The Economic Growth of Korea after 1990: Identifying
Contributing Factors from Demand and Supply Sides

Seok-Kyun Hur
Korea Development Institute

Abstract
This study is purposed to identify major factors that explains the growth path of the Korean
economy in the past decades and evaluate their relative contributions. To that end, we present
four economic models: Two of them contrast the recent changes in the determination of foreign
exchange rate as well as the monetary policy rule Korean economy underwent right after the
East Asian Currency Crisis in 1998, while the others are Blanchard and Quah (1989)’s original 2variable model and its 3-variable extension. Converted properly into the corresponding SVAR
systems with long-run restrictions, their estimation results confirm that the decreased rate of
economic growth of Korea since 2000 seems attributable to the decrease in Korea’s potential
growth rate.

JEL classifications: E32, E60
Key Words: Structural Vector Auto Regression (SVAR), long-run restrictions, fixed VS. flexible
exchange rate system, monetary aggregate targeting Vs. inflation targeting

1


I. Introduction
Our study stems from a question, "How should we understand the
growth pattern of the Korean economy after the 1990s?" Among various
quantitative methods applicable, this study chooses a Structural Vector
Auto Regression (SVAR) with long-run restrictions, identifies diverse
impacts from either demand or supply sides that gave rise to the current
status of the Korean economy, and differentiates relative contributions of
those impacts.



sources and derive long-run identification restrictions following
Blanchard and Quah (1989). Then, we levy the identifying restrictions to
VAR systems consisting of the key variables and estimate them with the
Korean data. We demonstrate estimation results in terms of Impulse
Responses (IR) and Forecasting Error Variance Decomposition(FEVD)
and interpret them in terms of economic growth. Eventually, it is our
destination to discern what portion of the economic growth of Korea is
influenced by either the impact of productivity growth through
technological progress, or changes in the aggregate demand induced by
fluctuating consumption and investment, or exogenous shocks like ones
from oil price.
The contents of this paper are construed as follows: The second section
observes the recent trend of the economic growth of Korea and reviews a
few relevant domestic literatures, which might help in clearly defining
the scope and analytic methodology of this study. The third section
provides a quantitative tool to be used in this study, which is Structural
VAR (SVAR) as mentioned above. Accordingly, variables used,
estimation equations, and identification conditions of impacts are also
explained here. The fourth section reports estimation results derived by
the previously introduced models, and the fifth section concludes.

3


II. The Economic Growth of Korea: A Phenomenon and Discussions
In this section, we exhibit the economic growth of Korea in the past
decades and summarize the relevant domestic literature. Despite the
abundant existing literature on the issue, we restrict our attention to the


Volatility

3.4

3.8

4.8

2.1

3.9

The fast growing Korean economy, dating back to 1960s, has been
showing a sign of gradual slowdown up to present. Especially, the
lowered economic growth after the financial crisis in 1997 is worried to
indicate slowdown in the growth of potential GDP, which attributes at
least partly to the fast aging demographic composition. As seen in
<Table 1>, the average real GDP growth has been falling from marvelous
8.1% during 1970s to 5.0% during 2000s.
In the meantime, the volatility of the GDP growth(measured by
standard deviation) rose from 3.4% during 1970s to 4.8% during 1990s
and fell again to 2.1% during 2000s. Reminded that the East Asian
Currency Crisis broke out in the fourth quarter of 1997, it seems that
the severity of business cycle fluctuations stayed more or less at the same
level up to late 1990s and it was subdued in 2000s (see [Figure 1]). Such
dampening business fluctuation seems to be related with the global
prevalence of low interest rate and the emergence of China as a new
world economic power.
Putting all these into consideration, it would be pivotal to identify

1979

1982

1985

1988

ln(real GDP)

1991

1994

1997

2000

2003

2006

ln(real GDP(S.A))

As is widely believed, financial restructuring led to changes of
behaviors in both demand and supply sides of domestic capital market.
Banks moved their concentration from business finance to consumer
loans in order to reduce risk exposure while enhancing profitability.
Accordingly, households could enjoy the benefit of consumption
smoothing from the alleviation of liquidity constraints (Hur and

