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Estimating overidentified, nonrecursive, time‐varying coefficients structural vector autoregressions

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  • Fabio Canova
  • Fernando J. Pérez Forero

Abstract

This paper provides a general procedure to estimate structural vector autoregressions. 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 nonlinear. It can deal in a unified way with just‐identified (recursive or nonrecursive) or overidentified systems where identification restrictions are of linear or of nonlinear form. We study the transmission of monetary policy shocks in models with time‐varying and time‐invariant parameters.

Suggested Citation

  • Fabio Canova & Fernando J. Pérez Forero, 2015. "Estimating overidentified, nonrecursive, time‐varying coefficients structural vector autoregressions," Quantitative Economics, Econometric Society, vol. 6(2), pages 359-384, July.
  • Handle: RePEc:wly:quante:v:6:y:2015:i:2:p:359-384
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    Cited by:

    1. Lütkepohl, Helmut & Woźniak, Tomasz, 2020. "Bayesian inference for structural vector autoregressions identified by Markov-switching heteroskedasticity," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    2. Petrova, Katerina, 2019. "A quasi-Bayesian local likelihood approach to time varying parameter VAR models," Journal of Econometrics, Elsevier, vol. 212(1), pages 286-306.
    3. Ortiz, Marco & Herrera, Gerardo & Perez, Fernando, 2022. "The shine beneath: foreign exchange intervention in resource-rich economies," MPRA Paper 116208, University Library of Munich, Germany.
    4. Liu, Xiaochun, 2021. "On fiscal and monetary policy-induced macroeconomic volatility dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).
    5. Canova, Fabio & Ferroni, Filippo, 2020. "A hitchhiker guide to empirical macro models," CEPR Discussion Papers 15446, C.E.P.R. Discussion Papers.
    6. Amine Ben Amar, 2022. "On the role of Islamic banks in the monetary policy transmission in Saudi Arabia," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(1), pages 55-94, March.
    7. Haroon Mumtaz & Konstantinos Theodoridis, 2016. "Volatility Co-movement and the Great Moderation. An Empirical Analysis," Working Papers 804, Queen Mary University of London, School of Economics and Finance.
    8. Belomestny, Denis & Krymova, Ekaterina & Polbin, Andrey, 2021. "Bayesian TVP-VARX models with time invariant long-run multipliers," Economic Modelling, Elsevier, vol. 101(C).
    9. Aymeric Ortmans, 2020. "Evolving Monetary Policy in the Aftermath of the Great Recession," Documents de recherche 20-01, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
    10. Casalis, André & Krustev, Georgi, 2022. "Cyclical drivers of euro area consumption: What can we learn from durable goods?," Journal of International Money and Finance, Elsevier, vol. 120(C).
    11. Amine Ben Amar, 2019. "The Effectiveness of Monetary Policy Transmission in a Dual Banking System: Further Insights from TVP-VAR Model," Economics Bulletin, AccessEcon, vol. 39(4), pages 2317-2332.
    12. Denis Belomestny & Ekaterina Krymova & Andrey Polbin, 2020. "Estimating TVP-VAR models with time invariant long-run multipliers," Papers 2008.00718, arXiv.org.
    13. Thomas A. Lubik & Christian Matthes, 2015. "Time-Varying Parameter Vector Autoregressions: Specification, Estimation, and an Application," Economic Quarterly, Federal Reserve Bank of Richmond, issue 4Q, pages 323-352.

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