The Effect of Health and FDI on Economic Growth in Developing Countries

 

Jennifer M. Doering

University of Akron Senior Project

May 7, 2009

 

 

 

 

 

 

 

 

 


Table of Contents

I. Introduction…………………………………………….…….3

II. Literature Review…………………………………….……..5

III. Methodology………………………………………….……..7

a.   Empirical Model ……………………………….............7

b.   Data ……………………………………………..............8

IV. Results………………………………………………….…....10

V. Conclusion…………………………………………...............12

IV. Appendix................................................................................15
I. Introduction

The role of Foreign Direct Investment (FDI) on economic growth in developing countries is widely disputed among scholars. This topic has been increasingly debated as many developing countries have begun to open their barriers to FDI in recent years. Many empirical studies have found FDI to be beneficial for economic growth and many others have found it to have no effect on growth. The continuing debate over the effect of FDI on growth is more crucial now in the coming global recession than ever before. According to the World Investment Report (2008) developing countries are predicted to experience a substantial decrease in FDI flows to their economies. Although the impact of the potential loss is unknown, it is important to investigate the relationship between FDI and economic growth, as increased inflows of FDI may aid in the recovery of these economies.

Health has already been acknowledged as a key factor of human capital in previous studies. Previous empirical literature has shown the significance of human capital, specifically health, on economic growth (Bhargava, Jamison, Lau and Murray 2001, and Bloom, Canning and Sevilla 2001). Bhargava et al. (2001) find that an increase in adult survival rate has a positively significant effect economic growth. Additionally, Bloom et. al (2001) find that life expectancy has a positively significant effect on economic growth.

            Past empirical studies have used secondary education as a measure of human capital (Borensztein et al. 1998, Khawar 2005). Borensztein et al. concluded that FDI was beneficial to growth only in the presence of a minimal level of human capital. In their empirical study, human capital was evaluated using secondary education. However, they failed to encompass all the aspects of human capital. Human capital is made of two components: education and health (Becker, 1993). By not evaluating the health of the labor force, the Borensztein et al. measure falls short of concluding that FDI is positive only with minimum levels of human capital. In the Commission on Macroeconomics and Health, the World Health Organization (2002) states that “higher life expectancy implies a higher rate of return on human capital investment: the value of education depends on future earnings gains”.  This increased life expectancy combined with increased FDI could result in an increased GDP.

Alsan (2006) finds that if life experience increases by one year, FDI will increase by 9 percent. FDI will more frequently be directed to economies that have populations with a longer life expectancy. Higher life expectancy may lead to fewer turnovers which may otherwise lead to an increased investment in training for the workforce. For example, if investors are looking at venturing into Country A or Country B, they will examine the health of each population. Holding other variables constant, if Country A has more health problems, they will choose Country B because there will be less turnover in employment. Training new workers can be very costly and is unattractive to a company looking to earn a profit. Alsan (2006) justifies using life expectancy as the variable of choice for health by referencing Murray & Lopez (1996), Shastry & Weil (2002), Savedoff & Schulz (2000) and Schulz (2002); therefore, this study also uses life expectancy as a measure for health.

            This paper will examine the combined effect of FDI and health on economic growth. The significance of this paper is that it will use the variable of life expectancy, as a proxy of health, in addition to education.

 

II. Literature Review

There have been numerous empirical analyses on the effect of Foreign Direct Investment (FDI) on economic growth in both developing and developed countries. Most studies have found that FDI in developed countries has led to continued economic growth. However, when investigating the effects in developing countries, no common consensus has been reached. The proceeding examines the previous literature which has been conducted on FDI and economic growth.

Herzer et al. (2008) examine the long term and short term effects of FDI on growth in 28 developing countries in Latin America, Asia and Africa. They use the Granger test to assess whether FDI causes growth or vice versa, controlling for heterogeneity among the sample countries. They permit long-run relationships between GDP and FDI, and short-run relationships with first differencing of FDI and GDP. Their findings indicate that in only 4 out of the 28 countries studied, FDI contributed to long run growth. For the remaining countries the results indicate that there is no relationship between FDI and growth in the long or short run. The study also states that in none of the 28 countries does a unidirectional positive long term effect appear from FDI toward GDP. They recommend that future research should evaluate the types of FDI that may affect growth.

