IDEAS home Printed from https://ideas.repec.org/a/gam/jecnmx/v7y2019i2p27-d239856.html
   My bibliography  Save this article

Looking Backward and Looking Forward

Author

Listed:
  • Zhengyuan Gao

    (Center for Operations Research and Econometrics (CORE), Universite Catholique de Louvain, Voie du Roman Pays 34, B-1348 Louvain-la-Neuve, Belgium)

  • Christian M. Hafner

    (Institut de Statistique, Biostatistique et Sciences Actuarielles (ISBA) and Center for Operations Research and Econometrics (CORE), Universite Catholique de Louvain, Voie du Roman Pays 20, B-1348 Louvain-la-Neuve, Belgium)

Abstract

Filtering has had a profound impact as a device of perceiving information and deriving agent expectations in dynamic economic models. For an abstract economic system, this paper shows that the foundation of applying the filtering method corresponds to the existence of a conditional expectation as an equilibrium process. Agent-based rational behavior of looking backward and looking forward is generalized to a conditional expectation process where the economic system is approximated by a class of models, which can be represented and estimated without information loss. The proposed framework elucidates the range of applications of a general filtering device and is not limited to a particular model class such as rational expectations.

Suggested Citation

  • Zhengyuan Gao & Christian M. Hafner, 2019. "Looking Backward and Looking Forward," Econometrics, MDPI, vol. 7(2), pages 1-24, June.
    • Handle: RePEc:gam:jecnmx:v:7:y:2019:i:2:p:27-:d:239856
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2225-1146/7/2/27/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2225-1146/7/2/27/
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Lars Peter Hansen & Thomas J Sargent, 2014. "Beliefs, Doubts and Learning: Valuing Macroeconomic Risk," World Scientific Book Chapters, in: UNCERTAINTY WITHIN ECONOMIC MODELS, chapter 10, pages 331-377, World Scientific Publishing Co. Pte. Ltd..
    2. Evans, George W & Ramey, Garey, 1992. "Expectation Calculation and Macroeconomic Dynamics," American Economic Review, American Economic Association, vol. 82(1), pages 207-224, March.
    3. D.S.G. Pollock, "undated". "Filters, Waves and Spectra," Discussion Papers in Economics 19/08, Division of Economics, School of Business, University of Leicester.
    4. D. Stephen G. Pollock, 2018. "Filters, Waves and Spectra," Econometrics, MDPI, vol. 6(3), pages 1-33, July.
    5. Lars Peter Hansen, 2007. "Beliefs, Doubts and Learning: Valuing Economic Risk," NBER Working Papers 12948, National Bureau of Economic Research, Inc.
    6. anonymous, 2007. "Bank asset growth robust, statistics show," Financial Update, Federal Reserve Bank of Atlanta, vol. 20(2).
    7. Lars Peter Hansen & Thomas J. Sargent, 2007. "Introduction to Robustness," Introductory Chapters, in: Robustness, Princeton University Press.
    8. Robert J. Elliott & Anatoliy V. Swishchuk, 2007. "Pricing Options and Variance Swaps in Markov-Modulated Brownian Markets," International Series in Operations Research & Management Science, in: Rogemar S. Mamon & Robert J. Elliott (ed.), Hidden Markov Models in Finance, chapter 4, pages 45-68, Springer.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dvouletý Ondřej & Čadil Jan & Mirošník Karel, 2019. "Do Firms Supported by Credit Guarantee Schemes Report Better Financial Results 2 Years After the End of Intervention?," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 19(1), pages 1-20, January.
    2. Yingxiu Zhao & Wei Zhang & Xiangyu Kong, 2019. "Dynamic Cross-Correlations between Participants’ Attentions to P2P Lending and Offline Loan in the Private Lending Market," Complexity, Hindawi, vol. 2019, pages 1-8, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pierre‐André Chiappori & Bernard Salanié & François Salanié & Amit Gandhi, 2019. "From Aggregate Betting Data to Individual Risk Preferences," Econometrica, Econometric Society, vol. 87(1), pages 1-36, January.
