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Estimation and Solution of Models with Expectations and Structural Changes

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  • Kulish, Mariano
  • Pagan, Adrian

Abstract

Standard solution methods for linearised models with rational expectations take the structural parameters to be constant. These solutions are fundamental for likelihood-based estimation of such models. Regime changes, such as those as- sociated with either changed rules for economic policy, institutional changes, or changes in the technology of production, can generate large changes in the statis- tical properties of observable variables. In practice, structural change is accounted for during estimation by selecting a sub-sample for which a time-invariant struc- ture seems valid. In this paper we develop solutions for linearised models with structural changes under a variety of assumptions regarding agents’ beliefs about those structural changes. We put the solutions in state space form and use the Kalman filter to construct the likelihood function. We apply the techniques to three examples: an inflationary program, a disinflation program and a transitory slowdown in trend growth.

Suggested Citation

  • Kulish, Mariano & Pagan, Adrian, 2014. "Estimation and Solution of Models with Expectations and Structural Changes," Dynare Working Papers 34, CEPREMAP.
  • Handle: RePEc:cpm:dynare:034
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Fabio Canova & Filippo Ferroni & Christian Matthes, 2015. "Approximating Time Varying Structural Models With Time Invariant Structures," Working Paper 15-10, Federal Reserve Bank of Richmond, revised 23 Oct 2015.
    2. Jesper Lindé & Mathias Trabandt, 2018. "Should we use linearized models to calculate fiscal multipliers?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 937-965, November.
    3. Pablo Cuba‐Borda & Luca Guerrieri & Matteo Iacoviello & Molin Zhong, 2019. "Likelihood evaluation of models with occasionally binding constraints," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1073-1085, November.
    4. M. Hashem Pesaran & Ron P Smith, 2014. "Tests of Policy Ineffectiveness in Macroeconometrics," Birkbeck Working Papers in Economics and Finance 1405, Birkbeck, Department of Economics, Mathematics & Statistics.
    5. Mariano Kulish & Adrian Pagan, 2016. "Issues in Estimating New Keynesian Phillips Curves in the Presence of Unknown Structural Change," Econometric Reviews, Taylor & Francis Journals, vol. 35(7), pages 1251-1270, August.
    6. M. Hashem Pesaran & Ron P. Smith, 2018. "Tests of Policy Interventions in DSGE Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(3), pages 457-484, June.
    7. Kapetanios, George & Millard, Stephen & Price, Simon & Petrova, Katerina, 2018. "Time varying cointegration and the UK Great Ratios," Essex Finance Centre Working Papers 23320, University of Essex, Essex Business School.
    8. Castelnuovo, Efrem & Pellegrino, Giovanni, 2018. "Uncertainty-dependent effects of monetary policy shocks: A new-Keynesian interpretation," Journal of Economic Dynamics and Control, Elsevier, vol. 93(C), pages 277-296.
    9. Christoffel, Kai & Mazelis, Falk & Montes-Galdón, Carlos & Müller, Tobias, 2020. "Disciplining expectations and the forward guidance puzzle," Working Paper Series 2424, European Central Bank.
    10. García-Cicco, Javier & García-Schmidt, Mariana, 2020. "Revisiting the exchange rate pass through: A general equilibrium perspective," Journal of International Economics, Elsevier, vol. 127(C).
    11. , 2020. "Two Illustrations of the Quantity Theory of Money Reloaded," Working Papers 774, Federal Reserve Bank of Minneapolis.
    12. Gibbs, Christopher G. & Kulish, Mariano, 2017. "Disinflations in a model of imperfectly anchored expectations," European Economic Review, Elsevier, vol. 100(C), pages 157-174.
    13. Sergei Seleznev, 2016. "Solving DSGE models with stochastic trends," Bank of Russia Working Paper Series wps15, Bank of Russia.
    14. Gomez-Gonzalez, Patricia & Rees, Daniel M., 2018. "Same Spain, less pain?," European Economic Review, Elsevier, vol. 110(C), pages 78-107.
    15. Gibbs, Christopher G. & McClung, Nigel, 2019. "Does my model predict a forward guidance puzzle?," Research Discussion Papers 19/2019, Bank of Finland.

    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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