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 3variable extension. Converted properly into the corresponding SVAR systems with longrun 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.
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 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 Following Blanchard and Quah(1989)'s tradition, we distinguish permanent supply shocks from transient demand ones by levying various identification restrictions In the first half of this paper, we replicate Blanchard and Quah’s original 2-variable model with the Korean macro data Then, we extend the models to a three variable one, which consist of demand, supply and price shocks We demonstrate the estimation results of these two models here because these types of models are quite popular and could be used as benchmarks for other estimations However, these models are not so sophisticated that they may reflect Korea specific features and historical experiences As of year 2007, looking back to 1990s, the East Asian Currency Crisis in 1997 marks a break point for the Korean economy Especially, in the foreign exchange market and in the money market, a flexible exchange rate system and an inflation targeting rule of monetary policy were introduced respectively Needless to say, all the reform measures taken since the financial crisis exerted huge impact on the whole economy Among them, however, the transition from a fixed exchange rate system to a floating one as well as the transition from a monetary aggregate targeting to an inflation targeting regime was very crucial In this context, we introduce the next two linear stochastic differential systems of equations, both of which contrast such drastic institutional changes while adhering to the same backbone in other aspects By solving the models we represent key macro variables as linear functions of exogenous shocks coming possibly from various As Blanchard and Quah(1989) admit, their model is a mere example showing how a SVAR with long run restrictions is estimated 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 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 ones using the methodology of SVAR 1 The Economic Growth of Korea Averages and Standard Deviations of Real GDP Growth Rate (1971.1Q~2007 2Q) (Year-on-Year % Change) Period 1971~1979 1980~1989 1990~1999 2000~2007.2/4 Whole Period Average 8.1 7.4 6.0 5.0 6.7 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 , 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 post crisis changes in various market institutions of Korea and the global environments surrounding them for understanding the growth path of Korean economy (at least) after 1990s To take a few but most remarkable post crisis reform measures taken in Korea, an inflation targeting rule and the floating exchange rate system were introduced, while financial institutions were restructured [Figure 1] Trends of Real GDP Growth Rate (with or without Treatment of Seasonality) (Year-on-Year % Change, Quarter-on-Quarter % Change) 15 10 -5 -10 1970 1973 1976 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 Sung[2003]) In the meantime, most large firms, enforced to lower the debt/equity ratio, began to accommodate required capital by IPOs or internal reserves rather than by debt financing By that much, the banks could hold excess capacity to lend, which in turn directed towards consumer credit In addition, the global phenomenon of low interest rates and mild inflation, which sustained stable growth for the last Some of these changes were caused by the Crisis but others happened to be taken after (or around) the outbreak of the Crisis Here, however, it is not our immediate concern to verify their causalities with the Crisis Instead we focus on evaluating the macroeconomic consequences of these post-crisis changes on the Korean economy decade, contributed to settling the newly adopted inflation targeting rule (in 1997) and the flexible exchange rate system (in 1998) in post-crisis Korea Admitted that those internal and external environmental changes may result in lowering the business cycle amplitude, still it remains a puzzle to explain the slowed pace of economic growth in Korea Hence, it would be crucial to devise analytical frameworks beyond merely introducing major institutional changes so as to include various sources of shocks and their transmission channels, which may hinder the economic growth 2 Literature In this section we introduce three papers, all of which, in common with others, explore the economic growth and/or the business cycle of 