Vietnam Development Forum, Tokyo

February 28, 2008

The Impact of a Common Currency on East
Asian Production Networks and China’s
Exports Behavior

Mizanur Rahman
Assistant Professor, University of Dhaka, BANGLADESH
Ph.D. Scholar, National Graduate Institute for Policy Studies (GRIPS)
7-22-1 Roppongi, Minato-ku,
Tokyo 106-8677
JAPAN
D0305@grips.ac.jp

THESIS Economic interdependency within East Asia has been growing
stronger in relation to the growth.
 Capital and technology have become increasingly mobile since theearly 1990s, while the condition of labor mobility is largely attainedby vertical fragmentation of production processes across borders inEast Asia.
 The region is an optimum currency area (OCA), but East Asian
countries have national currencies linked by flexible exchange rates.
 This study conjectures that a common currency, not flexible
exchange rates between national currencies, would reduce
flexibility in relative prices within East Asia. Its impact would be far
greater for exports that are produced along the regional production
networks.
 In order to test the hypothesis, this paper estimates the effect of acommon currency on China’s processing and ordinary exports
separately.
 The results validate the hypothesis. The findings show that the
production and exporting of processing exports is 20 percent below
the potential, only because the region does not share a fixedexchange rate system.

Mizanur Rahman, GRIPS, JAPA#

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Vietnam Development Forum, Tokyo

February 28, 2008

Previous literature and limitations
 The empirical gravity model is the workhorse, where the effect of a common
currency is captured by a dummy variable.
 The most common estimate implies that a membership in a currency union
would triple bilateral trade between member countries—(e1.38−1)≈≈3.0 (Roseand Engel, 2002; Frankel and Rose, 2002).
 The most credible estimate is 58 percent trade creating effect of currency
union for the Euroland countries (Rose and van Wincoop, 2001, based on a
fixed effect estimate of the Anderson and van Wincoop gravity model).
 Limitations: a cross-country database with a de facto fixed exchange rates accounting
for a small percent of total observations; a dummy variable representation is non-random in a large dataset; an

ex-post analysis of a fixed exchange rate system; one cannot estimate ex ante effect of a fixed exchange rate system on
trade of a particular country, when the country belongs to an optimum
currency area, but without a currency union.
 the role of regional organization of production is ignored in the literature.

The present study This paper offers both a conceptual framework and its
empirical application in order to obtain ex ante effect of acommon currency arrangement on East Asian production
networks and China’s exports.
 The paper obtains both short-run dynamics and long-run
relations for China’s processing and ordinary exports
separately.
 They are distinguished because the processing exports areproduced along the regional production networks, while theordinary exports are produced mainly by using local inputs.
 The paper also conducts comparative static implications of
intra-regional RER flexibility, which is otherwise the lack of acommon currency, for East Asian production networks.

Mizanur Rahman, GRIPS, JAPA#

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Vietnam Development Forum, Tokyo

February 28, 2008

Production networks and the evolving pattern of
economic interdependency in East Asia
 East Asian production networks underlie fragmentation of
product value chain across borders.
 IBM CEO Sam Palmisano called it, ‘globally integrated
business strategies’ of MNCs. It is the principal reason for thegrowing economic interdependency in East Asia. Figure 1
 Greenspan (2005) remarked, “...production within Asia has
evolved, with final stages of assembly and exporting to theUnited States and elsewhere being increasingly concentrated
in China.” The fragmentation mechanism is generally vertical intraindustry, not horizontal inter-industry.
 Trade along the production networks is called vertical intraindustry trade (VIIT). It mainly flows into China. Figure 2

Figure-1
Regional Growth and Economic Interdependency, 1985-2005
The Intra-regional Trade Share in %

0

30

40

5000

50

10000

60

70

15000

GDP in billion US dollars

1985

1990

1995
Year

NAFTA
EA15
Source: CHEPII CHELEM Database.

2000
EU15

2005

1985

1990

1995
Year

NAFTA

2000

2005

EU15

EA15
Source: CHEPII CHELEM Database.

• Three economic regions—NAFTA, EU-15 and East Asia-15. Over the 1985-2005 period, these regions
grew 3.0x, 4.5x and 4.3x respectively.
• The question is whether the economic interdependency has been growing stronger in relation to its growth.
• Intra-regional trade share: East Asia 37%-50%, EU-15 (about 60%) and NAFTA (about 45%).

