Foreign Direct Investment , Economic Freedom and Economic Growth : Evidence from Developing Countries

This paper has explores the interplay between economic freedom, foreign direct investment and economic growth using panel data analysis for a sample of 79 developing countries from 1998 to 2014 by considering the level of economic freedom, as provided by the “Heritage Foundation”. Panel unit root, pedroni residual co-integration test, generalized least square (GLS), feasible GLS (FGLS), pooled OLS, random effect, fixed effect, poisson regression, prais-winsten, generalized method of movement (GMM) and generalized estimating equation (GEE) methods have used to estimates the relationship. According to the OLS and generalized method of movement the coefficient implies that a one standard deviation improvement in business freedom, trade freedom, size, investment freedom, property rights, freedom from corruption, labor freedom, financial freedom, fiscal freedom, monetary freedom increases FDI by 21.4%, 15.6%, 21.6%, 17.5%, 11.55, 9.1%, 6.9%, 8.5%, 7.4%, 10.3% and 56.1%, 45.3%, 58.3%, 51.6%, 33.7%, 39.2%, 47.4%, 41.6%, 32.5%, 38.5% points respectively and for the economic variable ,the coefficient implies that a one standard deviation improvement in GDPG and GDPPC increases FDI by 24.1%, 17.4% and 30.2%, 33.4% points respectively. By using the other method like random effect, fixed effect, poisson regression, prais-winsten and generalized estimating equation (GEE) method explores that economic freedom in the host country is a positive determinants of FDI inflows in developing countries and also the result suggests that foreign direct investment is positively correlated with the economic growth in the host countries.


Introduction
Various literature have agreed that multinational corporations (MNCs) invest in a specific locations mainly because of the host countries" strong economic fundamentals, such as a large market size, stable macroeconomic environment, availability of skilled labor and infrastructure, that influence the attractiveness of the country to FDI inflows (e.g., Dunning, 1993;Globerman et al., 2003).Because of the transition of the economic phenomena less conventional determinants factors like economic freedom pay close attention for the business and economic researcher.It has been widely acknowledged among growth analysts that a country, which enjoys more economic freedom, tends to attract more FDI inflows and growth faster than country that is being denied enjoying same freedom (e.g., Ayal & Karras, 1998;Cebula & Mixon, 2012;Ajide, 2013).Considering the importance of these factors the Heritage Foundation has developed the Economic Freedom Index (EFI) based on these policy parameters.They have included business freedom, investment climate, trade openness, monetary and fiscal environment in the index.Heritage Foundation is defines the Economic Freedom as -aspect of human liberty that is concerned with the material independence of the individual in relation to the state and other prearranged groups.The highest form of economic freedom provides an absolute right of property ownership, fully realized freedoms of movement for labor, capital, and goods, and an absolute absence of coercion or constraint of economic liberty beyond the extent necessary for citizens to protect and maintain liberty itself.The basic purpose of ensuring economic freedom is to promote entrepreneurship and decentralizes and liberalized economic functions and business environment by decelerating government interferences.According to the Adkins et al. (2002) find that the level of economic freedom at the beginning of the growth period does not contribute significantly to explaining growth, but that positive changes in economic freedom do so.Economic freedom is a significant positive determinant of FDI.Economic freedom always stimulates foreign direct investment and because of unremitting flow of FDI escalates the economic competitiveness in a developing country.The nature of relationship between FDI and economic growth has been a vast discussed matter in the various amount of economic literature.Different literatures have highlights that there are positive and significant relationship between FDI and growth.Chakrabarti (2001), Asiedu (2002) and Zhao (2013) has pointed out that higher economic growth results in greater FDI inflows as it is a measure of the attractiveness of the host countries.There are still debates on this topic especially for the developing countries.According to Hansen and Rand (2006), the consensus seems to be that of a affirmative relationship between FDI inflows and economic growth in host countries provided the receiving countries have achieved a minimum level of educational, technological, and/or infrastructural development.FDI and economic freedom both are significantly correlated with the economic growth but it is also observed among the different developing countries that the host country requires adequate human capital, economic stability and liberalized markets to benefits from long-term capital flows.In this paper, the basic consideration factor is to observe the relationship among economic freedom, economic growth and FDI in the developing countries by using the Heritage Foundation economic index without considering the conventional factors.The paper has incorporated with the various sections; section 2 literature review, section 3 model specification, section 4 empirical evidence and section 5 conclusion.