Korea since 1990s using SVAR. Though, they differ in the time span of
data set used and the pool of variables chosen. Hence, direct comparison
of their results may be not much of consequence. Instead we highlight
their methodological differences.
First, Shim (2001) decomposes post-crisis business cycle by factors
based on B-Q(1989). A linear system of sectoral equations, intended for
deriving long-run restrictions, is arranged so that its Structural Moving
Average Representation (SMAR) or a long-run impulse response matrix
could be formed into a lower or upper triangular one 3. Shim (2001) does
not consider post-crisis changes in the monetary policy rule and the
exchange rate system 4, let alone foreign sectors.
Second, Kim (2005) concentrates on analyzing the impact of foreign
shocks on the domestic business cycle. Hence, Kim uses foreign variables,
such as oil price and exchange rates, jointly with domestic ones
including interest rate, CPI, and the growth rate. Kim (2005)'s model, in
In other words, Shim(2001)'s system of equations is simply reduced to a VAR with Cholesky
ordering.
4 Monetary aggregate targeting and inflation targeting diverge from each other in the treatment
of a money supply schedule. Under the monetary aggregate targeting, LM curve is derived from
money demand=money supply whereas money supply is replaced by an interest rate setting rule,
such as a Taylor rule under the inflation targeting. Furthermore, autonomy of monetary policy
is not guaranteed in a fixed exchange rate system because the domestic interest rate should be
always equal to the foreign interest rate. Otherwise, the exchange rate would fluctuate.
3

6


common with Shim(2001)'s, does not derive the relationship among
shocks from an economic model. Instead he orders them in a Cholesky

presumptions, the estimation results report that world supply shocks have larger impact in
contrast with the shrunken influence of domestic supply shocks after the financial crisis. It is
also revealed that the impact of domestic demand shocks has been magnified in the short-run.

5

7


in this category, based an economic model (however simple it may be),
allows economic intuition to work but it is not satisfying in that a slight
change in the architecture of the model may lead to a different result. In
this context, additional robustness check would be required.
This study encompasses the first approach from the standpoint of the
second one. In details, it derives long-run restrictions of an SVAR
representation from a simple macro economic model. In the meantime a
number of shocks are introduced in the model. Some of them affect a
sector while others have influence on the economy beyond a sector.
Roughly speaking, those shocks are categorized into two groupsdemand and supply shocks, which are, in turn, believed to match with
business cycle and long-run trend of growth respectively. Behind such a
logic lies a general notion that demand shocks are transient whereas
supply ones are permanent. As admitted by B-Q(1989), however,
transient supply shocks or persistent demand ones may exist in reality.
Thus, it would be absurd to associate demand shocks with volatile
business cycle and supply ones with the changing growth trend. In this
context, our paper keeps itself apart from trials to decompose the
economic growth into the long-run trend and the short run fluctuations

1. Sources of Shocks and Transmission Channels
In the following models all the shocks are classified into demand

to define TFP growth to be a sole domestic supply shock. TFP growth
may results from international competition or TFP growth may interact
with the increased demand for investment. In this regard, our way of
introducing shocks has limitations. As a remedy, we present the four
incomplete models and compare their results instead of searching
indefinitely for just one complete model.

2. Equations of Estimation and Identifying Restrictions
In this study, we estimate the following four SVARs with long run
restrictions. The first two of them, based on Blanchard and Quah(1989),
extend the original version of 2-variables and 2-shocks to a variant of 3variables and 3-shocks, which is to reflect the reality that the Korean
economy is exposed to foreign risks more heavily than other economies.
Thus, we add the inflation ( π t ) to the real GDP growth ( ∆y t ) and the

9


unemployment rate ( U t ) and match them with price shock 6 ( ε tπ ), supply
shock( ε ts ), and demand shock( ε td ) respectively.
The latter two, New Keynesian models borrowed from Stock and
Watson(2002), include the real GDP growth( ∆y t ) and inflation ( π t ) in common.
Then, depending on the types of the monetary policy regime and the

foreign exchange rate system, monetary aggregate growth ( ∆mt ) or
exchange rate change ( ∆et ) is added. In this context, we claim that these
models describes better the real image of Korean economy than B-Q(1989)
type ones 7) .

