Transcript Managing Risk in Africa through Institutional Reform

Managing Risk in Africa
through Institutional Reform
Phillip LeBel, Ph.D.
Professor of Economics
School of Business
Montclair State University
Upper Montclair, New Jersey 07043
[email protected]
Understanding Africa’s Weak Economic Performance
•
•
By almost any measure, Africa’s economic growth has been weak
over the past twenty-five years
While mean PPP GDP per capita has increased by modest
amounts, median PPP GDP per capita has hardly increased at all.
The Mixed Record of African Development Indicators:
Adult Illiteracy Rate
Drought Frequency in
Africa
Cereal Crop Yields
Africa’s Share in World Trade
Africa’s Share in Global Merchandise Trade
Reframing African Development Strategies Must
Begin With An Emphasis on Risk Management
•
Aggregate country risk, which includes political, economic,
financial, and environmental factors, is inversely related to the
level of per capita GDP
Corruption is a Determinant of Risk
•
Corruption is directly related to the level of risk.
In turn, corruption is a function of several factors:
•
Judicial independence is inversely related to the level of corruption
• Economic Freedom Affects the Level of Per Capita GDP
•
Economic freedom, an important contributor to development, has
improved little in Africa over the past twenty-five years.
Rising International Aid In Africa
International Aid has had a negative
impact on per capita GDP
•
International aid, which has often served political over economic interests,
has largely failed to raise per capita income in Africa, even when increases
have been made.
As a result, even rising levels of FDI
have had a lower impact than
elsewhere
•
As a result, even rising levels of FDI have but a limited impact on
economic development in Africa. In part this is because the level of FDI
is so small relative to GDP, which in turn reflects the overall level of
aggregate country risk.
Despite political instability, military
spending in Africa has remained
relatively low
•
Despite political instability, military spending in Africa has been lower
than in some developed countries. At the same time, it has been higher
than in most parts of Asia, China and North Korea being the principal
exceptions.
The Quality of Institutional Governance
is a Key to Managing Risk
•
Property rights in Africa have experienced some modest improvements,
with some relapses in more recent years. The effect has been negative on
the level of economic freedom, with higher risk resulting in lower levels
of per capita GDP.
Democracy Offers Some Modest
Gains in Per Capita GDP
•
Democracy, which in addition to transparent and fair elections, consists in
the level of civil liberties and political rights. Despite some gains in
Africa, the effects on per capita GDP have been weak.
Some Stylized Patterns of African Development
Determinants of Risk in Africa
Panel Nested Regression Equations
Basic Model Estimating Equations:
Dependent Variable:
CONSTANT
CIVLIBS
POLRTS
DEMOC
3.
-8.173
2.730
(42.534)
3.737
(67.292)
PROPRT
ECFREE
3.
1.245
JUDIND
4.
2.769
CORRUPA
4.
7.918
AIDGNI
6.
11.482
RCCRISK
4.
21.701
GNSGDP
7.
577.806
TRDEP
3.
133.203
MKTCAPRATE
9.
11.262
FDIGDP
8.
171.300
4.
-1662.856
0.106
(7.142)
DEMOC*
0.025
(10.675)
0.979
(15.225)
ECFREE*
JUDIND*
0.448
(3.480)
-0.138
(3.168)
MILBURD
-1.124
(6.134)
0.114
(6.137)
DEBTSRAT
AIDGNI*
0.314
(8.041)
2.903
(8.465)
CORRUPA*
RCCRISK*
-12.234
(3.225)
-1.670
(2.818)
-3.675
(5.474)
GNSGDP*
141.747
(15.120)
16.021
(14.388)
52.745
(53.057)
TRDEP*
MKTCAPRATE*
FDIGDP*
Number of Observations
Adj. R-Sq.
F
PPPRPCGDP
3.209
(6.842)
750
0.9830
1395.21
750
0.9701
810.92
750
0.9336
5267.19
750
0.9789
34796.17
750
0.7229
64.04
750
0.8402
196.24
Notes:
1. T-statistics are reported in parentheses
2. Starred variables are based on predicted values from a nested regression.
3. Estimate based on fixed effects using cross-section weights
4. Estimate based on no effects with cross-section weights.
5. Estimate based on two-stage least squares with cross-section weights and fixed effects.
6. Estimate based on fixed cross-section specification with period GLS weights.
7. Estimate based on two-stage least squares with rccrisk instrument, fixed cross-section specification with cross-section GLS weights.
8. Estimate based on two-stage least squares, with fixed effects and cross-section weights, d(RCCRISK) as instrument.
9. Estimate based on two-stage least squares with ecfree(-1) as instrument, fixed cross-section and cross-section GLS weights.
750
0.4769
750
0.8020
98.89
750
0.8932
357.25
750
0.8130
750
0.8998
2243.20
Basic Model Institutional Valuations:
• Estimates are based on parametric changes in selected
independent variables
Regional Variation Valuations:
Africa Sample Profile:
Model Descriptive Statistics:
Model Definitions and Sources:
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