Literature Review
Because of the radical transition of the business and its relevant fields, traditional determinants (wage costs, infrastructure or macroeconomic policy) of FDI is no longer hold rather less traditional determinants have become more important, like institutions or economic freedom.Economic freedom is a significant determinant of foreign direct investment as well as a noteworthy factor in economic growth (e.g., Barro, 1997;Dawson, 1998;Estrin, Bevan, & Meyer, 2001;Ghura & Goodwin, 2000;Heckelman, 2000).Bengoa, Marta, and Sanchez-Robles (2003) have investigated the relationship between economic freedom and foreign direct investment by using panel data of 18 different Latin American countries from the period 1970 to 1999.Empirical results has illustrated that economic freedom facilitated FDI inflow and the economic growth has also found definitely related with FDI.
Many empirical studies have also found that economic freedom exert a major effect on cross-country differences in both per capita income and economic growth (e.g., De Haan et al., 2006;Azman-Saini et al., 2010;Compton et al., 2011).
By using both fixed effects and first -difference GMM estimation, Levina (2011) has investigated the relationship between foreign direct investment, economic freedom and economic growth.According to the GMM estimation of dynamic model has explored that both of the variables foreign direct investment and economic freedom are positively influence on the economic growth.Gwartney (2009) has penetratingly determined that countries with having enormous amount of economic freedom leads to higher shares of private investment in GDP, higher productivity of private investment, grow more rapidly and achieve higher levels of per capita income than countries with lower levels of economic freedom.Different factors under the economic freedom index have made a significant consequence on unremitting flow of foreign direct investment.Barro (2000) has indentified that protected and secure property rights accelerate the growth performance not only by stimulating investments, but also by increasing the productivity of investments.Demetriades and Law (2006) have found that inadequate sound financial institutions may not succeed in delivering long-run economic growth in low-income countries.
There are also mixed opinion regarding the relationship among economic freedom, foreign direct investment and economic growth.Using generalized method-of-moment system estimator in 85 different countries Azman-Saini, Baharumshah, and Law (2010) has explored that FDI by itself has no direct (positive) effect on output growth.Instead, the effect of FDI is contingent on the level of economic freedom in the host countries.This means the countries promote greater freedom of economic activities gain significantly from the presence of multinational corporations.
Concentrates on Bengoa and Sanchez-Robles (2003) empirical work that FDI is positively and significantly correlated with economic growth, but host countries should accumulated human capital, economic stability, and liberalized markets in order to attain the benefit from long term inflows.Using data on 80 countries for the period 1979-98 Durham (2004) have failed to identify a positive relationship among FDI, economic freedom and economic growth, based on his empirical work he advocated that the effects of are contingent on the ""absorptive capability"" of host countries.

Model Specification
This paper is mainly explores the interplay between economic freedom, foreign direct investment (FDI) and economic growth using panel data analysis for a sample of 79 different developing countries from 1998-2014.As part of the methodological design, the basic equation is illustrated below: Where α 0 , α 1 -α 13 are parameters to be estimated.
e t is stochastic error terms assumed to be independently and identically distributed.
For measuring the relationship among economic freedom, foreign direct investment and economic growth different methods have used.
At first panel unit root test have accomplished for estimating whether the data are stationary or not.

Panel Unit Root Test: Levin, Lin and Chu
Levin, Lin and Chu start panel unit root test by consider the following basic ADF specification.
Where, DY i t = difference term of Y i t ; Y i t1 = panel data; α = ρ-1; p i = the number of lag order for difference terms; X * i t = exogenous variable in model such as country fixed effects and individual time trend; Ԑ i t = the error term of equation 2.
LLC panel unit root test has null hypothesis as panel data has unit root as well as can present below that: H 0 : null hypothesis as panel data has unit root (assumes common unit root process).
H 1 : panel data has not unit root.

Im, Pesaran and Shin
The properly standardized t* NT has an asymptotic standard normal distribution and also it was rewritten to be new t-statistics as well as can show below that: (see equation 3).
Where, W t*NT is W-statistics has been used to test panel data based on Im, Pesaran and Shin techniques.Also this technique has non-stationary as null hypothesis as well as to show below that: H 0 : null hypothesis as panel data has unit root (assumes individual unit root process).
H 1 : panel data has not unit root.