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 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 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 common with Shim(2001)'s, does not derive the relationship among shocks from an economic model Instead he orders them in a Cholesky way a priori Third, Oh (2007) considers an open economy version of the B-Q model Matched with three key variables of world import volume, GDP, and CPI, he introduces three shocks of domestic supply, demand, and world supply In terms of shock identification, Oh (2007) also assigns long-run restrictions to disturbances a priori Keeping distance from the predecessors, our paper is based on economic models, which allow the presence of shocks from various sources and introduces institutional changes in the monetary policy regime and the foreign exchange market Then, we derive long-run restrictions by solving the models and use them in estimating corresponding SVAR models III Models In a neoclassical framework, it is somewhat inevitable that an economy experiences slowdown of growth in the long run In reality, however, it is very intricate to distinguish the long-run trend of slowdown from the short-run business downturns There are various statistical methods for decomposing the path of economic growth into the long run trend and the short-run fluctuations With the long series of macro variables available, these statistical methods are relatively easy to implement but it is not rare to see the results hard to interpret under conventional economic reasoning In contrast, there have been many trials of identifying transmission channels of shocks with perception that the change of economic growth is accumulated responses of various sectors to external shocks Analysis Oh (2007) assumes that domestic demand shocks have only temporary effect while domestic supply shocks persist in the long-run He also assumes that world supply shocks increase world production and have permanent effect on world demand for imports whereas domestic supply shocks have only temporary effect on the world demand for imports Under such 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 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 Sources of Shocks and Transmission Channels In the following models all the shocks are classified into demand driven and supply driven ones, which are, in turn, grouped into domestic and foreign ones In addition, we consider the possibility that the changes of economic environments (internal or external) Korean economy has experienced since 1990 may have altered transmission channels while providing new sources of shocks To begin with, noticeable internal changes of the economic environments have been made in restructuring the financial markets and adopting the inflation targeting rule and the floating exchange rate system, most of which seem to contribute to altering transmission channels On the while, the global phenomenon of low interest rates, housing price hike and emergence of China as a world economic power are major external changes surrounding Korean economy Next, understanding demand and supply shocks within a framework of AD-AS, we define internal demand shocks to be idiosyncracies in consumption, investment, government budget, and the markets for domestic and foreign currencies, and represent external demand shocks to be rooted in the terms of trade and the world economic growth On the other hand, we comprehend that supply shocks are caused internally by changes in factor and total factor productivities and externally by price fluctuations of raw materials (such as oil and iron ore) and technology spill-over A notable point here is that such a way of sorting shocks (and discerning changes in transmission channels from those in the magnitudes of shocks) is rather conceptual and does not provide a reliable yardstick to apply in the reality For example, alleviation of household credit constraints induced by the restructuring of the financial sector accompanies consumption growth Also, it is not fully convincing 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 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 unemployment rate ( U t ) and match them with price shock ( 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 MAR(Moving Average Representation) and levy additional long-run restrictions on disturbances and their lags B-Q present a simple model based on Fisher (1979) and provides its solution in the form of long-run restrictions on demand and supply shocks Instead of repeating the already famous B-Q setup, we explain