Mizanur Rahman, GRIPS, JAPA#

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February 28, 2008

Figure 2: Intra-industry trade intensity between China
and the rest of East Asia

1992

1995

1998
Year

2001

2004

1995

1998
Year

1992

1995

2001

2004

1998
Year

2001

2004

ASEAN-10

Share of intra-industry trade
.1
.15
.2
.25

Share of intra-industry trade
0
.1
.2
.3
.4

Taiwan

1992

South Korea

Share of intra-industry trade.05 .1 .15 .2 .25

Share of intra-industry trade.05 .1 .15 .2 .25

Japan

1992

1995

1998
Year

2001

2004

Source: CHEPII CHELEM Database.

Table-1
China’s imports and exports in 2005 (in %)Partner
Import categories

2005
Total imports
Ordinary imports
Imports forprocessing
OthersPartner
Export categories

2005
Total Exports
Ordinary
Exports
Processed
Exports
Others

World

Japan
(1)

S. Korea&
Taiwan(2)

ASEA#5
(3)

Hong
Kong
(4)

East Asia(5=1+2+3+
4)

UnitedStates

EU-15

Rest of
the
World

100.0
42.4

15.2
5.4

23.0
5.7

10.9
3.1

1.9
0.5

50.9
14.8

7.4
3.9

10.7
6.4

31.1
17.3

41.5

6.9

14.4

5.7

1.2

28.1

1.9

1.8

9.7

16.1

2.9

2.9

2.1

0.1

8.1

1.5

2.4

4.1

World

Japan
(1)

S. Korea& Taiwan
(2)

ASEA
#-5
(3)

East Asia(4=1+2+3)

Hong
Kong

UnitedStates

EU-15

Rest of
the
World

100.0

11.0

6.8

6.3

24.1

16.3

21.4

17.3

20.9

41.3

4.4

3.2

2.9

10.5

3.3

6.9

7.4

13.2

54.7

6.5

3.4

3.2

13.1

12.2

13.9

9.5

6.0

4.0

0.1

0.2

0.2

0.5

0.9

0.6

0.4

1.7

Source: Updated from Rahman and Thorbecke (2007) and China Customs Statistics, 2006.

Mizanur Rahman, GRIPS, JAPA#

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Vietnam Development Forum, Tokyo

February 28, 2008

Table 1 (contd.)
China’s multilateral trade account balance –2005(in billions of U.S. dollars)Partner
Trade categories

World Japan
(1)

2005
Trade Account
102.0
Balance
Ordinary Trade 35.4
Processing
142.5
Trade
Others-75.9

S. Korea &Taiwan (2)ASEA#-5(3)

East Asia(4=1+2+3)

Hong
Kong

UnitedStates

EU-15

Rest of the
World

-16.4

-99.8

-23.8

-140.1

112.3

114.3

61.4

-45.8

-2.5

-12.9

2.0

-13.4

21.6

26.9

14.4

-14.0

4.5

-69.3

-13.3

-78.1

85.1

92.9

60.4

-17.9

-18.5

-17.7

-12.4

-48.6

5.6

-5.6

-13.4

-13.9

Source: As shown in Panel A.
Notes: China’s bilateral trade surplus against Hong Kong is considered as China’s bilateral trade surplus against the U.S. and EU-15.

Figure 3: Schematic view of production networks andreal exchange rate relationships

ASEA#

(x2)

Japan

China-(xC)(x1)

Country i(e.g., the US)#IEs-2(x3)

Mizanur Rahman, GRIPS, JAPA#

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Vietnam Development Forum, Tokyo

February 28, 2008

Modeling of observed exports from China-Standard two-country trade model is described by the following
system of equations:( ) ( gdp )Q = B ( p ) ( gdp )Qcix = A pcix
m
ic

m
ic

b

c

b > 0,

c≠0

(A1)

e

d < 0,

e>0

(A2)

c

d

i

P  PP ⋅ c  = pcix ⋅ RERci
picm = =PPE
ci Pi  i   cxm
Qci = Qic = Qci
m
ic

x
ci

(A3)
(A4)

-Eq.(4) is the equilibrium condition for the export market. Its solution
for real value of observed exports from c to i is shown below:(

