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Estimating overidentified, non-recursive, time varying coefficients structural VARs

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  • Canova, Fabio
  • Pérez Forero, Fernando J.

Abstract

This paper provides a general procedure to estimate structural VARs. The algorithm can be used in constant or time varying coefficient models, and in the latter case, the law of motion of the coefficients can be linear or non-linear. It can deal in a unified way with just-identified (recursive or non-recursive) or overidentified systems where identification restrictions are of linear or of non-linear form. We study the transmission of monetary policy shocks in models with time varying and time invariant parameters.

Suggested Citation

  • Canova, Fabio & Pérez Forero, Fernando J., 2014. "Estimating overidentified, non-recursive, time varying coefficients structural VARs," CEPR Discussion Papers 10022, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:10022
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    1. Uhlig, Harald, 2005. "What are the effects of monetary policy on output? Results from an agnostic identification procedure," Journal of Monetary Economics, Elsevier, vol. 52(2), pages 381-419, March.
    2. Jess Benhabib & Roger E.A. Farmer, 2000. "The Monetary Transmission Mechanism," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 3(3), pages 523-550, July.
    3. Markku Lanne & Helmut Lütkepohl, 2008. "Identifying Monetary Policy Shocks via Changes in Volatility," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(6), pages 1131-1149, September.
    4. Waggoner, Daniel F. & Zha, Tao, 2003. "A Gibbs sampler for structural vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 28(2), pages 349-366, November.
    5. Jonas E. Arias & Juan Rubio-Ramirez & Daniel F. Waggoner, 2013. "Inference Based on SVARs Identied with Sign and Zero Restrictions: Theory and Applications," Working Papers 2013-24, FEDEA.
    6. Fabio Canova & Matteo Ciccarelli, 2009. "Estimating Multicountry Var Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(3), pages 929-959, August.
    7. Canova, Fabio & Ciccarelli, Matteo & Ortega, Eva, 2012. "Do institutional changes affect business cycles? Evidence from Europe," Journal of Economic Dynamics and Control, Elsevier, vol. 36(10), pages 1520-1533.
    8. Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2010. "Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(2), pages 665-696.
    9. Bernanke, Ben S & Blinder, Alan S, 1992. "The Federal Funds Rate and the Channels of Monetary Transmission," American Economic Review, American Economic Association, vol. 82(4), pages 901-921, September.
    10. Canova, Fabio & Ferroni, Filippo, 2012. "The dynamics of US inflation: Can monetary policy explain the changes?," Journal of Econometrics, Elsevier, vol. 167(1), pages 47-60.
    11. Kociecki, Andrzej & Rubaszek, Michał & Ca' Zorzi, Michele, 2012. "Bayesian analysis of recursive SVAR models with overidentifying restrictions," Working Paper Series 1492, European Central Bank.
    12. Daniel F. Waggoner & Tao Zha, 1999. "Conditional Forecasts In Dynamic Multivariate Models," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 639-651, November.
    13. Christopher A. Sims & Tao Zha, 2006. "Were There Regime Switches in U.S. Monetary Policy?," American Economic Review, American Economic Association, vol. 96(1), pages 54-81, March.
    14. Luca Gambetti & Evi Pappa & Fabio Canova, 2008. "The Structural Dynamics of U.S. Output and Inflation: What Explains the Changes?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(2‐3), pages 369-388, March.
    15. Canova, Fabio & Gambetti, Luca, 2009. "Structural changes in the US economy: Is there a role for monetary policy?," Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 477-490, February.
    16. Ben S. Bernanke & Ilian Mihov, 1998. "Measuring Monetary Policy," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(3), pages 869-902.
    17. Timothy Cogley & Thomas J. Sargent, 2005. "Drift and Volatilities: Monetary Policies and Outcomes in the Post WWII U.S," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 262-302, April.
    18. Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," Review of Economic Studies, Oxford University Press, vol. 65(3), pages 361-393.
    19. Gordon, David B & Leeper, Eric M, 1994. "The Dynamic Impacts of Monetary Policy: An Exercise in Tentative Identification," Journal of Political Economy, University of Chicago Press, vol. 102(6), pages 1228-1247, December.
    20. Eric M. Leeper & Christopher A. Sims & Tao Zha, 1996. "What Does Monetary Policy Do?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 27(2), pages 1-78.
    21. Geweke, John & Tanizaki, Hisashi, 2001. "Bayesian estimation of state-space models using the Metropolis-Hastings algorithm within Gibbs sampling," Computational Statistics & Data Analysis, Elsevier, vol. 37(2), pages 151-170, August.
    22. Sims, Christopher A & Zha, Tao, 1998. "Bayesian Methods for Dynamic Multivariate Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 949-968, November.
    23. Jean Boivin & Marc P. Giannoni, 2006. "Has Monetary Policy Become More Effective?," The Review of Economics and Statistics, MIT Press, vol. 88(3), pages 445-462, August.
    24. Canova, Fabio & Paustian, Matthias, 2011. "Business cycle measurement with some theory," Journal of Monetary Economics, Elsevier, vol. 58(4), pages 345-361.
    25. Koop, Gary & Potter, Simon M., 2011. "Time varying VARs with inequality restrictions," Journal of Economic Dynamics and Control, Elsevier, vol. 35(7), pages 1126-1138, July.
    26. 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.
    27. Robertson, John C & Tallman, Ellis W, 2001. "Improving Federal-Funds Rate Forecasts in VAR Models Used for Policy Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(3), pages 324-330, July.
    28. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 821-852.
    29. Edward Herbst & Frank Schorfheide, 2014. "Sequential Monte Carlo Sampling For Dsge Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(7), pages 1073-1098, November.
    30. Strongin, Steven, 1995. "The identification of monetary policy disturbances explaining the liquidity puzzle," Journal of Monetary Economics, Elsevier, vol. 35(3), pages 463-497, June.
    31. Lakdawala, Aeimit, 2016. "Changes in Federal Reserve preferences," Journal of Economic Dynamics and Control, Elsevier, vol. 70(C), pages 124-143.
    32. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, December.
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    Cited by:

