Determinants of Economic Growth in Developing Countries

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A nation’s growth domestic product (GAP) represents the economic market values for the goods and services that businesses produce. Many factors influence the GAP growth process. These include government monetary and fiscal policy, political stability, domestic capital formation, development of unman capital, banking and financial infrastructure, export policies and foreign direct investment. In many cases, these factors all occur differently in each nation; other times, different factors can play a role.

These factors provide a significant platform to measure economic development collectively. But for the vast majority of the developing countries, due to the economic stages they are stuck in, lack of political will, shortage in capital or environmental resource or a combination of them, there have been cycles of economic chaos and encountered economic growth difficulties. For countries n Asia, Africa, and Latin America, sustained economic growth might be distant goal that is unachievable.

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In this paper, we examine the relationship between various developmental variables and their effect on economic growth over the period 1991 to 2010 for 30 developing countries in Africa, Asia, and Latin America. Literature Review Research studies have focused on the economic development of developing countries from various perspectives. Taken (2011) intends to investigate potential Granger causality among the real Gross Domestic Product (GAP), real exports and inward Foreign Direct Investment (FDA) in Least Developed

Countries (OLD) for the period between 1 970 and 2009. His study examines the ‘exports-growth’ connections in Olds, testing for both “export-led growth” and “growth-led export’ hypotheses-?the question of whether export revenues contribute significantly to real economic growth or whether it is domestic growth dynamics that trigger exports growth in Olds. His paper also aims to investigate potential causality directions between FDA inflows and economic growth empirically.

Taken (201 1) employed the SURE estimator proposed by Keller (1962) to estimate both abbreviate and tripartite systems o test Granger Causality of real GAP, real FDA, and real exports for Least Developed Countries from 1970 to 2009. His findings of the empirical test of the export-growth nexus are equally us abortive of the export-led growth and the growth-led export hypotheses in the case of Least Developed Countries. He also observes that the economic structure of Olds seems to be the primary determinant of the direction of causality between exports and economic growth.

Barrio (2003) in his research about determinants of economic growth concludes for given per capita GAP, high initial human UAPITA predicts higher growth, and for given values of per capita GAP and human capital, growth depends positively on the rule of law and international openness and negatively on the ratio of government consumption to GAP and the rate Of inflation. Growth increases with favorable movements in the terms of trade and declines with increases in the fertility rate.

The relation between growth and the investment, which includes foreign direct investment, ratio is positive but weak when the variables already mentioned are held constant. In fact, the effects of FDA inflows on economic development eve received a great amount of attention. A number of researchers agree that FDA, which provides needed financial capital, the necessary foreign currency, and generates additional tax revenues from the foreign investors, plays a crucial role in economic growth receiving countries (Quasi 2007).

Furthermore, FDA has been perceived as a major contributor to growth and development by bringing capital, technology, management expertise, jobs, and wealth. Capital inflows give a country foreign exchange they need to import goods and services and pay off foreign debt. The question is whether r not FDA inflows have actually resulted in real growth for developing countries.

Recent research studies on FDA inflows in Sub-Sahara Africa (AS), Asia and Latin America suggest that although FDA have some positive effects on economic development in these regions, the benefits are not accrued equally or uniformly across countries and across regions (Meningitis and Adams 2007). For AS countries, it appears that FDA stimulates domestic investment and this in turn results in economic growth. If domestic investment fails to respond to FDA inflows, then the correlation between FDA ND economic growth will be unclear. However, Stevens, et. Al. 2009) uses panel least square congregation test, and concludes that real exports, ICP, real government expenditure, literacy rates are statistically significant but not FDA. Therefore he states that in the long-run, real foreign direct investment is found to have no statistically significant influence on real GAP. Recent research studies on FDA inflows in Sub-Sahara Africa (AS), Asia and Latin America suggest that although FDA have some positive effects on economic development in these regions, the benefits are not equally or uniformly strutted across countries and across regions.

For AS countries, it appears that FDA stimulates domestic investment and this in turn results in economic growth (Adams 2009). If domestic investment and thus capital formation failed to be generated through FDA flows, the correlation between FDA and economic growth is unclear. In the study of a large number of developing countries about the effects of FDA on domestic investment and economic growth, Meningitis and Adams (2007) have observed that FDA is positively and statistically significantly correlated with the economic growth, and that FDA as had a greater impact in Asian than in other developing countries.

