Growth and Regional Trade in Africa: Some Empirical Evidence

1. Growth and Regional Trade in Africa: Some Empirical Evidence Jacob Musila, Athabasca University, Canada ZelealemYiheyis, Clark Atlanta University, USA

2. Abstract The formation of regional trade agreements among countries at different levels of economic development poses the question of whether the composition of trade, rather than trade itself, is relevant for growth. This question has not been thoroughly and conclusively investigated in the case of trade between developing countries. This paper analyzes the empirical relationship between growth and intra-African export trade as well as exports to other parts of the world as observed through an inter-country cross-section. A production function model is specified and estimated using cross-sectional data from Sub Saharan African countries for the period 1985-2010.

3. Research Problem/Motivation • Theoretical models have been constructed to analyze the relationship between growth and the composition of trade. Some of these models (e.g., Lucas, 1988) conclude that a more advanced country would grow more rapidly if it trades with a less advanced country. Others (e.g., Spilimbergo, 2000) demonstrate the possibility of growth in advanced country slowing down if it trades with a less developed partner. • These opposing conclusions about the impact of trade and/or its composition on growth have not been tested empirically in the case of SSA countries.

4. Literature review The trade-growth nexus: • access to markets leads to exploitation of economies of scale and comparative advantage, which increases productivity and growth. • trade can lead to technological transfers. • trade can change the competitive nature of some industries and, in turn influence the rate of economic growth. • trade can change the sectoral composition of production by changing the relative prices and supply and demand of goods, which can influence the overall rate of economic growth since different goods have different rates of technological progress.

5. Literature review (cont.) Theoretical papers: • The idea that trade composition can affect economic growth was first formalized in models by Lewis (1977), Jones (1979), and Grossman and Helpman (1991). • The conclusions of the models are dependent on the assumptions about the nature of technological progress and the structure of demand function. • Young (1991) presents a Ricardian model of trade among countries at different levels of development in which learning-by-doing and the spillover effects are same for all advanced products and the demand function is homothetic. This model concludes that trade between advanced country and less advanced country is beneficial to growth in the former.

6. Literature review (cont.) • Grossman and Helpman (1991) presents a supply-side model in which a country that is relatively more endowed with human capital can suffer a decrease in the rate of growth as a result of trade with a country that is less endowed with human capital. • Spilimbergo (2000) formulates a Ricardian model in which a more advanced country produces both sophisticated and less sophisticated goods while a less advanced country produces only a less sophisticated good. The model assumes non-homothetic demand functions and technological progress operates through a learning-by-doing process and is country-specific. The model demonstrates a theoretical possibility that trade between the two countries can lead to technological slowdown in the more advanced country.

7. Literature review (cont.) Empirical papers: • Majority of the cross-country studies find positive and significant correlations between trade and growth. Some of these studies include Frankel and Romer (1999), Irwin and Tervio (2002), Dollar and Kraay (2003), Yanikkaya (2003), Alcalá and Ciccone (2004), and Noguer and Siscart (2005). • None of the early empirical studies focuses on analysis of nature of the relationship between intra- and/or inter-African trade and growth in SSA.

8. The growth model The theoretical model: • The following production function is used to investigate the long-run growth. γyt= ƒ[y0, k0, h0, Z(t)] (1) where: γyt is the growth rate of real GDP per capita in year t y0 is initial real GDP per capita k0 is initial physical capital stock per person h0 is initial human capital per person Z is a vector of control and environmental variables

9. The growth model (cont.) Initial conditions • Telephone lines per person and secondary school gross enrolment rates in 1985 are used as proxies for initial stock of physical and human capital, respectively. • Real GDP per capita in 1985 is used as initial real GDP per capita and is intended to capture the tendency for SSA countries to converge or diverge. Control/environmental variables • The stock of democracy is constructed and used as a proxy for political competition. • The openness of executive recruitment is used as proxy for corporate openness. • The export-to-GDP ratios (X/GDP) are used to represent the variable for export trade. (Exports are disaggregated between Africa, other LDCs, and high income countries.)

10. The growth model (cont.) The econometric model: Rate of growth = ci + β1 log(real GDP per capita in 1985)i + β2 log(Telephone lines per capita in 1985)i + β3 (Sec sch. enrolment rates in 1985)i + β4 (Stock of democracy)it + β5 (Open executive recruitment)it + β6 (Trade flow ratio)it+ uit (2) where uit is the idiosyncratic errors and ci is a random effect for t = 1,…, T and i = 1,.., N.

11. The growth model (cont.) Data sources: • Data on initial real GDP per capita (GDP per capita in constant 2000 US$), telephone lines, secondary school gross enrolment rates, per capita real GDP growth rates, and shares of merchandize export trade are obtained from World Development Indicators (December, 2012). • Data on stock of democracy (Polity2 and durable) and openness of executive recruitment are obtained from Polity IV Data Series Version 2010.

12. Estimated results Summary Stats: 35 cross-sections (35 SSA countries)

13. Estimated results (cont.)

14. Estimated results (cont.)

15. Estimated results (cont.)

16. Estimated results (cont.)

17. Conclusion • This paper uses the aggregate production function to investigate the impact of export trade flows on growth in SSA. • The estimated results show that the trade ratios for aggregate exports, exports to HIC enter the growth equation positively and are statistically significant. The positive and significant coefficients of SSA-HIC export trade support the view that the SSA growth benefits more from trading with HIC (the North). • On the other hand, the estimated coefficients of the intra-Africa exports and other exports to LDCs are negative or insignificant. This suggests that exports of SSA countries to other SSA or LDCs have played an insignificant role in the growth of SSA economies.