dynare/matlab/ols/pooled_ols.m

167 lines
6.2 KiB
Matlab

function pooled_ols(ds, param_common, param_regex, overlapping_dates, save_structure_name)
% function pooled_ols(ds, param_common, param_regex, overlapping_dates, save_structure_name)
% Run Pooled OLS
% Apply parameter values found to corresponding parameter values in the
% other blocks of the model
%
% INPUTS
% ds [dseries] data to use in estimation
% param_common [cellstr] List of values to insert into param_regex,
% e.g. country codes {'FR', 'DE', 'IT'}
% param_regex [cellstr] Where '*' should be replaced by the first
% value in param_common
% overlapping_dates [bool] if the dates across the equations should
% overlap
% save_structure_name [string] Name of structure in oo_ to save results in
% (pooled_ols by default)
%
% OUTPUTS
% none
%
% SPECIAL REQUIREMENTS
% dynare must be run with the option: json=compute
% Copyright (C) 2017 Dynare Team
%
% This file is part of Dynare.
%
% Dynare is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% Dynare is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
global M_ oo_
%% Check input arguments
assert(~isempty(ds) && isdseries(ds), 'The first argument must be a dseries');
if isempty(param_common) && isempty(param_regex)
disp('Performing OLS instead of Pooled OLS...')
dyn_ols(ds);
return;
end
assert(~isempty(param_common) && iscellstr(param_common), 'The second argument must be a cellstr');
assert(~isempty(param_regex) && iscellstr(param_regex), 'The third argument must be a cellstr');
if nargin < 4
overlapping_dates = false;
else
assert(islogical(overlapping_dates) && length(overlapping_dates) == 1, 'The fourth argument must be a bool');
end
if nargin < 5
save_structure_name = 'pooled_ols';
else
assert(ischar(save_structure_name), 'The fifth argument must be a string');
end
%% Read JSON
jsonfile = [M_.fname '_original.json'];
if exist(jsonfile, 'file') ~= 2
error('Could not find %s! Please use the json=compute option (See the Dynare invocation section in the reference manual).', jsonfile);
end
jsonmodel = loadjson(jsonfile);
jsonmodel = jsonmodel.model;
[lhs, rhs, lineno] = getEquationsByTags(jsonmodel);
%% Replace parameter names in equations
country_name = param_common{1};
regexcountries = ['(' strjoin(param_common(2:end),'|') ')'];
for i = 1:length(param_regex)
splitp = strsplit(param_regex{i}, '*');
assert(length(splitp) >= 2);
rhs = regexprep(rhs, ...
strjoin(splitp, regexcountries), ...
strjoin(splitp, country_name));
end
%% Find parameters and variable names in every equation & Setup estimation matrices
M_exo_names_trim = cellstr(M_.exo_names);
M_param_names_trim = cellstr(M_.param_names);
[X, Y, startdates, enddates, startidxs, residnames, pbeta, vars, pidxs] = ...
pooled_sur_common(ds, lhs, rhs, lineno, M_exo_names_trim, M_param_names_trim);
if overlapping_dates
maxfp = max([startdates{:}]);
minlp = min([enddates{:}]);
nobs = minlp - maxfp;
newY = zeros(nobs*length(lhs), 1);
newX = zeros(nobs*length(lhs), columns(X));
newstartidxs = zeros(size(startidxs));
newstartidxs(1) = 1;
for i = 1:length(lhs)
if i == length(lhs)
yds = dseries(Y(startidxs(i):end), startdates{i});
xds = dseries(X(startidxs(i):end, :), startdates{i});
else
yds = dseries(Y(startidxs(i):startidxs(i+1)-1), startdates{i});
xds = dseries(X(startidxs(i):startidxs(i+1)-1, :), startdates{i});
end
newY(newstartidxs(i):newstartidxs(i) + nobs, 1) = yds(maxfp:minlp).data;
newX(newstartidxs(i):newstartidxs(i) + nobs, :) = xds(maxfp:minlp, :).data;
if i ~= length(lhs)
newstartidxs(i+1) = newstartidxs(i) + nobs + 1;
end
end
Y = newY;
X = newX;
startidxs = newstartidxs;
oo_.(save_structure_name).sample_range = maxfp:minlp;
oo_.(save_structure_name).residnames = residnames;
oo_.(save_structure_name).Y = Y;
oo_.(save_structure_name).X = X;
oo_.(save_structure_name).pbeta = pbeta;
oo_.(save_structure_name).country_name = country_name;
end
%% Estimation
% Estimated Parameters
[q, r] = qr(X, 0);
oo_.(save_structure_name).beta = r\(q'*Y);
st = dbstack(1);
if strcmp(st(1).name, 'pooled_fgls')
return
end
% Assign parameter values back to parameters using param_regex & param_common
regexcountries = ['(' strjoin(param_common(1:end),'|') ')'];
assigned_idxs = false(size(pbeta));
for i = 1:length(param_regex)
beta_idx = strcmp(pbeta, strrep(param_regex{i}, '*', country_name));
assigned_idxs = assigned_idxs | beta_idx;
value = oo_.(save_structure_name).beta(beta_idx);
assert(~isempty(value));
M_.params(~cellfun(@isempty, regexp(M_param_names_trim, ...
strrep(param_regex{i}, '*', regexcountries)))) = value;
end
idxs = find(assigned_idxs == 0);
values = oo_.(save_structure_name).beta(idxs);
names = pbeta(idxs);
assert(length(values) == length(names));
for i = 1:length(idxs)
M_.params(strcmp(M_param_names_trim, names{i})) = values(i);
end
residuals = Y - X * oo_.(save_structure_name).beta;
for i = 1:length(lhs)
if i == length(lhs)
oo_.(save_structure_name).resid.(residnames{i}{:}) = residuals(startidxs(i):end);
else
oo_.(save_structure_name).resid.(residnames{i}{:}) = residuals(startidxs(i):startidxs(i+1)-1);
end
oo_.(save_structure_name).varcovar.(['eq' num2str(i)]) = oo_.(save_structure_name).resid.(residnames{i}{:})*oo_.(save_structure_name).resid.(residnames{i}{:})';
idx = find(strcmp(residnames{i}{:}, M_exo_names_trim));
M_.Sigma_e(idx, idx) = var(oo_.(save_structure_name).resid.(residnames{i}{:}));
end
end