Fisher-Type Test using ADF and PP-Test (Maddala and Wu and Choi )
Madala and Wu proposed the use of the Fisher (Pλ) test which is based on combining the P-values of the test-statistics for unit root in each cross-sectional unit.Let p i are U [0,1] and independent, and -2log e p i has a χ 2 distribution with 2N degree of freedom and can be written in equation 4.
Where, P λ = Fisher (P λ ) panel unit root test N = all N cross-section -2 ∑ N i=1 log e p i = it has a χ 2 distribution with 2N degree of freedom In addition, Choi demonstrates that: (see more detail of Choi demonstrates that in equation 5).
Where, Z = Z-statistic panel data unit root test; N = all N cross-section in panel data; Ө i -1 = the inverse of the standard normal cumulative distribution function; p i = it is the P-value from the i th test.
Both Fisher (P) Chi-square panel unit root test and Choi Z-statistics panel data unit root test have non-stationary as null hypothesis as well as to show below that: H 0 : null hypothesis as panel data has unit root (assumes individual unit root process); H 1 : panel data has not unit root.

Hadri
The Hadri test for panel data has the hypothesis to be tested is H 0 is null hypothesis and H 1 is against null hypothesis and can show below that: H 0 : null hypothesis as panel data has not unit root (assumes common unit root process); H 1 : panel data has unit root.

Panel Cointegration Test
In order to solve the spurious regression problem and violation of the assumptions of the classical regr ession model, cointegration analysis is used to examine the long run relationship between the variables.This test is mainly accomplished for identifying the long run relationship among economic freedom, FD I and economic growth.
Here, Y indicates the dependent variable like FDI and X 1 to X m indicates the different independent variables.(See in details Table 2).
Another method have used that is known as a Kao for estimating the long run relationship between the variables.Kao have used both DF and ADF to test for co-integration in panel as well as this test similar to the standard approach adopted in the EG-step procedures.Also this test start with the panel regression model as set out in equation 7.
Where Y and X are presumed to be non-stationary and: (see equation 8) where e ^i t = (Y i t -X i t ß ^i t -Z i t ƴ ^ ) are the residuals from estimating equation 8. To test the null hypothesis of no co-integration amounts to test H 0 : ρ = 1 in equation 8 against the alternative that Y and X are co-integrated (i,e., H 1 : ρ < 1).
Considering the demand of the paper when Ω is known, β is efficiently estimated with generalized least squares (GLS).
Instead of assuming the structure of heteroskedasticity, the work may estimate the structure of heteroskedasticity from OLS.First, estimate Ω ̂ from OLS and, second, use Ω ̂ instead of Ω.
After GLS and FGLS the paper has also tested OLS.A standard panel OLS estimator for the coefficient ß i given by: Where i = cross-section data and N is the number of cross-section; t = time series data and T is the number of time series data; ß ^i OLS = a standard panel OLS estimator; X i t = exogenous variable in model; The most commonly used models in panel data analysis are fixed effects (FE) and random effects (RE) regressors in linear regression using ordinary least squares (OLS).
Here in this paper the fixed effects model is used binary variables.So the equation for the fixed effects model becomes: Where, Y it = is the dependent variable (DV) is FDI where i = entity and t = time.
X k , it = represents independent variables ( See in details in Table 2).
β k = is the coefficient for the IVs.
u it = is the error term.
E n = is the entity n.
γ 2 = is the coefficient for the binary repressors (entities).
The random effects model is: In Poisson regression, the paper supposes that the Poisson incidence rate  is determined by a set of k regressor variables (the X"s).The expression relating these quantities is μ.Using this notation, the fundamental Poisson regression model for an observation i is written as Where, That is, for a given set of values of the regressor variables, the outcome follows the Poisson distribution.
In the Prais-Winsten the equation is: Where Y t is the time series of interest at time, β is a vector of coefficients, X t is a matrix of explanatory variables and ε t error terms.The error terms can be serially correlated over time ε t = pε t-1 + е t , |p| < 1 and e t is a white noise.
In the Generalized Method of Moments estimator based on these population moments conditions is the value of θ that minimizes.
Where W n is a non-negative definite matrix that usually depends on the data but converges to a constant positive definite matrix as n ∞.
The GEE approach estimates β by solving the estimating equations (Liang and Zeger), and (Prentice): and V i is the working covariance matrix of Y i .V i can be expressed in terms of a correlation matrix R (α): V i = A i ½ R (α) A i ½ where A i is a diagonal matrix with elements var (Y it ) = V(μ it ), specified as functions of the means μ it, α is some unknown parameter.