    2. Massimo Guidolin & Francesca Rinaldi, 2013. "Ambiguity in asset pricing and portfolio choice: a review of the literature," Theory and Decision, Springer, vol. 74(2), pages 183-217, February.
    3. Andreas Fuster & Benjamin Hebert & David Laibson, 2012. "Natural Expectations, Macroeconomic Dynamics, and Asset Pricing," NBER Macroeconomics Annual, University of Chicago Press, vol. 26(1), pages 1-48.
    4. Hansen, Lars Peter & Sargent, Thomas J., 2022. "Structured ambiguity and model misspecification," Journal of Economic Theory, Elsevier, vol. 199(C).
    5. Orphanides, Athanasios & Williams, John C., 2008. "Learning, expectations formation, and the pitfalls of optimal control monetary policy," Journal of Monetary Economics, Elsevier, vol. 55(Supplemen), pages 80-96, October.
    6. Stefano d¡¦Addona, 2018. "Rational Ignorance in Long-run Risk Models," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 17(1), pages 43-54, June.
    7. Borovička, Jaroslav & Hansen, Lars Peter, 2014. "Examining macroeconomic models through the lens of asset pricing," Journal of Econometrics, Elsevier, vol. 183(1), pages 67-90.
    8. Luo, Yulei & Young, Eric R., 2016. "Induced uncertainty, market price of risk, and the dynamics of consumption and wealth," Journal of Economic Theory, Elsevier, vol. 163(C), pages 1-41.
    9. Durlauf, Steven N. & Navarro, Salvador & Rivers, David A., 2016. "Model uncertainty and the effect of shall-issue right-to-carry laws on crime," European Economic Review, Elsevier, vol. 81(C), pages 32-67.
    10. Calvet, Laurent E. & Czellar, Veronika, 2015. "Through the looking glass: Indirect inference via simple equilibria," Journal of Econometrics, Elsevier, vol. 185(2), pages 343-358.
    11. Campbell Leith & Eric Leeper, 2016. "Understanding Inflation as a Joint Monetary-Fiscal Phenomenon," Working Papers 2016_01, Business School - Economics, University of Glasgow.
    12. Lex Borghans & Bart H. H. Golsteyn & James J. Heckman & Huub Meijers, 2009. "Gender Differences in Risk Aversion and Ambiguity Aversion," Journal of the European Economic Association, MIT Press, vol. 7(2-3), pages 649-658, 04-05.
    13. Hill, Brian & Michalski, Tomasz, 2018. "Risk versus ambiguity and international security design," Journal of International Economics, Elsevier, vol. 113(C), pages 74-105.
    14. Li Qin & Moïse Sidiropoulos, 2016. "Robustness of Optimal Interest Rate Rules in an Open Economy," Bulletin of Applied Economics, Risk Market Journals, vol. 3(1), pages 29-46.
    15. Harjoat S. Bhamra & Raman Uppal, 2014. "Asset Prices with Heterogeneity in Preferences and Beliefs," The Review of Financial Studies, Society for Financial Studies, vol. 27(2), pages 519-580.
    16. Sumru Altug & Cem Cakmakli & Fabrice Collard & Sujoy Mukerji & Han Ozsoylev, 2020. "Ambiguous Business Cycles: A Quantitative Assessment," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 38, pages 220-237, October.
    17. Fabrice Collard & Sujoy Mukerji & Kevin Sheppard & Jean‐Marc Tallon, 2018. "Ambiguity and the historical equity premium," Quantitative Economics, Econometric Society, vol. 9(2), pages 945-993, July.
    18. Condie, Scott & Ganguli, Jayant, 2017. "The pricing effects of ambiguous private information," Journal of Economic Theory, Elsevier, vol. 172(C), pages 512-557.
    19. Luo, Yulei & Nie, Jun & Young, Eric, 2015. "Robust Permanent Income in General Equilibrium," MPRA Paper 63985, University Library of Munich, Germany.
    20. Julian Kozlowski & Laura Veldkamp & Venky Venkateswaran, 2019. "The Tail That Keeps the Riskless Rate Low," NBER Macroeconomics Annual, University of Chicago Press, vol. 33(1), pages 253-283.

    More about this item

    Keywords

    perception; filter; rational expectations; estimation;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jecnmx:v:7:y:2019:i:2:p:27-:d:239856. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.