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Determinants of FDI: Lessons from the African Economies

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Presentation on theme: "Determinants of FDI: Lessons from the African Economies"— Presentation transcript:

1 Determinants of FDI: Lessons from the African Economies
Journal of Applied Business and Economics, Vol. 9, No. 1, 2009

2 FDI in Africa (UNCTAD 2005). Africa accounts for:
Just 2 to 3 % of global FDI inflows, Down from a peak of 6 percent in the mid-1970s, and Less than 9 percent of developing-country flow receipts compared to an earlier peak of 28 percent in 1976

3 Foreign Direct Investment by region 1999-2003
Volume of FDI that flows into Africa: Only very low as a share of total global FDI flows or even as a share of FDI flows to developing countries, Also the share is on a steadily declining for several decades in the past. Source: UNCTAD (2006)

4 Foreign Direct Investment by region 2005-06
In 2006, FDI inflow to Africa rose by 20%, twice the amount recorded in 2004. Following substantial increases in commodity prices, many TNCs significantly expanded their activities in oil, gas, and mining industries (UNCTAD (2007)) 75% of FDI inflows to Africa go to S.Africa and oil- and mineral-abundant countries. Source: UNCTAD (2007)

5 Existing Studies Some Studies deal with the issues of FDI and their potential benefits for developing countries in terms of employment opportunities, technology transfers, and growth and development. Several studies on the determinants of FDI in developed countries and developing countries, Developed countries or developing countries cannot be grouped together given their different economic and socio-political conditions. Some studies concentrate on a region, but few on the African region.

6 Determinants of FDI – Dunning (1981, 1988) ‘electric theory’
Economic factors Policy framework Business facilitation measures Economic factors Policy framework Business facilitation measures Economic factors Policy framework Business facilitation measures Economic factors Policy framework Business facilitation measures Economic factors Policy framework Business facilitation measures Economic factors Policy framework Business facilitation measures Determinants of FDI 3 set of factors advantage that the firm has over its rivals in terms of its brand name, patent, or knowledge of technology and marketing 1. Firm-specific Advantage 2. Location- specific Advantage 3. Internalisation Advantage benefits for the firm in exploiting its competitive advantages & location advantages by investing in foreign affiliates that they control rather than dealing with unrelated firms located abroad

7 Research focused on the determinants of FDI identified the following factors as attracting FDI:
Comparative labour costs, Level of skills and Expertise, country size, economic openness nature of exchange rate regimes, return on investment, and political factors. Ease of Doing business

8 Benchmarking starting a business in COMESA countries
Starting a Business Region Ease of Doing Business Rank Overall Ranking: Starting a Business Procedures to start a Business (Number) Time to start a Business (Days) Cost to start a Business (% Income per Capita) Minimum Capital to Start a Business (% Income per Capita) World 1st Singapore New Zeland 1 0.4 2nd Canada 5 0.5 SSA Mauritius (24 th) Mauritius (7 th) 6 COMESA Burundi 177 138 11 43 215 Comoros 155 160 23 188 280 DRC 181 154 13 435 Djibouti 153 173 37 200 514 Egypt 114 41 7 18 2 Eritria 178 84 102 396 Ethiopia 116 118 16 30 693 Kenya 82 109 12 40 Madagascar 144 58 289 Malawi 134 122 10 39 125 Mauritius 24 Rwanda 139 60 8 14 108 Seychelles 104 68 9 38 Sudan 147 107 51 Swaziland 61 35 0.6 Uganda 111 129 25 100 Zambia 71 28 1.5 Zimbabwe 158 164 96 4.32

9 3 Specific Policies determining FDI
1. Rules and regulations governing the entry and establishment of foreign investors in a host country e.g., prohibition of entry, restrictions on ownership (joint venture requirement) or liberalization of entry 2. Treatment of foreign investors non-discrimination in the treatment of foreign and domestic firms (NT) preferential treatment of foreign or domestic firms (e.g., incentives) distinguish treatment before and after entry 3. Protection of foreign investors expropriation and nationalization; fund transfers; and dispute settlement are key issues in protection

10 METHODOLOGY Independent Variables included in the Study

11 Regression Equation

12 METHODOLOGY Natural Resource Intensity (RES):
As posited by the eclectic theory, all else equal, countries that are endowed with natural resources would receive more FDI. Omission of a measure of natural resources from the estimation, may cause the estimates to be biased We include the share of minerals and oil in total exports to capture the availability of natural resource endowments. A positive determinant is expected

13 Market Size: The size of the host market, which also represents the host country’s economic conditions and the potential demand for their output as well, is an important element in FDI decision-makings. Quoting Scaperlanda and Mauer (1969) FDI responds positively to the market size ‘once it reaches a threshold level that is large enough to allow economies of scale and efficient utilization of resources’. To proxy for market size (SIZE), we follow the literature and use real GDP per capita. The expected sign is positive.

14 Labour cost: Labour cost (wage) has always been argued to be a major component of total production cost Nominal wage rate (WAGE) as a proxy for labour cost. We would generally expect a negative sign on the coefficient However, the use of wage may not be entirely correct - Skilled Labour

15 Human Capital: Foreign direct investors are also concerned with the quality of the labour force in addition to its cost. A more educated labor force can learn and adopt new technology faster and is generally more productive. Higher level of human capital is a good indicator of the availability of skilled workers, which can significantly boost the locational advantage of a country. We control and test for the impact of labor quality, using the general secondary education enrollment rate (SER).

16 corporate tax rates (TAX):
Higher tax levels of the host country would be expected to deter potential FDI. However, there seems to be mixed empirical results as for instance Kemsley (1998) and Billington (1999) have found the host country tax rate to be a significant factor in determining FDI inflows. Wheeler and Mody’s (1992) have found the tax rate of the host country to be insignificant.

17 Openness (xmgdp): It is a standard hypothesis that openness promotes FDI Empirical evidences (Jun and Singh, 1996) exist to back up the hypothesis that higher levels of exports lead to higher FDI inflows. Trade/GDP has been included in the regression to examine the impact of openness on FDI.

18 Political instability (POL)
Political instability and the frequent occurrences of disorder ‘create an unfavorable business climate which seriously erodes the risk-averse foreign investors' confidence in the local investment climate and thereby repels FDI away’ (Schneider and Frey 1985). Political risk rating as provided by the International Country Risk Guide (2006) has been used as a proxy for Political Instability.

19 Regression Equation The dependent variable, FDI, is measured as the net foreign direct investment inflow as a percentage of GDP (see Adeisu,2002; Quarzi, 2005; Goospeed et al, 2006).

20 DATA SOURCE The main sources of data series are:
International Monetary Fund’s International Financial Statistics (IFS) (2006), World Development Indicators (WDI) (2006). Political risk ratings are obtained from internal country Risk Guide (2006).

21 ANALYSIS The Panel data techniques have been employed.
The use of panel data technique allows us to determine the temporal evolution of groups of countries rather than analyzing the temporal behaviour of each of them. Panel data may have group effects, time effects, or both. These effects are either fixed effect or random effect. The Hausman test specification, the test recommends the use of fixed effects model

22 Panel data estimates : Fixed effects (20 countries x 16 years (1990-2005))
Independent Variables Fixed effect estimates Constant Res size wage xmgdp pol Ser -3.64 (-1.75)* 0.063 (2.26)** 0.19 (2.46)** -0.086 (-2.13)** 0.34 (4.13)*** -0.12 (-2.25)** (2.22)* R2 Number of obs Hausman Test 0.45 320 Prob>chi2=0.052

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