Data Sources
This article has employed panel data for 79 countries over the period from 1998 to 2014 among different developing countries (See in Table 1).FDI which is noted as an dependent variable is measured in current U.S. dollars divided by the host country"s total population as the dependent variable, and data come from UNCTAD.
Data on FDI are provided by several sources, such as Balance of Payments Statistics Yearbook and International Finance Statistics by the International Monetary Fund (IMF), European Union Direct Investment Yearbook by EUROSTAT, World Investment Report by UNCTAD, World Development Indicators by the World Bank, and International Direct Investment Statistics Yearbook by OECD.Only the UNCTAD, OECD, and EUROSTAT offer a sectoral breakdown of FDI flows and stocks.The drawback is that OECD and EUROSTAT only cover a very limited number of world countries and thus the total direct investment received by any given country cannot be completely assessed.Moreover, the paper is more interested in FDI inflows than FDI stocks because policy recommendations are usually formulated to boost FDI inflows rather than to accumulate FDI stocks for a given period.However, only UNCTAD provides a break down into two different categories: FDI figures for developed and for developing countries that really serve our purpose.Because of making contemplative judgment FDI related data from accumulated from the UNCTAD.

Table 1. List of the countries
Here in this study the paper has applied the Index of Economic Freedom provided by Heritage Foundation, for measuring economic freedom that included 50 independent variables which fall into 10 categories of economic freedom.Each country receives its overall economic freedom score based on the simple average of the 10 individual factor score.Each factor has a unique scale that runs from 1 to 5, where a score of 1 indicates an economic environment that are most conducive to economic freedom and a score of 5 indicates the opposite.For the economic growth the proxy variables are GDPPG and GDPG, the data are accumulated from the World Development Indicators, 2014.The other control variable democracy, the data are accumulated from the Quality of Government Institute, 204, here the index value range from 0 (0= represent no democracy) to 100 (100 represent full democracy).Another control variable is political stability; the data are aggregating from the worldwide governance indicators.For the political stability the data collection method and research methodology all the things can be access in that particular website: www.govindicators.org.

Government Effectiveness
The quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government"s commitment to such policies.

Worlds governance
Indicator, 2014 Regulatory Quality The ability of the government to formulate and implement sound policies and regulations that permits and promotes private sector development.

Worlds governance
Indicator, 2014 Independent Variables

Rule of Law (RL)
The extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, the police, and the courts, as well as the likelihood of crime and violence.

Control of Corruption
The extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as "capture" of the state by elites and private interests.Fiscal Freedom Fiscal freedom is a measure of the burden of government from the revenue side and it includes both the tax burden in terms of the top tax rate on income and the overall amount of tax revenue as a portion of GDP.

Heritage Foundation, 2014 (+)
Monetary Freedom Monetary freedom combines a measure of price stability with an assessment of price controls.
Heritage Foundation, 2014 Democracy Index of Democratization.Index that could vary from 0 (no democracy) to 100 (full democracy).

Quality of Government Institute
(+)

