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Does Banque de France control inflation and unemployment?

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  • Kitov, Ivan
  • KItov, Oleg

Abstract

We re-estimate statistical properties and predictive power of a set of Phillips curves, which are expressed as linear and lagged relationships between the rates of inflation, unemployment, and change in labour force. For France, several relationships were estimated eight years ago. The change rate of labour force was used as a driving force of inflation and unemployment within the Phillips curve framework. Following the original problem formulation by Fisher and Phillips, the set of nested models starts with a simplistic version without autoregressive terms and one lagged term of explanatory variable. The lag is determined empirically together with all coefficients. The model is estimated using the Boundary Element Method (BEM) with the least squares method applied to the integral solutions of the differential equations. All models include one structural break might be associated with revisions to definitions and measurement procedures in the 1980s and 1990s as well as with the change in monetary policy in 1994-1995. For the GDP deflator, our original model provided a root mean squared forecast error (RMSFE) of 1.0% per year at a four-year horizon for the period between 1971 and 2004. The same RMSFE is estimated with eight new readings obtained since 2004. The rate of CPI inflation is predicted with RMSFE=1.5% per year. For the naive (no change) forecast, RMSFE at the same time horizon is 2.95% and 3.3% per year, respectively. Our model outperforms the naive one by a factor of 2 to 3. The relationships for inflation were successfully tested for cointegration. We have formally estimated several vector error correction (VEC) models for two measures of inflation. In the VAR representation, these VECMs are similar to the Phillips curves. At a four year horizon, the estimated VECMs provide significant statistical improvements on the results obtained by the BEM: RMSFE=0.8% per year for the GDP deflator and ~1.2% per year for CPI. For a two year horizon, the VECMs improve RMSFEs by a factor of 2, with the smallest RMSFE=0.5% per year for the GDP deflator. This study has validated the reliability and accuracy of the linear and lagged relationships between inflation, unemployment, and the change in labour force between 1970 and 2012.

Suggested Citation

  • Kitov, Ivan & KItov, Oleg, 2013. "Does Banque de France control inflation and unemployment?," MPRA Paper 50239, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:50239
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    References listed on IDEAS