1 (b −d ))Q% ci = Qci ⋅ pcix =  A−(1+ d ) B (1+ b ) gdpc− c(1+ d ) gdpie(1+b ) RERcid (1+ b ) 
= G ( gdpc , gdpi ,RERci )(A5)Modeling of observed exports ...
-Eq. (A5) does not recognize that Q% ci is the gross value of exports that are
produced across fragmented production blocks.
-Let vci represents the incremental value-added by the exporting country andΣv ji be the value of imorted intermediate goods from the rest of East Asia,
where j=1,L ,N.
-The study formulates (N+1) structural equations of supply and a coresponding(N+1) structural equations of demand. Each equation is thus for the incremental
value-added.
-At equilibrium, it gives (N+1) reduced-form solutions:v% ji = v ji ⋅ p vji = g j  gdp j , gdpi ,RER ji  ,j = 1,L ,

v%ci = vci ⋅ p = g c [ gdpc , gdpi ,RERci ]
v
ci

(A6)

-An Armington aggregation of the equilibrium conditions (A6) gives thethe reduced − form equation for the gross real value of final exports Q% :
ci

1/ α

Q% ci =  Σ jω jc v%αjc + (1 − Σ jω jc ) v%ciα (

Mizanur Rahman, GRIPS, JAPA#)(= G′ gdp j , gdpc ,gdpi ,RER jc ,RERci) (A7)

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Vietnam Development Forum, Tokyo

February 28, 2008

Conceptual framework ...
-Eq.(7) includes arguments RER jc and RERci , Q RER ji ≡ ( RER jc ⋅ RERci ) .

(RER jc = Σ jω jc ⋅ RERαjc

(

)

1/ α

(

⇒ lim Σ jω jc ⋅ RERαjc

)

α →0

)

1/ α

ln RER jc = Σ jω jc ⋅ ln ( RER jc ) = RERw

ω
ˆ
rule]
= Π j RER jcjc [L′Hopital's(* )-Excluding the set of other controls, a stochastic formulation of Eq.(A7) is:(1)

yi = β1 RERw + β 2 RERci + ui , β1 < 0 , β 2 < 0-A hypothetical case assuming that there exists a fixed exchange rate
system in East Asia is formulated below:
yi = β 2* RERci + vi ,( 2)

β 2* < 0()-When Eq.(2) is applied to real data, the bias is plim βˆ 2* − β 2 = β1b12 > 0.
-It is the well-known omitted variable problem.
-If the region were indeed an OCA, RERw would cease to be relevant, Eq.(2)will be the true specification.

( 2a )

yi = β 2 RERci + vi

Conceptual framework ...
-The long-run effect of a common currency arrangement on China's exports is:φ * = β1 + β1b12 . If b12 → 0, φ * → β1 .
Ha :β1 + β1b12 Pr o.Xp f β1 + β1b12 Ord .Xp-Estimating actual volume of exports relative to the potential volume:(i) Measure of Exchange risk:

dt = RERwt − RER wt(ii) Adjustment term:exp ( dt )

φ*

φ*

φ*

(iii) If either dt → 0 or φ * → 0, exp ( dt ) → 1; Otherwise exp ( dt ) < 1.
(iv) Potential volume of exports:

y*it =ŷit(v) Actual trade relative to the potential trade:

Mizanur Rahman, GRIPS, JAPA#φ*

exp ( dt ),yit* ≥ ˆyit , yit

yit
.
y*it

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Vietnam Development Forum, Tokyo

February 28, 2008

The dynamic panel data model-It is an autoregressive and distributed lag (ADL) formulation:
yit = ∑ k =1α k yit-k + β′(L)x it + γ ′z i + ηi + δ′i d it + u it ,p

( 3)

t = p + 1,L ,T; i = 1,L ,N-Two benchmark specifications:yit = ∑ k =1α k yit-k + β 0GDPit + β1GDPit −1 + β 2GDPit − 2 + ξ 0 RERcit +2

ξ1 RERcit −1 + ξ 2 RERcit −2 + ψ 0 RERwt + ψ 1 RERwt −1 ++ ψ 2 RERwt − 2 + γ′z i + ηi + δ′i d it + u it

(3.1)

yit = ∑ k =1α yit-k + β GDPit + β GDPit −1 + β GDPit − 2 + ξ RERcit +
2

*
k

*
0

*
1

*
2

*
0

ξ1* RERcit −1 + ξ 2* RERcit − 2 + γ *′z i + ηi + δ*i ′dit + vit(3.2)-Key features:
i. ADL terms are selected on the basis of observed minimum of AIC
and/or BIC criteria so that the conditional distribution is stationary.
ii. The model does not require that the system ( yit , x it ) is cointegrated.
iii. The specifications are more general than other restrictive
long-run specifications, e.g., DOLS or FMOLS.