how it is extended to a model with three variables and three shocks As for shocks, we decompose the supply shock into the two parts- the price shock ( eπt ) and the productivity shock ( ets ) and add them to the existing demand shock ( etd ) Especially, eπt has direct influence on price determination, while indirectly working against aggregate demand and employment (1) Aggregate Demand (a combinations of IS and LM urves) Price shocks represent situations like sudden hikes of oil price and foreign exchange rate By construction, they denote all the shocks from foreign economies B-Q(1989) mention that the model in the paper is an example intended for explaining the use of SVAR with long-run restrictions SVAR with short run restrictions differs from B-Q(10989) in that it constrains only the relationships between contemporaneous disturbances 10 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) Real GDP Supply Shock Demand Shock 0.030 0.005 0.025 0.000 0.020 -0.005 0.015 -0.010 0.010 -0.015 0.005 -0.020 0.000 10 12 14 16 18 20 22 24 10 12 14 16 18 20 22 24 Note: The dotted lines are 95% confidence intervals Unemployment rate Supply Shock Demand Shock 0.003 0.008 0.002 0.007 0.001 0.006 0.005 0.000 0.004 -0.001 0.003 -0.002 0.002 -0.003 0.001 -0.004 0.000 -0.005 -0.001 -0.006 -0.002 10 12 14 16 18 20 22 24 10 12 14 16 18 20 22 24 Note: The dotted lines are 95% confidence intervals An observation that unemployment rate rises significantly in response to positive demand shock is opposite to that of B-Q (1989), which may be attributed to the possibility that in Korea the effect of demand shock is transmitted faster through price and wage channels In contrast, in the next model, which is a three-variable extension of B-Q, such a phenomenon is not sustained statistically 22 24 [Figure 3] Forecast Error Variance Decomposition of the 2-variable B-Q model (1970.1/4~2007.2/4) Changes in Changes in growth rate of real GDP unemployment rate 1.0 0.9 0.8 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 Supply shock 11 13 15 17 19 Demand shock Supply shock 11 13 15 17 19 Demand shock FEVD results in [Figure 3] demonstrates that the relative contribution of supply shock compared with demand one to the fluctuations of real GDP growth is roughly 80:20 Conversely, the relative contribution of demand shock to unemployment rate change is about 85:15 IR and FEVD results for the previously defined four subperiods are summarized as follows First, IR results during Period I, compared with the whole sample period, show that the magnitude and the persistence of 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 Probably, the tightening and restructuring policy stance raised the contribution of demand shock while responses of supply shock were magnified due to the collapse of credit channels after the financial crisis Fourth, compared with the three preceding periods, the magnitude of IRs decreased for both demand and supply shocks during Period IV, which seems related to the reduced volatility since 2000 (refer ) On the other hand the relative contribution of productivity shock to the movement of real GDP growth grew substantially B An Extension of Blanchard and Quah(1989) (3-variable and 3-shocks) Here we extend the original B-Q model to accommodate three variables(real GDP, unemployment rate, and inflation) and three shocks(demand shock( etd ), productivity shock( ets ), and price shock( etπ )) [Figure 4] and [Figure 5] provide IR and FEVD results for the whole sample period (1970 Q1~2007 Q2) According to [Figure 4], productivity, demand and price shocks have biggest impact on real GDP, price level and unemployment respectively In addition, [Figure 5] shows that changes in real GDP growth, inflation, and unemployment rate can be best explained by productivity, demand and price shocks However, these patterns are not sustained for all the sub-periods, which may be attributed to outbreaks of special events or changes of economic environments, such as two times of oil shocks, (so called) the three-low phenomenon 23 and the financial crisis during the corresponding periods First, most IRs in 1970s (Period I) with the exception of price level decreased in terms of not only magnitude but also persistence, which is consistent with the results from the original B-Q model On the other hand, we could guess the impact of oil shocks on the Korean economy from the FEVD results that the relative contributions of price shock to the movements in real GDP growth and unemployment rate are greater than any other sources of shocks Second, compared with Period