THE IMPLICATIONS OF HO AND IRS THEORIES FOR BILATERAL TRADE FLOWS WITHIN

SUB-SAHARAN AFRICA

Julie Lohi

West Virginia UniversityJulie.lohi@mail.wvu.edu

MOTIVATION

Why Bilateral trade Flows are Low within Sub-Saharan Africa (SSA)?

LITERATURE Hanink and Owusu (1998) Used trade intensity index (TII) Find that ECOWAS has failed to promote trade

Alemayehu and Haile (2008) Regional grouping has insignificant effects on bilateral trade

flows in SSA. Reasons: poor private participation, compensation issue.

Faezeh and Pritchett (2009) Trade flows are low within SSA Gravity prediction similar to actual trade

Piet and Wheeler (2010) Transport infrastructure and border restrictions are main reasons

for lower trade rate in SSA

CONTRIBUTIONS Trade evaluation based on imperfect specialization in

production

Show that comparative advantages matter in stimulating trade

SSA countries exhibit similar endowments

Products are not differentiated in the region

1996 1998 2000 2002 2004 2006 20080

5000000000

10000000000

15000000000

20000000000

25000000000

30000000000

35000000000

40000000000Trade in Differentiated Good Vs. Homogeneous Goods in SSA

Differentiated goodsLinear (Differentiated goods)Homogeneous goodsLinear (Homogeneous goods)

Year

Trad

e Va

lue

UNDERLYING TRADE THEORIES

Heckscher-Ohlin Theory: Heckscher (1919) and Ohlin (1933)

Predicts high trade for large differences in factor endowment ratios.

Increasing return to scale theory: Krugman (1979, 1980)

Predicts intensive trade between industries producing different varieties of a product.

The love of varieties creates demand across countries.

METHODOLOGIES A- Build on Evenett and Keller (2002) to estimate the gravity equation for 118 countries grouped into 5 regions

Where , , are respectively imports of country i from country j, GDP of country i, j, world and region;

is importing country’s specifics;

represent respective dummies for common language, colony, contiguity, and landlocked;

is the log of distance between country i and j.

(1),

(2),

(3),

(4)

METHODOLOGIES

B- Compute the Grubel Lloyd index as:

, ,

where, represents a commodity, the Grubel Lloyd index reflects the intra industrial trade

(imports and exports) of country from (to) country. export value from country to country in differentiated

goods imports value in good of country from

METHODOLOGIES

C- Assess capital () to labor () ratio difference within each region

Compute for each country and the difference between each pair of countries

DATA

118 countries across the world grouped into 5 regions: Asia, Europe and North America, Latin America and Caribbean, Middle East and North Africa, and Sub-Saharan Africa.

Panel from 1997 to 2007

Data on bilateral imports is extracted from the IMF-DOT

Data on Real GDP, Investment Share, Real GDP per worker, and population are taken from the Penn World Tables (last version- 6.3)

Data on trade factor dummies can be found at http://www.cepii.fr/anglaisgraph/bdd/distances.htm

Capital stock and labor force data are from the World Bank’s World Development indicator (WDI) database

The Grubel Llyod is calculated using Uncomtrade data at 3-digit.

RESULTSTable 1: Testing Factor Endowments and the Comparative Advantage in SSA

Country Name 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007Angola K K K K L K L L L K KBenin L L L L L L L L L L LBurkina Faso L L L L L L L L L L .Burundi L L L L L L L L L L .Cameroon K K K K K K K K K L LCape Verde K K K K K K K K K K K1CAF L L L L L L L L L L LChad L L L L L K K L L L LComoros L L L L L L L L L L L2DRC L L L L L L L L L L LCongo, Republic K K K K K K K K K K KCôte d'Ivoire K K K L L L L L L L LEquatorial Guinea K K . K K K K K K K KEthiopia L L L L L L L L L L LGabon K K K K K K K K K K KGambia L L L L L L L L L L LGhana L L L L L L L L L K LGuinea L L L L L L L L L L L

Guinea-Bissau L L L L L L . . . . .

Kenya L L L L L L L L L L LLiberia . . . . L L L L L L LMadagascar L L L L L L L L L L LMalawi L L L L L L L L L L LMali L L L L K L K L L L LMauritius K K K K K K K K K K KMozambique L L L L L L L L L L LNiger L L L L L L L L L . .Rwanda L L L L L L L L L L LSenegal L L L K K K K K K K KSierra Leone L L L L L L L L L L LSouth Africa K K K K K K K K K K KTanzania L L L L L L L L L L LTogo L L L L L L L L L . .Uganda L L L L L L L L L L LZambia L L L L L L L L K K KZimbabwe K L L L L L L L L L L1Central African Republic2Democratic Republic of Congo

Note: The score k indicates the abundance of capital over labor in the country for a particular year, while the score L refers to the abundance of labor of capital

Source: Author's calculation using WDI database.