Estimation of dynamic panel models: pooled OLS,
covariance estimators, ...
 Since the model is dynamic including fixed effects, standard
estimation methods, such as pooled OLS and covarianceestimators are inconsistent.
 The pooled OLS estimators are inconsistent because they′itηi)=0.
assume that E(x′′ituit)=0 and E(x′
 Covariance estimators are also inconsistent for reasons thatthe model includes lagged dependent variable and that thestrict exogeneity assumption E(x′′ituit)=0 would fail when thevector xit is not strictly exogenous. For example, the strict
exogeneity assumption fails if either E(x′′ituis)≠0 for s≤t orE(x′′ituis)≠0 for s<t.
 The present study thus uses GMM approach for dynamic
models of panel data.
 The basic assumption is that E(uit)=E(uituis)=0, for all t≠s.

Mizanur Rahman, GRIPS, JAPA#

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Vietnam Development Forum, Tokyo

February 28, 2008

First-diff GMM estimators...
o Following Arellano and Bond (1991), the assumptions that
uit 's are serially uncorrelated and that the vector xit is, say, predeterminedin the sense that E ( x′it uis ) ≠ 0 for s < t or zero otherwise will giverise to a set of moment conditions in the first-differenced equations.
o Written compactly, E( Z i′∆ui ) = 0 for i = 1,L ,  ,where ∆ui = ( ∆ui 3 ,L , ∆uiT )′, and the optimal matrix of instruments
Z i = diag ( yi1 L yis x′i1 L x′is ) for ( s = 1,L ,T − 3) are valid instruments.
o Different exogeneity assumption about the vector xit will lead to avarying set of moment conditions.
o GMM estimators that are based on these moment conditions are called
the first-differenced GMM estimators.

System GMM estimators...
o However, if the autoregressive parameter approaches to unity and/or
the relative variance of the fixed effects ηi increases to infinity, i.e.,(σ σ ) → ∞, the first-differenced GMM estimators can be further biased
2

η

2
u

than the within estimates.
o Based on the stationary properties that E ( yit + pηi ) = E ( yit + qηi ) andE ( xit + pηi ) = E ( xit + qηi ) for all p and q, Blundell and Bond (1999)
showed that one could use an additional set of moment conditions related
to the levels equations.
o Continuing with ADL(2,2) model including weakly exogenous x it ,the moment conditions related to the levels equations can be shown to
be E ( ∆yit −1uit ) = 0 and E ( ∆x it uit ) = 0 for t = 4 ,...,T .
o A system of equations combining both the differenced equations andthe levels equations is then estimated and the resultant estimator iscalled the system GMM estimator.

Mizanur Rahman, GRIPS, JAPA#

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Vietnam Development Forum, Tokyo

February 28, 2008

Results (Table 4)—Dynamic estimates for China’s
processing exports to 33 countries, 1992-2005
Hypothetical
model

Fully specified model
1
2
Pooled OLS Fixed-Effect
0.988***
0.774***(0.073)(0.084)2.466***
2.480***(0.49)(0.48)-3.037*** -2.382***(0.77)(0.74)-0.784*** -0.799***(0.19)(0.19)-1.691*** -1.368***(0.44)(0.27)-0.799**-0.738***(0.32)(0.25)

Independent Variables
Lagged real exportsi(t-1)
GDP of importerit
GDP of importeri(t-1)
Bilateral RMB RERci,tIntra-regional RER flexibilitywt
Intra-regional RER flexibilityw(t-2)
m1
m2
Hansen J Statistic
P-value (d.f.)
No. of Groups
Estimation Period
No. of obs.

33
1992:2005
396

33
1992:2005
396

3
GMM1
0.791***(0.07)
2.674***(0.56)-2.515***(0.72)-0.718***(0.19)-1.088***(0.22)-0.439*(0.22)-2.94***
-0.29
0.009
(10)
33
1992:2005
396

4
GMM2
0.776***(0.07)
2.560***(0.51)-2.091**(0.80)-0.754***(0.18)-1.306***(0.37)-0.715*(0.35)-2.91***
-0.28
0.59
(28)
33
1992:2005
396

Significance tests: *** p<0.01, ** p<0.05, * p<0.1.

