CHAPTER THREE METHODOLOGY 3
This chapter discusses the methodology employed in the study and is divided into eight sections. The first section introduces the chapter. Section 3.1 presents the theoretical framework build from the model on exports diversification and economic growth used in the study. Section 3.2 specifies the functional forms and variables used in the model. Section 3.3 defines variables and justifies the inclusion of the variables in the model. Section 3.4 presents data sources used in the study. Section 3.5 is where model specification tests are done. Diagnostic checks such as Fixed Effects, Hausman, Bruesch and Pagan Lagrange Multiplier and many other tests are discussed. Section 3.6 presents parameter tests as well as misspecification test. Section 3.7 concludes the chapter.
3.1 Theoretical Framework
Traditional theories of international trade had argued that economic differences between countries are resulting from differences in the factor endowments, policy regimes and technology. The theories however failed to explain the reason behind differences in economic activities and growth for countries with similar or the same factor endowments (Matthee and Naude, 2008). The study’s theoretical framework was drawn from an augmented Cobb-Douglas production function in which it incorporates real exports, fixed capital formation, human capital and real imports as factors that affect economic growth. This is estimated in equation 3.1 presented below (Del Negro and Schorfheide, 2002)
Y_t=(K_t )^? ?(A_t L_t)?^(1-?)…………………………………………………………………………………3.1
Where:? Y?_t = real GDP
? K?_t= physical capital stock (predetermined at the beginning of period t)
? L?_t= labor input
? A?_t= technological progress (augmenting technology)
0 ; ? F = 0.0000***
Note: *** indicate significance at 1%, **, significance at 5% and *, significance at 10%
4.8 Discussion of the Results
The F statistic 52.90 (0.0000***) shows that the model is correctly specified and that the null hypothesis of variable inclusion is rejected at the 1% level of significance and therefore it can be concluded that at least one of the variables in the model explain the magnitude of annual economic growth in SADC economies.
The coefficient of Herfindal-Hirschman Concentration Index (HHI) has a negative value and significant at the 1% level indicating that a decrease in export concentration (an increase in export diversification) seems to cause a positive growth in economies of SADC states. Coefficient of export diversification index equals to 8.924755 and is significant at the 1% level which indicates that export diversification has a positive impact on growth in developing countries. According to the coefficient of estimation the export diversification index, if export concentration is reduced by 1 percent in developing countries, economic growth increases amounted to 8.92 percent in these countries. This result is consistent with the study results of Hesse (2008) for more than 80 developing countries and studies of Nicet-Chenaf and Rougier (2008) for the Middle East and North Africa and many other studies conducted in developing countries. Thus, based on the results obtained, it can be seen that the effect of export diversification on economic growth is positive in the countries surveyed and with increase the export diversification and export promotion based on more export destinations as well as wide range of commodities in total export basket of the country in long run can increase economic growth through increased export diversification and reduce volatility in export revenue.
The coefficient of Capital Investment (CAP) is 0.157738, with a p-value of 0.0000 showing that the coefficient of capital investment was positive and significant at 1% level. Based on the results; a 1% increase in capital investment would lead to a 0.16% increase in economic growth. Thus, countries may maintain and improve their economic growth with an increase in their Capital Investment. This result is in line with the result obtained by Arip et al (2010), as they found a positive impact of capital expenditure on economic growth in Malaysia by using OLS and time series data.
Foreign Direct Investment (FDI) is significant at 1% level and reports a positive sign. From the results above; a 1% increase in FDI could lead to a 0.24 increase in economic growth. This is in line with economic theory. The results for this variable are in line with what Al-Marhubi (2000) obtained. The results indicate that if FDI increases, economic growth can also increases.
Employment rate (EMP) is also another variable which is significant at 1% and has positive sign; it has a probability value of 0.0000. Based on the results; a 1% increase in Employment rate would result in 0.18% increase in economic growth. A positive sign was also obtained by Arip et al (2010) as it was having a positive contribution on the growth of the Malaysian economy. The possible reason for such result is that as employment rate increases (unemployment decreases) holding other things equal, economic growth can be increasing.
The overall model reported Adjusted R-squared of 0.56. This means that; approximately 56.11% variation in economic growth is explained by the explanatory variables included in the model. The obtained Adjusted R-squared by Hassan*, Nemati and Darabi (2014) reports a value 0.37 (Adj R-Squared) for the role of export diversification on economic growth in developing countries’ regression using pooled GMM, no justification was given for such results. It automatically reports to us that there are some variables that explain economic growth that have been omitted. Some variables have been omitted such as the human capital formation due to the lack of adequate data. According to Mudenda (2012), it is an indicator of capital improvement and it is measured by government expenditure on education. It is expected to have a negative impact on the growth of economies as its impact of positive growth can be obtained in the long-run.
