THE SHADOW ECONOMY, HUMAN DEVELOPMENT AND FOREIGN DIRECT INVESTMENT INFLOWS

During the past few decades, competition between countries has intensified. Every country seeks to become an essential player in international economic relations and take a prominent place in the world market. In this context, foreign direct investment inflows are accepted as a source of competitiveness through knowledge, know-how and technology transfer, but competitiveness is also accepted as a significant determinant of foreign direct investment attraction. Therefore, the specification of foreign direct investment inflow determinants is also important to improve competitiveness. In this research article, we aim to evaluate the impact of shadow economies and human development on foreign direct investment inflows as a possible determinant of competitiveness in 11 post-transition EU members over 1995-2015 period. The methodology employed in the applied section includes comparative and systematic literature analysis as well as second generation panel cointegration and causality analyses regarding both cross-sectional dependence and heterogeneity. The empirical analyses revealed that both the shadow economy and human development are significant determinants of foreign direct investment inflows. The causality analysis revealed a mutual interaction between foreign direct investment inflows and human development for all the countries in the sample, but a two-way causality between the foreign direct investment inflows and shadow economies only for Bulgaria, Croatia, and Romania and a one-way causality from shadow economies to the foreign direct investment inflows in the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Slovakia, and Slovenia. The long-run analysis revealed that shadow economies negatively affected foreign direct investment inflows, while human development positively affected foreign direct investment inflows.

The related literature on the determinants of FDI inflows have focused on many economic, institutional, social, and cultural factors such as market size, economic growth, inflation, openness, labor costs, tax rate, infrastructure, political environment, government intervention level and property rights (Tocar, 2018). However the literature has generally disregarded the interaction among the FDI inflows, the shadow economy and human development. Given the positive effects of the FDI inflows, in this paper we focus on the influence of shadow economies and human development on these inflows The phenomenon of the shadow economy is inherent to any country, and in accordance with its size it more or less significantly affects a country's social welfare and policies. Due to the multiple causes involves, including among these inefficient taxation, improper functioning of public institutions and excessive governmental interference in the labor and trade/service markets, a shadow economy jeopardizes the sustainable economic and social development of a country. As noted by Mara (2011), "The shadow economy affects the market functions as a phenomenon of erosion of the formal economy because speculate any opportunities generated by non-synchronization and indecision, following infiltration into any space left open by it." Attempting to cover their budget deficits, the governments of the countries with large shadow economies may find it attractive to invoke FDI to potentially raise taxes on domestically sold goods and services as well as on international trade (Nikopour et al., 2009). At first glance, this attitude proposes that high shadow economies may cause higher inflows of FDI, especially keeping in mind that MNEs tend to invest in developing economies with ambiguous legislation, high corruption levels and tax havens (Okada & Samreth, 2010;Davidescu & Strat, 2015, Jones & Temouri, 2016. On the other hand, some studies reveal that high shadow economies may discourage FDI due to the unacceptably high levels of business environment uncertainty caused by poor control and corruption (Tanzi, 2002;Castro & Nunes, 2013;Fahad, 2016, etc.). The conclusions of the effects of FDI inflows on the shadow economy in a host country are also bidirectional: some studies (Deilami, 2010;Nikopour et al., 2009, etc.) propose that FDI may help foster a shadow economy, while others (e.g., Davidescu &Strat, 2015) suggest that in encouraging FDI, MNEs bring with them higher standards of regulation compliance, which in turn may contribute to a reduction in the size of the shadow economy in a host country. However, previous studies have not provided unequivocal results concerning the causal relationship between FDI and shadow economies.
Human development is also a significant determinant of competitiveness and economic growth, with FDI assumed to affect economic growth through the enhancement of human capital by education and training, along with the transfer of new information, know-how, and technology into the investee country (Li & Liu, 2005;Majeed & Ahmad, 2008;Agbola, 2013). However, human capital may contribute to FDI attraction, as FDI proceeds more readily in countries with relatively higher human capital development (Majeed & Ahmad, 2008). Therefore, theoretically a two-way interaction between FDI and human development is expected, but the empirical studies conducted have been generally focused mainly on the impact of FDI on human development (Zhuang, 2017).
The present paper investigates the influence of shadow economies and human development on the FDI inflows for sample post-communist EU countries, and the article seeks to contribute significantly to the relevant literature in three ways. First, whereas certain factors regarding FDI inflows have been investigated extensively in the related literature, the shadow economy as a potential factor has been researched by relatively few scholars. Secondly, no studies on the interaction between the shadow economy and the FDI inflows have been conducted specifically for EU transition economies, therefore, the uniqueness of the study sample is another contribution of the paper. Lastly, the use of both a cointegration test and causality test regarding the crosssectional dependence and heterogeneity enable us to obtain more reliable results considering the relative lack of relevant empirical literature.
In the first part of the paper, a theoretical background regarding the relationships among a shadow economy, FDI and human development is presented, with the second section dedicated to the presentation of methodology, followed by the results of the empirical calculations in the third part of the article.

