Transcript Convergence Prospects for CEE Countries

ACADEMY OF ECONMIC STUDIES
DOCTORAL SCHOOL OF FINANCE AND BANKING
Convergence Prospects for CEE
Countries
Mihaescu Flaviu
M. Sc. Dissertation Paper
Coordinator: Professor Moisa Altar
Convergence:
Hypotheses
•Poor countries catch-up with the rich ones.
•The farther the initial level of (per capita) output from
the steady state, the faster the growth.
•Equation:
1
1  e   T
(ln Yi ,T  ln Yi ,0 )  a  (
)  Yi ,0
T
T
Convergence:
Major drawbacks
•“Steady states”: different countries have different steady
states
•Unconditioned convergence holds only for some
countries / regions
•E.g.: U.S. states, Japanese prefectures and OECD
regions
•They have the same steady states
Conditional Convergence
•Conditional convergence accounts for different
steady states
•Conditioning variables may be:
•Government consumption
•Domestic savings
•Domestic investments
Conditional Convergence
•Equation:
1
1  e   T
(ln Yi ,T  ln Yi ,0 )  a  (
)  Yi ,0    X i ,0
T
T
•Empirical evidence:
•Barro and Sala-i-Martin (1991),
•Mankiw, Romer and Weil (1990),
•Sachs and Warner (1995)
Unconditional Convergence:
CEEC11
Premises for convergence:
•the same pattern of output growth
•EU accession candidates and proximity
•converging structure of the
economies
•legislative and institutional
approximation
•openness of trade
Unconditional Convergence:
CEEC11
0.07
y = 0.0999x - 0.0787
R2 = 0.0336
0.06
Average
Growth Vs.
Initial Level of
GNP per
capita, PPP,
1992 - 2000
Average Growth
0.05
0.04
0.03
0.02
0.01
0
1.04
1.06
1.08
1.1
-0.01
Initial Level
1.12
1.14
1.16
1.18
Conditional Convergence:
Accounting for Different Steady-States
•Split the 11 countries group by EU - Accession criteria:
1998 Group:
Poland, Czech Republic, Estonia, Hungary and Slovenia
2000 Group:
Bulgaria, Lithuania, Latvia, Romania, Slovak Republic
plus Croatia
Conditional Convergence:
Accounting for Different Steady-States
•The 1998 Group will have the per capita income level of
Spain as steady state (about 80% of EU level)
•The 2000 Group will have the per capita income level of
Greece as steady state (about 60% of EU level)
Conditional Convergence:
Accounting for Different Steady-States
Bulgaria
Croatia
Czech Republic
Estonia
Hungary
Latvia
Lithuania
Poland
Romania
Slovak Republic
Slovenia
Relative Per Capita Relative Per Capita
Income Level as a % Income Level as a
of Steady State
% of EU Average
1992
2000
2000
39.87
42.40
25.1
40.56
53.71
31.8
79.17
80.38
63.1
44.95
66.72
39.5
59.25
69.94
54.9
42.01
49.66
29.4
53.86
50.66
30.0
38.68
51.97
40.8
42.91
46.62
27.6
59.76
61.91
48.6
78.57
97.32
76.4
The highlighted countries are those from the 1998 group
and their per-capita GNP was divided by Spain’s. The rest –
not highlighted – are the 2000 group countries plus Croatia
and they have Greece as steady state.
Conditional Convergence
0.05
y = -0.1847x + 0.0029
R2 = 0.1256
Average Growth
Vs. Initial Level
of relative GNP
per capita, PPP,
1992 - 2000
Average Growth
0.04
0.03
0.02
0.01
0
-0.12
-0.1
-0.08
-0.06
-0.04
-0.02
0
-0.01
Initial Level
Unconditional Convergence in
Expanded Sample
24 countries sample, CEEC11 + CIS countries + Turkey
AVG v s. INI
0.10
Average Growth Vs.
