DRAFT
not to be quoted
Reforms and Growth in MENA Countries :
New Empirical Evidence
by
Mustapha Kamel Nabli
World Bank, Washington, D. C.
and
Marie-Ange Veganzones-Varoudakis
Centre National de la Recherche Scientifique,
CERDI, Clermont Ferrand
(May 2002)
1
Introduction
 Despite apparent Reforms from the end of the 1980s and the
beginning of the 1990s, the growth performance of the MENA
region has often been disappointing.
 We show that this has been the case because MENA economies
have most of the time lagged behind in terms of Reforms.
 Another explanation can be seen in the fact that the Growth
dividend of some Reforms has been small or non existent.
 For this purpose we have generated aggregated Reform indicators
using the Principal Component Analysis method which permits to
aggregate basic indicators in a more rigorous way than a subjective
scoring system. This methodology also avoids multicollinearity
problems when estimating an equation including several
disaggregated indicators.
 We have used panel data estimations techniques which allow some
comparative analysis between the different regions of our sample,
as well as between the MENA countries themselves.
 In addition to Economic Reforms, the link of Human capital and
Physical infrastructure to Economic Growth has also been
discussed.
 No studies have been undertaken ─ to our knowledge ─ in the area
of Economic Policy and Economic Growth using the same
methodology in the case of the MENA region.
2
This presentations is organised as follows:
 In the second section, we present the Principal Component
Analysis of the Economic Reform, Human capital and Physical
infrastructure indicators. Our analysis is based on a panel of 56
countries over the period 1970/80 (depending of the countries) to
19991.
 The third section discuss  in a comparative perspective  the
progress in Economic Reform of the MENA economies and their
development in Human capital and Core infrastructures.
 In the fourth section, we estimate a growth equation including the
various composite indicators.
 The fifth section presents the impact of Economic Reforms,
Human capital and Physical infrastructure on the growth
performance of the MENA economies.
 We illustrate that some inappropriate policies had a strong negative
influence on the growth performance of the region.
 The last section concludes.
1
Among these countries, 19 are African countries (8 CFA and 11 non CFA), 13
Latin American countries, 11 Asian countries and 12 MENA countries (of which
11 developing countries, see Annex 1 for the list of countries).
3
Economic Reform, Human Capital and Physical Infrastructures
A-Macroeconomic Stability (MS):
 Inflation (p) and Public Deficit as a percentage of GDP (PubDef),
(Fischer, 1993 ; De Gregorio, 1992);
 Foreign Exchange Parallel Market’s Premium [(lBmp, in log, Pinto, 1990]
B-External Stability (ES):
 External Debt in percentage of GNI (DebExGni) and of exports (DebExX),
 Current Account in percentage of exports (CurAcX)
C-Structural Reforms (SR):
 Trade Policy: (Balassa, 1978 ; Feder, 1982).
- TradeP1 = X+M/GDP from which we have deducted the “Natural Trade Openness”
(Frankel and Romer, 1999) and TradeP2 = TradeP1- X (oil + Mining)
 M3 to GDP [(M3) (Levine, 1997)
D-Human capital (H):
 the Infant Mortality rate (lMort) as a proxy of the Health conditions of the
population.
 the number of years of schooling of the population (lH1) for Primary, (lH2)
Secondary and (lH3) Superior education.
(Lucas, 1988, Psacharopoulos, 1988 ; Mankiw, Romer and Weil, 1992).
E-Physical infrastructures (Phys):
 the density of the Road Network [lRoads in km per km2]
 the number of Telephone Lines per 1000 people [lTel ]
(Barro, 1990 ; Aschauer, 1989 ; Murphy, Shleifer and Vishny, 1989).
4
Macroeconomic Reforms
 Most MENA countries undertook better Macroeconomic policies 
some starting in the 1980s (Morocco, Tunisia and Jordan essentially)
and others in the 1990s after a decade of regression (Iran, Syria,
Algeria, Egypt, Charts 1.1 and 1.2)

Successes were achieved in containing Inflation, which is now
particularly low in Morocco, Jordan and Tunisia (Chart 2.2, Annex
3).
 Improvements in reducing Public Deficit were made in Egypt,
Jordan, Iran, Syria, Algeria (Chart 3.2, Annex 3).
 Black Market in Exchange Rate was ended in almost all the countries
(Chart 4.2, Annex 3).
 However, Public Deficit still fluctuated between 1 to 3 % of GDP in
the 1990s  which is a bit high compared to other regions (Charts
3.1 and 3.2, Annex 3).
 In Egypt, less success was achieved in fighting Inflation, which is
even higher in Algeria and Iran (above MENA, Asia and CFA Africa
average, Charts 2.1 and 2.2, Annex 3).