There is also a recent study by Alfalfa et al. (2004) on FDA and economic development in Africa, Asia, and Latin America suggest that the preconditions needed for FDA effects to play a positive role on increase in real GAP are not easily perceivable. In his cross-country study, he finds that countries with more structured financial systems can exploit FDA more efficiently than those that have inefficient financial systems. F-or Latin American countries, FDA inflows seem to be beneficial when the countries policies encourage FDA inflows with ewer restrictions (Benign and Sanchez-Rubles 2005).

Hence, according to the previous studies, for the developing countries of Africa, Asia, and Latin America, FDA inflows may result in an uneven growth in economic development across regions and countries. It appears that the effects of FDA are affected by some interfering variables as economic freedom, domestic capital formation, country’s financial institutional structure, export promotion policies, and local environment for foreign investors (Alfalfa, et- al. 2004; Quasi 2007).

In these studies FDA flows are a contributing factor in the economic velveteen of developing countries; however, at the same time, it is difficult to ignore the effects of other factors such as domestic capital formation and human capital development on the economic development of developing countries. Furthermore, Flintiness, et. Al. (2010) completed a study of a number of rapidly growing East Asian countries (four BRICK countries are included) and finds that a fixed exchange rate combined with a surplus labor market has resulted in relatively inexpensive domestic assets.

Research has also shown that economic growth is influenced by a country’s financial velveteen-?at least among the Asian developing countries. In addition to the financial infrastructure as a precondition for growth Of economic development, another related factor seems to be the development of the stock market. In a study on the importance of financial systems that also support a fully developed stock market for economic growth, Levine and Servos (1996), using data on index of stock market development for 41 countries, shows that stock market is strongly related to long run economic growth.

However, there are other studies finds that the importance of stock arrest development on economic growth was not clear. For example, in a study by Miner (2009) for 70 countries between 1970 and 1998, it was learned that stock exchange developments for these countries generated increases in growth during their first five years of existence, despite the longer-term results were ambiguous. Besides the above mentioned factors, research studies have also shown the existence of other influences such as the macroeconomic conditions of country effects of the prevalence of corruption in a country.

Many authors of economic development studies have also approached the issue from the application of methodology-?using the same internal and external factors identified previously such as FDA, financial development, etc. These studies intend to make progress on the statistical analysis to obtain more reliable results. Authors of these studies have also focused on regional and country specific implications. Researchers have studied countries within a region as well as across regions.

In this study, we focus on the developing countries of Africa, Asia, and Latin America, in attempt to improve on what was done in past research in both investigating he influence of multiple factors on economic development using congregation techniques and also in utilizing a cross-sectional, time series dataset including 30 countries across three regions (Africa, Asia, and Latin America) from 1991 to 2010. The goal is to determine the factors that have a statistically significant influence on real GAP in this twenty-year period using panel congregation techniques.

Data and Methods In order to determine the relationship between the dependent variable, real GAP, and the prescriptive variables, the data was collected for thirty countries ever the period 1 991 to 2010 in Africa, Asia and South America (ten each) from Penn World Table 8. 0, an online database with information on relative levels of income, output, inputs and productivity, covering 1 67 countries between 1950 and 2011. A listing of the countries and regions used in this study is in Appendix 1 .

Selected descriptive statistics for these variables for the three world regions are below: Table . Selective Variables Descriptive Statistics Region Real GAP Mean SST. M ax Min Africa 69956. 8 93212. 7 387424. 2 519. 4 Asian 740501 . 0 1776473. 3 1 1 504292. 8 4745. 0 Latin America 357467. 439391 . 0 1705861. 7 17914. 3 SST. Max 943. 5 1758. 0 9885. 0 -489. 1 9813. 1 31925. 2 272986. 6 -4550. 4 6080. 4 9206. 1 53344. 6 -2553. 0 Real GE 9580. 4 1508. 8 137377. 5 94 40627. 3 2058. 4 408147. 6 2 401 74. 9 7455. 3 347252. We intend to determine the relationship between the dependent variable real national GAP and independent variables government expenditure, real household consumption, real exports, foreign direct investment (FDA), and capital stock, etc. All Of the variables used in this study have been considered in the literature. Real GAP is used as the dependent variable because it is rice adjusted and represents the real value of goods and services in the economy. In Penn World Table 8. 0, real GAP is National Accounts (AN) data.

