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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. Fabio Canova & Matteo Ciccarelli & Eva Ortega, 2004. "Similarities and convergence in G-7 cycles," Working Papers 0404, Banco de España;Working Papers Homepage.
  3. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-95, November.
  4. 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.
  5. 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.
  6. Mario Forni & Lucrezia Reichlin, 1998. "Let's get real: a factor analytical approach to disaggregated business cycle dynamics," ULB Institutional Repository 2013/10147, ULB -- Universite Libre de Bruxelles.
  7. Canova, Fabio & Ciccarelli, Matteo, 2004. "Forecasting and turning point predictions in a Bayesian panel VAR model," Journal of Econometrics, Elsevier, vol. 120(2), pages 327-359, June.
  8. Binder, M. & Hsaio, C. & Pesaran, M.H., 2000. "Estimation and Inference in Short Panel Vector Autoregressions with Unit Roots and Cointegration," Cambridge Working Papers in Economics 0003, Faculty of Economics, University of Cambridge.
  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.
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  15. Massimiliano Marcellino & James H. Stock & Mark W. Watson, . "Macroeconomic Forecasting in the Euro Area: Country Specific versus Area-Wide Information," Working Papers 201, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  16. 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.
  17. 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.
  18. Jeffrey A. Frankel, 1993. "On Exchange Rates," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061546, December.
  19. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
  20. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
  21. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409 National Bureau of Economic Research, Inc.
  22. Chib, Siddhartha & Greenberg, Edward, 1995. "Hierarchical analysis of SUR models with extensions to correlated serial errors and time-varying parameter models," Journal of Econometrics, Elsevier, vol. 68(2), pages 339-360, August.
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Cited by:

  1. João Leitão, 2004. "Demand Pull And Supply Push In Portuguese Cable Television," Econometrics 0409011, EconWPA.
  2. 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.
  3. 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.
  4. 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.

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