004;Durham, 2004;Hermes & Lensink, 2003). If the country is financially developed, it facilitates the positive spillovers of FDI on new business startups.

Conclusion
Knowing the importance of new business formation, numerous studies have been conducted that focused on the factors affecting entrepreneurship. In the recent past, it has been identified that foreign investment inflows create opportunities for local entrepreneurs and stimulate new business formation. Therefore, in this paper, we investigated the effect of foreign direct investment on the new business startups and also explained the role of financial development in facilitating the spillover effects of FDI. This study has been carried out notably on the EAGLE countries over the period of 2006-2016. For unbalanced panel data, we used the generalized system method of moments (SGMM) approach to estimate the relationship. Empirical results revealed that foreign direct investment crowdin new business startups in emerging economies (EAGLEs), whereas, domestic credit to financial and private sector, both have a positive and significant effect on new business creation. In addition, it is also noted that gross domestic product has an insignificant but a positive effect on new business startups, while the mix relationship noted between business regulations and new business formation in all the four models. Most importantly, both the interaction terms have a positive and significant effect on the new business creation, indicating that the financial market has a fundamental role in explaining the relationship of foreign inflows and new business startups.
The empirical findings obtained from the present study can draw some reasonable implications for the policymakers. As the study evidence that foreign direct investment crowd-in new business formation, it is likely because of the greater amount of FDI flow and the efficiency of domestic firms. The rapid adaptation of local competition leads to an improvement of the local firm's efficiency. Therefore, the policy should be aimed to facilitate domestic firms to enhance their capacities and subsequent efficiencies. Moreover, governments need to attract the right type of foreign direct investment that provides optimal benefits to the host economy as well as their local businesses. Also, policies should be made that encourage foreign firms to participate in collaborative projects with local firms and pave the way for new businesses. In addition, the empirical findings also suggest that financial development plays an important role in explaining the relationship between FDI and new business formation. Thus, policies should be designed to regularize existing financial sector in order to improve financial depth, access, and intermediation. On the other side, this study also opens up some new avenues for the future researches. One, the present study only focused on 11 countries listed in EAGLEs. Also, we used unbalanced panel data with minimum of four years and maximum eleven years over the period of 2006-2016. The studied model can also be strengthened by using some other measurement of financial development.