A panel study conducted by Li and Liu (2005), tested if FDI affects growth in the recipient countries. Their analysis covers a period of time from 1970 to 1999 for 84 developed and developing countries. The authors also investigate the effect of FDI interacted with infrastructure, human capital and the technology gap. They also test for FDI endogeneity, finding that endogeneity only occurs after 1985. As a consequence, the authors use a simultaneous model from 1985 to 1999. They find a strong complimentary connection in both developed and developing countries between FDI and growth. . Not only does FDI have a direct effect on growth, but it also operates indirectly through three channels, which were mentioned above.

Borensztein et al. (1998) analyze FDI flows from industrialized nations to 69 developing countries from 1970 to 1989. Their study evaluates the effect of FDI on technological diffusion and economic growth. Their study indicates that the effect of FDI on growth is larger than the effect of domestic investment. Moreover, the effect of FDI is stronger when there is a minimum level of human capital available in the host country. Multinational corporations can finance through direct investment or they can finance in the domestic market through debt and equity. This causes an underestimation of the total amount of investment by multinational corporations, resulting in the overestimation of the FDI coefficient. The authors recommend future researchers examine the effects of FDI on the level of human capital and human capital accumulation.

            Khawar’s (2005) empirical work is a response to Borensztein et al. (1998). The study examines if the effect of FDI on economic growth is really contingent on the level of human capital available. The author conducts a cross-country growth analysis from 1970 to 1992.  This study concludes that FDI does indeed have a positive effect on growth regardless of the level of human capital. However, the author admits that simultaneity may bias the findings and note that faster growth in a country may lead to an increase in FDI, resulting in reverse causality. The author recommends doing an analysis of both an open and closed door economy, to further investigate the relationship.

Previous literature has focused on the combined effects of education and FDI on economic growth. In 2006, Alsan et al. published an empirical study that shows that health also has an important effect on FDI. This paper evaluates data from 74 countries, both industrialized and developing, from 1980 to 2000. The goal was to test if inflows of FDI are increased by population health. Until their paper, no previous empirical studies had analyzed the relationship between health and foreign direct investment. They find that FDI can be increased by 9 percent for every one year increase in life expectancy. Health has already been acknowledged as a key factor in human capital, and this study shows that it is an integral part of FDI as well. The major implication of their study is that developing countries should invest in the health of their population. Alsan et al.’s (2006) research is the justification for using life expectancy in addition to education when evaluating FDI’s effect on economic growth in this paper.

Bloom, Canning and Sevilla (2001) examine the effect of life expectancy on economic growth. They perform a panel study of countries from 1960 to 1990, which observed every 10 years of the countries data. They reason that healthier worker are more productive, have less days of absence from work, and earn higher wages. They also reference previous authors where life expectancy has been used in cross country regressions, which have found the variable to have positively significant effect on economic growth (Bloom and Canning, 2000, 2001). Ultimately their model indicates that for a one year increase in life expectancy, output increases by 4 percent.

 

III. Methodology

a. Empirical Model

The neoclassical theory of economic growth is used to evaluate the effect of FDI and health on economic growth in this paper. The model used in this paper is similar to Borenzstein et al.’s (1998) study where the economic growth rate is described by

git = c0 + c1FDIit + c2LEit + c3Y0it + c4Ait + ε.

            In the above equation, g is the growth rate of real GDP per capita, FDI is foreign direct investment, LE is life expectancy, Y0 is the initial GDP per capita and A is a vector of other variables affecting growth. A includes government consumption, political rights, inflation, financial depth, political instability and dummy variables used for the region in which the country is located. This is a panel data study of 109 countries over a 14 years time period. The years included are from 1990 to 2003. The time periods are split into two separate sample periods, the first 7 years and the second 7 years are each averaged over the time period. This set includes 38 low income, 41 lower middle income, and 30 upper middle income countries as defined by the World Development Report 2008.

