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Modeling the link between US inflation and output: the importance of the uncertainty channel

Author

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  • Conrad, Christian
  • Karanasos, Menelaos

Abstract

This paper employs an augmented version of the UECCC GARCH specification proposed in Conrad and Karanasos (2010) which allows for lagged in-mean effects, level effects as well as asymmetries in the conditional variances. In this unified framework we examine the twelve potential intertemporal relationships between inflation, growth and their respective uncertainties using US data. We find that high inflation is detrimental to output growth both directly and indirectly via the nominal uncertainty. Output growth boosts inflation but mainly indirectly through a reduction in real uncertainty. Our findings highlight that macroeconomic performance affects nominal and real uncertainty in many ways and that the bidirectional relation between inflation and growth works to a large extend indirectly via the uncertainty channel.

Suggested Citation

  • Conrad, Christian & Karanasos, Menelaos, 2010. "Modeling the link between US inflation and output: the importance of the uncertainty channel," Working Papers 0507, University of Heidelberg, Department of Economics.
  • Handle: RePEc:awi:wpaper:0507
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    Cited by:

    1. Karanasos, M. & Koutroumpis, P. & Karavias, Y. & Kartsaklas, A. & Arakelian, V., 2016. "Inflation convergence in the EMU," Journal of Empirical Finance, Elsevier, vol. 39(PB), pages 241-253.
    2. Mihaela SIMIONESCU, 2016. "The Identification Of Inflation Rate Determinants In The Usa Using The Stochastic Search Variable Selection," CES Working Papers, Centre for European Studies, Alexandru Ioan Cuza University, vol. 8(1), pages 171-181, March.

    More about this item

    Keywords

    Bivariate GARCH process; volatility feedback; inflation uncertainty; output variability;

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • 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

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