Black Market in Exchange Rate has not been controlled in Iran,
Syria and Algeria, due to capital controls or political instability (Chart
4.2, Annex 3).
5
External Stability Reforms

MENA countries achieved poorly during the whole period  far behind
Latin America and Asia (Chart 5.1). External Stability shows a clear
deterioration in the 1980s.

This result is largely explained by the unsustainable level of external Debt
(Charts 6.1 and 7.1, Annex 4) due to the high level of public investment of
the 1970s and 1980s (Annex 8).

Even if in the 1990s sizeable efforts were made in re–negotiate the
external Debt, its burden remains a problem in most MENA economies.

In the 1990s, MENA countries’ external Debt accounts for 60-70% of
GNI in Morocco, Egypt, Algeria, Tunisia (around 150 to 200% of
exports) and more than 130% of GNI in Syria and Jordan (Charts 6.2
and 7.2, Annex 4).

In the 1990s, Morocco and Egypt were the only two countries which
have reduced their external Debt2.

This situation indicates that a significant scope for debt reduction still
exists in the region.

However, MENA economies are among the best performers as far as
Current Account balance is concerned (Chart 8.1, Annex 4) and efforts in
reducing deficits are noticeable almost everywhere.
2
Morocco and Egypt did benefit from major debt forgiveness following the Gulf War in the
early 1990s.
6
Structural Reforms

MENA countries has performed rather well and only been surpassed by
the Asian economies in the 1990s (Chart 9.1.A and 9.1.B., Annex 5).

This result is largely due to the high financial depth of the MENA
economies (M3 to GDP having averaged 60 to 80 % ).

Financial depth has been particularly significant in Jordan and Egypt
(more than 100% of GDP) but has improved in almost all MENA
countries to reach 50-60 % of GDP (Chart 10.2, Annex 5 ).

This result does not mean that the economies benefit from a strong
Banking system or a developed Financial sector (Nabli, 2000).


On the opposite, Trade openness (30 to 40% of GDP) has been by far
inferior than in Asia (45 to 70% of GDP, Chart 11.1, Annex 5).

This is the case despite progress in the 1990s, particularly with the exports’
diversification of the non oil producing countries (Chart 11.2, Annex 5).

Trade openness is now rather high in Jordan and Tunisia (60% of GDP),
these countries being (with Morocco) the most diversified of the region.

It remains, however, weak in Iran, Syria and Algeria (around 30% of GDP
in the 1990s) who have difficulties in moving from oil production and a
State
dominated
management
of
their
economies.
7
Human Capital

Realisations of MENA countries have been rather satisfactory during the
1980s and the 1990s.

Progress was, nevertheless, slightly better in Asia and Latin America
(Chart 12.1).

Mortality rates have been divided by 3 compared to the 1970s. Levels are
now comparable to Asia and Latin America (Chart 13.1, Annex 6).

Best performer has been Egypt, but noticeable efforts were also made by
Iran, Algeria, Tunisia and Morocco (Chart 13.2, Annex 6).

For Primary Education Tunisia exhibits the best results in the 1990s (5
years of Primary schooling) followed by Jordan, Algeria, Syria and Iran
(around 4 years of schooling, Chart 14.2, Annex 6).

In Secondary education, leaders have been Syria, Iran, Egypt, and
Jordan (with 1.5 to 2 years of schooling). Progress in Algeria, Tunisia
and Morocco have conversely been weaker (Chart 15.2, Annex 6).

In Superior education, Syria, Jordan and Egypt (with 0.6 years of
schooling) performed far better than Algeria, Tunisia, Morocco and
Iran, whose level of Superior education remains low (around 0.1 years
of schooling, Chart 16.2, Annex 6).
8
Core Infrastructures

MENA countries indicators of Physical infrastructure are weak.
(Chart 17.1).

This assessment hides differences between countries (Chart 17.2)
 Performance of MENA countries in Road network are not better than
in Africa (Charts 18.1 and 18.2, Annex 7).
 Even if a majority of countries have improved their level of Roads
infrastructure, this level remains low in Jordan, Algeria and Egypt.
 Better progress has been made by Syria, Tunisia, Morocco and Iran,
which level is close to that in Latin American  but far from the
Asian level.
 In spite of real progress in almost all MENA countries, the level of
Telephone equipment of the region remains low compared to Latin
America and Asia (Charts 19.1 and 19.2, Annex 7).
 Only Iran, Syria and Jordan reveal level of equipment similar to
Latin America.