Initial Level of GNP
per capita at PPP in
expanded sample,
1992 - 1999
0.05
AVG
0.00
-0.05
-0.10
-0.15
-0.20
1.0
1.1
1.2
1.3
INI
1.4
1.5
Unconditional Convergence in
Expanded Sample
Regression output
(CIS is a dummy variable for CIS countries):
Avg  a  (1  e
with a  0.2153
(0.0139)
  T
)  Ini    CIS
  0.0239 and    0 . 0463
(0.0478)
(0.0259)
Adj. R-sqr = 0.4225
Prob. (F-Stat.) = 0.0016
Conditional Convergence:
Conditioning Variables
Conditioning Intercept
Variable Name
EU-Dummy
-0.0213
[0.112]
Institutional
-0.0301
Quality
[0.088]
Liberalization -0.0795
Index
[0.065]
Trade
-0.0488
(%GDP,PPP) [0.029]
Secondary
-0.1365
School
[0.024]
Enrolment
Beta
Conditioning
Variable
-0.0509 [0.054] 0.023 [0.013]
Adjusted Rsquared
0.515
-0.0628 [0.068] 0.0035 [0.025]
0.437
-0.0464 [0.103] 0.012
[0.050]
0.344
-0.0640 [0.047] 0.0895 [0.012]
0.523
-0.046 [0.071] 0.0015 [0.012]
0.467
Conditional Convergence:
Conditioning Variables
Avg  a  (1  e  T )  Ini   1  Trade  2  InstQ
With
a = -0.06
β = -0.089
[0.005]
[0.017]
γ1 = 0.068 γ2 = 0.0025
[0.019]
[0.037]
R - sqr. = 0.803F-stat. = 9.539 [0.007]
Adj. R - sqr. = 0.719
Conditional Convergence:
Conditioning Variables
•“Institutional Quality” comprises voice and
accountability, politically instability and violence,
government effectiveness, regulatory burden, rule
of law and graft.
•“Trade” is the sum of imports and exports
divided by GDP, all at PPP, and it is often taken
as a measure of openness.
Timing Convergence
•The 1998 group (Czech Republic, Estonia,
Hungary, Poland and Slovenia) will reach Spain or
approximately 80 percent of EU average per
capita income in 16 – 18 years
•The 2000 group (Bulgaria, Latvia, Lithuania,
Slovak Republic, Romania plus Croatia) will
reach Greece or approximately 60 percent of EU
average income also in 16 – 18 years.
Scenario Analysis
Assumptions:
•“Trade” will increase with one Standard Deviation
•“Institutional Quality”: the 1998 Group will improve
their institutional quality with 2 points, while the 2000
Group will improve with 4 points.
•“Optimistic” scenario assumes a 9% speed of
convergence, the “pessimistic” one a 2.4%, while the
“intermediate” one assumes 6%.
Scenario Analysis
Country Trade
St. Dev.
BLG
0.2329
Trade +
Institution
1 St. Dev. al Quality
0.2572
0.1
0.0243
Increase
4
New Inst.
Q. Level
4.1
HRV
0.4087
0.0357
0.4444
0.3
4
4.3
CZ
0.3852
0.0658
0.4511
6.8
2
8.8
EST
0.5720
0.1407
0.7127
6.1
2
8.1
HUN
0.3850
0.0887
0.4738
8.7
2
10.7
LAT
0.2971
0.0742
0.3713
2.6
4
6.6
LIT
0.349
0.090
0.4392
2.6
4
6.6
POL
0.2232
0.0513
0.2745
7.0
2
9
ROM
0.1336
0.0237
0.1574
-0.8
4
3.2
SVK
0.3982
0.0572
0.4553
2.8
4
6.8
SVN
0.6336
0.0533
0.6869
8.5
2
10.5
Scenario Analysis
CZ
EST
HU
POL
SVN
Optimistic
0.89
3.92
2.56
2.91
1.56
Intermediate
0.44
3.07
1.81
1.55
1.51
Pessimistic
-0.20
1.86
0.75
-0.37
1.43
BLG
HRV
LAT
LIT
ROM
SVK
Optimistic
3.04
2.65
3.31
3.65
1.40
2.32
Intermediate
1.25
1.36
1.85
2.22
-0.16
1.33
Pessimistic
-1.26
-0.46
-0.21
0.21
-2.36
-0.08
Convergence of
“Cohesion”Countries to EU
INI v s. AVG
0.37
0.36
INI
Average Vs.
Initial levels of
per –capita
income, EU-14,
1975-1998
0.35
0.34
0.33
0.04
0.05
0.06
AVG
0.07
0.08
Convergence of
“Cohesion”Countries to EU
Conditioning variables:
Avg  a    Ini   1  GC   2  DI   3  DUM
a = -0.37
β = -0.281 γ1 = 0.051 γ2 = 0.082 γ3 = -0.021
[0.006]
[0.077]
[0.013]
R - sqr. = 0.809Adj. R - sqr. = 0.777
[0.003]
Scenario Analysis
Scenario 1:
Theoretical assumptions - GC = 10% and DI = 30%
Scenario 2:
Average values of GC and DI for CEECs, 1994 - 1999
Scenario 3:
Average values of GC and DI for Greece, Spain and
Portugal, 1991 - 1999
Scenario 4:
Average values of GC and DI for Ireland, 1991 - 1999
Scenario Analysis
Scenario 1
Scenario 2
(average values over 1994 – 1998
for CEECs)
BUL
HRV
CZ
EST
HUN
LAT
LIT
POL
ROM
SVK
SLV
Scenario 3
(average values over 1991-1998 for GR., POR.,
SP.)