Empirical Evidence
Concentrates on the model specification the following table interprets whether the panel data are stationary or not.For identifying this, five different panel unit test is being accomplished (Levin, Lin, & Chu; Breitung, Im, Pesaran, & Shin), Fisher-Type test using ADF and PP-test (Maddala, Wu, & Choi) and Hadri.To solve the spurious regression problem and violation of the assumptions of the classical regression model, cointegration analysis has used to examine the long run relationship between the variables.From the no deterministic trends there are 7 different and separate outcomes.Out of 7 outcomes, 3 outcomes interprets that accept the null hypothesis (H 0 = No cointegration), because the p value is > 5. On the other hand 4 outcomes illustrates that reject the null hypothesis and accept the alternative hypothesis.Therefore it is to be noted that base on the no deterministic trend elucidate that the variables are cointegrate.On the other hand from the deterministic intercept and trends have 7 outcomes, out of 7 outcomes 5 outcomes interprets that accept the null hypothesis (H 0 = No cointegration), because the p value is > 5. On the other hand 2 outcomes illustrates that reject the null hypothesis, it means that accept the alternative hypothesis.Therefore it is to be noted that base on the deterministic intercept and trend elucidates that the variables are not cointegrate.According to the no deterministic intercept and trends, out of 7 outcomes 4 outcomes interprets that reject the null hypothesis (H 0 = No cointegration), because the p value is < 5. On the other hand 3 outcomes illustrates that accept the null hypothesis, it means that reject the alternative hypothesis.Therefore it is to be noted that base on the no deterministic intercept and trend method elucidates that the variables are cointegrated.Two trends out of three trends of the Pedroni Residual Cointegration test the variables are cointegrate.Another lucid method (Kao Residual Cointegration) has used to find out the cointegration regarding the variables.From the Table 6 it exhibits that the p value is less than 5%, means that reject the null hypothesis (H 0= No cointegration).So from the two methods of co-integration (Pedroni Residual Co-integration Test, Kao Residual Co-integration Test) reveals that the variables are cointegrate.
In the first column of the Table 7 here presented the GLS estimates.The impacts of all the variables under the economic freedom are positive and significant.In the case of business freedom the coefficient implies that a one standard deviation improvement in business freedom increases FDI by 8.36 %.Other different variables like trade freedom, government size, investment freedom, property rights, freedom from corruption, labor freedom, financial freedom, fiscal freedom and monetary freedom the coefficient implies that a one standard deviation improvement in trade freedom, government size, investment freedom, property rights, freedom from corruption, labor freedom, financial freedom, fiscal freedom and monetary freedom increases FDI by 8.95%, 9.43%, 9.28%, 5.62%, 5.94%, 4.25%, 5.37% and 4.33% respectively.For the economic variable, GDPG and GDPPC, the coefficient implies that a one standard deviation improvement in GDPG and GDPPC increases FDI by 10.92% and 10.34% respectively.
In the Second column of the table presented the FGLS estimates.The impacts of all the variables under the economic freedom are positive and significant.Here all the variables under the economic freedom like business freedom, trade freedom, government size, investment freedom, property rights, freedom from corruption, labor freedom, financial freedom, fiscal freedom, and monetary freedom the coefficient implies that a one standard deviation improvement in business freedom, trade freedom, government size, investment freedom, property rights, freedom from corruption, labor freedom, financial freedom, fiscal freedom and monetary freedom increases FDI by 12.09%, 10.27%, 10.94%, 12.42%, 13.45%, 10.22%, 8.61%, 7.33%, 8.44% and 8.25% respectively, it means that the value is slightly higher from the GLS.Economic variable, GDPG and GDPPC, the coefficient implies that a one standard deviation improvement in GDPG and GDPPC increases FDI by 14.36% and 12.37% respectively.From the Pooled OLS method, the impact of all the variables under the economic freedom has also explored to be positive and significant.In the case of business freedom the coefficient implies that a one standard deviation improvement in business freedom increases FDI by 24.5%.The coefficient of trade freedom implies that a one standard deviation improvement in business freedom increase FDI by 37.3%.Another variable under the economic freedom the coefficient of government size implies that a one standard deviation improvement in government size increase FDI by 26.3%.In the case of investment freedom the coefficient implies that a one standard deviation improvement in investment freedom increases FDI by 14.5%.On the concentration of the property rights the coefficient implies that a one standard deviation improvement in property rights increases FDI by 22.4%.The coefficient of freedom from corruption implies that a one standard deviation improvement in freedom from corruption increases FDI by 11.5%.In the case of labor freedom the coefficient implies that a one standard deviation improvement in business freedom increases FDI by 31.9%.In the case of financial freedom the coefficient implies that a one standard deviation improvement in financial freedom increases FDI by 32.7%.The coefficient of fiscal freedom implies that a one standard deviation improvement in fiscal freedom increases FDI by 32.4%.In the case of monetary freedom the coefficient implies that a one standard deviation improvement in monetary freedom increases FDI by 24.5%.Economic variable like GDPG and GDPPC, the coefficient implies that a one standard deviation improvement in GDPG and GDPPC increases FDI by 37.8% and 29.1% respectively.
According to the OLS estimates from the Table 9, the impact of all the variables under the economic freedom are positive and significant.In the case of business freedom the coefficient implies that a one standard deviation improvement in business freedom increases FDI by 21.4%.On the concentration of the trade freedom, the coefficient implies that a one standard deviation improvement in trade freedom increases FDI by 15.6%.Other different variables like government size, investment freedom, property rights, freedom from corruption, labor freedom, financial freedom, fiscal freedom and monetary freedom the coefficient implies that a one standard deviation improvement in size, investment freedom, property rights, freedom from corruption, labor freedom, financial freedom, fiscal freedom and monetary freedom increases FDI by 21.6%, 17.5%, 11.5%, 9.1%, 6.9%, 8.5%, 7.4% and 10.3% respectively.For the economic variable, GDPG and GDPPC, the coefficient implies that a one standard deviation improvement in GDPG and GDPPC increases FDI by 24.1% and 17.4% respectively.
