The Implications of HO and IRS Theories for Bilateral Trade Flows

Report
THE IMPLICATIONS OF HO AND IRS THEORIES
FOR BILATERAL TRADE FLOWS WITHIN
SUB-SAHARAN AFRICA
Julie Lohi
West Virginia University
[email protected]
MOTIVATION

Why Bilateral trade Flows are Low within SubSaharan 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
4E+10
Trade in Differentiated Good Vs. Homogeneous Goods in SSA
3.5E+10
Trade Value
3E+10
2.5E+10
Differentiated goods
2E+10
Homogeneous goods
Linear (Differentiated goods)
1.5E+10
Linear (Homogeneous goods)
1E+10
5E+09
0
1996
1998
2000
2002
2004
2006
2008
Year
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
(1),
(2),
(3),
(4)

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.
METHODOLOGIES
B- Compute the Grubel Lloyd index as:

 = 1 − [







 − 



 +  ], 0 <  ≤ 1,
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,

Panel from 1997 to 2007

Data on bilateral imports is extracted from the IMF-DOT




Europe and North America, Latin America and Caribbean, Middle East and North Africa,
and Sub-Saharan Africa.
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.
RESULTS
Table 1: Testing Factor Endowments and the Comparative Advantage in SSA
Country Name
Angola
Benin
Burkina Faso
Burundi
Cameroon
Cape Verde
1
CAF
Chad
Comoros
2
DRC
Congo, Republic
Côte d'Ivoire
Equatorial Guinea
Ethiopia
Gabon
Gambia
Ghana
Guinea
Guinea-Bissau
Kenya
1997
1998
1999
2000
2001
2002
K
K
K
K
L
K
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
K
K
K
K
K
K
K
K
K
K
K
K
L
L
L
L
L
L
L
L
L
L
L
K
L
L
L
L
L
L
L
L
L
L
L
L
K
K
K
K
K
K
K
K
K
L
L
L
K
K
.
K
K
K
L
L
L
L
L
L
K
K
K
K
K
K
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
Liberia
.
.
.
.
L
L
Madagascar
Malawi
Mali
Mauritius
Mozambique
Niger
Rwanda
Senegal
Sierra Leone
South Africa
Tanzania
Togo
Uganda
Zambia
Zimbabwe
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
K
L
K
K
K
K
K
K
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
K
K
K
L
L
L
L
L
L
K
K
K
K
K
K
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
K
L
L
L
L
L
1
Central African Republic
2
Democratic Republic of Congo
2003
L
L
L
L
K
K
2004
L
L
L
L
K
K
2005
L
L
L
L
K
K
2006
L
K
L
L
L
L
L
L
L
L
L
K
L
K
L
K
L
L
L
.
L
L
L
L
K
K
L
L
L
K
L
K
L
L
L
L
L
L
K
L
K
L
K
L
L
L
.
L
L
L
L
L
K
L
L
L
K
L
K
L
L
L
L
L
L
K
L
K
L
K
L
L
L
.
L
L
L
L
L
K
L
L
L
K
L
K
L
L
L
K
L
K
L
L
L
L
K
L
L
2007
K
L
.
.
L
K
L
L
L
K
L
K
L
K
L
K
L
L
L
L
L
K
L
K
L
K
L
.
.
L
L
L
L
L
L
K
L
.
L
K
L
K
L
.
L
K
L
L
L
L
L
K
L
.
L
K
L
K
L
.
L
K
L
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
East and South Asia
Europe and North America
Latin America and Caribbean
Middle East and North Africa
Sub-Saharan Africa
Mean
Minimum Maximum
0.12
0.00
0.28
0.24
0.00
0.43
0.06
0.00
0.16
0.06
0.00
0.17
0.02
0.00
0.11
Source: Author's calculation using UNCOMTRADE data.
RESULTS
Table 3: Statistics on SSA Countries' Trade in Differentiated Goods from 1997-2007
Reporter Name
South Africa
Kenya
Zimbabwe
Mozambique
Nigeria
Côte d'Ivoire
Ghana
Tanzania
Burkina Faso
Mali
Malawi
Mauritius
Senegal
Togo
Uganda
Botswana
Benin
Madagascar
Cameroon
Guinea
Gabon
Niger
Namibia
Rwanda
Ethiopia
Seychelles
Gambia
Burundi
Sierra Leone
Guinea-Bissau
1
CAF
Comoros
Eritrea
Cape Verde
São Tomé and Príncipe
Import Value (Million $U.S.)
42781.6
3107.8
1153.0
246.0
644.9
3090.1
609.0
475.8
309.8
73.7
366.4
906.0
1394.0
1024.2
137.8
993.6
652.1
129.3
447.1
38.9
126.5
92.2
457.8
20.9
28.2
37.1
32.5
16.2
21.7
28.8
4.5
3.5
18.2
14.3
7.6
Export Value (Million $U.S.) Regional Share (percentage)
6502.3
47.16
1650.9
4.55
3556.7
4.51
4112.8
4.17
3177.5
3.66
679.0
3.61
3034.7
3.49
2448.3
2.80
2347.3
2.54
2440.0
2.41
2073.4
2.33
1263.2
2.08
756.2
2.06
1103.5
2.04
1584.3
1.65
620.8
1.54
911.7
1.50
1249.1
1.32
819.2
1.21
745.3
0.75
640.5
0.73
504.1
0.57
58.6
0.49
470.7
0.47
416.8
0.43
380.4
0.40
383.3
0.40
306.1
0.31
239.0
0.25
173.2
0.19
145.3
119.8
41.1
38.3
10.3
0.14
0.12
0.06
0.05
0.02
2
Gli
0.027
0.023
0.031
0.027
0.029
0.027
0.027
0.025
0.026
0.026
0.027
0.023
0.023
0.029
0.021
0.033
0.027
0.021
0.025
0.022
0.022
0.024
0.031
0.025
0.024
0.022
0.022
0.023
0.024
0.022
0.020
0.021
0.024
0.022
0.026
1
Central African Republic
2
The 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.
RESULTS
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!

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