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Equilibrium Modeling of Asset Prices: Rationality versus Rules of Thumb

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  • Ingram, Beth Fisher

Abstract

General equilibrium models with representative agents have proved to be inadequate descriptions of U.S. financial data. I present a model with heterogeneous agents, optimizers, and nonoptimizers that exhibits high stock-price volatility and mimics empirical regularities found in U.S. consumption, stock return, and three-month treasury-bill return data. The simulation and estimation of the model are performed using a new technique called "backsolving," which is of independent interest to researchers attempting to solve nonlinear, stochastic models.

Suggested Citation

  • Ingram, Beth Fisher, 1990. "Equilibrium Modeling of Asset Prices: Rationality versus Rules of Thumb," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 115-125, January.
  • Handle: RePEc:bes:jnlbes:v:8:y:1990:i:1:p:115-25
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    Cited by:

    1. B. Ravikumar & Enchuan Shao, 2005. "Search Frictions and Asset Price Volatility," 2005 Meeting Papers 227, Society for Economic Dynamics.
    2. Brandt, M.W.Michael W. & Zeng, Qi & Zhang, Lu, 2004. "Equilibrium stock return dynamics under alternative rules of learning about hidden states," Journal of Economic Dynamics and Control, Elsevier, vol. 28(10), pages 1925-1954, September.
    3. Taylor, John B & Uhlig, Harald, 1990. "Solving Nonlinear Stochastic Growth Models: A Comparison of Alternative Solution Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 1-17, January.
    4. Albert Marcet & David A. Marshall, 1994. "Solving nonlinear rational expectations models by parameterized expectations: convergence to stationary solutions," Working Paper Series, Macroeconomic Issues 94-20, Federal Reserve Bank of Chicago.
    5. Zhang, Harold H., 2000. "Explaining bond returns in heterogeneous agent models: The importance of higher-order moments," Journal of Economic Dynamics and Control, Elsevier, vol. 24(10), pages 1381-1404, September.
    6. He, Hua & Modest, David M, 1995. "Market Frictions and Consumption-Based Asset Pricing," Journal of Political Economy, University of Chicago Press, vol. 103(1), pages 94-117, February.
    7. Harald Uhlig & Martin Lettau, 1999. "Rules of Thumb versus Dynamic Programming," American Economic Review, American Economic Association, vol. 89(1), pages 148-174, March.
    8. Rodepeter, Ralf & Winter, Joachim, 1999. "Rules of thumb in life-cycle savings models," Papers 99-81, Sonderforschungsbreich 504.
    9. Diaz-Gimenez, Javier & Prescott, Edward C., 1997. "Real returns on government debt: A general equilibrium quantitative exploration," European Economic Review, Elsevier, vol. 41(1), pages 115-137, January.
    10. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
    11. Felix Kubler & Karl Schmedders, 2003. "Approximate Versus Exact Equilibria," Discussion Papers 1382, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    12. Duffie, Darrell & Singleton, Kenneth J, 1993. "Simulated Moments Estimation of Markov Models of Asset Prices," Econometrica, Econometric Society, vol. 61(4), pages 929-952, July.
    13. Lettau, M. & Uhlig, H.F.H.V.S., 1995. "Rule of Thumb and Dynamic Programming," Discussion Paper 1995-27, Tilburg University, Center for Economic Research.
    14. Krusell, Per & Smith, Anthony Jr., 1996. "Rules of thumb in macroeconomic equilibrium A quantitative analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 20(4), pages 527-558, April.

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