Commit Graph

13 Commits (5145bd0708697230c7adeb23c8a0dabf37f4cb3f)

Author SHA1 Message Date
Sébastien Villemot 5145bd0708
New option “relative_to_initval” to “mshocks” block 2023-10-18 16:45:06 -04:00
Sébastien Villemot daa6b5569d
mshocks: better match to the semantics given in the manual
Ensure that the block is always interpreted multiplicatively relative to the
steady state, and not relative to the pre-existing shock value (if there was
already a shock declared for the same exogenous and period(s)).
2023-10-18 14:28:54 -04:00
Sébastien Villemot 39f9d4352a
The “mshocks” block now accepts the “learnt_in” option 2023-10-17 17:24:15 -04:00
Sébastien Villemot d5a3a8e16a
Various improvements to perfect foresight homotopy
– new option “endval_steady” to pf_setup command to recompute terminal
  steady state in the homotopy loop

– new options “homotopy_linearization_fallback” and
  “homotopy_marginal_linearization_fallback” to pf_solver and pfwee_solver
  commands, to get an approximate solution when homotopy fails to go to 100%

– new options “homotopy_initial_step_size”, “homotopy_min_step_size”,
  “homotopy_step_size_increase_success_count” and “homotopy_max_completion_share”
  to pf_solver and pfwee_solver commands to fine tune the homotopy behaviour

– removed option “homotopy_alt_starting_point” to pf_solver command, not really
  useful

– new options “steady_solve_algo”, “steady_tolf”, “steady_tolx”,
  “steady_maxit”, “steady_markowitz” to pf_solver and pfwee_solver commands, to
  control the computation of the terminal steady state (and remove the
  equivalent options which previously had different names in pfwee_solver command)
2023-06-21 15:58:23 +02:00
Sébastien Villemot c1b78e26ac
perfect_foresight_with_expectation_errors_{setup,solver}: streamline handling of guess values
– Remove the terminal_steady_state_as_guess_value option to pfwee_solver
– pfwee_setup now sets the same guess values as pf_setup (i.e. terminal steady
  state at all periods)
– With constant_simulation_length option, pfwee_solver uses terminal steady
  state as guess values for periods that are added to the simulation
2023-06-15 15:37:48 +02:00
Sébastien Villemot 37870e4a40
evaluate_steady_state: accept exogenous steady state as argument instead of whole oo_ structure
This is a move towards a more functional programming style.
2023-06-07 17:58:19 +02:00
Sébastien Villemot 5aca770931
perfect_foresight_with_expectation_errors_{setup,solver}: fix bugs with several exogenous
Closes: #1883
2023-01-24 15:02:07 +01:00
Sébastien Villemot 63a116fb28
New += and *= syntaxes in “endval(learnt_in=…)” blocks 2022-05-03 17:46:59 +02:00
Sébastien Villemot b084c2e931
Perfect foresight with expectation errors: move computation of terminal steady states to the setup command
This is more logical, since those values are constraints from the point of view
of the solver.

Also, this allows to have maxit and tolf options for the steady state solver,
at the level of the setup command, without a clash with the same option names
for the deterministic solver at the level of the solver command.
2022-04-29 15:56:11 +02:00
Sébastien Villemot a600336c92
New “add” and “multiply” keywords in “shocks(learnt_in=…)” block 2022-04-26 15:22:15 +02:00
Sébastien Villemot 8488674ce4
New shocks(learnt_in=…) and endval(learnt_in=…) blocks
For use with perfect_foresight_with_expectation_errors_setup.
2022-04-21 17:10:52 +02:00
Sébastien Villemot b70b864829
perfect_foresight_with_expectation_errors_setup: move terminal condition to last line of CSV file 2022-04-12 15:51:04 +02:00
Sébastien Villemot abd64c256e
New perfect_foresight_with_expectation_errors_{setup,solver} commands
These command solve the problem where agents think they know perfectly the
future (they behave as in perfect foresight), but make expectation errors.
Hence they can potentially be surprised in every period, and their expectations
about the future (incl. the final steady state) may change.

Currently the sequence of information sets needs to be passed through a CSV
file. Another interface may be added in the future.

The algorithm uses a sequence of (true) perfect foresight simulations (not
necessarily as many as there are periods, because if the information set does
not change between two periods, there is no need to do a new computation).

There are two possibilities for guess values:
— the default is to use the initial steady state for the simulation using the
  first-period information set; then use previously simulated values as guess
  values
— alternatively, with the terminal_steady_state_as_guess_value option, use the
  terminal steady state as guess value for all future periods (this is actually
  what the “true” perfect foresight solver does by default)
2021-07-09 18:16:46 +02:00