IDEAS home Printed from https://ideas.repec.org/p/ihs/ihsesp/320.html
   My bibliography  Save this paper

Solving OLG Models with Many Cohorts, Asset Choice and Large Shocks

Author

Listed:
  • Reiter, Michael

    (Institute for Advanced Studies, Vienna)

Abstract

The paper presents a computationally efficient method to solve overlapping generations models with asset choice. The method is used to study an OLG economy with many cohorts, up to 3 different assets, stochastic volatility, short-sale constraints, and subject to rather large technology shocks. On the methodological side, the main findings are that global projection methods with polynomial approximations of degree 3 are sufficient to provide a very precise solution, even in the case of large shocks. Globally linear approximations, in contrast to local linear approximations, are sufficient to capture the most important financial statistics, including not only the average risk premium, but also the variation of the risk premium over the cycle. However, global linear approximations are not sufficient to reliably pin down asset choices. With a risk aversion parameter of only 4, the model generates a price of risk, measured as the Sharpe ratio, that is almost half of what it is for US stocks. However, the asset price fluctuations and the equity premium are much smaller than in US data.

Suggested Citation

  • Reiter, Michael, 2015. "Solving OLG Models with Many Cohorts, Asset Choice and Large Shocks," Economics Series 320, Institute for Advanced Studies.
  • Handle: RePEc:ihs:ihsesp:320
    as