However, this level still remain inferior to Asian countries.
9
Growth Performance in the MENA Countries
 MENA countries reveal a rather disappointing pattern in
economic growth. This is the case despite some progress in
various areas of Reforms.
 Even if the growth performance of the 1990s has improved
in almost all MENA countries, GDP per capita growth rates
have been largely surpassed by Asia (Chart 20.1).
 Syria and Tunisia have been the best performers of the
group, followed by Egypt and Iran.

Outcome are, however, poor in the case of Morocco whith a
decreasing trend across the period, as well as Algeria
affected by the fall in oil prices and the political turmoil
(Chart 20.2).
10
Economic Reforms, Human Capital, Physical Infrastructure and
Growth
The long run Growth equation is based on Barro and Sala-I-Martin
(1995)3
ln(y i,t) = c + a*ln(y i,t -1) + b*l.ln(Inv i,t) + d1* (MSi,t) + d2*(ESi,t)
+ d3 *(SRi,t)+ e1*(Physi,t) + e2.*(Hi,t)
(1)
with: - y i,t –1 = GDP per Capita of the previous period
- Inv i,t = Investment ratio to GDP
- MSi,, t = Macroeconomic Stability Indicator
- ESi,,t = External Stability Indicator
- SRi,,t = Structural Reform Indicator (SR1 and SR2)4
- Physi,,t = Physical Infrastructures Indicator
- Hi,,t = Human Capital Indicator
- c = intercept, a, b, d1 to d3, e1 to e2, = parameters, t = time
index and t = error term.
3
The short-run dynamic of the REER has also been estimated through an error
correction model (Equation (A3-1) in Annex 10)
4
(SR1) is based on the first Trade Policy indicator (TradeP1) and (SR2) on the
second one (TradeP2)
11
Table 2: Estimation Results of the Long Term Growth Equations
Dependent Variable ln(yt)
Independent Variables
ln(yt-1 )
In(invt)
MSt
ESt
SRt
Physt
Ht
Adjusted R²
Fischer test
Haussmann test
Eq1
-0.15
(7.93)
0.07
(5.90)
0.009
(1.81)
0.03
(5.71)
-0.0008a
(0.10)
0.02
(1.05)
0.02
(1.72)
0.26
3.6
44.7
Eq2
-0.11
(6.14)
0.011
(1.96)
0.03
(5. 10)
0.014a
(1.64)
0.02
(1.18)
0.0003
(0.03)
0.19
2.79
37.5
Eq3
-0.15
(7.87)
0.08
(6.70)
0.009
(1.76)
0.03
(5.51)
-0.002b
(0.32)
0.02
(1.00)
0.03
(2.03)
0.28
3.5
49.9
Eq4
-0.10
(5.26)
0.01
(1.92)
0.023
(4.56)
-0.007b
(0.98)
0.02
(0.97)
0.004
(0.30)
0.26
3.6
44.7
Note: Student t statistics are within brackets.
The number of observations used in the regression is respectively 648 and 578.
Data have been compiled from WDI, GDF, GDN and LDB World Bank databases.
Coefficient in bold are significant at 1%, 5% or 10 % level.
a: SR1 (including TradeP1) and b: SR2 (including TradeP2)
 Estimated relationships are consistent with the theory. An increase in
Investment, Human capital, Macroeconomic and External Stability
leads to higher Growth rates.
 Estimations do not validate the role of Structural Reforms in
improving the growth performance of the economies.
 They do not confirm neither the role of Physical infrastructure
12
Impact of Economic Reform, Human Capital and Physical
Infrastructure on Growth of MENA Countries
Calculation is based on the estimated elasticity of the aggregate
indicators, as well as on the weights of each Principal Component in the
aggregate indicator combined with the loadings of the initial variables in
each Principal Component.
Table 3 : Economic Policy and Infrastructure Variables
Short and Long Term Coefficients/Elasticities (Equation (1):
Index
Variables
Short Term Elasticities Long Term
Standardized
Level
Elasticities
Variables Variables
-0.004
-0.001
-0.008
-0.002
-0.002
-0.014
0.001
0.014
0.09
MS
P
ln(Bmp)
PubDef
ES
DebExX
DebExGni
CurAccX
-0.015
-0.012
0.011
-0.006
-0.029
0.021
-0.04
-0.19
0.14
SR*
TradeP*
M3*
-0.0005
-0.0005
-0.001
-0.002
-0.007
-0.013
0.012
0.012
0.01
0.01
0.07
0.05
-0.013
0.013
0.015
0.014
-0.017
0.023
0.013
0.009
-0.11
0.15
0.09
0.06
Phys* ln(Roads)*
ln(Tel)*
H
ln(Mort)
ln(H1)
ln(H2)
ln(H3)
* These variables are non significant
13
Table 4:Contribution of Human Capital to growth
Years
H
Education
Mortality Tot contribution GDP per Capita
Primary Secondary Superior per 1000
of H
Growth rate
number of years of schooling
pop
Improvment
Actual
3.6
5.5
7.7
-3.9
1980-89
Annual
-0.7
2.9
6.3
7.4
-3.7
1990-99 Growth Rate
1.8
Without
LT Elasticity 0.15
0.09
0.06
-0.11
Progress in H
0.5
0.5
0.5
0.4
1980-89 Contribution
1.9
-2.6
0.4
0.6
0.4
0.4
1990-99 to Growth
1.8
0
 Human capital presents a strong effect on growth (table 3).
 Primary education shows a greater impact than Secondary and Superior
education (Table 3).
 Improving Health conditions turns out to have a stronger impact than
Secondary education (Table 3).
 Knowing that MENA region have developed a satisfactory level of
Primary, Secondary education and Health conditions, Human capital
has constituted a clear engine of growth (Table 4) .
 Improvement in Primary schooling has contributed to an average per
year of 0.5 points of GDP per capita growth rate in the 1980s and of
0.4 during the 1990s. The same conclusions can be drawn for
Secondary and Superior education (0.5 in the 1980s and of 0.6 and
0.4 respectively in the 1990s)
 Amelioration of the Health conditions has contributed to 0.4 point of
growth for each period
 Globally, improvement in Human capital explains 1.9 points of
growth for both period. This means that, without progress in Human
capital, GDP per capita growth rate would have been of –2.6% in the
1980s (instead of –0.7%) and of 0% in the 1990s (instead of 1.8%,
Table 4).
14
Table 5:Contribution of External Instability to growth
Years
ES
DebX
DebGNI CurAcc
% Exports % GNI % Exports
15.4
3.0
0.7
1980-89
Annual
-7.3
1.1
-1.4
1990-99 Growth Rate
LT Elasticity
1980-89 Contribution
1990-99 to Growth
-0.04
-0.6
0.3
-0.19
-0.6
-0.2
0.14
0.10
-0.20
Tot
contribution
of External
Instability
-1.1
-0.1
GDP per Capita
Growth rate
Actual
-0.7
1.8
Without External
Instability
0.4
1.9

