Exact expectations - Efficient calculation of DSGE models

Global solution methods for dynamic stochastic general equilibrium (DSGE) models are acurrate but computationally expensive. In particular computing conditional expectations for numerous points in the state-space leads to significant complexity. In the present paper, I show how to remove the majority of calculations required for the evaluation of conditional expectations. Therefore I replace the approximated conditional expectation obtained by e.g. quadrature rules with an exact expectation. Further, similar to Judd et al. (2011), the required integrals are evaluated at the initial stage of the algorithm. I adopt Chebyshev polynomials as basis functions and provide a general framework. Subsequently, I adapt the technique to the neoclassical model with recursive utility and labor choice.