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Analytic policy function iteration

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  • Han, Zhao
  • Tan, Fei
  • Wu, Jieran

Abstract

We propose an approach to solving and analyzing linear rational expectations models with general information frictions. Our approach is built upon policy function iterations in the frequency domain. We develop the theoretical framework of this approach using rational approximation, analytic continuation, and discrete Fourier transform. Conditional expectations, which are difficult to evaluate in the time domain, can be calculated efficiently in the frequency domain. We provide the numerical implementation accompanied by a flexible object-oriented toolbox. We demonstrate the efficiency and accuracy of our method by studying four models in macroeconomics and finance that feature asymmetric information sets, endogenous signals, and higher-order expectations.

Suggested Citation

  • Han, Zhao & Tan, Fei & Wu, Jieran, 2022. "Analytic policy function iteration," Journal of Economic Theory, Elsevier, vol. 200(C).
  • Handle: RePEc:eee:jetheo:v:200:y:2022:i:c:s002205312100212x
    DOI: 10.1016/j.jet.2021.105395
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    as
    1. Miao, Jianjun & Wu, Jieran & Young, Eric R., 2021. "Macro-financial volatility under dispersed information," Theoretical Economics, Econometric Society, vol. 16(1), January.
    2. Al-Sadoon, Majid M., 2018. "The Linear Systems Approach To Linear Rational Expectations Models," Econometric Theory, Cambridge University Press, vol. 34(3), pages 628-658, June.
    3. Olivier J. Blanchard & Jean-Paul L'Huillier & Guido Lorenzoni, 2013. "News, Noise, and Fluctuations: An Empirical Exploration," American Economic Review, American Economic Association, vol. 103(7), pages 3045-3070, December.
    4. Christiano, Lawrence J. & Eichenbaum, Martin & Evans, Charles L., 1999. "Monetary policy shocks: What have we learned and to what end?," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 2, pages 65-148, Elsevier.
    5. George-Marios Angeletos & Zhen Huo & Karthik A. Sastry, 2021. "Imperfect Macroeconomic Expectations: Evidence and Theory," NBER Macroeconomics Annual, University of Chicago Press, vol. 35(1), pages 1-86.
    6. Kenneth Kasa & Todd B. Walker & Charles H. Whiteman, 2014. "Heterogeneous Beliefs and Tests of Present Value Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(3), pages 1137-1163.
    7. Hansen, Lars Peter & Sargent, Thomas J., 1980. "Formulating and estimating dynamic linear rational expectations models," Journal of Economic Dynamics and Control, Elsevier, vol. 2(1), pages 7-46, May.
    8. Acharya, Sushant & Benhabib, Jess & Huo, Zhen, 2021. "The anatomy of sentiment-driven fluctuations," Journal of Economic Theory, Elsevier, vol. 195(C).
    9. Kristoffer Nimark, 2007. "Dynamic higher order expectations," Economics Working Papers 1118, Department of Economics and Business, Universitat Pompeu Fabra, revised Mar 2011.
    10. Ryan Chahrour & Gaetano Gaballo, 2021. "Learning from House Prices: Amplification and Business Fluctuations [House Price Booms and the Current Account]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(4), pages 1720-1759.
    11. Chahrour, Ryan & Ulbricht, Robert, 2017. "Information-driven Business Cycles: A Primal Approach," TSE Working Papers 17-784, Toulouse School of Economics (TSE), revised Dec 2017.
    12. Ryan Chahrour & Kyle Jurado, 2018. "News or Noise? The Missing Link," American Economic Review, American Economic Association, vol. 108(7), pages 1702-1736, July.
    13. Tan, Fei & Walker, Todd B., 2015. "Solving generalized multivariate linear rational expectations models," Journal of Economic Dynamics and Control, Elsevier, vol. 60(C), pages 95-111.
    14. Kenneth Kasa, 2000. "Forecasting the Forecasts of Others in the Frequency Domain," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 3(4), pages 726-756, October.
    15. Leonardo Melosi, 2017. "Signalling Effects of Monetary Policy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 84(2), pages 853-884.
    16. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
    17. George-Marios Angeletos & Chen Lian, 2018. "Forward Guidance without Common Knowledge," American Economic Review, American Economic Association, vol. 108(9), pages 2477-2512, September.
    18. Sargent, Thomas J., 1991. "Equilibrium with signal extraction from endogenous variables," Journal of Economic Dynamics and Control, Elsevier, vol. 15(2), pages 245-273, April.
    19. George-Marios Angeletos & Chen Lian, 2016. "Incomplete Information in Macroeconomics: Accommodating Frictions in Coordination," NBER Working Papers 22297, National Bureau of Economic Research, Inc.
    20. Guido Lorenzoni, 2009. "A Theory of Demand Shocks," American Economic Review, American Economic Association, vol. 99(5), pages 2050-2084, December.
    21. Taub, Bart, 1989. "Aggregate fluctuations as an information transmission mechanism," Journal of Economic Dynamics and Control, Elsevier, vol. 13(1), pages 113-150, January.
    22. Nimark, Kristoffer, 2008. "Dynamic pricing and imperfect common knowledge," Journal of Monetary Economics, Elsevier, vol. 55(2), pages 365-382, March.
    23. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, December.
    24. Graham, Liam & Wright, Stephen, 2010. "Information, heterogeneity and market incompleteness," Journal of Monetary Economics, Elsevier, vol. 57(2), pages 164-174, March.
    25. Mario Forni & Luca Gambetti & Luca Sala, 2019. "Structural VARs and noninvertible macroeconomic models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(2), pages 221-246, March.
    26. Whiteman, Charles H., 1985. "Spectral utility, wiener-hopf techniques, and rational expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 9(2), pages 225-240, October.
    27. George-Marios Angeletos & Zhen Huo, 2021. "Myopia and Anchoring," American Economic Review, American Economic Association, vol. 111(4), pages 1166-1200, April.
    28. Robert B. Barsky & Eric R. Sims, 2012. "Information, Animal Spirits, and the Meaning of Innovations in Consumer Confidence," American Economic Review, American Economic Association, vol. 102(4), pages 1343-1377, June.
    29. Angeletos, G.-M. & Lian, C., 2016. "Incomplete Information in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 1065-1240, Elsevier.
    30. Makarov, Igor & Rytchkov, Oleg, 2012. "Forecasting the forecasts of others: Implications for asset pricing," Journal of Economic Theory, Elsevier, vol. 147(3), pages 941-966.
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    Cited by:

    1. Zhao Han & Chengcheng Jia, 2023. "How Important Is the Information Effect of Monetary Policy?," Working Papers 23-32, Federal Reserve Bank of Cleveland.
    2. Jia, Chengcheng, 2023. "The informational effect of monetary policy and the case for policy commitment," European Economic Review, Elsevier, vol. 156(C).
    3. Meyer-Gohde, Alexander & Tzaawa-Krenzler, Mary, 2023. "Sticky information and the Taylor principle," IMFS Working Paper Series 189, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    4. Jurado, Kyle, 2023. "Rational inattention in the frequency domain," Journal of Economic Theory, Elsevier, vol. 208(C).

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    More about this item

    Keywords

    Endogenous information; Policy function iteration; Frequency-domain methods; Higher-order expectations;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • G1 - Financial Economics - - General Financial Markets

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