Scenario 4
(average values over 1991 – 1998 for IRL
GC
DI
0.1
0.14
0.27
0.20
0.23
0.11
0.22
0.20
0.16
0.13
0.22
0.20
0.3
0.12
0.20
0.23
0.22
0.21
0.32
0.29
0.22
0.34
0.23
0.26
0.16
0.22
0.14
0.18
Scenario Analysis
CZ
EST
HUN
POL
SVN
Scenario 1
3.60
5.25
4.15
5.16
2.79
Scenario 2
2.52
3.90
3.39
4.13
1.94
Scenario 3
2.63
4.27
3.18
4.18
1.83
Scenario 4
2.31
3.95
2.86
3.86
1.51
BLG
HRV
LAT
LIT
ROM
SVK
Scenario 1
7.04
5.70
6.27
6.12
6.43
4.36
Scenario 2
5.22
3.91
5.83
5.46
6.68
3.16
Scenario 3
6.05
4.71
5.29
5.13
5.44
3.39
Scenario 4
5.72
4.39
4.96
4.80
5.11
3.07
σ - Convergence
•Output gap between the group members decline
over time
•σ - convergence does dot imply β - convergence,
nor conversely
•“catch-up at the top and downward
convergence at the bottom” (Ben- David, 1997)
σ - Convergence
0.4
y = -0.0079x + 0.355
R2 = 0.6246
0.35
0.3
0.25
0.2
0.15
y = 0.0138x + 0.1422
R2 = 0.9001
0.1
1
2
3
4
1998 Group
Linear (1998 Group)
5
6
7
2000 Group
Linear (2000 Group)
8
σ - Convergence
Variance trend for restricted sample, 1992 - 1999
Var(Group1998) = 0.347 - 0.0078 * trend
[0.00]
[0.02]
R – sqr = 0.56
Var(Group 2000) = 0.156 + 0.0138 * trend
[0.00]
[0.00]
R – sqr = 0.88
Ergodic Distribution
•Follows Quah (1997)
•Considers the entire income distribution
• Transition probabilities matrix of moving from one
income group to another. The diagonal probabilities
show the probability of staying in the same income
group, while the off-diagonal probabilities are the
probabilities of moving from one income group to the
subsequent one (up or down).
Ergodic Distribution
•The ergodic distribution is:
lim P m   1
m 
Where P is the transition probabilities matrix.
•The ergodic distribution can be obtained as the
left eigenvector corresponding to the unit
eigenvalue. (Because each row of the matrix sums
to one)
Ergodic Distribution
Number of observations per income
group ( as a % of EU average)
Income
groups
< 0.3
< 0.3
[0.3 ; 0.33)
[0.33 ; 0.47)
> 0.47
Total
22
3
1
0
26
[0.3 ; 0.33 )
2
15
5
0
22
[0.33 ; 0.47)
0
3
21
2
26
> 0.47
0
0
3
22
25
Ergodic Distribution
Income
groups
< 0.3
< 0.3
[0.3 ; 0.33)
[0.33 ; 0.47)
> 0.47
Total
0.846
0.115
0.038
0
1
[0.3 ; 0.33 )
0.091
0.682
0.227
0
1
[0.33 ; 0.47)
0
0.115
0.807
0.077
1
> 0.47
0
0
0.12
0.88
1
Ergodic Distribution
Initial and ergodic distribution
< 0.3
Initial
distribution
Ergodic
distribution
[0.3 ; 0.33) [0.33 ; 0.47)
> 0.47
0.26
0.22
0.26
0.25
0.115
0.19
0.42
0.27
Conclusions
•β - convergence is achieved after controlling for different
steady states
• σ - convergence shows that there is rather divergence
among 2000 Group countries, while 1998 Group
countries do also exhibit σ - convergence
•The ergodic distribution shows that there is convergence
among CEEC 11 countries, namely the 2000 Group will
converge in per capita income to the 1998 Group.