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Modelling inflation in the Euro Area

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  • Eilev S. Jansen

    (Norges Bank and Norwegian University of Science and Technology)

Abstract

The paper presents an incomplete competition model (ICM), where inflation is determined jointly with unit labour cost growth. The ICM is estimated on data for the Euro area and evaluated against existing models, i.e. the implicit inflation equation of the Area Wide model (AWM) - cf. Fagan, Henry and Mestre (2001) - and estimated versions of the (single equation) P* model and a hybrid New Keynesian Phillips curve. The evidence from these comparisons does not invite decisive conclusions. There is, however, some support in favour of the (reduced form) AWM inflation equation. It is the only model that encompasses a general unrestricted model and it forecast encompasses the competitors when tested on 20 quarters of one step ahead forecasts.

Suggested Citation

  • Eilev S. Jansen, 2004. "Modelling inflation in the Euro Area," Working Paper 2004/10, Norges Bank.
    • Handle: RePEc:bno:worpap:2004_10
    Note: This paper is a revised version of ECB Working Paper No. 322 (Jansen (2004)), which is prepared for presentation at the Econometric Society European Meeting in Madrid 20.-24. August 2004. It was written as part of the project "Modelling wages and prices in the Euro area", while the author was a Research Visitor to DG Research, European Central Bank, Frankfurt from February through June 2003. Parts of the paper will be published in The Econometrics of Macroeconomic Modelling, forthcoming in the series Advanced Texts in Econometrics from Oxford University Press (Bårdsen et al. (2004a)). I am grateful to Øyvind Eitrheim for his permission to include unpublished material from Eitrheim and Jansen (2003). While working on this project, I have received valuable data assistance from Elena Angelini and Alistair Dieppe of DG Research as well as from Mika Tujula and Focco Vijselaar of DG Economics at the ECB. An anonymous ECB referee has provided helpful advice and comments from Christopher Bowdler, Gabriel Fagan, David Hendry, Jérôme Henry, Ricardo Mestre, Ragnar Nymoen and seminar participants at the ECB, Norges Bank, Norwegian University of Science and Technology, and University of California San Diego are also gratefully acknowledged. The views expressed in this paper represent exclusively the views of the author and do not necessarily reflect those of the European Central Bank or Norges Bank.
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    Cited by:

    1. D.M. Nachane & Amlendu Kumar Dubey, 2008. "The vanishing role of money in the macroeconomy: An Empirical investigation based on spectral and wavelet analysis," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2008-022, Indira Gandhi Institute of Development Research, Mumbai, India.
    2. Heather Anderson & Mardi Dungey & Denise Osborn & Farshid Vahid, 2007. "Constructing Historical Euro Area Data," Money Macro and Finance (MMF) Research Group Conference 2006 99, Money Macro and Finance Research Group.
    3. Jansen, Eilev S., 2004. "Modelling inflation in the euro area," Working Paper Series 322, European Central Bank.
    4. Paul De Grauwe & Magdalena Polan, 2005. "Is Inflation Always and Everywhere a Monetary Phenomenon?," Scandinavian Journal of Economics, Wiley Blackwell, vol. 107(2), pages 239-259, June.
    5. Bowdler, Christopher & Jansen, Eilev S., 2004. "A markup model of inflation for the euro area," Working Paper Series 306, European Central Bank.
    6. Assenmacher-Wesche, Katrin & Gerlach, Stefan, 2008. "Money growth, output gaps and inflation at low and high frequency: Spectral estimates for Switzerland," Journal of Economic Dynamics and Control, Elsevier, vol. 32(2), pages 411-435, February.
    7. William A. Barnett & Soumya Suvra Bhadury & Taniya Ghosh, 2016. "An SVAR Approach to Evaluation of Monetary Policy in India: Solution to the Exchange Rate Puzzles in an Open Economy," Open Economies Review, Springer, vol. 27(5), pages 871-893, November.
    8. Antonin Rusek, 2008. "Inflation Dynamics in New EU Member States: The Czech Case," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 14(2), pages 191-204, May.
    9. Elsa Cristina Vaz, 2012. "Sectoral leadership in international competitiveness: the Portuguese case," Applied Economics Letters, Taylor & Francis Journals, vol. 19(14), pages 1319-1330, September.
    10. Nachane, D.M. & Dubey, Amlendu Kumar, 2011. "The vanishing role of money in the macro-economy: An empirical investigation for India," Economic Modelling, Elsevier, vol. 28(3), pages 859-869, May.
    11. D. M. Nachane & Amlendu Kumar Dubey, 2008. "The Vanishing Role of Money in the Macroeconomy - An Empirical Investigation Based On Spectral and Wavelet Analysis," Macroeconomics Working Papers 22369, East Asian Bureau of Economic Research.
    12. Ascari, Guido & Rankin, Neil, 2007. "Perpetual youth and endogenous labor supply: A problem and a possible solution," Journal of Macroeconomics, Elsevier, vol. 29(4), pages 708-723, December.
    13. Bardsen, Gunnar & Eitrheim, Oyvind & Jansen, Eilev S. & Nymoen, Ragnar, 2005. "The Econometrics of Macroeconomic Modelling," OUP Catalogue, Oxford University Press, number 9780199246502.
    14. Elsa Cristina Neves Januário Vaz, 2008. "Sectoral Leadership in International Competitiveness," CEFAGE-UE Working Papers 2008_07, University of Evora, CEFAGE-UE (Portugal).
    15. repec:kap:iaecre:v:14:y:2008:i:2:p:191-204 is not listed on IDEAS
    16. Tea Šestanović & Josip Arnerić, 2021. "Neural network structure identification in inflation forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 62-79, January.
    17. Czudaj, Robert, 2011. "P-star in times of crisis - Forecasting inflation for the euro area," Economic Systems, Elsevier, vol. 35(3), pages 390-407, September.

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    More about this item

    Keywords

    inflation; incomplete competition model; Area Wide model; P*-model; New Keynesian Phillips curve; model evaluation; forecast encompassing.;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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