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Solving nonlinear stochastic optimization and equilibrium problems backwards

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  • Christopher A. Sims

Abstract

In a stochastic equilibrium model some stochastic processes are usually exogenously given, while others are either chosen optimally by agents or emerge from market equilibrium conditions. When we simulate such a model, often we aim at studying the relations among variables in the model as we vary parameters of policy and of behavior of economic agents. We are no more certain (indeed often less certain) of what is reasonable or interesting behavior for the exogenous variables (some of which may be unobservable) than of the variables chosen by agents or fixed in markets. It turns out that if we are flexible about which variables’ behavior we take as given in the model solution computation, freeing ourselves from the convention that the variables exogenous to the model economy must be taken as given in the simulation computations, great computational savings may result.

Suggested Citation

  • Christopher A. Sims, 1989. "Solving nonlinear stochastic optimization and equilibrium problems backwards," Discussion Paper / Institute for Empirical Macroeconomics 15, Federal Reserve Bank of Minneapolis.
    • Handle: RePEc:fip:fedmem:15
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    References listed on IDEAS

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    1. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-1370, November.
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    Cited by:

    1. Perez, Javier J. & Hiebert, Paul, 2004. "Identifying endogenous fiscal policy rules for macroeconomic models," Journal of Policy Modeling, Elsevier, vol. 26(8-9), pages 1073-1089, December.
    2. Felix Kubler & Karl Schmedders, 2003. "Approximate Versus Exact Equilibria," Discussion Papers 1382, Northwestern University, Center for Mathematical Studies in Economics and Management Science.

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    Keywords

    Econometrics;

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