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Exact Expectations: Efficient Calculation of DSGE Models
Fabian Goessling1 - Personal Name
Global solution methods for dynamic stochastic general equilibrium models
are accurate but computationally expensive. In particular, evaluating conditional
expectations at numerous points in the state-space leads to significant computational
complexity. In the paper at hands, I show how to remove the majority of calculations
required for the evaluation of conditional expectations. Therefore, I replace the
approximated integrals obtained by e.g. quadrature rules with an analytic expression.
I provide a general framework and carry out the approach in detail using Chebyshev
basis functions. Subsequently, I adapt the exact expectations technique to the neoclassical
model with recursive utility, labor choice and student-t shocks to log-productivity
are accurate but computationally expensive. In particular, evaluating conditional
expectations at numerous points in the state-space leads to significant computational
complexity. In the paper at hands, I show how to remove the majority of calculations
required for the evaluation of conditional expectations. Therefore, I replace the
approximated integrals obtained by e.g. quadrature rules with an analytic expression.
I provide a general framework and carry out the approach in detail using Chebyshev
basis functions. Subsequently, I adapt the exact expectations technique to the neoclassical
model with recursive utility, labor choice and student-t shocks to log-productivity
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