I, the magnitude of IRs and persistence increased while the relative contribution of price shock to the growth rate change The three-low phenomenon points to the Korean economy in mid 1980s in which three favorable economic conditions, such as low oil price, low interest rate and low value of Korean Won to Japanese Yen, induced the economic boom 23 26 remained greater than any other shocks These patterns could be at least partly explained by the favorable price shocks hitting Korean economy in mid 1980s (so called the three-low phenomenon) Third, compared with Period I and II, the responses of real GDP and unemployment increased Especially, unemployment rate responded more sensitively to productivity shock than in the past, which, we infer, is attributable to the drastic measures of corporate restructuring taken after the financial crisis in 1997 Fourth, the most notable point in the estimation results of Period IV(in 2000s) is that the magnitude of IRs was reduced in comparison with Period II and III Furthermore, the persistence of IRs was shortened (mostly within 20 Quarters) On the other hand the relative contribution of productivity shock to the movement of real GDP growth grew substantially 27 [Figure 4] Impulse Response of the 3-variable B-Q model (1970.1/4~2007.2/4) Real GDP Price Index Unemployment Supply shock 0.003 0.14 0.030 0.002 0.12 0.025 0.001 0.10 0.020 0.000 0.08 0.015 -0.001 0.06 -0.002 0.04 0.010 -0.003 0.02 0.005 -0.004 0.00 0.000 -0.005 -0.02 10 12 14 16 18 20 22 24 10 12 14 16 18 20 22 24 -0.006 10 12 14 16 18 20 22 24 10 12 14 16 18 20 22 24 10 12 14 16 18 20 22 24 Demand shock 0.005 0.14 0.000 0.12 0.006 0.005 0.10 -0.005 0.004 0.08 0.003 0.06 0.002 -0.010 -0.015 -0.020 -0.025 0.04 0.001 0.02 0.000 0.00 10 12 14 16 18 20 22 24 -0.001 10 12 14 16 18 20 22 24 -0.002 Price shock 0.002 0.010 0.007 0.000 0.005 0.006 -0.002 -0.004 0.000 -0.006 -0.005 0.005 0.004 -0.008 0.003 -0.010 -0.010 -0.012 -0.015 0.002 0.001 -0.014 -0.016 -0.020 0.000 -0.018 -0.025 -0.001 10 12 14 16 18 20 22 24 10 12 14 16 18 20 22 24 No te: T he tt ed l in e s a re 95 % co n fid enc e i nt e rval s 28 [Figure 5] Forecast Error Variance Decomposition of the 2-variable B-Q model (1970.1/4~2007.2/4) Real GDP growth 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 Supply shock 11 13 Demand shock 15 17 19 Price shock Inflation 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 Supply shock 11 13 15 Demand shock 17 19 Price shock Unemployment rate 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 Supply shock 11 13 Demand shock 29 15 17 19 Price shock C An Economy under Inflation Targeting Rule and Flexible Exchange Rate System The previous B-Q type models not provide explicit descriptions of the foreign exchange market and the monetary policy regime Reminded that the monetary policy regime switched from the monetary aggregate targeting to inflation targeting and the floating foreign exchange rate system was introduced after or around the 1997 financial crisis, we suggest two new Keynesian models In the following two sections, we report the estimation results from them sequentially [Figure 6] Impulse Responses :2000.1/4~2007.2/4 Real GDP Exchange rate Price Index Supply shock 0.008 0.007 0.006 0.005 0.004 0.003 0.002 0.001 0.000 -0.001 -0.002 -0.003 0.04 0.006 0.03 0.004 0.002 0.02 0.01 0.000 0.00 -0.002 -0.004 -0.01 -0.006 -0.02 -0.008 -0.03 -0.010 -0.04 -0.012 -0.05 10 12 14 16 18 20 22 24 10 12 14 16 18 20 22 24 -0.014 10 12 14 16 18 20 22 10 12 14 16 18 20 22 10 12 14 16 18 20 22 24 Exchange rate shock 0.014 0.006 0.08 0.005 0.07 0.012 0.06 0.010 0.004 0.003 0.002 0.05 0.001 0.04 0.000 0.03 -0.001 0.008 0.006 0.004 0.02 -0.002 0.01 -0.003 -0.004 0.002 0.00 10 12 14 16 18 20 22 24 10 12 14 16 18 20 22 24 0.000 24 Demand shock 0.012 0.025 0.008 0.020 0.006 0.010 0.015 0.004 0.008 0.010 0.002 0.005 0.006 0.000 0.000 -0.005 -0.002 0.004 -0.010 -0.004 0.002 -0.015 -0.006 -0.020 10 12 14 16 18 20 22 24 0.000 10 12 14 No te: T he tt ed l in e s a re 95 % co n fid enc e i nt e rval s 30 16 18 20 22 24 24 To begin with, this section reports the estimation results of the SVAR model under the inflation targeting and the flexible exchange rate system Accordingly, the estimation covers the post-crisis period from the first quarter of 2000 to the second quarter of 2007 [Figure 7] Forecast Error Variance Decomposition :2000.1/4~2007.2/4 Real GDP growth 1.0 0.9 0.8 0.7 0.6 0.5 0.4 Demand shock 0.3 Exchange rate shock 0.2 Supply shock 0.1 0.0 11 13 15 17 19 Change of the logarized exchange rate 1.0 0.9 0.8 0.7 0.6 0.5 Demand shock 0.4 