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Inflation Uncertainty and Output Growth - Evidence from the Asia-Pacific Countries Based on the Multiscale Bayesian Quantile Inference

Author

Listed:
  • Dejan Zivkov

    (Novi Sad business school, University of Novi Sad, Serbia)

  • Marina Gajic-Glamoclija

    (Kragujevac business school for management and economics, Serbia)

  • Jelena Kovacevic

    (LEMIT company, Novi Sad, Serbia)

  • Sanja Loncar

    (Novi Sad business school, University of Novi Sad, Serbia)

Abstract

This paper investigates how inflation uncertainty affects real GDP growth in five Asia-Pacific countries – Australia, New Zealand, Japan, South Korea and Indonesia, whereby these countries adopted inflation targeting (IT) strategy at some point in time. We use several elaborate methodologies – wavelet technique, GARCH with innovative distributions and the Bayesian quantile regression. We determine that inflation uncertainty negatively (positively) affects real GDP growth in periods of economic contraction (prosperity) in all the countries. In addition, the results indicate that this effect is notably stronger in the period after IT than in the period before IT, which particularly applies for Australia, New Zealand, Japan and Korea. As for Indonesia, the impact of inflation uncertainty to real GDP growth is very similar in both subsamples, because expectations about high inflation in Indonesia are well-rooted. The conclusion indicates that if country pursue reliable anti-inflationary policy, output growth can be affected relatively significantly by an excess inflation uncertainty. However, this is not the case in the systems, which are not based on a prudent and well-established anti-inflationary policy, such as Indonesian.

Suggested Citation

  • Dejan Zivkov & Marina Gajic-Glamoclija & Jelena Kovacevic & Sanja Loncar, 2020. "Inflation Uncertainty and Output Growth - Evidence from the Asia-Pacific Countries Based on the Multiscale Bayesian Quantile Inference," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 70(5), pages 461-486, November.
  • Handle: RePEc:fau:fauart:v:70:y:2020:i:5:p:461-486
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    2. Esparcia, Carlos & Fakhfakh, Tarek & Jareño, Francisco, 2024. "The green, the dirty and the stable: Diversifying equity portfolios by adding tokens of different nature," The North American Journal of Economics and Finance, Elsevier, vol. 69(PB).

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    More about this item

    Keywords

    inflation uncertainty; GDP; Bayesian quantile regression; wavelet; Asia-Pacific countries;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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