5
GMM2
0.663***(0.09)
2.494***(0.57)-1.465**(0.70)-0.584***(0.16)-2.81***
-1.11
0.11
(21)
33
1992:2005
396

Results (Table 5)—Dynamic estimates for China’s
ordinary exports to 33 countries, 1992-2005
Hypothetical model

Fully specified model
Independent Variables

Pooled OLS

Fixed-Effect

GMM1

GMM2

GMM2

Lagged real exportsi(t-1)

0.657***

0.504***

0.572***

0.537***

0.545***(0.10)(0.10)(0.08)(0.11)(0.08)

Lagged real exportsi(t-2)

0.288***

0.198**

0.342***

0.384***

0.301**(0.10)(0.09)(0.09)(0.10)(0.11)GDP of importerit1.795***

1.823***

1.768***

1.564**

1.850***(0.47)(0.49)(0.63)(0.64)(0.60)

Bilateral RMB RERci,t-0.861***-1.001***-0.821***-0.889***-0.749***(0.13)(0.14)(0.16)(0.15)(0.12)

Bilateral RMB RERci,(t-1)

0.526***

0.417***

0.500**

0.480***

0.204(0.15)(0.15)(0.19)(0.17)(0.14)

Bilateral RMB RERci,(t-2)

0.414***

0.233*

0.411***

0.352**

0.559***(0.12)(0.14)(0.11)(0.13)(0.14)

Intra-regional RER flexibilitywt-0.853***-1.028***-0.455**-0.676**(0.32)(0.25)(0.21)(0.33)

Intra-regional RER flexibilityw(t-1)

0.409*

0.348

0.436*

0.398*(0.23)(0.23)(0.22)(0.23)

Intra-regional RER flexibilityw(t-2)-0.904***-1.119***-0.701***-0.937***(0.24)(0.22)

m1
m2
Hansen J Statistic
P-value (d.f.)
No. of Groups
Estimation Period
No. of obs.

Mizanur Rahman, GRIPS, JAPA#(0.16)-1.71*
-0.08
0.009
(10)
33
33
33
1992:2005
1992:2005
1992:2005
396
396
396
Significance tests: *** p<0.01, ** p<0.05, * p<0.1.

(0.22)-1.84**
-0.34
0.289
(28)
33
1992:2005
396-1.68*
0.06
0.087
(21)
33
1992:2005
396

10Vietnam Development Forum, Tokyo

February 28, 2008

Results (Table 6)—Estimates of long-run parameters(based dynamic estimates of the fully specified model)
Specifications and estimations methods(Dynamic model Eq.(3.1) only)
Panel A: China’s processing exports to 33
countries—1992-2005(1) Within estimates(2) GMM system estimates (both the RER vars
are treated strictly exogenous)(3) GMM system estimates (both the RER vars
are treated predetermined)
Panel B: China’s ordinary exports to 33
countries—1992-2005(1) Within estimates(2) GMM system estimates (both the RER vars
are treated strictly exogenous)(3) GMM system estimates (both the RER vars
are treated predetermined)

Income ofimportingcountry (β̂ )Bilateral RMB Intra-regional
real exchange
RER
rate (ξ̂ )flexibility (ψ̂ )2.497***(0.772)
1.011***(0.153)0.975***(0.180)−1.131***(0.374)−0.257(0.321)−0.934**(0.481)−4.503***(0.572)−5.432***(1.002)−8.465**(4.558)0.219(0.727)1.064***(0.103)0.946***(0.269)−1.175***(0.338)1.049**(0.397)−0.715(1.607)−6.022***(0.696)−8.376(5.743)−15.389(31.130)

Notes: *** p<0.01, ** p<0.05, * p<0.1

Results (Table 7)—Trade effect of a fixed exchange rate
system in East Asia (Estimates for China’s processing exports)
Importer Importing
IDs
countryyi(inmillionUSD) [1]yi*(inmillionUSD)

y i* − y i(inmillionUSD) [3]t-ratio[4]( y i / y i* )