These data are used, first, to estimate Pups where benchmark or interpolated data is not available using national price indices. Second, PUT relies on AN for data on GAP at national prices, which can converted to real GAP using the GAP on the expenditure side and GAP on the output side Pups. Comparative GAP figures are thus subject to change if the underlying AN data are revised. In advanced economies, such revisions are typically quantitatively small. Real FDA is also price-adjusted and measures the net investment inflows of earnings reinvestment, equity capital, short-term capital, and other long-term capital.

FDA has received the most attention in the literature because of its assumed influence on economic development. As mentioned in previous research, studies on FDA flows in Sub-Sahara Africa (AS), Asia and Latin America suggest that the influence of FDA on economic development is not equally or uniformly distributed across countries and/or regions. Therefore, in addition to the above discussed explanatory variables, two interaction arms are included in order to capture the differential effect of real FDA across regions.

These interaction terms are calculated by multiplying the regional dummy variable (Africa or Asia) by real FDA. Some other variable descriptions are below (from PUT website): Average Annual Hours Worked by Persons Engaged-?reports average annual hours worked by persons engaged. Per person engaged is defined in the Penn World Table (PUT) to include all persons aged 15 years and over, who during the reference week performed work, even just for one hour a week, or were not at work but had a job or equines from which they were temporarily absent.

Index of Human Capital per Person-?provides an index of human capital per person, which is related the average years of schooling and the return to education. Capital Stock at Constant 2005 National Prices-?reports capital stock levels in terms of the constant (2005) prices. Real GAP at Constant 2005 National prices-?reports real gross domestic product (GAP) at constant (2005) national prices. Real GAP in the Penn World Table means GAP converted to international dollars using purchasing power parity (POP) rates.

Share of Household Consumption t Current Pups – Reports the share of output-based real gross domestic product (GAP) per capita that is represented by household consumption, where GAP is converted using current purchasing power parities (Pups). Output-side real GAP allows comparison of productive capacity across countries and over time. Share of Gross Capital Formation at Current Pups-?reports the share of output-based real gross domestic product (GAP) per capita that is represented by capital formation (investment), at current purchasing power parities (Pups).

Output-side real GAP allows comparison of productive capacity across countries and over time. Share of Government Consumption at Current pups-?reports the share Of output-based real gross domestic product (GAP) per capita that is represented by government consumption, at current purchasing power parities (Pups). Output-side real GAP allows comparison of productive capacity across countries and over time. Share of Merchandise Exports at Current Pups -?reports the share of output-based real gross domestic product (GAP) per capita that is represented by merchandise exports, at current purchasing power parities (Pups).

Output-side real GAP allows comparison of productive capacity across entries and over time. TFTP at Constant National Prices (2005=1) -?reports total factor productivity (TFTP) levels at constant (2005) prices against the reference year, 2005. TFTP is the portion of output not explained by the amount of inputs used in production. Share of Labor Compensation in GAP at Current National Prices-?reports the share represented by labor income in gross domestic product in terms of the prices in that period (ii, current prices).

Exchange Rate, National Currency/USED (Market+Estimated) reports the exchange rate (national currency vs.. US dollar) for a period in national runners. Market exchange rates are replaced by estimated rates whenever price levels spiked due to misaligned exchange rates. Model Specification We use Ordinary Least Square (OILS) to determine the selection of fixed or random effects. The first decision to make is whether to use cross-section fixed effects or random effects model in the panel data.

The panel data was first estimated using a fixed effect model: where (I= 1,2, 30) and (t= The I refers to the 30 countries in Africa, Asia and South America, and t represents time from 1991-2010. To test if random effects model is appropriate, Houseman Test is preformed and it results in a p-value less than 0. 01, which suggests that random effects model is not appropriate (See Appendix 2). The second decision is to test if variables are congregated. The assumptions are both Y it and all of the variables in X it are non-stationary and integrated of order one-I (1).