A. A Three Variable Extension of Blanchard and Quah(1989)
Blanchard and Quah (1989) understand a VAR system in an equivalent


Wt = W |E

t −1 [ N t

or

]= N

= W |Et −1[U t ] = 0 , U t ≡ N − N t

Et −1[ Wt ] = Wt , Et −1[ N t ] = N

(5) All the shocks of this economy follow AR(1) processes. Furthermore, demand
π

shock( et ), supply shock( et ), and price shock( e t ) are orthogonal to each
s

d

other.

Mt = Mt −1 + etd , θ 1 , t = θ 1 , t −1 + e st , θ 2 , t = θ 2 , t −1 + eπt

Manipulating (1)~(5) properly, we derive the following matrix, in
which key macro variables 9, such as real GDP growth( ∆Yt ), inflation( π t ),
and unemployment rate ( U t ) 10 are represented as moving averages of
exogenous shocks.
1 − 1  e st   − a

11


By simply ignoring the subscripts t and summing the right hand side of the
SVMAR, we obtain the long run restriction matrix C.
1 − 1  − a
( a + 1)
 −1
0
1  +  a

 − a − 1
1   0

−1

1 
1
0 0


1 − 1 = ( a − 1)
1 0
0
0   − a − 1 1

0 
 NA 0

C =  NA NA 0 

rt = Rt −

1 k
Et [ π t + j ] , qt = pt − ( et + ptf )
∑
k j =1

(2) New Keynesian Phillips curve(Aggregate supply curve)
∞

π t = γ ∑ δ i Et [ y tp+i − y t +i ] + ε td + ε te
i =0

(3) A forward looking Taylor rule
h

rt = βπ Et [ π t +h ] + β y ∑ δ i Et [ y tp+ j − y t + j ]
j =1

(4) An equilibrium condition in foreign exchange market
Rt = Rtf + Et [ et +1 − et ] + ε te

11 Fiscal policy, another pillar of economic policy, is not considered in the model, which is partly
due to the long-time (at least since mid 1980s) held fiscal stance of so called "expenditure-withinrevenue". In addition, some empirical works report that fiscal stimuli through either increasing
expenditure or reducing tax revenue have not been effective in boosting the Korean economy
(Hur[2007]).
12
Pt
ln Pt
f

X t (1 − ρL ) = ε ts ⇒ X t =

∞
ε ts
= ∑ ρ jε ts− j
1 − ρL j =0

Next, the equilibrium condition of the foreign exchange market is
transformed into Equation (6), which defines the exchange rate ( et ) to be
the sum of interest parity ( Rt − j − Rtf− j ) and the cumulative exchange rate
shock ( θ te ).

et = ( Rt −1 − Rtf−1 ) + et −1 + ε te
= ( Rt −1 − Rtf−1 ) + ( Rt −2 − Rtf−2 ) + et −2 + ε te−1 + ε te
∞

= ∑ ( Rt − j − Rtf− j ) + θ te

(6)

j =1
∞

θ te ≡ ∑ ε te− j
j =0

14

Based on the concenpt of "a small open economy", we assume that interest rate( Rt f ), price


i =0

Xt
+ ε td + ε te
1 − δρ

χ ∞ j s
∑ ρ ε t− j + ε td + ε te , (0 ≤ δρ < 1)
1 − δρ j =0

=
=
h

∑ E [y
i =1

t

p
t +i

]

1− ρh
1 − ρ h χρ ∞ j s
Xt =
∑ ρ ε t− j
1− ρ
1 − ρ 1 − δρ j =0

1− ρh 
X t
=  βπ
+ βy ρ
1 − ρ 
 1 − δρ
Third, converting the expression on the real interest rate ( rt ) to that on
the nominal interest rate ( Rt ) and combining the new expression with (6),
we derive the following.

15


Rt = rt +

[ ]

1 s
∑ Et π t+ j = AXt ,
s j =1

χρ h
1 − ρ h 1 χρ 1 − ρ s
A ≡ βπ
+ βy ρ
+
1 − δρ
1 − ρ s 1 − δρ 1 − ρ
∞


∆X t = (1 − ρL )X t − (1 − ρ )X t −1
= B∆X t −

= ε ts − (1 − ρ )X t −1
∞

= ε ts − ∑ ρ j (1 − ρ )ε ts−1− j
j =0

∆et = et − et −1
∞

∞

∞

j =0

j =0

j =0

= ∑ ( A∆X t − j − ∆Rtf− j ) + ∑ ε te− j − ∑ ε te− j −1

16


Properly rearranged, the vector of ( ∆yt , π t , ∆et ) is represented as a
SVMAR(Structural




 ∆et  = A(L ) ε t  = ∑ A j  ε t  , A∞ =  NA NA 0 
 ε d  j =0  ε d 
 NA NA NA 
π 


 t 
 t 
 t 
The above long-run restriction matrix

A∞ indicates the following

properties of the model economy, which is also characterized by
Equation (1)-(5).