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    1. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    2. Jamie Hall & Jarkko P. Jääskelä, 2011. "Inflation Volatility and Forecast Accuracy," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 44(4), pages 404-417, December.
    3. Chauvin, V. & Devulder, A., 2008. "An Inflation Forecasting Model for the Euro Area," Working papers 192, Banque de France.
    4. A. Espasa & E. Senra & R. Albacete, 2002. "Forecasting inflation in the European Monetary Union: A disaggregated approach by countries and by sectors," The European Journal of Finance, Taylor & Francis Journals, vol. 8(4), pages 402-421.
    5. Hendry, David F. & Hubrich, Kirstin, 2011. "Combining Disaggregate Forecasts or Combining Disaggregate Information to Forecast an Aggregate," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(2), pages 216-227.
    6. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 115(1), pages 147-180.
    7. Ivan Kitov, 2007. "Inflation, Unemployment, Labor Force Change in European Counties," Mechonomics mechonomics7, Socionet.
    8. A. W. Phillips, 1958. "The Relation Between Unemployment and the Rate of Change of Money Wage Rates in the United Kingdom, 1861–1957," Economica, London School of Economics and Political Science, vol. 25(100), pages 283-299, November.
    9. James H. Stock & Mark W. Watson, 2010. "Modeling inflation after the crisis," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 173-220.
    10. Hubrich, Kirstin, 2005. "Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?," International Journal of Forecasting, Elsevier, vol. 21(1), pages 119-136.
    11. David F. Hendry & Katarina Juselius, 2001. "Explaining Cointegration Analysis: Part II," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 75-120.
    12. Andrew Levin & Jeremy Piger, 2003. "Is Inflation Persistence Intrinsic in Industrial Economies?," Computing in Economics and Finance 2003 298, Society for Computational Economics.
    13. Jordi Galí & Tommaso Monacelli, 2005. "Monetary Policy and Exchange Rate Volatility in a Small Open Economy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 707-734.
    14. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    15. repec:pri:cepsud:155sims is not listed on IDEAS
    16. Elena Angelini & Jérôme Henry & Ricardo Mestre, 2001. "Diffusion index-based inflation forecasts for the euro area," BIS Papers chapters, in: Bank for International Settlements (ed.), Empirical studies of structural changes and inflation, volume 3, pages 109-138, Bank for International Settlements.
    17. Kitov, Ivan, 2013. "Inflation, unemployment, and labour force. Phillips curves and long-term projections for Austria," MPRA Paper 49700, University Library of Munich, Germany.
    18. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2003. "Macroeconomic forecasting in the Euro area: Country specific versus area-wide information," European Economic Review, Elsevier, vol. 47(1), pages 1-18, February.
    19. Ivan O. KITOV & Oleg I. KITOV, 2010. "Dynamics Of Unemployment And Inflation In Western Europe: Solution By The 1- D Boundary Elements Method," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 5(2(12)/Sum), pages 94-113.
    20. Gali, Jordi & Gertler, Mark, 1999. "Inflation dynamics: A structural econometric analysis," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 195-222, October.
    21. Bilke, Laurent, 2005. "Break in the mean and persistence of inflation: a sectoral analysis of French CPI," Working Paper Series 463, European Central Bank.
    22. 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.
    23. O. De Bandt & E. Michaux & C. Bruneau & A. Flageollet, 2007. "Forecasting inflation using economic indicators: the case of France," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(1), pages 1-22.
    24. Ivan O. Kitov, 2006. "Inflation, unemployment, labor force change in the USA," Working Papers 28, ECINEQ, Society for the Study of Economic Inequality.
    25. James H. Stock & Mark W. Watson, 2008. "Phillips curve inflation forecasts," Conference Series ; [Proceedings], Federal Reserve Bank of Boston.
    26. Christopher A. Sims, 2007. "Monetary Policy Models," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 38(2), pages 75-90.
    27. Stock, James H. & Watson, Mark W., 2006. "Forecasting with Many Predictors," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 10, pages 515-554, Elsevier.
    28. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    29. Célérier, C., 2009. "Forecasting inflation in France," Working papers 262, Banque de France.
    30. Christopher A. Sims, 2007. "Monetary Policy Models," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 38(2), pages 75-90.
    31. Roma, Moreno & Skudelny, Frauke & Benalal, Nicholai & Diaz del Hoyo, Juan Luis & Landau, Bettina, 2004. "To aggregate or not to aggregate? Euro area inflation forecasting," Working Paper Series 374, European Central Bank.
    32. Jondeau, E. & Le Bihan, H. & Sedillot, F., 1999. "Modelisation et prevision des indices de prix sectoriels," Working papers 68, Banque de France.
    33. Canova, Fabio, 2007. "G-7 Inflation Forecasts: Random Walk, Phillips Curve Or What Else?," Macroeconomic Dynamics, Cambridge University Press, vol. 11(1), pages 1-30, February.
    34. Kitov, Ivan & Kitov, Oleg, 2013. "The dynamics of personal income distribution and inequality in the United States," MPRA Paper 48649, University Library of Munich, Germany.
    35. 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.
    36. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    37. Lucas, Robert Jr., 1972. "Expectations and the neutrality of money," Journal of Economic Theory, Elsevier, vol. 4(2), pages 103-124, April.
    38. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    39. 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.
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    Citations

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    1. The French economy needs ”helicopter money” to boost labor force growth and avoid deflation
      by Ivan Kitov in Economics as Classical Mechanics on 2017-01-14 02:46:00

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    More about this item

    Keywords

    monetary policy; inflation; unemployment; labour force; Phillips curve; measurement error; forecasting; cointegration; France;
    All these keywords.

    JEL classification:

    • 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
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E6 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search

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