Y it is the dependent variable real GAP and it X contains the explanatory variables includes real FDA inflows, the level of real exports, and real government expenditures, etc. The intercepts, a it, are assumed to be heterogeneous, the coefficient vector, B, is homogeneous cross cross-sectional units (or countries), and there is no trend term. The parameters of the equation cannot be estimated by usual methods (OILS), since all variables are I (1 This assumption of non-stationary is examined by testing for the presence of panel unit.

If the null hypothesis of a panel unit root cannot be rejected, then we test for the absence of congregation amongst the variables in equation. The results from Aka Residual Congregation Test are in Appendix 3. The (1) variables are congregated-?the null hypothesis of no congregation IS rejected at the . 01 level of significance. Consequently, from 1 991 to 2010, a steady state equation can be estimated using fixed, cross-sectional effects ordinary least-squares procedure. Moreover, there is possibility that the model of real GAP is autoregressive.

In an autoregressive model, we not only forecast the variable of interest using a linear combination of predictors, but also using a linear combination of past values of the variable. The term autoregressive indicates that it is a regression of the variable against itself. Thus an autoregressive model of order p can be written as We refer to this as an AR(p) model. Rest Its The results of the unrestricted model can be found in Appendix 4. As the unrestricted model shows, FDA does play an important role (at 0. 01 level) to the real GAP over 1 991 to 2010.

However, with interaction terms, the coefficient of FDA behaves a little strangely. While the coefficient of interaction term with Asia is positive, the coefficient of FDA is negative, suggesting that the inflow of FDA on average hinders the real GAP to grow, contradicting the results of many previous studies on foreign investment. Also the interaction term between FDA and Africa is not statistically significant. Human capital mess to be insignificant to the real GAP with the presence of number of people engaged in the workforce. The capital stock has statistically significant but not economically significant coefficients.

It suggests that holding other variables constant, for one additional million dollars increased in capital stock, the real GAP will increase about fifty-six thousand dollars. Furthermore, for fixed cross-section and fixed periods affects model, the Durbin-Watson statistics is about 0. 78, suggesting there might be autocorrelation. The results of the restricted model can be found in Appendix 5. This model eliminates variables that are not statistically significant. The estimation result of the congregation equation has R Square of 0. 9998.

The final explanatory variables are real government expenditure, real household consumption, real exports, number of people engaged in workforce, and capital stock, which are all statistically significant at the . 01 level. Furthermore, these variables all have positive influences upon real GAP, and their coefficients are economically significant as well. The coefficient of number of people engaged in workforce is noticeably large; one way to explain is that on average, holding other rabbles constant; one additional person engaged in workforce, real GAP will increase 1 , 898 U.

S. Dollars. The standardized parameter estimates are also included in and the magnitude of influence of each explanatory variable on real GAP can be perceived nicely. Furthermore, the restricted model is autoregressive at AR(3). It produces Durbin-Watson statistics of 2. 1 . Because of the strange combination of coefficients of FDA, interactions between FDA, Asian countries and African countries, we take the interaction term out to determine what average effect of FDA has on developing countries.

The restricted model shows that from 1991-2010, real foreign direct investment is found to have no statistically significant influence on real GAP. Consequently, we may be able to suggest that the effect that real FDA has on real GAP from 1991 to 2010 does not depend on whether a country is in Africa or Asia, and this result pose disagreeing point of views at what previous studies have found. In addition, the 1 9905 financial crisis in Asia and Latin America did not appear to have much of a lasting impact on real GAP across these countries and years in looking at the residual series. Conclusion

From literature review, there seem to be a general agreement in the previous studies that the inflow of foreign direct investment plays an important role in the economic growth of receiving countries. However, the restricted model indicates that from 1991-2010, real foreign direct investment is found to have no statistically significant influence on real GAP in the developing countries. Rather, it appears to be the economic factors internal to a country that have the most influence on real GAP over the long term: trade, monetary and fiscal policy, and household consumption and number of people engaged in the workforce.

From the result of my models, my restricted model includes imperfectly selected variables. However, my restricted model does not solve the problem of the interaction terms be;en FDA and African and Asian countries. Overall, my data has limited time-twenty years and limited cross- section terms-thirty countries. Furthermore, the country selection is rather arbitrary. It is not clear that these thirty countries represent the average development of the entire population of developing countries, nor is it clear that other independent variables play the similar role in economic development over all developing countries.

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