    1. Pérez, Fernando & Vega, Marco, 2015. "Asymmetric exchange rate pass-through: Evidence from Peru," Working Papers 2015-011, Banco Central de Reserva del Perú.
    2. Koop, Gary & Korobilis, Dimitris, 2013. "Large time-varying parameter VARs," Journal of Econometrics, Elsevier, vol. 177(2), pages 185-198.
    3. Canova, Fabio & Ciccarelli, Matteo, 2013. "Panel vector autoregressive models: a survey," Working Paper Series 1507, European Central Bank.
    4. Jacopo Cimadomo & Antonello D'Agostino, 2016. "Combining Time Variation and Mixed Frequencies: an Analysis of Government Spending Multipliers in Italy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1276-1290, November.
    5. Moon Jung Choi & Geun-Young Kim & Joo Yong Lee, 2015. "An Analysis of Trade Patterns in East Asia and the Effects of the Real Exchange Rate Movements," Working Papers 2015-29, Economic Research Institute, Bank of Korea.
    6. Khalfan, Twahir M. & Wendt, Stefan, 2020. "The impact of ownership concentration on payout across Nordic firms," Journal of Multinational Financial Management, Elsevier, vol. 56(C).
    7. Carrera, César & Pérez-Forero, Fernando & Ramírez-Rondán, Nelson, 2014. "Effects of the U.S. quantitative easing on the Peruvian economy," Working Papers 2014-017, Banco Central de Reserva del Perú.

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    More about this item

    Keywords

    Identification restrictions; Metropolis algorithm; Monetary transmission mechanism.; Time-varying coefficient structural var models;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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