Exchange rate shock 0.3 Supply shock 0.2 0.1 0.0 11 13 15 17 19 13 15 17 19 Inflation 1.0 0.9 Demand shock 0.8 Exchange rate shock 0.7 Supply shock 0.6 0.5 0.4 0.3 0.2 0.1 0.0 11 [Figure 6] and [Figure 7] summarize the estimation results of SVAR consisting of three endogenous variables (the real GDP growth ( ∆yt ), domestic inflation ( π t ), and the change rate of the exchange rate of US 31 dollar to Korean Won ( ∆et )) and three exogenous shocks(productivity, demand and exchange rate shocks ( ε ts , ε td , ε te )) First, the IR graphs in [Figure 6] demonstrate that productivity, demand, and exchange rate shocks have biggest impact on real GDP, price index and exchange rate respectively The impacts of shocks disappear completely after 30 quarters but they become almost negligible approximately after 20 quarters Second, the FEVD analysis confirms that productivity, demand, and exchange rate shocks have the greatest forecasting power for changes in real GDP, inflation and exchange rate respectively Especially, the influence of exchange rate shock on the exchange rate (KOR Won/US dollar) turns out to be more dominant than any other cases, which implies that the exchange rate is influenced more by foreign factors than domestic variables D An Economy under Monetary Aggregate Targeting Rule and Fixed Exchange Rate System This section reports the estimation results of the SVAR model under the monetary aggregate targeting and the fixed exchange rate system Accordingly, the estimation covers the period between 1988 Q1 and 1997 Q3 [Figure 8] and [Figure 9] summarize the estimation results of SVAR 24 consisting of two endogenous variables (the real GDP growth ( ∆yt ) and the inflation( π t )) First, the IR graphs in [Figure 8] demonstrate that the two variables respond sensitively to productivity shock and it takes 30~40 quarters for IRs to phase out completely Second, FEVD analysis shows that productivity and demand shocks have the greater contribution to explaining the changes of real GDP and inflation each 24 Reminded that this model includes monetary aggregate targeting as well as the fixed exchange rate system, the long-run impulse-response matrix ( A∞ ) is over-identified We find the log-likelihood χ (1) test statistic of 2.647, whose p-value is 0.104 Accordingly, we cannot reject a null hypothesis that additional restrictions are valid 32 Combining the estimations results of the two new Keynesian models 25, we note the following two points First, compared with 1990s, the magnitudes of impulse responses become smaller in 2000 Second, FEVD results show that 70% of inflation and 80% of real GDP growth are explained by demand and productivity shocks respectively in 2000s These numbers are in good contrast with the outcome that in 1990s 40% of inflation and 87% of real GDP growth are explained by demand and productivity shocks respectively [Figure 8] Impulse Responses (1988.1/4~1997.3/4) Real GDP Supply Shock Demand Shock 0.002 0.020 0.018 0.000 0.016 0.014 -0.002 0.012 0.010 -0.004 0.008 -0.006 0.006 0.004 -0.008 0.002 -0.010 0.000 10 12 14 16 18 20 22 24 10 12 14 16 18 20 22 24 Price Index Supply Shock Demand Shock 0.030 0.020 0.025 0.018 0.016 0.020 0.014 0.015 0.012 0.010 0.010 0.005 0.008 0.006 0.000 0.004 -0.005 0.002 -0.010 0.000 10 12 14 16 18 20 22 24 10 12 14 16 18 20 22 24 Note: The dotted lines are 95% confidence intervals A SVAR model with the inflation targeting and the floating exchange rate system uses three variables of ( ∆y t , π t , ∆et ) whereas one with the monetary aggregate targeting and the fixed exchange rate 25 system uses two variables-( ∆y t , π t ) Hence, the results from the two are not directly comparable 33 [Figure 9] Forecast Error Variance Decomposition (1988.1/4~1997.3/4) Real GDP growth Inflation 1.00 1.0 0.9 0.8 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 Supply shock 11 13 15 17 19 Demand shock Supply shock 11 13 15 17 19 Demand shock The first point is easily confirmed by two previous B-Q type models Thus, further comments would be redundant In contrast the second point (especially the relative contributions of productivity shock to real GDP growth) conflicts with the results from the B-Q models, which, accordingly, requires additional discussions as follows: To begin with, it is notable that the relative contributions of productivity shock to real GDP growth from the two new Keynesian model representing separate time intervals before and after the financial crisis are not much different from each other (87% and 80%) Second, the SVAR model covering 1990s does not use the exchange