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Cost-based Phillips Curve forecasts of inflation

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  • Mazumder, Sandeep

Abstract

It is a well-established idea that prices are a function of marginal cost, yet estimating a reliable measure of marginal cost is difficult to do. Stock and Watson (1999) use the Phillips Curve to forecast inflation for a variety of existing activity variables that researchers commonly use to proxy for marginal cost. This paper uses a similar type of approach to examine the performance of a new candidate for the activity variable, which is marginal cost measured following the theoretical methodology of Bils (1987), which we find to be simple yet powerful when implemented empirically. We then use the Phillips Curve to conduct pseudo out-of-sample inflation forecasts for the US using: output, unemployment, hours, the labor share, the capacity utilization rate, and the new measure of marginal cost. For almost all cases, forecast errors are lowest in the regressions with the new marginal cost variable, indicating that this new measure is an improvement over previous attempts to proxy for marginal cost.

Suggested Citation

  • Mazumder, Sandeep, 2011. "Cost-based Phillips Curve forecasts of inflation," Journal of Macroeconomics, Elsevier, vol. 33(4), pages 553-567.
  • Handle: RePEc:eee:jmacro:v:33:y:2011:i:4:p:553-567
    DOI: 10.1016/j.jmacro.2011.04.004
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    1. Orphanides, Athanasios & van Norden, Simon, 2005. "The Reliability of Inflation Forecasts Based on Output Gap Estimates in Real Time," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 583-601, June.
    2. James H. Stock & Mark W. Watson, 2008. "Phillips curve inflation forecasts," Conference Series ; [Proceedings], Federal Reserve Bank of Boston.
    3. Gwin, Carl R. & VanHoose, David D., 2008. "Alternative measures of marginal cost and inflation in estimations of new Keynesian inflation dynamics," Journal of Macroeconomics, Elsevier, vol. 30(3), pages 928-940, September.
    4. Mazumder, Sandeep, 2010. "The new Keynesian Phillips curve and the cyclicality of marginal cost," Journal of Macroeconomics, Elsevier, vol. 32(3), pages 747-765, September.
    5. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    6. Jeffrey C. Fuhrer & Giovanni P. Olivei, 2005. "Estimating forward-looking Euler equations with GMM estimators: an optimal-instruments approach," Proceedings, Board of Governors of the Federal Reserve System (U.S.), pages 87-114.
    7. Douglas Staiger & James H. Stock & Mark W. Watson, 1997. "The NAIRU, Unemployment and Monetary Policy," Journal of Economic Perspectives, American Economic Association, vol. 11(1), pages 33-49, Winter.
    8. Ang, Andrew & Bekaert, Geert & Wei, Min, 2007. "Do macro variables, asset markets, or surveys forecast inflation better?," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May.
    9. Faust, Jon & Wright, Jonathan H., 2009. "Comparing Greenbook and Reduced Form Forecasts Using a Large Realtime Dataset," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 468-479.
    10. Sbordone, Argia M., 2002. "Prices and unit labor costs: a new test of price stickiness," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 265-292, March.
    11. Stockton, David J & Glassman, James E, 1987. "An Evaluation of the Forecast Performance of Alternative Models of Inflation," The Review of Economics and Statistics, MIT Press, vol. 69(1), pages 108-117, February.
    12. Gali, Jordi & Gertler, Mark & David Lopez-Salido, J., 2005. "Robustness of the estimates of the hybrid New Keynesian Phillips curve," Journal of Monetary Economics, Elsevier, vol. 52(6), pages 1107-1118, September.
    13. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    14. Jeremy Rudd & Karl Whelan, 2007. "Modeling Inflation Dynamics: A Critical Review of Recent Research," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 155-170, February.
    15. Jonas D. M. Fisher & Chin Te Liu & Ruilin Zhou, 2002. "When can we forecast inflation?," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 26(Q I), pages 32-44.