First, the productivity shock ( ε ts ) has permanent

impact on the real GDP, price level, and the exchange rate. Second, the
demand shock ( ε td ) has permanent effect on the price level, but they have
transient effect on the real GDP and the exchange rate. Third, the impact
of the exchange rate shock ( ε te ) has permanent effect on the exchange
rate itself and the price level.

C. An Economy under Monetary Aggregate Targeting Rule and Fixed
Exchange Rate System
The next model differs from the previous one in the selection of the
monetary policy regime as well as the foreign exchange rate system. First,


(1) IS curve
y t = κrt − qt + θ tIS , θ tIS = θ tIS−1 + ε tIS ,
rt = Rt −

[ ]

1 k
∑ Et π t+ j , qt = pt − ( et + ptf ) ,
k j =1

π tf ≡ ptf − ptf−1 = S f ,π Xtf
Xtf ≡ y tf ,p − y tf = ρ f Xtf−1
(2) LM curve
mt − pt = yt + bRt
Combining (1) and (2), we derive an aggregate demand schedule as
follows:

κ
yt =

b

(mt − pt ) −

κ
k

(1 +


κ
π t = χ ∑ δ i Et [ y tp+i − y t +i ] + (1 + )ε td

b

i =0

(4) An equilibrium condition in foreign exchange market
Rt = Rt f , et = et , Rt f = S f ,R X t f
(5) Money Supply
mt = yt + bRt f + pt

Equation (1)~(4) consist of the demand shock ( ε td ) and four macro
variables ( yt , Rt , π t , mt ). In order to handle with the mismatch, we define
the GDP gap to be an AR(1) process with a noise of ε ts , which is in turn
defined to be the productivity shock.
X t ≡ y tp − y t = ρX t −1 + ε ts , 0 < ρ < 1
X t (1 − ρL ) = ε ts ⇒ X t =

∞
ε ts
= ∑ ρ jε ts− j
1 − ρL j =0

Now, we represent the four variables of the real GDP ( yt ), inflation
( π t ), nominal interest rate ( Rt ), and the monetary aggregate ( mt ) as
functions of the supply shock and the demand shock ( ε ts , ε td ) in the
following procedure. First, inserting the AR(1) representation of the
potential GDP ( X t ) to the right hand side of (3) , we could describe the
inflation ( π t ) to be a function of exogenous shocks.

b
1 − δρ
=

χ ∞ j s
κ
ρ ε t − j + (1 + )ε td (0 ≤ δρ < 1)
∑
b
1 − δρ j =0

Then, considering the working mechanism of the fixed exchange rate
system, we note that the domestic interest rate ( Rt ) has the following
relationship with the inflation of the foreign economy ( π t f ).

Rt = Rtf = S f ,R X tf , π tf = S f ,π X tf

(7)

Now, we take the first order differences of the real GDP ( yt ) and the
monetary aggregate ( mt ) in consideration of their non-stationarity.

(1 +

κ
κ k
χ
aκ
)∆y t = ( ∆mt − ∆pt ) − ∑
ρ j Xt


χ

k

∑ 1 − ρδ ρ ∆X
k
j =1

j

t

 χ
X t − S f ,π X tf
− 
 1 − ρδ





∆mt = ∆y t + b∆Rtf + π t
∆qt =

χ
κ
χ
κ
X t + (1 + )ε td − π tf =

change) is estimated for the period before the financial crisis.