In this chapter we have estimated and interpreted the regression results which have indicated that export diversification seem to have positively affected the growth of economies in SADC countries. It is in support with the with the theoretical literature started with development models based on industrialization and implied a link between export diversification and growth/development (Roseinstein Rodam, 1943; Presbish, 1950; and Singer, 1950). From this earlier literature, it appears that because export stability entails low costs including unstable demand and more risky investments, so sustained economic growth requires a shift from dependence on a limited number of export products towards a diversified export portfolio. Some of the determinants of economic growth included in the study including Capital Investment, Foreign Direct Investment, Employment rate and Population growth. These findings are the basis for policy prescriptions to be outlined in the next chapter.
CONCLUSION AND POLICY RECOMMENDATION
This chapter contains a detailed conclusion to the study and also some policy lessons drawn from the empirical results of the previous chapter. In addition, the chapter also gives possible areas of future research.
5.1 Summary of the Study
The study has attempted to examine empirically the role of export diversification on economic growth in the developing nations using a panel of 12 SADC countries information for the period 2000-2016. The motivation of the study sort to address the neglected quality dimension of export diversification leading to biased policies, low economic growth rate against potential growth rate that can be experienced as a result of export diversification, continuous fluctuation in the rates of diversification that are also low as compared to developed nations leading to low growth rate of the economies in developing countries as compared to developed countries.
The study utilises static panel model. Random Effects model was the econometric method used in the analysis; the results suggested that export diversification positively affects economic growth. This result suggests that diversification of exports seem to increase economic growth. Possible reasons of this result may be due to reduced volatility of export prices most probably of primary products in world markets, resulting in large fluctuations in the terms of trade for primary products compared to industrial goods.
Apart from export diversification, the study had found that growth of Capital Investment, growth of Foreign Direct Investment, and Employment rate growth to be the other determinants of economic growth. FDI growth rate and Capital Investment growth can support the notion of ongoing industrialization in developing nations. The industrial sector is worth to be noted, it contributes significantly to growth of the economies. Respective countries can improve their growth by actively encouraging growth in both primary and industrial sectors; they should not undermine one sector since both have positive impacts in contributing the product range in the export basket as well as market destinations.
Conclusively, it is shown in the study that export diversification is significant in influencing economic growth in Southern Africa as well as other variables that are included in the model such as Capital Investment, FDI and Employment rate. This then calls for prioritization of effective policies that can improve FDI and Capital Investment hence at the same time an export-led growth would also increase.
5.3 Policy Recommendations
Since the findings had suggesting a significant positive relationship between export diversification and economic growth in SADC, The policy implication from these findings suggest that, in order to sustain future economic growth under the static effect of multilateral and regional trade liberalization, developing countries should diversify their export commodities and develop greater social and economic cooperation with the rest of the world. As the export-oriented economies, in the long run, this strategy could help stabilizing their export earnings. Greater emphasis on export diversification should be given on countries’ trade and industrial policies. In other words, the Southern African countries’ governments can embark on policies in which it can subsidize small to medium scale firms that engage in the innovation and production of new products. The support to such firms will increase future possibilities of a diversified export basket for the countries. It is expected that if a country encourages a proper and diverse mixture of export portfolio then all or remarkable portion of the fluctuations in a subset of export goods maybe evened out (Arip et al, 2010). Therefore, diversification of export goods is recommended as a solution to get rid of drops in export prices and export earnings instability.
Apart from that, strategies aimed at increasing economic growth are beneficial. The policies should be aiming at taking special considerations of the findings in the study. Factors aimed at taking appropriate decisions on variables like Capital Investment and FDI since they have been found to have a positive impact on economic growth. An effort to improve their significance will be an appropriate measure to be undertaken.
Development policies should not be biased towards the growth of one sector rather it has to be across all sectors. Both the primary, industrial and service sectors have proved to have a significance effect in export diversification as well as economic growth hence they have to be treated without disparity.
5.4 Suggestions for Future Researchers
Future studies may focus on the extent to which export diversification can continue to be a source of economic growth in Southern African economies.
They can also use Granger Causality between economic growth and export diversification in order for them to find what causes what as the current study was only look at one side of only diversification on economic growth.
Again, if they have adequate data they can do the same but adding other variables or other SADC countries like Angola, DRC and Lesotho which were not included in the study due to lack of adequate data for some of the variables used in the model.