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Convergence-driven inflation and the channels of its absorption

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  • Konopczak, Karolina
  • Welfe, Aleksander

Abstract

Convergence-driven inflation is an important issue from the perspective of catching-up economies, especially those within a heterogeneous monetary union. This study contributes to the existing literature by analysing the role of the labour and product markets in mitigating inflationary pressure stemming from the catching-up process. It is demonstrated that disregarding the developments of sectoral wages and mark-ups severely distorts the estimates of the convergence-driven inflation. The empirical results obtained for the Czech Republic, Hungary, Poland and Slovakia provide a basis for assessing the risk of common monetary policy in the euro area being inadequate for their economies.

Suggested Citation

  • Konopczak, Karolina & Welfe, Aleksander, 2017. "Convergence-driven inflation and the channels of its absorption," Journal of Policy Modeling, Elsevier, vol. 39(6), pages 1019-1034.
    • Handle: RePEc:eee:jpolmo:v:39:y:2017:i:6:p:1019-1034
    DOI: 10.1016/j.jpolmod.2017.02.001
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    4. Grabowski, Wojciech & Welfe, Aleksander, 2020. "The Tobit cointegrated vector autoregressive model: An application to the currency market," Economic Modelling, Elsevier, vol. 89(C), pages 88-100.
    5. Liu, Tie-Ying & Lee, Chien-Chiang, 2021. "Global convergence of inflation rates," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).

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    More about this item

    Keywords

    Real convergence; Inflationary processes; Monetary integration; Panel cointegration; Balassa–Samuelson effect;
    All these keywords.

    JEL classification:

    • F45 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Macroeconomic Issues of Monetary Unions
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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