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Aggregating Phillips Curves

Author

Listed:
  • FAME,Eric Jondeau, University of Lausanne-HEC
  • Jean Imbs

    (Department of Economics and Econometrics University of Lausanne-HEC, CEPR and FAME)

  • Eric Jondeau

    (University of Lausanne-HEC and FAME)

  • Florian Pelgrin

    (University of Lausanne-HEC and IEMS)

Abstract

Since it burst onto the scene of mainstream monetary economics, the New Neo-Classical Phillips Curve has been the focus of two important empirical debates. First, to what extent properly measured marginal costs affect inflation dynamics. Second, to what extent purely forward looking inflation can be reconciled with the data. In this paper, we show heterogeneity in the pricing behavior of firms, matters for both issues. If pricing is heterogeneous, estimations based on GMM techniques are flawed, to an extent that increases with the correlation between aggregate and disaggregate price dynamics. We use sectoral quarterly French data on prices and marginal costs to illustrate this possibility and quantify the magnitude and direction of the implied bias. Two results arise when the estimation accounts for the possibility of heterogeneity. First, marginal costs become substantially more important in affecting inflation dynamics (i.e. heterogeneity induces a negative bias in the response of aggregate inflation to marginal costs). Second, lagged inflation also becomes more important than previously reported using GMM techniques. We provide analytical expressions for the biases which arise when heterogeneity is not taken into account. It helps pinpoint the sources of the differences in results. These are relevant to our data, where they help explain the biases just described, but they also provide a toolkit with which to gauge the magnitude and direction of an aggregation bias in any disaggregated data.

Suggested Citation

  • FAME,Eric Jondeau, University of Lausanne-HEC & Jean Imbs & Eric Jondeau & Florian Pelgrin, 2006. "Aggregating Phillips Curves," Computing in Economics and Finance 2006 314, Society for Computational Economics.
  • Handle: RePEc:sce:scecfa:314
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    3. Milda Norkute, 2015. "Can the sectoral New Keynesian Phillips curve explain inflation dynamics in the Euro Area?," Empirical Economics, Springer, vol. 49(4), pages 1191-1216, December.
    4. Knell, Markus & Stiglbauer, Alfred, 2009. "The impact of reference norms on inflation persistence when wages are staggered," Working Paper Series 1047, European Central Bank.
    5. Oleg Korenok & Stanislav Radchenko & Norman R. Swanson, 2010. "International evidence on the efficacy of new-Keynesian models of inflation persistence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 31-54.
    6. Kapetanios, George & Price, Simon & Tasiou, Menelaos & Ventouri, Alexia, 2021. "State-level wage Phillips curves," Econometrics and Statistics, Elsevier, vol. 18(C), pages 1-11.
    7. Martina Cecioni, 2010. "Firm entry, competitive pressures and the US inflation dynamics," Temi di discussione (Economic working papers) 773, Bank of Italy, Economic Research and International Relations Area.
    8. Kalim Hyder & Stephen G. Hall, 2020. "Estimates of the New Keynesian Phillips Curve for Pakistan," Empirical Economics, Springer, vol. 59(2), pages 871-886, August.
    9. Fröhling, Annette & Lommatzsch, Kirsten, 2011. "Output sensitivity of inflation in the euro area: Indirect evidence from disaggregated consumer prices," Discussion Paper Series 1: Economic Studies 2011,25, Deutsche Bundesbank.
    10. Borek Vašícek, 2011. "Inflation Dynamics and the New Keynesian Phillips Curve in Four Central European Countries," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 47(5), pages 71-100, September.
    11. Alvarez González, Luis Julián, 2008. "What Do Micro Price Data Tell Us on the Validity of the New Keynesian Phillips Curve?," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 2, pages 1-36.
    12. Dhyne, Emmanuel & Fuss, Catherine & Pesaran, M. Hashem & Sevestre, Patrick, 2011. "Lumpy Price Adjustments: A Microeconometric Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(4), pages 529-540.
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    14. Carlos Carvalho & Niels Arne Dam, 2009. "Estimating the cross-sectional distribution of price stickiness from aggregate data," Staff Reports 419, Federal Reserve Bank of New York.
    15. Cagliarini, Adam & Robinson, Tim & Tran, Allen, 2011. "Reconciling microeconomic and macroeconomic estimates of price stickiness," Journal of Macroeconomics, Elsevier, vol. 33(1), pages 102-120, March.
    16. Felipe Schwartzman & Carlos Carvalho, 2008. "Heterogeneous Price Setting Behavior and Monetary Non-neutrality: Some General Results," 2008 Meeting Papers 1040, Society for Economic Dynamics.
    17. Stefano Eusepi & Bart Hobijn & Andrea Tambalotti, 2011. "CONDI: A Cost-of-Nominal-Distortions Index," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(3), pages 53-91, July.
    18. Petrella, Ivan & Santoro, Emiliano, 2012. "Inflation dynamics and real marginal costs: New evidence from U.S. manufacturing industries," Journal of Economic Dynamics and Control, Elsevier, vol. 36(5), pages 779-794.
    19. Kontonikas, Alexandros, 2010. "A new test of the inflation-real marginal cost relationship: ARDL bounds approach," Economics Letters, Elsevier, vol. 108(2), pages 122-125, August.
    20. Markus Knell & Alfred Stiglbauer, 2012. "Reference Norms, Staggered Wages, And Wage Leadership: Theoretical Implications And Empirical Evidence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(2), pages 569-592, May.
    21. Mumtaz, Haroon & Zabczyk, Pawel & Ellis, Colin, 2009. "What lies beneath: what can disaggregated data tell us about the behaviour of prices?," Bank of England working papers 364, Bank of England.

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    More about this item

    Keywords

    New Keynesian Phillips Curve; Aggregation; GMM; bias;
    All these keywords.

    JEL classification:

    • E2 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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