Output Growth Volatility and Inflation Uncertainty in East Asian Countries. Dilshod N. Murodov

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Output Growth Volatility and Inflation Uncertainty in East Asian Countries Dilshod N. Murodov Lecturer, Department of Finance, Banking and Finance Academy of Uzbekistan Visiting Scholar, Policy Research Institute Ministry of Finance, Japan

Contents Part 1: Part 2: Part 3: Part 4: Part 5: Introduction Literature Review Data and Analysis Econometric Approach Results and Concluding Remarks

Introduction

Overview of the study Almost a decade after the GFC of 2008, the nexus between volatile output growth and inflation uncertainty performance is still a critical subject to policymaking. The increase in output volatility, especially in developing countries, owes to relatively recent reductions in government spending, a fall in inflation and several structural reforms. The outward oriented economy and strong performance in the financial markets tends to cause more external shock spillover and output volatility (Bloom, 2009). The foremost impetus is the cognate economic structure and the rapid industrialization after WWII, which suffer different degrees of setback, especially during recessions (Li and Kwok, 2009).

Mainland China Since 1979, market economic reforms and opening up policy adaptation. In the 1990s, FDI massively oriented towards agriculture and industrial output, from service sectors in coastal areas to the establishment of the modern enterprise system. Prior to the 1990s, the government took advantage of the relative stability of the overall price level to undertake major price reforms. Since the 1990s, the government has liberalized industrial output prices from the state determined methodology. Consequently, two double digit inflationary spells appeared and inflation rates exhibited conspicuous patterns.

Japan Has unique originality of growth in that so far it is the only nation among the G7 not from Western Europe or North America. Growth stages are split into catch up (1945 1960s), bubble economy (1970s 1980s) and long stagnation (1990s<) periods. Common shared purpose was to catch up with North America and Western European nations experience in the government, household and business sectors. The government created a system that was able to mobilize and direct funds to key industries; After achieving common goals, business and households should have changed their behavior from collective to autonomous with greater competition.

Japan cont. Lacking innovative investment opportunities and poor corporate governance, business entities and financial institutions rushed into speculation in financial and real estate markets, creating a bubble. In the 1990s, the adaptation of restrictive monetary policies caused the bubble to burst in stock and property markets. Struggling with the aftermath of the burst, the pile up due to excessive investment and lending and over borrowing resulted in excess capacity and setting non performing loans. It caused long lasting stagnation, persistent deflation, and financial crashes, despite the expansion of government expenditures and the money supply, and it shaped a public domestic debt overhang as well. On solvation, the economy was confronted with a multi pronged fight to cease deflation, introduce a new policy on budget, adopt regular reforms on business by giving tax reforms, resolve non performing loans, and stabilize the financial system.

South Korea Since the 1960s, catching up, maintenance of good institutions, high investment, financial openness and human capital in technology have contributed to strong growth. Until the 1980s, government intervened DDI along the lines of comparative advantage in industrial output. Tax exemptions were provided to labor intensive manufacturing to enhance exports, and high tariffs were imposed to preserve local products. Due to the shocks of AFC in 1998, inflation targeted policy geared towards setting more stability in internal price. Notwithstanding, the persistence of inflation remained relatively high while that of output measures has declined considerably.

Objectives of the study The underlying issue of the current work proposes three main objectives: First, the impact of output growth volatility on performance of inflation growth uncertainty for the respective East Asian economies will be examined. Next, the Granger causality in variance test will be conducted on any shock or volatility spillover effects between the variables to see how the estimated growth series react to each other s on cross variance correlation analysis. Lastly, we carry out generalized impulse response function analysis to inspect the effects of historical innovations on the conditional standard deviations and covariances.

Authors Keynes (1936) Cukierman and Meltzer (1986) Devereux (1989) Grier and Perry (2000) Cukierman and Gerlach (2003) Korap (2009) Türkyılmaz and Özer (2010) Literature Review Results no permanent trade off between output and inflation, except for short periods. more output growth reduces inflation, higher output volatility reduces inflation uncertainty. more real output growth reduces the optimal amount of wage indexation and pushes the policymaker to engineer more inflation surprises to obtain favorable real effects. higher output growth volatility raised the average inflation rate in the US from 1948 1996. positive causal effect of output growth volatility and inflation uncertainty. an increase in output growth volatility leads to more inflation for Turkey (1987:M1-2008:M9). a causal relation between output growth volatility and inflation in agreement with Devereux (1989). Note: In literature, negative relations between inflation uncertainty and output growth volatility is known as the Taylor effect.

Data and Analysis

Data source & description Country China Japan South Korea Source National Bureau of Statistics of China Statistics Bureau of Japan Statistics Korea Timespan 1990:1-2016:12, monthly 1957:1-2016:12, monthly 1970:1-2016:12, monthly Scale Corresponding Period of the Previous Year (index, CPPY=100) (Index, 2015=100) (Index, 2015=100) Adjustment Price index, not seasonally adjusted Price index, not seasonally adjusted Price index, not seasonally adjusted Notes: Index of real industrial production (IIP) and consumer price index (CPI) are proxies of output and inflation growth for the respective economies. The data are retrieved through DataStream online services.

