This paper extends the work of Hansen and Jagannathan (1997) by showing how to decompose approximation errors in stochastic discount factor models by frequency. This decomposition is applied to a number of prominent consumption-based discount factor models top investigate how well they fit at...

This article extends the work of Hansen and Jagannathan by showing how to decompose approximation errors in stochastic discount factor models by frequency. This decomposition is applied to a number of consumption-based discount factor models in order to investigate how well they fit at low...

We study a Markov decision problem with unknown transition probabilities. We compute the exact Bayesian decision rule and compare it with two approximations. The first is an infinite-history, rational-expectations approximation that assumes that the decision maker knows the transition...

This paper explores various strategies for estimating rational expectations models when the trend specification is uncertain. One approach modified the likelihood function in order to reduce the influence of low-frequency dynamics. Hansen and Sargent (1993) conjectured that this would have...