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dyn_ols: add dictionary option for renaming fitted values, save fitted values in dseries, return dseries

time-shift
Houtan Bastani 2017-11-13 16:17:18 +01:00
parent cd85a58d73
commit f5bef07232
1 changed files with 33 additions and 12 deletions
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45
matlab/ols/dyn_ols.m
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@ -1,15 +1,19 @@
function dyn_ols(ds, varargin)
function ds = dyn_ols(ds, varargin)
% function dyn_ols(ds, varargin)
% Run OLS on chosen model equations; unlike olseqs, allow for time t
% endogenous variables on LHS
%
% INPUTS
% ds [dseries] data
% varargin [cellstr] names of equation tags to estimate. If empty,
% estimate all equations
% ds [dseries] data
% varargin{1} [cell] Nx2 cell array to be used in naming fitted
% values; first column is the var name,
% second column is the name of the
% associated fitted value.
% varargin{2} [cellstr] names of equation tags to estimate. If empty,
% estimate all equations
%
% OUTPUTS
% none
% ds [dseries] data updated with fitted values
%
% SPECIAL REQUIREMENTS
% none
@ -33,7 +37,7 @@ function dyn_ols(ds, varargin)
global M_ oo_
assert(nargin <= 2, 'Incorrect number of arguments.');
assert(isdseries(ds), 'dyn_ols: the first argument must be a dseries');
jsonfile = [M_.fname '_original.json'];
if exist(jsonfile, 'file') ~= 2
@ -43,10 +47,18 @@ end
%% Get Equation(s)
jsonmodel = loadjson(jsonfile);
jsonmodel = jsonmodel.model;
fitted_names_dict = {};
if nargin == 1
[lhs, rhs, lineno] = getEquationsByTags(jsonmodel);
else
[lhs, rhs, lineno] = getEquationsByTags(jsonmodel, 'name', varargin{:});
fitted_names_dict = varargin{1};
assert(iscell(fitted_names_dict) && columns(fitted_names_dict) == 2, ...
'dyn_ols: the second argument must be an Nx2 cell array');
if nargin == 2
[lhs, rhs, lineno] = getEquationsByTags(jsonmodel);
else
[lhs, rhs, lineno] = getEquationsByTags(jsonmodel, 'name', varargin{2:end});
end
if isempty(lhs)
disp('dyn_ols: Nothing to estimate')
return
@ -168,11 +180,11 @@ for i = 1:length(lhs)
%% Estimation
% From LeSage, James P. "Applied Econometrics using MATLAB"
if nargin == 2
if iscell(varargin{1})
tagv = varargin{1}{i};
if nargin == 3
if iscell(varargin{2})
tagv = varargin{2}{i};
else
tagv = varargin{1};
tagv = varargin{2};
end
else
tagv = ['eq_line_no_' num2str(lineno{i})];
@ -189,7 +201,15 @@ for i = 1:length(lhs)
end
% Yhat
oo_.ols.(tagv).Yhat = dseries(X*oo_.ols.(tagv).beta, fp, [lhs{i} '_hat']);
lhsrep = regexprep(lhs{i}, '[\(\)\-+\*/]', '_');
yhatname = [lhsrep '_FIT'];
if ~isempty(fitted_names_dict)
idx = strcmp(fitted_names_dict(:,1), lhsrep);
if any(idx)
yhatname = fitted_names_dict{idx, 2};
end
end
oo_.ols.(tagv).Yhat = dseries(X*oo_.ols.(tagv).beta, fp, yhatname);
% Residuals
oo_.ols.(tagv).resid = Y - oo_.ols.(tagv).Yhat;
@ -198,6 +218,7 @@ for i = 1:length(lhs)
for j = 1:lhssub.vobs
oo_.ols.(tagv).Yhat = oo_.ols.(tagv).Yhat + lhssub{j}(fp:lp);
end
ds = [ds oo_.ols.(tagv).Yhat];
%% Calculate statistics
% Estimate for sigma^2