b. Data

The GDP, population, life expectancy, net FDI inflow as a percentage of GDP, financial development and inflation variables were all collected from the World Development Indicators database. GDP per capita, life expectancy, financial development and net FDI inflows as a percentage of GDP should all have a positive effect on the growth rate. Inflation is expected to have a negative effect on the growth rate. Real GDP is calculated as a measure of nominal GDP minus inflation. As inflation increases it decreases the amount of real output for a country.  The political rights variable is ranked from 1 to 7 (one being the best and seven being the worst). This variable was collected from Freedom House. This variable is also expected to have a positive value because as the country becomes more politically free, it opens itself up to more opportunities such as FDI. The growth rate of real GDP per capita and government consumption variables were collected from the Penn World Tables. Due to the nonlinear relationship between government consumption and economic growth, a squared value of government consumption was also added into the econometric model. Government consumption can increase economic growth through its purchases of goods and services, however the bigger the government becomes, the more inefficient it becomes in its actions, causing a negative effect on economic growth (Grossman, 1988). Political Stability is a measurement from the World Governance Indicators. The World Governance Indicators measures political stability on a scale of -2.5 to 2.5, with 2.5 being the most stable a country can be.

Dummy variables include the regions in which the country is located and time. FDI flows can be attracted to one region over another, which is why these variables are included. According to the World Investment Report (2008) developing countries of Asia was the top ranked region to receive FDI inflows, where as Oceanis developing countries only received 1.1 billion. The year of these flows will have an effect on the economic growth as well. FDI flows to developing countries have been increasing since the 1990’s. Since this study covers 1990 to 2003, it is likely that the second half of the time period will have a more positive effect on economic growth relative to the first time period. A full table of the variable descriptions is shown in the Appendix, Table 1.

 

 

 

IV. Results

            The Ordinary Least Squares (OLS) model was used to estimate the effects of human capital and FDI on economic growth rates in developing countries. In the Appendix, Table 2 shows the summary statistics of all the variables. The next several tables in the appendix show a series of other regressions. The first regression, 3.1, examines the log of initial GDP per capita, secondary education, life expectancy, government consumption (as well as the squared variable) and net FDI inflow as a percentage of GDP. The log of initial GDP per capita, life expectancy and net FDI inflow as a percentage of GDP are all statistically significant variables. If there is a one percent increase in the log of initial GDP per capita, the growth rate of real GDP per capita decreases by 0.814 percent. For a one year increase in life expectancy, the growth rate of GDP per capita increases by 0.09 percent. For a one percent increase in net FDI inflows as a percentage of  GDP, the growth rate of GDP per capita increases by 0.315 percent. In equation 3.2, an interaction term is added to the equation which replaces net FDI inflow as a percentage of GDP. This interaction between FDI and life expectancy, if significant, can account for other factors that are not accounted for in the equation (Borensztein, 1998). Since the interaction term is significant, it will be added into the remaining regressions. Adding the reaction term renders net FDI inflow as a percentage of GDP only significant in the final equation, 3.5. A one percent increase in net FDI inflow as a percentage of GDP results in a 0.784 percent increase in the growth rate of real GDP per capita. Life expectancy remains significant through all of the equations in Table 3. The most significant change that occurs in Table 3 is when financial development and inflation are added into the regression, adjusted R2 increases to 19.4 percent. This adjusted R2 remains constant around 6 percent through the other regressions in Table 3; however, when financial development and inflation are taken into account it dramatically increases attesting to the goodness of fit for this regression. Financial development has a significant impact on growth, if financial development increases, the growth rate of real GDP per capita increases by 0.0417 percent. This variable is statistically significant at a 99 percent confidence interval; remaining statistically significant variables are life expectancy, log of initial GDP per capita, and government consumption squared, however they are only significant at a 10 percent level.