101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116

179
2112
241
1520
692
2183
511
749
2812
8065
235
42306
8
793
712
1599

[2]
243
2508
396
1691
769
2651
669
785
3912
9809
321
48473
13
844
667
2290

63.6
396.1
154.2
170.7
76.3
468.3
158.0
36.7
1099.71744.086.8
6167.8
5.1
51.3
-45.2
690.8

2.4
3.7
5.6
2.2
1.1
2.7
4.8
0.7
4.0
3.3
2.8
1.7
1.9
0.9
-0.7
9.0

0.74
0.84
0.61
0.90
0.90
0.82
0.76
0.95
0.72
0.82
0.73
0.87
0.61
0.94
1.07
0.70

Argentina
Australia
Austria
BelgiumBrazilCanadaDenmark
FinlandFranceGermany,FR
GreeceHong Kong
IcelandIndonesia
Ireland
Italy[5]

Continued.....

Mizanur Rahman, GRIPS, JAPA#

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Vietnam Development Forum, Tokyo

February 28, 2008

Results (Table 7)—Trade effect of a fixed exchange rate
system in East Asia (Estimates for China’s processing exports)yiyi*

y i* − y i(in million
USD) [1](in million
USD) [2](in million
USD) [3]Importer
IDs

Importingcountry

117
118
119
120
121
122

Japan
27891 42850 14958.8
Korea Rep
7241
9439
2198.8326
161-164.8Luxembourg
Malaysia
2189
2388
199.6
Mexico972
965-7.6
Netherlands
6175
5487
-687.8
New
219
273
54.3
Zealand
Philippines
918
878
-40.0
Portugal
110
156
46.2
Russia
636
932
296.7
Singapore
4565
5313
748.3
Spain
997
1384
386.4
Sweden
470
722
252.4
Taiwan pro
4075
6533
2457.5Thailand
1397
1472
75.5
United4726
6084
1358.7
Kingdom
United46779 52286 5507.8
StatesOverall
174400 213365 38965

123
124
125
126
127
128
129
130
131
132
133

t-ratio[4]( y i / y i* )
[5]

8.8
7.2
-1.6
1.9
-0.1
-1.0

0.65
0.77
2.02
0.92
1.01
1.13

4.3

0.80

-0.5
5.4
5.0
2.8
6.4
6.6
10.5
1.2

1.05
0.70
0.68
0.86
0.72
0.65
0.62
0.95

6.1

0.78

1.8

0.89

2.35

0.81

Major findings
 In short-run: the impact elasticity of RERw is −1.31 and that of RERci is −0.75 for the panelof processing exports.
 The coefficient of RERci is −0.58 in the hypothetical model. The upward bias
term (β1b12) is −0.20.
 The overall trade effect of RERw on the processing exports is (β1+ β1b12 =−1.51).
 the impact elasticity of RERw is −0.67 and that of RERci is −0.89 for the panelof ordinary exports.
 The overall trade effect of RERw on the ordinary exports is (β1+ β1b12 =−0.75).
 The overall trade effect of RERw on China’s processing exports is just double
the corresponding effect on the ordinary exports.

 In the long-run, we consider only the fully specified model, because the bias
term β1b12 is insignificant.

 For the panel of processing exports, the long-run effect of RERw is −8.5, whilethat of a unilateral RMB appreciation is −0.93.
 By contrast, the long-run effects, based on the consistent GMM estimates, arestatistically insignificant for the ordinary exports.

 The long-run coefficient of RERw implies that production and exporting ofprocessing exports is 20 percent below the potential.
 In other words, a regional fixed exchange rate mechanism will enhance
performance of East Asian production networks by 25 percent.

Mizanur Rahman, GRIPS, JAPA#

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Vietnam Development Forum, Tokyo

February 28, 2008

Further robustness checks alternative definitions of key variables—the results areunchanged.
 augmenting the model by including proxies of supplyside effects—the results provide the lower bound limit
and hence conservative estimates.
 arbitrary changes in the lag-lengths—no change in the
short-run dynamics, some changes in the long-run
estimates.

Concluding remarks
 East Asian integration has been mainly through market
mechanisms, but it has created new demand for regional
institutions.
 A common currency is such an institution.
 It would capitalize the current attainment and provide asolid foundation of the kind Europe has achieved.
 The existing regime is non-optimal and not viable during
a crisis period.
THANK YOU ALL

Mizanur Rahman, GRIPS, JAPA#

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