In the 1980s External Instability had an important negative impact on
growth.

The increase in the Debt ratios led to the deterioration of 1.2 points of
the GDP per capita growth rate (0.6 for each ratio, Table 5).

On average, External Instability have cost yearly 1.1 points of GDP
per capita growth rate in the 1980s and 0.1 in the 1990s.

Growth could have reach of 0.4% on average per year (instead of 0.7%) in the 1980s and 1.9% (instead of 1.8%) in the 1990s.

These results illustrate also the efforts made in the 1990s by most of
the countries of the region in reducing their external fragility.
15
Table 6:Contribution of Macroeconomic Instability to growth
Years
MS
1980-89
Annual
1990-99 Growth Rate
p
%
9.00
-5.79
LT Elasticity -0.008
1980-89 Contribution -0.07
0.05
1990-99 to Growth
bmp
pubdef Tot contribution GDP per Capita
of Economic
Growth rate
Actual
level % GDP
Instability
14.70
-0.08
-0.7
3.00
-0.02
1.8
Without External
-0.014 -0.09
Instability
-0.2
-0.01
-0.3
-0.4
-0.04
0.00
-0.04
1.8
 Macroeconomic Stabilisation exhibits a much lower impact on
growth.
 The only variable that seems to have substantially contributed to the
absence of growth in the 1980s is the distortions in Exchange Rate .
 Augmentation of this variable has cost on average yearly 0.2 points
of GDP per capita growth rate (Table 6). This makes of the
Exchange Rate a non negligible factor in accompanying Economic
Reforms.
 Overall, estimations fail to show a strong impact of Stabilisation of
the economies
 Macroeconomic distortions have only cost on average yearly 0.3
points of GDP per capita growth rate in the 1980s. This means that
growth performance of the region could have been of –0.4% per year
(instead of -0.7%).
16
Conclusion
 Most MENA countries undertook better Macroeconomic policies 
starting in the 1980s (Morocco, Tunisia and Jordan essentially) or in
the 1990s after a decade of regression (Iran, Syria, Algeria, Egypt)
 Performance in Structural Reforms seem also, at a first glance,
satisfactory. This is, however, due to a high financial depth. On the
opposite, Trade openness has been more deficient.
 MENA economies achieved also poorly in External Stability. This is
largely explained by the unsustainable level of external Debt due to the
high level of public investment of the 1970s and 1980s.
 Realisations of MENA countries in Human capital have been rather
good. On the opposite Physical infrastructure has been weak.
 Our estimations show that Investment, Human capital, Macroeconomic
and External Stability have led to higher Growth.
 They do not validate, however, the role of Structural Reforms and of
Physical infrastructure.
 Human capital has presented a strong effect on Growth (1.9 points
yearly of GDP per capita growth rate in the 1980s and the 1990s).

External Instability has cost, on the contrary, 1.1 points of Growth
yearly in the 1980s. This emphasises the importance to reduce MENA
external fragility.