            In Table 4, geographical dummy variables are added to the regression equation. Once again, in equation 4.3, adjusted R2 increases to 18.6 percent, explaining the most variance in any of the equations. The constant term for the geographical dummy variables is Latin America and the Caribbean. In the first equation, a country in South Asia will have a 2.776 percent increase in growth relative to Latin America and the Caribbean. The Middle East and North African countries will have a 1.83 percent increase in growth compared to Latin American and the Caribbean. East Asia and the Pacific countries have the most significant growth at 2.8 percent compared Latin American and the Caribbean. However when inflation and financial development are taken into consideration, none of the geographical dummy variables are significant. An increase of 1 percent in inflation causes a decrease in economic growth by 0.002 percent, and an increase in financial development causes an increase when geographical region is added into the regressions, neither life expectancy nor FDI have a significant impact on economic growth.

            Another model that was examined was with the addition of the income category as defined by the World Bank. The dummy variable held constant was upper middle income countries. Lower income countries have a significant negative effect on economic growth compared to upper middle income countries. Once again the highest Adjust R2 comes in the third equation at 22.96 percent of the variance is explained by the model. In this equation, being a lower income country has a decrease of 3.326 percent of economic growth in relevance to upper middle income countries. Once again financial development is positively significant to economic growth, implying that a 1 percent increase of financial development will increase economic growth by 0.042 percent. Life expectancy is significant in equations 5.1 and 5.2. An increase in life expectancy by one year, will increase economic growth by 0.086 percent, in equation 5.1, and by 0.080 percent in equation 5.2. FDI is not significant in this table, secondary education is found to be significant in the third equation as well as government consumption (squared).

            In addition a regression was run to add in a dummy variable for time, Table 6 in Appendix. Since FDI has been increasing in the past 20 years to developing countries, when compared to the year 1990, FDI should have a positive impact on economic growth. The results indicate that FDI does have a positive effect on economic growth, however insignificant. Life expectancy does have a positive significant impact, for every one year increase in life expectancy, economic growth increases by 0.078 percent. This equation has an adjusted R2 of 18.73 percent, and the dummy variable for time has no impact on economic growth.

 

V. Conclusion

            This paper examines the effect of health and FDI on economic growth in developing countries. The results indicate that life expectancy has a significant positive effect on economic growth, and although FDI starts out as having a significant positive effect, falls short of being able to conclude it has any impact on economic growth. There are several reasons why this may have resulted. Not until 1995 did FDI begin to rapidly increase in developing countries. This means that there are only 8 years in this data set to show the effect on economic growth. To fully encompass the effect that FDI may have on economic growth more years may need to be examined.

            These results should encourage policy makers to take a strong initiative towards the health of their country’s population. As discussed in previous sections, life expectancy has been found to have a significantly positive effect on economic growth, as well as attracting FDI to developing countries. When FDI occurs between developed and developing countries it closes a technological gap that the developing country had no previous access too. FDI has become increasingly popular, and although the majority of FDI flows go to developing countries, developing countries have begun participating as well. If governments can continue to remove barriers towards FDI and aim towards a healthy population it can be beneficial to the economic development of a country.

            One of the constraints of this study is the setback of endogenous variables with in the equation. Although FDI and life expectancy can effect economic growth, economic growth can also have a reverse effect on FDI and life expectancy as well. While an increased life expectancy can bring about more economic growth through work experience and advanced skills, an increase in economic growth can also result in a longer life expectancy too.  Due to time restraints this paper is unable to correct for the endogeniety. This can be corrected by using a two stage least squares model, as was used in Borensztien et. al (1998). As far as the data set is concerned, the variable for health, life expectancy, has missing variables in earlier years which may under play its effect on growth. Similarly the FDI is measured not only from developed countries, but also developing countries to other developing countries. When passing between developing countries it can have a harmful effect due to the loss of technological advances a country might experience. A better defined variable, for example FDI flows from strictly developed to developing may offer different results than what has been examined in this paper.

            Future research, unconstrained by time, would include a two stage least squares model, as well as a three stage least squares model, which was performed in the Borenztein et. al (1998) empirical study. Borensztein et. al (1998) also concluded that FDI was significantly effective on economic growth in the presence of a minimum threshold of secondary education. This aspect should also be reexamined to see if it holds true for recent years of economic growth. Future research should also examine if mortality rate would have a greater impact on economic growth in developing countries.