    Download full text from publisher

    File URL: https://irihs.ihs.ac.at/id/eprint/3875
    File Function: First version, 2015
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alexander Ludwig & Michael Reiter, 2010. "Sharing Demographic Risk--Who Is Afraid of the Baby Bust?," American Economic Journal: Economic Policy, American Economic Association, vol. 2(4), pages 83-118, November.
    2. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, December.
    3. Jasmina Hasanhodzic & Laurence J. Kotlikoff, 2013. "Generational Risk - Is It a Big Deal?: Simulating an 80-Period OLG Model with Aggregate Shocks," NBER Working Papers 19179, National Bureau of Economic Research, Inc.
    4. Krueger, Dirk & Kubler, Felix, 2004. "Computing equilibrium in OLG models with stochastic production," Journal of Economic Dynamics and Control, Elsevier, vol. 28(7), pages 1411-1436, April.
    5. Alan J. Auerbach & Laurence J. Kotlikoff, 1983. "National Savings, Economic Welfare, and the Structure of Taxation," NBER Chapters, in: Behavioral Simulation Methods in Tax Policy Analysis, pages 459-498, National Bureau of Economic Research, Inc.
    6. Judd, Kenneth L. & Maliar, Lilia & Maliar, Serguei & Valero, Rafael, 2014. "Smolyak method for solving dynamic economic models: Lagrange interpolation, anisotropic grid and adaptive domain," Journal of Economic Dynamics and Control, Elsevier, vol. 44(C), pages 92-123.
    7. Marcet, Albert & Singleton, Kenneth J., 1999. "Equilibrium Asset Prices And Savings Of Heterogeneous Agents In The Presence Of Incomplete Markets And Portfolio Constraints," Macroeconomic Dynamics, Cambridge University Press, vol. 3(2), pages 243-277, June.
    8. Dirk Krueger & Felix Kubler, 2006. "Pareto-Improving Social Security Reform when Financial Markets are Incomplete!?," American Economic Review, American Economic Association, vol. 96(3), pages 737-755, June.
    9. Sy-Ming Guu & Kenneth L. Judd, 2001. "Asymptotic methods for asset market equilibrium analysis," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 18(1), pages 127-157.
    10. Benjamin Malin & Dirk Krueger & Felix Kubler, 2007. "Computing Stochastic Dynamic Economic Models with a Large Number of State Variables: A Description and Application of a Smolyak-Collocation Method," NBER Technical Working Papers 0345, National Bureau of Economic Research, Inc.
    11. Ravi Bansal & Amir Yaron, 2004. "Risks for the Long Run: A Potential Resolution of Asset Pricing Puzzles," Journal of Finance, American Finance Association, vol. 59(4), pages 1481-1509, August.
    12. Kenneth Judd & Lilia Maliar & Serguei Maliar, 2012. "Merging simulation and projection approaches to solve high-dimensional problems," Working Papers. Serie AD 2012-20, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    13. Per Krusell & Anthony A. Smith & Jr., 1998. "Income and Wealth Heterogeneity in the Macroeconomy," Journal of Political Economy, University of Chicago Press, vol. 106(5), pages 867-896, October.
    14. Albert Marcet & Guido Lorenzoni, 1998. "Parameterized expectations approach; Some practical issues," Economics Working Papers 296, Department of Economics and Business, Universitat Pompeu Fabra.
    15. Judd, Kenneth L., 1992. "Projection methods for solving aggregate growth models," Journal of Economic Theory, Elsevier, vol. 58(2), pages 410-452, December.
    16. Reiter, Michael, 2010. "Approximate and Almost-Exact Aggregation in Dynamic Stochastic Heterogeneous-Agent Models," Economics Series 258, Institute for Advanced Studies.
    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. Grzegorz R. Dlugoszek, 2016. "Solving DSGE Portfolio Choice Models with Asymmetric Countries," SFB 649 Discussion Papers SFB649DP2016-009, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Amaral, Pedro S., 2023. "The demographic transition and the asset supply channel," European Economic Review, Elsevier, vol. 151(C).
    3. Dan Cao & Wenlan Luo & Guangyu Nie, 2023. "Global GDSGE Models," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 51, pages 199-225, 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. Michael Reiter, 2015. "Solving OLG Models with Asset Choice," 2015 Meeting Papers 1509, Society for Economic Dynamics.
    2. Marlon Azinovic & Luca Gaegauf & Simon Scheidegger, 2022. "Deep Equilibrium Nets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(4), pages 1471-1525, November.
    3. Lilia Maliar & Serguei Maliar & John B. Taylor & Inna Tsener, 2020. "A tractable framework for analyzing a class of nonstationary Markov models," Quantitative Economics, Econometric Society, vol. 11(4), pages 1289-1323, November.
    4. Serguei Maliar & John Taylor & Lilia Maliar, 2016. "The Impact of Alternative Transitions to Normalized Monetary Policy," 2016 Meeting Papers 794, Society for Economic Dynamics.
    5. Judd, Kenneth L. & Maliar, Lilia & Maliar, Serguei & Valero, Rafael, 2014. "Smolyak method for solving dynamic economic models: Lagrange interpolation, anisotropic grid and adaptive domain," Journal of Economic Dynamics and Control, Elsevier, vol. 44(C), pages 92-123.
    6. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 527-724, Elsevier.
    7. Daniel Harenberg & Alexander Ludwig, "undated". "Social Security and the Interactions Between Aggregate and Idiosyncratic Risk," Working Papers ETH-RC-14-002, ETH Zurich, Chair of Systems Design.
    8. Ángel Gavilán & Juan A. Rojas, 2009. "Solving Portfolio Problems with the Smolyak-Parameterized Expectations Algorithm," Working Papers 0838, Banco de España.
    9. Grey Gordon, 2020. "Computing Dynamic Heterogeneous-Agent Economies: Tracking the Distribution," Economic Quarterly, Federal Reserve Bank of Richmond, issue 2Q, pages 61-95.
    10. Daniel Harenberg & Alexander Ludwig, 2019. "Idiosyncratic Risk, Aggregate Risk, And The Welfare Effects Of Social Security," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 60(2), pages 661-692, May.
    11. Kenneth Judd & Lilia Maliar & Serguei Maliar, 2009. "Numerically Stable Stochastic Simulation Approaches for Solving Dynamic Economic Models," NBER Working Papers 15296, National Bureau of Economic Research, Inc.
    12. Arellano, Cristina & Maliar, Lilia & Maliar, Serguei & Tsyrennikov, Viktor, 2016. "Envelope condition method with an application to default risk models," Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 436-459.
    13. Kenneth L. Judd & Lilia Maliar & Serguei Maliar & Inna Tsener, 2017. "How to solve dynamic stochastic models computing expectations just once," Quantitative Economics, Econometric Society, vol. 8(3), pages 851-893, November.
    14. Aruoba, S. Boragan & Fernandez-Villaverde, Jesus & Rubio-Ramirez, Juan F., 2006. "Comparing solution methods for dynamic equilibrium economies," Journal of Economic Dynamics and Control, Elsevier, vol. 30(12), pages 2477-2508, December.
    15. YiLi Chien & Hanno Lustig, 2010. "The Market Price of Aggregate Risk and the Wealth Distribution," The Review of Financial Studies, Society for Financial Studies, vol. 23(4), pages 1596-1650, April.
    16. repec:hal:spmain:info:hdl:2441/8845 is not listed on IDEAS
    17. Isaiah Hull & Or Sattath & Eleni Diamanti & Göran Wendin, 2024. "Quantum Technology for Economists," Contributions to Economics, Springer, number 978-3-031-50780-9.
    18. Dario Caldara & Jesus Fernandez-Villaverde & Juan Rubio-Ramirez & Wen Yao, 2012. "Computing DSGE Models with Recursive Preferences and Stochastic Volatility," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 15(2), pages 188-206, April.
    19. Kenneth L. Judd & Lilia Maliar & Serguei Maliar, 2014. "Lower Bounds on Approximation Errors: Testing the Hypothesis That a Numerical Solution Is Accurate?," BYU Macroeconomics and Computational Laboratory Working Paper Series 2014-06, Brigham Young University, Department of Economics, BYU Macroeconomics and Computational Laboratory.
    20. Algan, Yann & Allais, Olivier & Den Haan, Wouter J., 2008. "Solving heterogeneous-agent models with parameterized cross-sectional distributions," Journal of Economic Dynamics and Control, Elsevier, vol. 32(3), pages 875-908, March.
    21. repec:hal:wpspec:info:hdl:2441/8823 is not listed on IDEAS
    22. repec:spo:wpecon:info:hdl:2441/8845 is not listed on IDEAS
    23. Dario Caldara & Jesus Fernandez-Villaverde & Juan F. Rubio-Ramirez & Wen Yao, 2009. "Computing DSGE Models with Recursive Preferences," PIER Working Paper Archive 09-018, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

    More about this item

    Keywords

    OLG models; asset choice; projection methods;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ihs:ihsesp:320. 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: Doris Szoncsitz (email available below). General contact details of provider: https://edirc.repec.org/data/deihsat.html .

    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.