THEORETICAL BACKGROUND
The phenomenon of the shadow economy is complex and multifaceted, a situation caused by the many different determinants involved, among which the burden of taxes and social insurance contributions, along with the associated high level of bureaucracy and corruption, as well as inefficiency of regulatory and legal frameworks (Schneider, 2016;Medina & Schneider, 2018;Remeikienė et al., 2018, etc.) are recognized as most influential.
In researching the links between a shadow economy and FDI, some authors focus on particular determinants of the former (e.g., corruption, tax avoidance, poor quality of public institutions), while others follow a more general approach. Among the previous findings concerning the links between a shadow economy and FDI, Nikopour et. al.  Peres et al. (2018), the institutional quality positively and significantly affected FDI in developed countries, but the impact on institutional quality on FDI in developing countries was insignificant. Lee & Park (2013) found out that FDI are attracted to the countries with smaller shadow economies and stronger public institutions. According to Davidescu & Strat (2015), in Romania, during 2000-2010, there existed an unidirectional short-run causality running from FDI to the shadow economy and the relationship between FDI and the shadow economy was negative in a short-run. The the relationship between corruption and FDI was negative in 48 countries (Hossain, 2016). Similar results have been obtained by Canare (2017) and Hakimi & Hamdi (2017) in their studies: corruption had a negative effect on the FDI inflows and investment activities. In Ali & Bohara (2017) study, a general approach to the links between FDI and the shadow economy is followed. Their findings indicate that, in general, the size of the shadow economy in a host economy relative to an investor's economy can significantly contribute to the attraction of FDI. The main methods used in calculations were the panel data Granger causality analysis, causality methods, GMM estimator, gravity model, Threshold effect model, standard panel regression model, Toda-Yamamoto causality, random effect model (REM), feasible general least squares method (FGLS), panels corrected standard errors (PCSE), correlation and variance inflation factor analysis. Davidescu & Strat (2015) as well as Deilami (2010) place the importance of their studies on tax avoidance which, in their opinion, significantly raises the capacity of capital to cross borders to escape the obligations of national taxation, and thus promotes investment in more favourable economic environment all over the world (as it was noted by Ali & Bohara (2017), frequently, in tax heaven areas). Deilami's (2010) empirical results suggest that higher shadow economy causes higher FDI, and vice versa, whereas Davidescu & Strat (2015) reveal a unidirectional shortrun causality, running from FDI to the shadow economy, and a short-run negative relationship between FDI and the shadow economy. The findings are explained proposing that FDI may stimulate a host economy and generate reforms in its taxation system. On balance, previous studies mainly analyze the relationship between FDI and the shadow economy by invoking such shadow economy determinants such as corruption, tax avoidance and institutional quality (in particular, in terms of IPR protection). The studies on the relationship between FDI and institutional quality provide least contradictory results and, in general, propose that smaller shadow economies with stronger public institutions, capable of protecting IPR, are able to attract more FDI inflows than larger shadow economies. The studies, focused on the relationship between FDI and tax avoidance, are much more contradictory and suggest that the links between the variables can either be positive or negative, bidirectional or unidirectional. The same applies to the studies addressing the links between FDI and corruption. It should also be noted that the relationship between FDI and the shadow economy may vary depending on the level of a country's development and trade openness.
Human capital is another important determinant underlying FDI inflows, but generally disregarded in the relevant literature, although the two variables may theoretically affect each other. The empirical studies on the effect of human capital proxied by different indicators such as illiteracy rate, primary/secondary/tertiary school enrolment rates, and human expenditures on the FDI attraction have remain inconclusive. In this context, Root & Ahmed (1979), Schneider & Frey (1985), and Narula (1996)

AIM, METHODOLOGY AND DATA
The main purpose of this article is to investigate the impact of shadow economy together with human development on the FDI inflows. To fulfil the defined purpose, the following objectives were set: 1) to review previous scientific findings on the relationship between FDI, shadow economy, and human development; 2) to select and substantiate the research methodology; 3) to provide results of the empirical research on the relationship between FDI and the shadow economy.
The s it term in the above-mentioned equation represents the partial sum of error terms, while is the long-run variance. Both terms are derived from the cointegration model estimated by a full, modified ordinary least squares method. For the test involving LM + N , critical values, bootstrapping should be employed in the event of a cross-sectional dependence among the series.
Lastly, the reciprocal interaction among the FDI inflows, shadow economy, and human development was analyzed with bootstrap Granger causality test of Kónya (2006) regarding both cross-sectional dependency and heterogeneity. Furthermore, the test is based on the Wald test with country-specific bootstrap critical values, so it does not require the joint hypothesis for all members of a panel. Lastly, it does not need any pre-testing and in turn is not exposed to the weaknesses resulting from the pre-tests.