 

           


VI. Appendix

 

Table 1: Variable Descriptions

 

Variable

Description

Source

grgdp

Growth Rate of real GDP per capita

PWT

linitgdppc

Log of Initial GDP per capita

WDI

secedu

Percentage of population 25 years or older enrolled in Secondary Education

Barro-Lee Dataset

le

Life Expectancy at Birth, total population

WDI

gc

Government Share of real GDP

PWT

fdinigdp

Foreign Direct Investment net inflows as a % of GDP

WDI

fdile

FDI * Life expectancy Interaction Term

 

ps

Political Stability and Absence of Violence (-2.5 to 2.5 scale, 2.5 represents highest stability)

WGI

pr

Poltical Rights (Scale of 1-7, 1 represents highest degree of Freedom)

Freedom House

inf

Inflation consumer prices, % annual

WDI

findev

M2/GDP

WDI

ecadv

Dummy variable for Europe and Central Asia

WDR

sadv

Dummy variable for South Asia

WDR

ssadv

Dummy variable for Sub-Saharan Africa

WDR

menadv

Dummy variable for Middle East and North Africa

WDR

eapdv

Dummy variable for East Asia and the Pacific

WDR

lacdv

Dummy variable for Latin America and the Carribean

WDR

dyr

Dummy variable for the year 1997

 

dyr1

Dummy variable for the year 1990

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 2: Summary Statistics

 

 

Variable

N

Mean

Std. Dev

 

 

Growth rate of real GDP per capita

218

1.259

3.540

 

 

Log of Initial GDP per capita

216

6.777

1.073

 

 

Secondary Education

141

20.246

0.855

 

 

Life Expectancy

217

61.232

10.829

 

 

Government Consumption

218

24.827

11.076

 

 

Government Consumption - Squared

218

738.478

687.782

 

 

FDI net inflows of GDP

218

2.836

3.410

 

 

FDI and Life Expectancy Interaction

217

178.597

219.488

 

 

Political Stability

216

-0.340

0.858

 

 

Political Rights

218

3.890

1.815

 

 

Inflation

218

89.374

395.954

 

 

Financial Development

218

33.500

22.959

 

 

Europe & Central Asia dummy

218

0.165

0.373

 

 

South Asia dummy

218

0.064

0.246

 

 

Sub-Saharan Africa dummy

218

0.339

0.476

 

 

Middle East & North Africa dummy

218

0.073

0.262

 

 

East Asia & the Pacific dummy

218

0.128

0.336

 

 

Latin America and Carribean dummy

218

0.229

0.422

 

 

Dummy variable for 1997

218

0.498

0.501

 

 

Dummy variable for 1990

218

0.498

0.501

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 3: OLS Regression Results

Variable

Coefficient

 

 

 

 

(T-value)

 

 

 

 

 

3.1

3.2

3.3

3.4

3.5

Intercept

0.697

1.443

0.158

-0.061

-1.336

 

(0.31)

(0.65)

(0.06)

(-0.02)

(-0.49)

Log of Initial GDP per capita

-0.814

-0.776

-0.838

-0.087

-0.717

 

(-2.16)**

(-2.05)**

(-2.19)**

(-2.19)**

(-1.92)*

Secondary Education

-0.012

-0.012

0.012

-0.017

-0.023

 

(-0.58)

(-0.58)

(-0.58)

(-0.83)

(-1.16)

Life Expectancy

0.093

0.078

0.103

0.110

0.078

 

(2.69)***

(2.24)**

(2.45)**

(-2.59)***

(1.91)*

Government Consumption

0.029

0.012

0.039

0.057

0.175

 

0.026

(0.11)

(0.34)

(0.49)

(1.60)

Government Consumption - Squared

-0.001

-0.001

-0.001

-0.056

-0.004

 

(-0.53)

(-0.32)

(-0.62)

(0.49)

(-1.94)*

FDI net inflow of GDP

0.315

 

0.536

0.576

0.784

 

(2.95)***

 

(1.05)

(1.13)

(1.65)*

FDI & Life Expectancy Interaction

 

0.00513

-0.04

-0.01

-0.01

 

 

(2.79)***

(-0.44)

(-0.63)

(-1.13)

Political Stability

 

