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Factor Model Forecasting of Inflation in Croatia

  • Davor Kunovac

    (Croatian National Bank, Zagreb)

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    This paper tests whether information derived from 144 economic variables (represented by only a few constructed factors) can be used for the forecasting of consumer prices in Croatia. The results obtained show that the use of one factor enhances the precision of the benchmark model’s ability to forecast inflation. The methodology used is sufficiently general to be able to be applied directly for the forecasting of other economic variables.

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    File URL: http://www.ijf.hr/eng/FTP/2007/4/kunovac.pdf
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    Article provided by Institute of Public Finance in its journal Financial Theory and Practice.

    Volume (Year): 31 (2007)
    Issue (Month): 4 ()
    Pages: 371-393

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    Handle: RePEc:ipf:finteo:v:31:y:2007:i:4:p:371-393
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    1. Jean Boivin & Marc Giannoni, 2006. "DSGE Models in a Data-Rich Environment," NBER Working Papers 12772, National Bureau of Economic Research, Inc.
    2. Mario Forni & Lucrezia Reichlin, 1996. "Dynamic common factors in large cross-sections," ULB Institutional Repository 2013/10149, ULB -- Universite Libre de Bruxelles.
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    4. James H. Stock & Mark W. Watson, 1998. "Diffusion Indexes," NBER Working Papers 6702, National Bureau of Economic Research, Inc.
    5. Schumacher, Christian & Breitung, Jörg, 2006. "Real-time forecasting of GDP based on a large factor model with monthly and quarterly data," Discussion Paper Series 1: Economic Studies 2006,33, Deutsche Bundesbank, Research Centre.
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    7. Angelini, Elena & Henry, Jérôme & Mestre, Ricardo, 2001. "Diffusion index-based inflation forecasts for the euro area," Working Paper Series 0061, European Central Bank.
    8. Ziegler, Christina & Eickmeier, Sandra, 2006. "How good are dynamic factor models at forecasting output and inflation? A meta-analytic approach," Discussion Paper Series 1: Economic Studies 2006,42, Deutsche Bundesbank, Research Centre.
    9. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 1999. "The Generalized Dynamic Factor Model: Identification and Estimation," CEPR Discussion Papers 2338, C.E.P.R. Discussion Papers.
    10. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
    11. Stock, J.H. & Watson, M.W., 1989. "New Indexes Of Coincident And Leading Economic Indicators," Papers 178d, Harvard - J.F. Kennedy School of Government.
    12. Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2008. "Forecasting Macroeconomic Variables Using Diffusion Indexes in Short Samples with Structural Change," Economics Working Papers ECO2008/17, European University Institute.
    13. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    14. Jean Boivin & Serena Ng, 2005. "Understanding and Comparing Factor-Based Forecasts," NBER Working Papers 11285, National Bureau of Economic Research, Inc.
    15. Daniel Grenouilleau, 2006. "The Stacked Leading Indicators Dynamic Factor Model: A Sensitivity Analysis of Forecast Accuracy using Bootstrapping," European Economy - Economic Papers 2008 - 2015 249, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    16. George Kapetanios & Gonzalo Camba-Mendez, 2005. "Forecasting euro area inflation using dynamic factor measures of underlying inflation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(7), pages 491-503.
    17. Ben S. Bernanke & Jean Boivin, 2001. "Monetary Policy in a Data-Rich Environment," NBER Working Papers 8379, National Bureau of Economic Research, Inc.
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