Macroeconomic Stability exhibits a low impact on Growth, except for
the distortions in Exchange Rate which appear to be a non negligible
factor in accompanying Economic Reforms.
17
Annex 1
List of countries of the sample
MENA
AFRI CA
CFA
United Arab Emirates(ARE)
Bahrain (BHR)
Algeria (DZA)
Egypt, Arab Rep. (EGY)
Iran, Islamic Rep.(IRN)
Burkina Faso (BFA)
Cote d'Ivoire (CIV)
Gabon (GAB)
Cameroon (CMR)
Gambia, The (GMB)
Jordan (JOR)
Kuwait (KWT)
Malta (MLT)
Morocco (MAR)
Syrian Arab Republic (SYR)
Tunisia (TUN)
Niger (NER)
Senegal (SEN)
Togo (TGO)
ASIA
LATIN
AMERICA
NonCFA
Botswana (BWA)
Ghana (GHA)
Kenya (KEN)
Madagascar (MDG)
Mozambique
(MOZ)
Mauritius (MUS)
Malawi (MWI)
Nigeria (NGA)
Tanzania (TZA)
South Africa (ZAF)
Zambia (ZMB)
Other Countries
Israel (ISR)
18
Bangladesh (BGD)
China (CHN)
Indonesia (IDN)
India (IND)
Korea, Rep.(KOR)
Argentina (ARG)
Bolivia (BOL)
Brazil (BRA)
Chile (CHL)
Colombia (COL)
Sri Lanka (LKA)
Malaysia (MYS)
Pakistan (PAK)
Philippines (PHL)
Singapore (SGP)
Thailand (THA)
Costa Rica (CRI)
Ecuador (ECU)
Guatemala (GTM)
Mexico (MEX)
Peru (PER)
Paraguay (PRY)
Uruguay (URY)
Venezuela, RB (VEN)
Annex 2 : Principal Component Analysis
Table A2.1 : Macroeconomic Stability Variables
Component Eigenvalue Cumulative R2
P1
P2
P3
1.19
0.96
0.85
Loadings
P
lBmp
PubDef
P1
0.48
0.72
-0.67
0.40
0.72
1
P2
0.86
-0.16
0.45
P3
0.19
-0.68
-0.60
MS = 0.39/ 0.71*P1 + (0.71-0.39)/ 0.71*P2
**********************************************************************
Table A2.2: External Stability Variables
Component Eigenvalue Cumulative R2
P1
1.83
0.60
P2
0.81
0.87
P3
0.362
1
Loadings
DebExX
DebExGni
CurAccX
P1
0.89
0.74
-0.69
P2
0.03
0.58
0.67
P3
0.45
-0.31
0.24
ES = P1
19
Table A2.3: Structural Reform Variables
Component Eigenvalue Cumulative R2
P1
1.36
0.68
P2
0.63
1
Loadings
TradeP1
M3
P1
P2
0.82 0.56
0.82 -0.56
SR = P1
Table A2.4: Human Capital Variables
Component Eigenvalue Cumulative R2
P1
2.95
0.73
P2
0.50
0.86
P3
0.34
0.95
P4
0.19
1
Loadings
ln(Mort)
ln(H1)
ln(H2)
ln(H3)
P1
0.79
-0.84
-0.91
-0.89
P2
0.58
0.33
-0.004
0.20
P3
0.15
-0.42
0.25
0.27
P4
0.08
0.03
0.32
-0.29
H = P1
**********************************************************************
Table A2.5: Physical Infrastructure Variables
Component Eigenvalue Cumulative R2
P1
P2
1.41
0.58
0.70
1
Loadings
ln(Roads)
ln(Tel)
P1
P2
0.84 0.53
