- Different versions of Dynare are now available as [Docker Containers](https://hub.docker.com/r/dynare/dynare).
- New perfect foresight simulation with expectation errors. In such a scenario, agents make expectation errors, in the sense that the path they had anticipated in period 1 does not realize exactly. More precisely, in some simulation periods, they may receive new information that makes them revise their anticipation for the path of future shocks. Also, under this scenario, it is assumed that agents behave as under perfect foresight, *i.e.* they take their decisions as if there was no uncertainty and they knew exactly the path of future shocks; the new information that they may receive comes as a total surprise to them. Implemented by new `perfect_foresight_with_expectation_errors_setup` and `perfect_foresight_with_expectation_errors_solver` commands, and `shocks(learnt_in=…)` and `endval(learnt_in=…)` blocks.
- New perfect foresight simulation with expectation errors. In such a scenario, agents make expectation errors, in the sense that the path they had anticipated in period 1 does not realize exactly. More precisely, in some simulation periods, they may receive new information that makes them revise their anticipation for the path of future shocks. Also, under this scenario, it is assumed that agents behave as under perfect foresight, *i.e.* they take their decisions as if there was no uncertainty and they knew exactly the path of future shocks; the new information that they may receive comes as a total surprise to them. Implemented by new `perfect_foresight_with_expectation_errors_setup` and `perfect_foresight_with_expectation_errors_solver` commands, and `shocks(learnt_in=…)`, `mshocks(learnt_in=…)` and `endval(learnt_in=…)` blocks.
- Pruning à la Andreasen et al. (2018) is now available at an arbitrary approximation order when performing stochastic simulations with `stoch_simul` (!2147)
