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Bug fix, wrong definition of the growth neutrality correction... 

In PAC equations with optimizing and rule of thumb agents (division
by lambda was missing). Also add comments.
var-model-with-constant
Stéphane Adjemian (Ryûk) 2021-07-09 21:56:36 +02:00
parent abd64c256e
commit d9298ca03a
Signed by: stepan
GPG Key ID: 295C1FE89E17EB3C
1 changed files with 16 additions and 10 deletions
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26
matlab/+pac/+update/parameters.m
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@ -159,9 +159,11 @@ for e=1:number_of_pac_eq
% Growth neutrality as returned by hVector is valid iff
% there is no exogenous variables in the model and in the
% absence of non optimizing agents.
gg = -(growthneutrality-1);
cc = 1.0-gamma*gg;
gg = -(growthneutrality-1); % Finite sum of autoregressive parameters + infinite sum of the coefficients in the PAC expectation term.
cc = 1.0-gamma*gg; % First adjustment of the growth neutrality correction (should also be divided by gamma, done below at the end of this section).
% We may have to further change the correction if we have nonzero mean exogenous variables.
if isfield(equations.(eqtag), 'optim_additive')
% Exogenous variables are present in the λ part (optimizing agents).
tmp = 0;
for i=1:length(equations.(eqtag).optim_additive.params)
if isnan(equations.(eqtag).optim_additive.params(i)) && equations.(eqtag).optim_additive.bgp(i)
@ -173,17 +175,21 @@ for e=1:number_of_pac_eq
cc = cc - gamma*tmp;
end
if gamma<1
tmp = 0;
for i=1:length(equations.(eqtag).non_optimizing_behaviour.params)
if isnan(equations.(eqtag).non_optimizing_behaviour.params(i)) && equations.(eqtag).non_optimizing_behaviour.bgp(i)
tmp = tmp + equations.(eqtag).non_optimizing_behaviour.scaling_factor(i);
elseif ~isnan(equations.(eqtag).non_optimizing_behaviour.params(i)) && equations.(eqtag).non_optimizing_behaviour.bgp(i)
tmp = tmp + DynareModel.params(equations.(eqtag).non_optimizing_behaviour.params(i))*equations.(eqtag).non_optimizing_behaviour.scaling_factor(i);
if isfield(equations.(eqtag), 'non_optimizing_behaviour.params')
% Exogenous variables are present in the 1-λ part (rule of thumb agents).
tmp = 0;
for i=1:length(equations.(eqtag).non_optimizing_behaviour.params)
if isnan(equations.(eqtag).non_optimizing_behaviour.params(i)) && equations.(eqtag).non_optimizing_behaviour.bgp(i)
tmp = tmp + equations.(eqtag).non_optimizing_behaviour.scaling_factor(i);
elseif ~isnan(equations.(eqtag).non_optimizing_behaviour.params(i)) && equations.(eqtag).non_optimizing_behaviour.bgp(i)
tmp = tmp + DynareModel.params(equations.(eqtag).non_optimizing_behaviour.params(i))*equations.(eqtag).non_optimizing_behaviour.scaling_factor(i);
end
end
cc = cc - (1.0-gamma)*tmp;
end
cc = cc - (1.0-gamma)*tmp;
end
if isfield(equations.(eqtag), 'additive')
% Exogenous variables are present outside of the λ and (1-λ) parts (or we have exogenous variables in a "pure" PAC equation.
tmp = 0;
for i=1:length(equations.(eqtag).additive.params)
if isnan(equations.(eqtag).additive.params(i)) && equations.(eqtag).additive.bgp(i)
@ -194,6 +200,6 @@ for e=1:number_of_pac_eq
end
cc = cc - tmp;
end
DynareModel.params(pacmodel.growth_neutrality_param_index) = cc;
DynareModel.params(pacmodel.growth_neutrality_param_index) = cc/gamma;
end
end