Econometric Approach

Methodology A general multivariate GARCH in mean process: highly functional in financial issues related works owing to volatility on them. conventionally applied to describe and forecast the correlations between the volatilities and co volatilities as well as spillover effects directly (through conditional standard deviations) or indirectly (through covariances) (Bauwens et al., 2006).

Main equation of the study Y t = M + p Γ i i=1 Y t i + Ψ H t + U t ; U t Ω t 1 ~ 0, H t, H t = h y,t h y,π,t h π,y,t h π,t Y t is an exogenous variable that captures y t output growth and π t inflation growth. M is the intercept while Γ i is the coefficient of lagged Y t. Ψ (Psi) is the coefficient of captured heteroscedasticity, H t, and as usual U t represents the residual terms. Also, Ω t 1 is available information set at the time t 1, and zero is the null vector. Y t = y t π t (i) ; M = μ y μ ; Γ i = γ 11 π (i) γ 21 (i) γ 12 ; Y (i) t i = y t i γ π t i 22 Ψ = ψ 11 ψ 12 ψ 21 ψ 22 ; U t = u y,t u π,t ;

Methodology cont. y t π t (i) = μ y μ + γ 11 π + u y,t u π,t ; (i) γ 21 (i) γ 12 (i) γ 22 y t i π t i + ψ 11 ψ 12 ψ 21 ψ 22 h y,t h π,t where the discrete equations can be drawn as follows (i) (i) y t = μ y + γ 11 yt 1 + γ 12 πt 1 + ψ 11 h y,t + ψ 12 h π,t + u y,t (i) (i) π t = μ π + γ 21 yt 1 + γ 22 πt 1 + ψ 21 h y,t + ψ 22 h π,t + u π,t

Methodology cont. Second moment equation to ensure positive definiteness (BEKK variance covariance specification) H t = C C + A u t 1 u t 1 A + B H t 1 B + D ζ t 1 ζ t 1 D C = c 11 0 c 21 c 22 ; A = a 11 a 12 a 21 a 22 ; B = b 11 b 12 b 21 b 22 ; D = d 11 d 12 d 21 d 22 ; ζ t 1 = ζ y,t 1 ζ π,t 1 ; C is an upper triangular matrix to ensure for the positive definiteness of H t ; A, B and D are 2 2 dimensional matrices to capture the lagged conditional standard deviations and covariances; H t 1 as well as the past values of u t 1 u t 1 and ζ t 1 ζ t 1, are joint estimations of contemporaneous volatility of output growth and inflation uncertainty. This parametrization further contains a possible asymmetry, which is captured by the matrix D. As proposed by Grier et al., (2004), a term, ζ t 1 ζ t 1, accounts for the potential asymmetric responses. More specifically, if the output growth volatility and inflation uncertainty are lower than their expected levels, it is generally treated as negative innovations or bad news regarding the changes of the growth. Hence, the variables ζ y,t, and ζ π,t are defined as min {u y,t, 0} and min {u π,t, 0}, which are negative residuals or bad news about the output and inflation growth, respectively. The acronym BEKK was named after the scholars Yoshi Baba, Robert Engle, Dennis Kraft, and Ken Kroner.

Results

Granger causality in variance Based on Hafner and Herwartz (2008), we demonstrate two conditionally heteroscedastic and stationary series y t and π t. π t does not Granger cause y t in variance, designated by π t y t if, Var y t F t 1 = Var y t F t 1 t Z. Here, there is no causality relationship if y t does Granger cause π t in variance, and the conditional variance of π t can be prophesied more precisely by fitting the information set of y t.

Generalized Impulse Response Function To inspect an innovation in output volatility (often measured by one standard deviation), a shock may affect inflation uncertainty through dynamic interactions. Allowing for composition dependence in multivariate models of GIRFs is their main advantage compared to other customary IRFs. The effects of a shock to output volatility is not isolated from having a contemporaneous impact on inflation uncertainty. GIRF K n, ρ t, ω t 1 = E K t+n ρ t, ω t 1 E K t+n ω t 1 where, n = 0,1,2,3, GIRF is conditional on ρ t and ω t 1 and constructs the response by averaging out future shocks given the past and present. A natural reference point for the GIRF is the conditional expectation of K t+n given only the history ω t 1, and in this benchmark response, the current shock is also averaged out.

Concluding Remarks Real output growth volatility has a significant positive effect in China, whereas in Japan and South Korea it has an adverse impact on inflation uncertainty. Strong evidence of bi directional causal relations in China and uni directional relations in South Korea. No causality relations are detected for Japan. Significant influences in response to the shocks in China and South Korea s inflation uncertainty, while insignificant influence in Japan.

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