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Panel Index VAR Models: Specification, Estimation, Testing and Leading Indicators

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  • Canova, Fabio
  • Ciccarelli, Matteo

Abstract

This Paper proposes a method to conduct inference in panel VAR models with cross-unit interdependencies and time variations in the coefficients. The set-up used is Bayesian, and Markov chain Monte Carlo (MCMC) methods are used to estimate the posterior distribution of the features of interest. The model is re-parameterized to resemble an observable index model and specification searches are discussed. The approach can be used to construct multi-unit forecasts, leading indicators and to conduct policy analysis in multi-unit set-ups. The methodology is employed to construct leading indicators for inflation and GDP growth in the euro area.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 4033.

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Date of creation: Aug 2003
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Handle: RePEc:cpr:ceprdp:4033
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Keywords: bayesian methods; leading indicators; markov chain monte carlo methods; panel var;

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Find related papers by JEL classification:
  • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
  • E50 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - General

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  1. Otrok, C. & Whiteman, C.H., 1996. "Bayesian Leading Indicators: Measuring and Predicting Economic Conditions in Iowa," Working Papers 96-14, University of Iowa, Department of Economics.
  2. n/a, 2002. "Credibility of the Russian Stabilisation Programme in 1995-98," NIESR Discussion Papers 149, National Institute of Economic and Social Research.
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  7. Gallant, A Ronald & Rossi, Peter E & Tauchen, George, 1993. "Nonlinear Dynamic Structures," Econometrica, Econometric Society, vol. 61(4), pages 871-907, July.
  8. Fabio Canova & Matteo Ciccarelli, 2000. "Forecasting And Turning Point Predictions In A Bayesian Panel Var Model," Working Papers. Serie AD 2000-05, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
  9. Forni, Mario & Reichlin, Lucrezia, 1998. "Let's Get Real: A Factor Analytical Approach to Disaggregated Business Cycle Dynamics," Review of Economic Studies, Wiley Blackwell, vol. 65(3), pages 453-73, July.
  10. Timothy Cogley & Thomas Sargent, . "Drifts and Volatilities: Monetary Policies and Outcomes in the Post WWII US," Working Papers 2133503, Department of Economics, W. P. Carey School of Business, Arizona State University.
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  12. Canova, Fabio & Ciccarelli, Matteo & Ortega, Eva, 2007. "Similarities and convergence in G-7 cycles," Journal of Monetary Economics, Elsevier, vol. 54(3), pages 850-878, April.
  13. Pesaran, H.M., 2003. "Estimation and Inference in Large Heterogeneous Panels with Cross Section Dependence," Cambridge Working Papers in Economics 0305, Faculty of Economics, University of Cambridge.
  14. Michael Binder & Cheng Hsiao & M. Hashem Pesaran, 2000. "Estimation and Inference In Short Panel Vector Autoregressions with Unit Roots And Cointegration," CESifo Working Paper Series 374, CESifo Group Munich.
  15. Pesaran, M.H. & Smith, R., 1992. "Estimating Long-Run Relationships From Dynamic Heterogeneous Panels," Cambridge Working Papers in Economics 9215, Faculty of Economics, University of Cambridge.
  16. 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.
  17. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
  18. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1983. "Forecasting and Conditional Projection Using Realistic Prior Distributions," NBER Working Papers 1202, National Bureau of Economic Research, Inc.
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  20. Hsiao, C. & Pesaran, M. H. & Tahmiscioglu, A. K., 1998. "Bayes Estimation of Short-run Coefficients in Dynamic Panel Data Models," Cambridge Working Papers in Economics 9804, Faculty of Economics, University of Cambridge.
  21. Canova, Fabio, 1993. "Modelling and forecasting exchange rates with a Bayesian time-varying coefficient model," Journal of Economic Dynamics and Control, Elsevier, vol. 17(1-2), pages 233-261.
  22. Jeffrey A. Frankel, 1993. "On Exchange Rates," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061546, June.
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Cited by:

  1. Fabio Canova & Matteo Ciccarelli & Eva Ortega, 2004. "Similarities and convergence in G-7 cycles," Banco de Espa�a Working Papers 0404, Banco de Espa�a.
  2. João Leitão, 2004. "Demand Pull and Supply Push in Portuguese Cable Television," Econometrics 0411009, EconWPA.
  3. Fabio Canova & Luca Gambetti, 2004. "On the Time Variations of US Monetary Policy: Who is right?," Money Macro and Finance (MMF) Research Group Conference 2004 96, Money Macro and Finance Research Group.
  4. Fabio Canova & Carlo Favero, 2005. "Monetary policy in the Euro area: Lessons from 5 years of ECB and implications for Turkey," Economics Working Papers 922, Department of Economics and Business, Universitat Pompeu Fabra.

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