From the second column of the table 9 the paper present the random effect estimates.The impacts of all the variables under the economic freedom are also found positive and significant.In the case of business freedom the coefficient implies that a one standard deviation improvement in business freedom increases FDI by 37.3% which is slightly higher from than in the case of OLS.On the other hand in the case of the trade freedom, the coefficient implies that a one standard deviation improvement in trade freedom increases FDI by 12.9 %.Other different variables like government size, investment freedom, property rights, freedom from corruption, financial freedom and monetary freedom the coefficient implies that a one standard deviation improvement in government size, investment freedom, property rights, freedom from corruption, financial freedom and monetary freedom increases FDI by 16.3% 12.2%, 10.5%, 7.5%, 5.4% and 9.3% which is slightly lower from than in the case of OLS.On the other hand labor Freedom and Fiscal Freedom the coefficient implies that a one standard deviation improvement in labor freedom and fiscal freedom increases FDI by 7.2% and 8.5% which is slightly higher than OLS.Economic variable like GDPG and GDPPC, the coefficient implies that a one standard deviation improvement in GDPG and GDPPC increases FDI by 25.3% and 35.9% respectively.According to the fixed effect estimates here are also the impact of all the variables under the economic freedom has also explored to be positive and significant.In the case of business freedom, trade freedom, government size, investment freedom, property rights, freedom from corruption, labor freedom, financial freedom, fiscal freedom and monetary freedom the coefficient implies that a one standard deviation improvement in business freedom, trade freedom, government size, investment freedom, property rights, freedom from corruption, labor freedom, financial freedom, fiscal freedom and monetary freedom increases FDI by 45.4%, 37.8%, 40.6%, 36.4%,26.9%, 29.4%, 18.9%, 17.4%, 21.8% and 18.2% respectively which is higher than OLS and Random Effect Model.For the economic variable, GDPG and GDPPC, the coefficient implies that a one standard deviation improvement in GDPG and GDPPC increases FDI by 35.6% and 18.2% respectively.
From the fourth column of the table presented the Poisson Regression estimates.Here also the impacts of all the variables under the economic freedom are explored to be positive and significant.In the case of business freedom, trade freedom, government size, investment freedom, property rights, freedom from corruption the coefficient implies that a one standard deviation improvement in business freedom, trade freedom, government size, investment freedom, property rights and freedom from corruption increases FDI by 41.4%, 28.3%, 35.2%, 23.3%, 17.6%, 15.7% respectively which is slightly lower than in the case of OLS, Random Effect Model and Fixed Effect Model.On the other hand the other variables like labor freedom, financial freedom, fiscal freedom and monetary freedom the coefficient implies that a one standard deviation improvement in labor freedom, financial freedom, fiscal freedom and monetary freedom increases FDI by 25.9%, 21.4%, 23.6% and 28.2% respectively and which is slightly higher than Fixed Effect Model.For the economic variable, GDPG and GDPPC, the coefficient implies that a one standard deviation improvement in GDPG and GDPPC increases FDI by 41.7% and 11.2% respectively.
From the fifth column according to the Prais-Winsten estimates, here all the variables under the economic freedom are explored to be positive and significant.In the case of business freedom, trade freedom, labor Freedom, fiscal Freedom and monetary freedom the coefficient implies that a one standard deviation improvement in business freedom, trade freedom, labor Freedom, fiscal freedom and monetary freedom increases FDI by 36.8%,23.7%, 22.9%, 21.9% and 21.1% respectively and that is lower value from the Poisson Regression.On the other hand government size, investment freedom, property rights, freedom from corruption and fiscal freedom the coefficient implies that a one standard deviation improvement in government size, investment freedom, property rights, freedom from corruption and fiscal freedom increases FDI by 36.8%,32.6%, 22.8%, 21.5% and 31.7%respectively which is higher value from the Poisson Regression.Economic variable like GDPG and GDPPC, the coefficient implies that a one standard deviation improvement in GDPG and GDPPC increases FDI by 26.7% and 21.5% respectively.
From the sixth column of the table concentrates on the GMM estimates, here noted that all the variables under the economic freedom are also explored to be positive and significant.In the case of business freedom, trade freedom, government Size, property rights, freedom from corruption, labor freedom, fiscal freedom and monetary freedom the coefficient implies that a one standard deviation improvement in business freedom, trade freedom, government Size, property rights, freedom from corruption, labor freedom, fiscal freedom and monetary freedom increases FDI by 54.7%, 34.8%, 45.1%, 28.4%, 31.4%, 35.2%, 28.4% and 31.3%respectively which implies that is slightly higher from the Prais-Winsten estimates.On the other hand the other variables from the economic freedom like investment freedom and financial freedom the coefficient implies that a one standard deviation improvement in investment freedom and financial freedom increases FDI by 29.3% and 25.4% respectively and that is slightly lower from the previous estimates.Economic variable like GDPG and GDPPC, the coefficient implies that a one standard deviation improvement in GDPG and GDPPC increases FDI by 35.8% and 26.1% respectively.
From the seven column of the table has presented the GEE estimates.All the variables under the economic freedom are also explored to be positive and significant.In the case of business freedom, trade freedom, government size, investment freedom, property rights, freedom from corruption, labor freedom, financial freedom, fiscal freedom and monetary freedom the coefficient implies that a one standard deviation improvement in business freedom, trade freedom, government Size, investment freedom, property rights, freedom from corruption, labor freedom, financial freedom, fiscal freedom and monetary freedom increases FDI by 56.1%, 45.3%, 58.3%, 51.6%, 33.7%, 39.2%, 47.4%, 41.6%, 32.5% and 38.5% respectively.Economic variable like GDPG and GDPPC, the coefficient implies that a one standard deviation improvement in GDPG and GDPPC increases FDI by 30.2% and 33.4% respectively.