RESULTS

Table 2: Regional Average Grubel Llyod Index from 1997 to 2007

Mean Minimum MaximumEast and South Asia 0.12 0.00 0.28Europe and North America 0.24 0.00 0.43Latin America and Caribbean 0.06 0.00 0.16Middle East and North Africa 0.06 0.00 0.17Sub-Saharan Africa 0.02 0.00 0.11

Source: Author's calculation using UNCOMTRADE data.

RESULTSTable 3: Statistics on SSA Countries' Trade in Differentiated Goods from 1997-2007

Reporter Name Import Value (Million $U.S.) Export Value (Million $U.S.) Regional Share (percentage) 2GliSouth Africa 42781.6 6502.3 47.16 0.027Kenya 3107.8 1650.9 4.55 0.023Zimbabwe 1153.0 3556.7 4.51 0.031Mozambique 246.0 4112.8 4.17 0.027Nigeria 644.9 3177.5 3.66 0.029Côte d'Ivoire 3090.1 679.0 3.61 0.027Ghana 609.0 3034.7 3.49 0.027Tanzania 475.8 2448.3 2.80 0.025Burkina Faso 309.8 2347.3 2.54 0.026Mali 73.7 2440.0 2.41 0.026Malawi 366.4 2073.4 2.33 0.027Mauritius 906.0 1263.2 2.08 0.023Senegal 1394.0 756.2 2.06 0.023Togo 1024.2 1103.5 2.04 0.029Uganda 137.8 1584.3 1.65 0.021Botswana 993.6 620.8 1.54 0.033Benin 652.1 911.7 1.50 0.027Madagascar 129.3 1249.1 1.32 0.021Cameroon 447.1 819.2 1.21 0.025Guinea 38.9 745.3 0.75 0.022Gabon 126.5 640.5 0.73 0.022Niger 92.2 504.1 0.57 0.024Namibia 457.8 58.6 0.49 0.031Rwanda 20.9 470.7 0.47 0.025Ethiopia 28.2 416.8 0.43 0.024Seychelles 37.1 380.4 0.40 0.022Gambia 32.5 383.3 0.40 0.022Burundi 16.2 306.1 0.31 0.023Sierra Leone 21.7 239.0 0.25 0.024Guinea-Bissau 28.8 173.2 0.19 0.0221CAF 4.5 145.3 0.14 0.020Comoros 3.5 119.8 0.12 0.021Eritrea 18.2 41.1 0.06 0.024Cape Verde 14.3 38.3 0.05 0.022São Tomé and Príncipe 7.6 10.3 0.02 0.0261Central African Republic2The Grubel Llyod index (Gli) takes the maximum value of 1 for intensive intra industrial trade (importvalue = expport value),the minimum value of the Gli is 0 (in case of only import or export). Lower Gli means less intra industrial trade flows.

Source: Author's calculation using UNCOMTRADE data.

RESULTSTable 6: Estimation of Equation (4) using the Hausman- Taylor Methodology

Variables Asia EU_NAM LAC MENA SSAHTaylor HTaylor HTaylor HTaylor HTaylor

Y i Y j /Y r 0.339*** 0.153 0.050*** 0.042*** 0.041***(0.028) (0.238) (0.016) (0.004) (0.013)

D ij -4.108* -2.983** 0.004 -0.049 -0.033***(2.371) (1.252) (0.046) (0.046) (0.012)

Coli -22.835*** -13.077*** -0.532 0.006

(7.329) (2.391) (0.396) (0.078)

LL i 12.559*** -4.139 -0.191 0.079***(4.281) (2.708) (0.193) (0.013)

contigij -20.833 10.166 0.520** -0.278 -0.118**

(15.681) (7.713) (0.213) (0.215) (0.056)

CLij 21.626*** 16.015*** -0.042 0.479*** 0.031

(7.522) (4.931) (0.158) (0.104) (0.021)Constant 29.273 23.010** 0.010 0.026 0.225**

(19.973) (9.626) (0.370) (0.397) (0.097)

Observations 6,170 9,900 6,339 2,907 12,135Number of groups 606 900 631 273 1,190Wald chi2(31)= 13564.94 Wald chi2(35)= 3409.09 Wald chi2(31)= 2678.7 Wald chi2(21)= 1857.51 Wald chi2(41)= 8938.35prob> chi2= 0.0000 prob> chi2= 0.0000 prob> chi2= 0.0000 prob> chi2= 0.0000 prob> chi2= 0.0000

Note: ***, **, and * represent respectively 99, 95, and 90 percent significance. The heteroscedasticity- consistent standard errors are in parentheses.

CONCLUDING REMARKS

Bilateral trade flows are low within SSA compare to that of other regions due to:

Lack of comparative advantage in production across countries in SSA

Similar endowments in factors of production across countries within SSA

Homogeneity of traded goods

Less product differentiation

SUGGESTIONS

SSA countries might want to increase efforts towards accessing developed markets

Gain the “know-how” from interacting with mature markets

Benefit from their comparative advantage over industrialized countries

Use new technologies for industrialization and differentiate their products in many varieties.

THANK YOU FOR YOUR ATTENTION

YOUR COMMENTS ARE VERY WELCOME!