rate, which is included in the model covering 2000s Hence, it is very likely that the exchange rate shock in 1990s is perceived to be productivity one 26 Third, a three variable SVAR, which adds money growth ( ∆mt ) to the two-variable-two-shock model covering 1990s, provides an outcome that the relative contribution of productivity shock to real GDP growth is smaller in 1990s than in 2000s by more than 10% Though much milder and less frequently than under a floating exchange rate system, the exchange rate is adjusted from time to time by the government under a fixed exchange rate system 26 34 V Concluding Remarks Defining growth to be accumulated responses of an economy to various shocks internal and external, our paper identifies diverse impacts that gave rise to the current status of the Korean economy, and differentiates relative contributions of those impacts To that end, SVAR in presence of long run restrictions is applied to four economic models, two of which are borrowed from Blanchard and Quah(1989) and the rest of which are modified from a new Keynesian setup as in Stock and Watson (2002) Especially, the last two models 27 are devised to reflect the recent changes in the determination of foreign exchange rate (from a fixed rate regime to a flexible rate one) as well as the monetary policy rule (from aggregate targeting to inflation targeting) 28 When organizing the assumed results in the form of impulse response and forecasting error variance decomposition, two common denominators are found as follows First, changes in the rate of economic growth are mainly attributable to the impact on productivity, and such trend has grown strong since the 2000s, which indicates that Korea’s economic growth since the 2000s has been closely associated with its potential growth rate Second, the magnitude or consistency of impact responses tends to have subsided since the 2000s Given Korea’s high dependence on trade, it is possible that low interest rates, low inflation, steady growth, and the economic emergence of China as a world player have helped secure capital and demand for export and import, which therefore might reduced the impact of on the whole economy Despite the fact that a diverse mixture of model specifications and shock identifications has been tried for analysis, consistently are Unlike B-Q type models, these new Keynesian models assume a small open economy, which is consistent with heavy dependency of Korean economy on international trade 28 These systemic reforms may have caused changes in shock transmission channels 27 35 sustained these two findings 29 Therefore, it can be concluded that the decreased rate of economic growth of Korea since 2000 appears to be on the same track as the decrease in Korea’s potential growth rate Of course these two findings are consistent with the possibilities either that the inflation targeting rule and the flexible exchange rate system absorb shocks more before they reach the whole economy or that the size of shocks themselves has shrunken Especially, compared with supply shocks, it seems that both the impact and the size of demand originated shocks have been diminished In addition, the successful global co-ordination of the low interest rate regime led by FRB 30 (at least until mid 2000s) contributed to diminishing the magnitudes of external shocks to a small open economy like Korea These two patterns are also confirmed regardless of the number of lags included in the estimation of SVAR systems 30 Price competitiveness of Chinese manufacturing sectors could be identified as a prop for the low interest rate regime in early 2000s 29 36 Reference (In Korean) Kwon Sik Kim, 2005, ｢Impacts of Foreign Shocks on Domestic Macroeconomic Fluctuations｣, Policy References, no.05-06, KIEP Jae Woong Shim, 2001, ｢Decomposing Factors of Post-Crisis Business Cycle｣, Research Paper Series, LGERI Hyoung-Seok Oh, 2007, ｢Structural Break in Potential Growth and Business Cycle after korean Currency Crisis｣, Working Paper, V.21 no.1, Bank of Korea (In English) Amisano, G and C Giannini, Topics in Structural VAR Econometrics 2nd ed., Heidelberg, Springer, 1997 Blanchard, O J and D Quah, "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, V.79, 1989, pp.655~673 Blanchard, O J and R Perotti, "An Empirical Characterization of the Dynamic Effects of Changes in Government Spending and Taxes on Output," Quarterly Journal of Economics, V.117, 2002, pp.1329~1368 Christiano, L., M Eichenbaum, and C Evans, 1999, "Monetary Policy Shocks : What have we learned and to What End?", Hand book of Macroeconomics 