    16. Ichiro Muto, 2009. "Estimating A New Keynesian Phillips Curve With A Corrected Measure Of Real Marginal Cost: Evidence In Japan," Economic Inquiry, Western Economic Association International, vol. 47(4), pages 667-684, October.
    17. Yash P. Mehra, 2004. "Predicting the recent behavior of inflation using output gap-based Phillips curves," Economic Quarterly, Federal Reserve Bank of Richmond, vol. 90(Sum), pages 65-88.
    18. Rotemberg, Julio J. & Woodford, Michael, 1999. "The cyclical behavior of prices and costs," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 16, pages 1051-1135, Elsevier.
    19. Walter Y. Oi, 1962. "Labor as a Quasi-Fixed Factor," Journal of Political Economy, University of Chicago Press, vol. 70, pages 538-538.
    20. Christopher A. Sims, 2002. "The Role of Models and Probabilities in the Monetary Policy Process," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 33(2), pages 1-62.
    21. Roberts, John M., 1997. "Is inflation sticky?," Journal of Monetary Economics, Elsevier, vol. 39(2), pages 173-196, July.
    22. James H. Stock & Mark W. Watson, 2007. "Erratum to "Why Has U.S. Inflation Become Harder to Forecast?"," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1849-1849, October.
    23. James H. Stock & Mark W.Watson, 2003. "Forecasting Output and Inflation: The Role of Asset Prices," Journal of Economic Literature, American Economic Association, vol. 41(3), pages 788-829, September.
    24. Gali, Jordi & Gertler, Mark, 1999. "Inflation dynamics: A structural econometric analysis," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 195-222, October.
    25. Sbordone, Argia M., 2005. "Do expected future marginal costs drive inflation dynamics?," Journal of Monetary Economics, Elsevier, vol. 52(6), pages 1183-1197, September.
    26. Bils, Mark, 1987. "The Cyclical Behavior of Marginal Cost and Price," American Economic Review, American Economic Association, vol. 77(5), pages 838-855, December.
    27. Kleibergen, Frank & Mavroeidis, Sophocles, 2009. "Weak Instrument Robust Tests in GMM and the New Keynesian Phillips Curve," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(3), pages 293-311.
    28. Kevin J. Lansing, 2002. "Can the Phillips curve help forecast inflation?," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, issue oct4.
    29. Heckman, James J, 1974. "Shadow Prices, Market Wages, and Labor Supply," Econometrica, Econometric Society, vol. 42(4), pages 679-694, July.
    30. Jeffrey C. Fuhrer, 1995. "The Phillips curve is alive and well," New England Economic Review, Federal Reserve Bank of Boston, issue Mar, pages 41-56.
    31. Andrew Atkeson & Lee E. Ohanian, 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 25(Win), pages 2-11.
    32. Robert J. Gordon, 1981. "Inflation, Flexible Exchange Rates, and the Natural Rate of Unemployment," NBER Working Papers 0708, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Murphy, Robert G., 2014. "Explaining inflation in the aftermath of the Great Recession," Journal of Macroeconomics, Elsevier, vol. 40(C), pages 228-244.
    2. Robert G. Murphy, 2019. "Can the Phillips Curve Explain Inflation over the Past Half-Century?," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 25(2), pages 137-149, May.
    3. Robert G. Murphy, 2016. "Why Has Inflation Been So Unresponsive to Economic Activity in Recent Years?," Boston College Working Papers in Economics 920, Boston College Department of Economics.
    4. Conti, Antonio M., 2021. "Resurrecting the Phillips Curve in Low-Inflation Times," Economic Modelling, Elsevier, vol. 96(C), pages 172-195.
    5. Robert Murphy, 2016. "Explaining the Recent Behavior of Inflation in the United States," EcoMod2016 9550, EcoMod.
    6. Antonio M. Conti & Andrea Nobili, 2019. "Wages and prices in the euro area: exploring the nexus," Questioni di Economia e Finanza (Occasional Papers) 518, Bank of Italy, Economic Research and International Relations Area.

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    More about this item

    Keywords

    Inflation forecasting; Phillips Curve; Marginal cost;
    All these keywords.

    JEL classification:

    • 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
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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