EMPIRICAL ANALYSIS
In the econometric analysis, the first cross-sectional dependence was tested with the tests of LM (lagrange multiplier), LM CD (LM cross-section dependence) and LM adjusted and the test consequences were shown in Table 3. The null hypothesis suggesting the cross-sectional independence was denied at 1% significance level. So, the tests pointed out the presence of cross-sectional dependence among three series. The cointegration coefficients were estimated by FMOLS (Full Modified OLS) estimator taking notice of heterogeneity and the test consequences were shown in Table 7. The test consequences revealed that the shadow economy size negatively affected the FDI inflows overall panel, but human development had positive effects on the FDI attraction in the overall panel.
However, the individual coefficients revealed that the impact of shadow economy and human development on the FDI inflows varied from country to country. The shadow economy size had the largest decreasing effect in Estonia and Bulgaria, while human development had the largest positive effect in Croatia and Latvia. The causal interaction among FDI inflows, shadow economy, and human development was tested by bootstrap panel Granger causality method of Kónya (2006) and the test consequences were shown in Table 8 and 9. The causality analysis revealed a two-way causality between FDI inflows and shadow economy in Bulgaria, Croatia, and Romania and a one-way causality from shadow economy to FDI inflows in the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Slovakia, and Slovenia. A causality analysis between FDI inflows and shadow economies revealed a two-way causality between FDI inflows and shadow economies in Bulgaria, Croatia, and Romania, i.e. a mutual interaction between FDI inflows and the shadow economy in Bulgaria, Croatia, and Romania was indicated in the short run. However, a one-way causality of shadow economies to FDI inflows was revealed in the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Slovakia, and Slovenia, i.e. the shadow economy had a significant effect on FDI inflows in the short run for these countries. Lastly, the causality analysis disclosed a two-way causality between FDI inflows and human development. The causality analysis between human development and FDI inflows revealed that human development is a significant factor regarding FDI inflows in the short run, while FDI inflows are a significant determinant of human capital development. In other words, FDI inflows and human development foster each other in the short run.

DISCUSSION
The study aims to explore the influence of the shadow economy and human development on FDI inflows. The related literature about the interaction between FDI and the shadow economy remains inconclusive, but the institutional quality proxied by various indicators generally had a positive effect on FDI inflows. On the other hand, the effect of human development on FDI inflows varied depending on the type of FDI inflows. The FDI inflows including technology intensive and service industries generally preferred the destinations with higher human capital development. The negative long-run effect of the shadow economies on FDI inflows might have been made possible because each shadow economy generally resulted from a high tax and labor burden. Therefore, the shadow economies may have negatively affected FDI inflows if the additional costs from tax and labor issues were not eliminated by additional incentives for MNEs. Also, a company's decision to invest abroad is based on the interplay of market power, contractual uncertainties, intellectual property rights and other factors of international markets in terms of information. According to Lee et al. (2016), the quality of institutions effects FDI inflows into the host economy's country. In institutionally weak countries plagued by bureaucracy as well as corruption and government predation, FDI attraction is not as strong due to these problems. Furthermore, human capital quality is another important factor in FDI decisions, as MNEs need a given threshold of labor quality to carry out their activities. Therefore, higher human development is expected to positively influence FDI inflows, a result described in our paper. Lastly, the causality analysis disclosed a reciprocal interaction between human development and FDI inflows l (Kheng et al., 2017). Human development triggered FDI inflows, while in turn FDI inflows led to an improvement in human development. On the other hand, the causality direction between the shadow economies and FDI inflows changed depending on the country. Along these lines, a mutual interaction between the shadow economies and FDI inflows was found in Bulgaria, Croatia, and Romania. However, the shadow economies were a significant determinant of FDI inflows in the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Slovakia, and Slovenia in the short run.

CONCLUSION
International capital inflows have increased considerably with the contribution of liberalization and globalization processes during the past four decades. In this context, foreign direct investments with a long-term horizon in particular have caused many economic and non-economic effects in these countries. However, the distribution of FDI flows have change substantially among the countries, with flows to developing countries increasing steadily in recent years, and FDI flows to developed countries decreasing sharply as of 2015. This has caused many scholars to research the causes behind the differences in FDI flows, with many economic and non-economic factors revealed as determinants of FDI inflows. This study aims to make a contribution to the relevant literature by exploring the effects on FDI attraction through the second generation econometric tests of shadow economies and human development, factors which have been rarely researched.
The causality analysis revealed a mutual interaction between FDI inflows and human development for all the countries in the sample, but a two-way causality between FDI inflows and shad-ow economies only for Bulgaria, Croatia, and Romania, and a one-way causality from the shadow economies to FDI inflows in the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Slovakia, and Slovenia. The long-run analysis revealed that the shadow economies negatively affected FDI inflows, while human development positively affected the inflows. Consequently, both the shadow economy and human development have been found as significant determinants of FDI attraction. In this context, institutional and regulatory arrangements contributing to the improvements regarding shadow economies will also foster FDI attraction. Furthermore, human development and FDI inflows show feedback loops with each other. On one hand, higher human development may cause more FDI attraction, on the other, FDI inflows may contribute to human development through the transfer of know-how, management and technology.
A limitation of the research was the time period of the study. This drawback was due to data availability and our disregard of the possible structural breaks of the econometric tests in the study period.