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Computing Sunspot Solutions to Rational Expectations Models with Timing Restrictions

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Abstract

Rational expectations (RE) frameworks featuring informational constraints are becoming increasingly popular in macroeconomic research. A recent strand of literature has explored the analytics of RE models with informational subperiods, in which the occurrence of exogenous shocks is period-specific and decision makers thus condition their own choices and expectations upon a sequence of nested information sets (timing restrictions). Assuming the unrestricted (full information) RE model satisfies saddle-path stability, this paper provides (i) necessary and sufficient conditions for existence of an uncountably infinite set of linearly perturbed solutions to its restricted (informationally constrained) counterpart, and (ii) an algorithm for computing the full set of (sunspot) solutions when equilibrium indeterminacy occurs.

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  • Marco M. Sorge, 2018. "Computing Sunspot Solutions to Rational Expectations Models with Timing Restrictions," CSEF Working Papers 514, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    • Handle: RePEc:sef:csefwp:514
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    1. Shibayama, Katsuyuki, 2011. "A Solution Method For Linear Rational Expectation Models Under Imperfect Information," Macroeconomic Dynamics, Cambridge University Press, vol. 15(4), pages 465-494, September.
    2. Klein, Paul, 2000. "Using the generalized Schur form to solve a multivariate linear rational expectations model," Journal of Economic Dynamics and Control, Elsevier, vol. 24(10), pages 1405-1423, September.
    3. Bacchetta, Philippe & Mertens, Elmar & van Wincoop, Eric, 2009. "Predictability in financial markets: What do survey expectations tell us?," Journal of International Money and Finance, Elsevier, vol. 28(3), pages 406-426, April.
    4. Thomas Lubik & Christian Matthes & Elmar Mertens, . "Indeterminacy and Imperfect Information," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics.
    5. Christiano, Lawrence J, 2002. "Solving Dynamic Equilibrium Models by a Method of Undetermined Coefficients," Computational Economics, Springer;Society for Computational Economics, vol. 20(1-2), pages 21-55, October.
    6. Gourinchas, Pierre-Olivier & Tornell, Aaron, 2004. "Exchange rate puzzles and distorted beliefs," Journal of International Economics, Elsevier, vol. 64(2), pages 303-333, December.
    7. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, Oxford University Press, vol. 117(4), pages 1295-1328.
    8. King, Robert G & Watson, Mark W, 2002. "System Reduction and Solution Algorithms for Singular Linear Difference Systems under Rational Expectations," Computational Economics, Springer;Society for Computational Economics, vol. 20(1-2), pages 57-86, October.
    9. Schmitt-Grohe, Stephanie & Uribe, Martin, 2004. "Solving dynamic general equilibrium models using a second-order approximation to the policy function," Journal of Economic Dynamics and Control, Elsevier, vol. 28(4), pages 755-775, January.
    10. Pearlman, Joseph & Currie, David & Levine, Paul, 1986. "Rational expectations models with partial information," Economic Modelling, Elsevier, vol. 3(2), pages 90-105, April.
    11. Frank Hespeler & Marco M. Sorge, 2019. "Solving Rational Expectations Models with Informational Subperiods: A Comment," Computational Economics, Springer;Society for Computational Economics, vol. 53(4), pages 1649-1654, April.
    12. Meyer-Gohde, Alexander, 2010. "Linear rational-expectations models with lagged expectations: A synthetic method," Journal of Economic Dynamics and Control, Elsevier, vol. 34(5), pages 984-1002, May.
    13. Anna Kormilitsina, 2013. "Solving Rational Expectations Models with Informational Subperiods: A Perturbation Approach," Computational Economics, Springer;Society for Computational Economics, vol. 41(4), pages 525-555, April.
    14. Lubik, Thomas A. & Schorfheide, Frank, 2003. "Computing sunspot equilibria in linear rational expectations models," Journal of Economic Dynamics and Control, Elsevier, vol. 28(2), pages 273-285, November.
    15. Laurence Broze & Ariane Szafarz, 1991. "The Econometric Analysis of Non-Uniqueness in Rational Expectations Models," ULB Institutional Repository 2013/649, ULB -- Universite Libre de Bruxelles.
    16. Francesco Carravetta & Marco Sorge, 2010. "A “Nearly Ideal” Solution to Linear Time-Varying Rational Expectations Models," Computational Economics, Springer;Society for Computational Economics, vol. 35(4), pages 331-353, April.
    17. Baxter, Brad & Graham, Liam & Wright, Stephen, 2011. "Invertible and non-invertible information sets in linear rational expectations models," Journal of Economic Dynamics and Control, Elsevier, vol. 35(3), pages 295-311, March.
    18. Sims, Christopher A, 2002. "Solving Linear Rational Expectations Models," Computational Economics, Springer;Society for Computational Economics, vol. 20(1-2), pages 1-20, October.
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    Cited by:

    1. Angelini, Giovanni & Sorge, Marco M., 2021. "Under the same (Chole)sky: DNK models, timing restrictions and recursive identification of monetary policy shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 133(C).

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    Keywords

    Rational expectations; Timing restrictions; Perturbation theory;
    All these keywords.

    JEL classification:

    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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