 

 

0.597

0.402

 

 

 

 

(1.68)*

(1.21)

Political Rights

 

 

 

0.109

0.001

 

 

 

 

(0.66)

(0.01)

Inflation

 

 

 

 

-0.002

 

 

 

 

 

(-2.18)

Financial Development

 

 

 

 

0.0417

 

 

 

 

 

(-3.46)***

R-squared

0.108

0.102

0.110

0.129

0.257

Adj. R-Sq

0.068

0.062

0.063

0.069

0.194

*** Significant at a critical value of 99%

**Significant at a critical value of 95%

*Significant at a critical value of 90%

 

 

 

 

 

 

 

 

Table 4: OLS Regression Results with Geographical Regions

Variable

Coefficient

 

 

(T-value)

 

 

 

4.1

4.2

4.3

Intercept

-4.135

-2.274

-2.311

 

(-1.12)

(-0.57)

(-0.60)

Log of Initial GDP per capita

-0.172

-0.274

-0.317

 

(-0.40)

(-0.60)

(-0.72)

Secondary Education

-0.017

-0.019

-0.027

 

(-0.68)

(-0.75)

(1.11)

Life Expectancy

0.074

0.062

0.052

 

(1.36)

(1.14)

(0.96)

Government Consumption

1.172

0.087

0.145

 

(0.63)

(0.76)

(1.28)

Government Consumption - Squared

-0.002

-0.002

-0.003

 

(-0.88)

(-1.04)

(-1.56)

FDI net inflow of GDP

0.368

0.379

0.625

 

(0.74)

(0.77)

(1.28)

FDI & Life Expectancy Interaction

0.000

-0.001

-0.006

 

(-0.05)

(-0.17)

(-0.73)

Europe & Central Asia dummy

-0.034

-0.176

0.071

 

(-0.04)

(-0.18)

(0.07)

South Asia dummy

2.779

2.867

1.917

 

(2.32)

(2.37)

(1.57)

Sub-Saharan Africa dummy

1.411

0.994

0.218

 

(1.41)

(0.95)

(0.21)

Middle East & North Africa dummy

1.830

1.940

0.410

 

(1.84)

(1.71)

(0.33)

East Asia & the Pacific dummy

2.809

2.645

1.227

 

(3.15)

(2.86)

(1.17)

Political Stability

 

0.580

0.528

 

 

(1.55)

(1.45)

Political Rights

 

-0.005

0.056

 

 

(-0.03)

(0.30)

Inflation

 

 

-0.002

 

 

 

(-1.93)

Financial Development

 

 

0.031

 

 

 

(2.06)

R-squared

0.2076

0.2258

0.279

Adj. R-Sq

0.133

0.140

0.186

*** Significant at a critical value of 99%

**Significant at a critical value of 95%

*Significant at a critical value of 90%

 

 

 

Table 5: Regression Results Income Dummy Variables

Variable

Coefficient

 

(T-value)

 

 

 

5.1

5.2

5.3

Intercept

7.356

7.266

7.627

 

(1.74)

(1.61)

(1.84)

Log of Initial GDP per capita

-1.508

-1.485

-1.564

 

(-2.94)

(-2.84)

(-3.25)

Secondary Education

-0.024

-0.025

-0.038

 

(-1.08)

(-1.19)

(-1.87)

Life Expectancy

0.086

0.080

0.059

 

(1.83)

(1.71)

(1.34)

Government Consumption

0.043

0.069

0.184

 

(0.38)

(0.60)

(1.71)

Government Consumption - Squared

-0.002

-0.002

-0.004

 

(-0.73)

(-0.98)

(-2.13)

FDI net inflow of GDP

0.471

0.442

0.728

 

(0.91)

(0.86)

(1.52)

FDI & Life Expectancy Interaction

-0.003

-0.004

-0.009

 

(-0.32)

(-0.40)

(-1.04)

Lower income countries dummy

-2.668

-2.491

-3.326

 

(-2.09)

(-1.95)

(-2.80)

Lower middle income countries dummy

-1.012

-0.575

-1.346

 

(-1.25)

(-0.68)

(-1.69)