IV. Estimation Results

1. Data
The data for real GDP, price index (GDP deflator), the exchange rate of
US dollar to Korean won, a monetary aggregate (M2), and the
unemployment rate used in the paper are obtained from the Bank of
Korea. They cover the period between the first quarter of 1970 and the
second quarter of 2007. As a pretest, we examine the existence of unit

21


roots in these variables. Results from DF-GLS procedure (Eliot,
Rothenberg and Stock (1996)) exhibit that all the key variables, such as
the real GDP growth, inflation, the exchange rate change, and the
unemployment rate, do reject the existence of a unit root at 1%
significance level (See <Table 2>).
<Table 2> Unit Root Test Results (DF-GLS)
Test statistic

1% level

5% level

10% level

-2.661


(DF-GLS)

∆y t
(GDP deflator)
(

₩K O

Ut

Next, we run various lag-order selection tests. Each of <Table 3> and
<Table 4> reports the test results for B-Q type or New Keynesian type
models. According to them, most of the lag order selection criteria
prescribe longer lags than the data can accommodate. Thus, we take 4
lags in every SVAR estimation 19.
<Table 3> Lag Order Selection Criteria for B-Q type Models
Variables

LR

FPE

AIC

HQIC

SBIC

( ∆y t , U t )



A rationale for taking 4 lags is that all the data are gathered on a quarterly basis.

22


<Table 4> Lag Order Selection Criteria for New Keynesian Models

Periods
2000.1/4~2007.2/4
1991.1/4~1997.3/4

Variables
( ∆y t , ∆et

, πt )

( ∆y t , π t )

LR

FPE

AIC

HQIC

SBIC

35

To begin with, we demonstrate the IR and FEVD results for the period
between 1970 Q1 and 2007 Q2 from our benchmark of B-Q(1989)’s
original model. We also estimate the same model for the following four
sub-periods-from 1970 Q1 till 1979 Q4(Period I), from 1980 Q1 till 1989
Q4(Period II), from 1990 Q1 till 1999 Q4(Period III), and from 2000 Q1 till
2007 Q2(Period IV). However, we will mention their results only if
necessary. Such division of the time series is intended to treat structural
changes, which arose from 1970 Q1 till 2007 Q2. 21
IR results in [Figure 2] show that supply shock has permanent effect
on both real GDP and unemployment whereas demand shock affects real
GDP temporarily, which is consistent with the corresponding long-run
The magnitude of a shock is one standard deviation and 95% confidence intervals are calculated by
bootstrappings (1,000 trials each).
21 Instead we could take dummies for certain periods (for example, two oil shocks and the east Asian
financial crisis) and measure the level changes in key macro variables induced by them. But it doesn’t
provide a perfect solution because the dummy variables cannot detect possible functional changes among
the key variables.
20

23


restrictions derived in the previous section. In details, positive supply
shock raises real GDP and temporarily (for the first 20 quarters) lowers
unemployment. In contrast, positive demand shock in the form of money
(M2) growth lowers real GDP although temporarily (for the first 20
quarters) 22.

[Figure 2] Impulse Response of the 2-variable B-Q model
(1970.1/4~2007.2/4)


4

6

8

0

10 12 14 16 18 20 22 24

2

4

6

8

10 12 14 16 18 20 22 24

Note: The dotted lines are 95% confidence intervals.

Unemployment rate
Supply Shock

Demand Shock

0.003



-0.005

-0.001

-0.006

-0.002
0

2

4

6

8

10 12 14 16 18 20 22 24

0

2

4

6

8


1.00
0.95
0.90

0.7
0.6
0.5
0.4
0.3

0.85
0.80
0.75
0.70

0.2
0.1
0.0

0.65
0.60
1

3

5
7
9
Supply shock


IRs become smaller and shorter (20 quarters→10 quarters). Furthermore,
FEVD analysis shows that the relative contribution of supply shock to
the movement of real GDP growth is reduced to 60:40 (compare with
80:20 for the whole sample period).
Second, the magnitude of IRs during Period II is close to that during
Period I. However, the persistence of a shock and FEVD results are closer
to those of the whole sample period as in [Figure 2] and [Figure 3].
Third, in comparison with Period I-II, the magnitude of IRs increased
during Period III. Especially, response to supply shock increased
substantially and the persistence of supply shock on the unemployment
rate became longer from 20qaurters to 30 quarters. On the other hand,
the relative contribution of supply shock to the GDP growth rate change
steps back to the level of 1970s(60:40) whereas that of supply shock to
the unemployment fluctuation rises to 70%. We suspect that these
patterns are attributed to the 1997 financial crisis and its aftermath.
25