0.84 -0.53
Phys = P1
20
Annex 3: Macroeconomic Stability Indicators
21
Annex 4: External Stability Indicators
22
Annex 5 : Structural Reform Indicators
23
Annex 5 : Structural Reform Indicators (end)
24
Annex 6: Human Capital Indicators
25
Annex 6(end)
26
Annex 7 : Physical Infrastructure Indicators
27
Annex 9
Table A-5: Augmented Dickey Fuller Test (ADF)
Equations (1)
Variable
ln(y)
ln(Inv)
MS
P
lBmp
PubDef
ADF statistic
k(1) Trend
-1.89 1
yes
-1.92 1
no
Critical
value(2)
-1.82*
-1.82*
ADF
test
I(0)
I(0)
-2.76
1
no
-1.82*
I(0)
-2.43
1
no
-1.82*
I(0)
ES
DebExX
DebExGni
CurAccX
-1.06
-2.47
5.12
1
1
1
no
no
no
-1.69***
-1.82*
-1.69***
I(1)
I(0)
I(1)
SR
TradeP
M3
-3.77
-2.90
1
1
no
no
-1.82*
-1.82*
I(0)
I(0)
H
ln(Mort)
ln(H1)
ln(H2)
ln(H3)
- 3.3
- 1.83
- 2.05
-1.93
1
1
1
1
no
no
no
no
-1.82*
-1.82*
-1.82*
-1.82*
I(0)
I(0)
I(0)
I(0)
Phys
ln(Roads)
ln(Tel)
-3.65
-2.76
1
1
no
no
-1.82*
-1.82*
I(0)
I(0)
-1.82
3
no
-1.82*
I(0)
Residual of
the
Estimation
(1) k is the number of lags in the ADF test. (2) Im, Pesaran and Shin (1997)
critical values (respectively * 1%, ** 5% and *** 10% level). Data have been
compiled from WDI, GDF, GDN and LDB World Bank databases.
28
Annex 10
The Short-Term Dynamics of the Growth Equation
The short-term dynamic adjustment of the GDP per capita toward its equilibrium level
has been estimated through an error correction model:
ln(y i,t) = - a ln(y i,t -1) - ln(y i,t- 1 )
+ a’ ln(y i,t -1 )
+ b1.ln(Inv i,t) + b2.(SRi,t) + b3.(MSi,t) + b4.(ESi,t)
+ b5.(Physi,t) + b6.(Hi,t)
+ c1.ln(Inv i,t -1) + c2.(SRi,t -1) + c3.(MSi,t -1)+c4.(ESi,t -1)
+c5.(Physi,t -1) + c6.(Hi,t -1)
(A4-1)
Table A-6 : Estimates of the Error Correction Model
Dependent variable: ln(yt)
Variable
1t-1*
ln(y i, t-1 )
ln(Inv i, t)
(SR i, t )
(MS i, t)
(ES i, t)
(Phys i, t)
(Hi, t)
ln(Inv i, t-1)
(SR i, t-1)
(MS i, t-1)
(ES i, t-1)
(Physi, t-1)
(Hi, t-1)
D-W
Elasticity
-1.00
-0.83
0.04
-0.01
-0.001
-0.006
0.013
-0.003
-0.04
-0.013
0.005
0.006
0.002
-0.006
2.20
Student
(6.57)
(6.49)
(2.05)
(1.5)
(0.18)
(0.94)
(0.31)
(0.12)
(1.74)
(0.42)
(1.31)
(0.99)
(0.01)
(0.2)
Note: Student t statistics are within brackets. The sample includes 176
observations over 1969/80 -1999 period. * 1t-1 is the lagged error term of the
cointegrating Equations (1). Data have been compiled from WDI, GDF,
GDN and LDB World Bank databases.
29