Conclusion
This paper has examined the relations among economic freedom, FDI and economic growth in the developing country.It finds that there are positive relations among economic freedom, FDI and economic growth.Economic freedom is a significant determinants of foreign direct investment because of unremitting flow of investment it helps to enhance the competitiveness of the economic outlooks.Due to the economic freedom, the foreign entrepreneurs are accumulates substantial amount of confidence to make investment in the host countries and that consequence on enhancing the economic growth.It is true that not always economic freedom stimulates FDI; there are also some inevitable factors that may consider the different MNC"s to make investment in the host countries especially in developing countries.Investment in the host countries may depends on the market size, economic growth, financial development, macroeconomic stability, geographical distance and many more.Above all host countries governments should ensure to achieve a sound degree of political and economic stability, along with a market-oriented environment that really assists for proliferating economic growth in the developing countries.
and β 1 is called the intercept.The regression coefficients β 1 , β 2,….. β k are unknown parameters that are estimated from a set of data.Their estimates are labeled b 1, b 2….b k.

Table 3 .
Panel unit root testBase on the five different type of panel unit root test such as Levin, Lin and Chu, Im, Pesaran and Shin, Fisher-Type test using ADF and PP-test(Maddala, Wu, & Choi, 2001)and Hadri methods the variables are not stationary at a level.Now let"s see at first difference the data are stationary or not.From the Table4concentrates on the five different type of panel unit root test such as Levin, Lin and Chu, Im, Pesaran and Shin, Fisher-Type test using ADF and PP-test (Maddala, Wu, & Choi) and Hadri methods the variables are stationary at a first differences.

Table 6 .
Kao residual co-integration test

Table 7 .
Generalized least square and feasible generalized least square method

Table 9 .
Panel data estimates