1A, pp 65~148 Hamilton, J., Time Series Analysis, Princeton, 1994 Hur, S., 2007, Measuring the effectiveness of fiscal policies in Korea, Ch in NBER-EASE series #16 ed by T Ito and A Rose Hur, S and T Sung, 2003, The impact of lifting liquidity constraints on the distributions of consumption, assets and debts, KDI Policy Study 2003-03 King R., C Plosser, J Stock, and M Watson, 1991, "Stochastic Trends and Economic Fluctuations", American Economic Review, V.81, 1991, pp.819~840 Leeper, A., C Sims, and T Zha, 1996, "What does monetary policy do?" Brookings Papers on Economic Activity Lippi, M, and L Reichlin, 1993, "The Dynamic Effects of Aggregate Demand and Supply Disturbances: Comment," American Economic Review, V.83, 1993, pp.644~652 McCallum, B., 1989, Monetary Economics: Theory and Policy, Maxwell McMillan 37 Rothenberg, T and J Stock, "Inference in a Nearly Integrated Autoregressive Model with Non-normal Innovations", Journal of Econometrics, 1997, pp 269286 Stock, J, and M Watson, 2002 "Has the Business Cycle Changed and Why?", NBER Macroeconomics Annual 2002, pp.159-218 38 [...]... that these patterns are attributed to the 1997 financial crisis and its aftermath 25 Probably, the tightening and restructuring policy stance raised the contribution of demand shock while responses of supply shock were magnified due to the collapse of credit channels after the financial crisis Fourth, compared with the three preceding periods, the magnitude of IRs decreased for both demand and supply. .. consistent with the results from the original B-Q model On the other hand, we could guess the impact of oil shocks on the Korean economy from the FEVD results that the relative contributions of price shock to the movements in real GDP growth and unemployment rate are greater than any other sources of shocks Second, compared with Period I, the magnitude of IRs and persistence increased while the relative... 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... 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... 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... sustained these two findings 29 Therefore, it can be concluded that the decreased rate of economic growth of Korea since 2000 appears to be on the same track as the decrease in Korea s potential growth rate Of course these two findings are consistent with the possibilities either that the inflation targeting rule and the flexible exchange rate system absorb shocks more before they reach the whole economy... Responses(IR) and Forecasting Error Variance Decomposition (FEVD) We estimate SVAR models based on the long-run restrictions previously derived In this section we summarize and analyze the estimation results in forms of IR and FEVD IR analysis tracks down the impact of a shock 20 on an endogenous variable along the passage of time On the other hand, FEVD measures the fraction of the error in forecasting the. .. seems related to the reduced volatility since 2000 (refer ) On the other hand the relative contribution of productivity shock to the movement of real GDP growth grew substantially B An Extension of Blanchard and Quah(1989) (3-variable and 3-shocks) Here we extend the original B-Q model to accommodate three variables(real GDP, unemployment rate, and inflation) and three shocks (demand shock( etd... with demand one to the fluctuations of real GDP growth is roughly 80:20 Conversely, the relative contribution of demand shock to unemployment rate change is about 85:15 IR and FEVD results for the previously defined four subperiods are summarized as follows First, IR results during Period I, compared with the whole sample period, show that the magnitude and the persistence of IRs become smaller and. .. 2000s) is that the magnitude of IRs was reduced in comparison with Period II and III Furthermore, the persistence of IRs was shortened (mostly within 20 Quarters) On the other hand the relative contribution of productivity shock to the movement of real GDP growth grew substantially 27 [Figure 4] Impulse Response of the 3-variable B-Q model (1970.1/4~2007.2/4) Real GDP Price Index Unemployment Supply shock ... section concludes 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... consistent with the results from the original B-Q model On the other hand, we could guess the impact of oil shocks on the Korean economy from the FEVD results that the relative contributions of price... Despite the abundant existing literature on the issue, we restrict our attention to the ones using the methodology of SVAR 1 The Economic Growth of Korea Averages and Standard Deviations of