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Together in bad times? The effect of COVID-19 on inflation spillovers in China

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  • Xu, Yingying
  • Lien, Donald

Abstract

This study estimates the cross-category inflation spillovers of consumption markets in China in the time-frequency domain, and evaluates the impact of the COVID-19 pandemic on the connectedness. Using the daily internet Consumer Price Index (iCPI), we measure the dynamic inflation connectedness among eight consumption categories in different frequency bands. We find, in the aftermath of the pandemic, inflation rates in eight consumption categories show significant changes. When China was in the active control period from January 2020 to April 2020, the overall connectedness of all frequency bands increases dramatically, but fluctuates widely in the normal control period since April 2020. Further research finds that the fear indexes for COVID in China and globally increase the overall connectedness in the high frequency band, thus indicating that prices tend to move together in bad times of the pandemic in the short-term. The fear for COVID in China and globally increases spillovers received and transmitted at the high frequency in most categories, with the exception of transportation and communication, where the spillovers are reduced. Nevertheless, in the medium-term and long-term, the impacts of the pandemic on directional spillovers show significant heterogeneity across categories. Compared with the fear for the COVID-19 in China, the fear for the global pandemic generates a stronger impact on inflation spillovers. Overall, pandemic-induced shocks have immediate and persistent impacts on cross-category inflation spillovers.

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  • Xu, Yingying & Lien, Donald, 2024. "Together in bad times? The effect of COVID-19 on inflation spillovers in China," International Review of Economics & Finance, Elsevier, vol. 91(C), pages 316-331.
  • Handle: RePEc:eee:reveco:v:91:y:2024:i:c:p:316-331
    DOI: 10.1016/j.iref.2024.01.015
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    1. Xu, Yingying & Shao, Xuefeng & Tanasescu, Cristina, 2024. "How are artificial intelligence, carbon market, and energy sector connected? A systematic analysis of time-frequency spillovers," Energy Economics, Elsevier, vol. 132(C).

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    More about this item

    Keywords

    Connectedness; COVID-19; Inflation; Spillover; Frequency;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • F30 - International Economics - - International Finance - - - General
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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