Political Stability

 

0.665

0.365

 

 

(1.78)

(1.05)

Political Rights

 

0.071

-0.030

 

 

(0.44)

(-0.19)

Inflation

 

 

-0.003

 

 

 

(-2.60)

Financial Development

 

 

0.042

 

 

 

(3.55)

R-squared

0.1394

0.16

0.3012

Adj. R-Sq

0.0802

0.0884

0.2296

*** Significant at a critical value of 99%

**Significant at a critical value of 95%

*Significant at a critical value of 90%

 

 

 


 

Table 6: Regression Results with Time Dummy

 

Variables

Coefficient

 

 

(T-value)

 

Intercept

-1.335

 

 

(-0.48)

 

Log of Initial GDP per capita

-0.717

 

 

(-1.91)*

 

Secondary Education

-0.023

 

 

(1.15)

 

Life Expectancy

0.078

 

 

(1.88)*

 

Government Consumption

0.175

 

 

(1.60)

 

Government Consumption - Squared

-0.004

 

 

(-1.93)*

 

FDI net inflow of GDP

0.784

 

 

(1.64)

 

FDI & Life Expectancy Interaction

-0.009

 

 

(-1.13)

 

Year dummy

-0.001

 

 

(0.00)

 

Political Stability

0.402

 

 

(1.18)

 

Political Rights

0.001

 

 

(0.01)

 

Inflation

-0.002

 

 

(-2.15)**

 

Financial Development

0.042

 

 

(3.37)***

 

R-squared

25.70%

 

Adj. R-Sq

18.73%

 

*** Significant at a critical value of 99%

**Significant at a critical value of 95%

*Significant at a critical value of 90%


 

VI. Bibliography

Alsan, Marcella, David E. Bloom, and David Canning. "The Effect of Population Health on Foreign Direct Investment Inflows to Low- and Middle-Income Countries." World Development 34.4 (2006): 613-30.

Barro, Robert J. and Jong-Wha Lee, "International Data on Educational Attainment: Updates and Implications" (CID Working Paper No. 42, April 2000).

Bhargava, Alok, Dean T. Jamison, Lawrence Lau and Christopher JL Murray. “Modeling the Effects of Health on Economic Growth”. (2001). GPE Discussion Paper Series: No. 33. World Health Organization.

Becker, Gary. “Human Capital: A Theoretical and Empirical Analysis, with special reference to Education.” Third Edition. University of Chicago Press (1993).

Bloom, D., D. Canning and J. Sevilla. “The Effect of Health on Economic Growth: Theory and Evidence”. (2001). NBER Working Paper No. 8587.

Borensztein, E., J. De Gregorio, and J-W Lee. "How does Foreign Direct Investment Affect Economic Growth?" Journal of International Economics 45.1 (1998): 115-35.

Herzer, Dierk, Stephan Klasen, and Felicitas Nowak-Lehmann D. "In Search of FDI-Led Growth in Developing Countries: The Way Forward." Economic Modelling 25.5 (2008): 793-810.

Khawar, Mariam. "Foreign Direct Investment and Economic Growth: A Cross-Country Analysis." Global Economy Journal 5.1 (2005): 1-12.

Heston, Alan, Robert Summers and Bettina Aten, Penn World Table Version 6.2, Center for International Comparisons of Production, Income and Prices at the University of Pennsylvania, September 2006.

Li, Xiaoying, and Xiaming Liu. "Foreign Direct Investment and Economic Growth: An Increasingly Endogenous Relationship." World Development 33.3 (2005): 393-407.

The World Bank. 2005. World development indicators CD-ROM. Washington D.C.: (accessed 2/20/09).

The World Bank. 2008. “World Development Report: Agriculture for Development.” Washington D.C.

The World Bank. The World Governance Indicators. http://info.worldbank.org/governance/wgi/index.asp (accessed 4/15/09).

World Health Organization. “Report of the WHO Commission on Macroeconomics and Health.” 23 April 2002.

United Nations. “World Investment Report 2008: Transnational Corporations, and the Infrastructure Challenge.” (2008). New York and Geneva: (accessed 3/3/09).