Commit 2156f672 authored by Sébastien Villemot's avatar Sébastien Villemot
Browse files

New option analytic_derivation for estimation

parent 9867003d
......@@ -4196,6 +4196,9 @@ This is the convergence criterion used in the fixed point lyapunov solver. Its d
@anchor{lyapunov_doubling_tol}
This is the convergence criterion used in the doubling algorithm to solve the lyapunov equation. Its default value is 1e-16.
@item analytic_derivation
Triggers estimation with analytic gradient. The final hessian is also
computed analytically.
@end table
......
......@@ -89,7 +89,7 @@ class ParsingDriver;
#define yylex driver.lexer->lex
%}
%token AIM_SOLVER AR AUTOCORR
%token AIM_SOLVER ANALYTIC_DERIVATION AR AUTOCORR
%token BAYESIAN_IRF BETA_PDF BLOCK
%token BVAR_DENSITY BVAR_FORECAST
%token BVAR_PRIOR_DECAY BVAR_PRIOR_FLAT BVAR_PRIOR_LAMBDA
......@@ -1498,6 +1498,7 @@ estimation_options : o_datafile
| o_lyapunov
| o_lyapunov_fixed_point_tol
| o_lyapunov_doubling_tol
| o_analytic_derivation
;
list_optim_option : QUOTED_STRING COMMA QUOTED_STRING
......@@ -2525,6 +2526,7 @@ o_regimes : REGIMES { driver.option_num("ms.regimes","1"); };
o_regime : REGIME EQUAL INT_NUMBER { driver.option_num("ms.regime",$3); };
o_data_obs_nbr : DATA_OBS_NBR EQUAL INT_NUMBER { driver.option_num("ms.forecast_data_obs",$3); };
o_discretionary_tol: DISCRETIONARY_TOL EQUAL non_negative_number { driver.option_num("discretionary_tol",$3); };
o_analytic_derivation : ANALYTIC_DERIVATION { driver.option_num("analytic_derivation", "1"); }
range : symbol ':' symbol
{
......
......@@ -457,6 +457,7 @@ string eofbuff;
<DYNARE_STATEMENT>growth_factor {return token::GROWTH_FACTOR;}
<DYNARE_STATEMENT>cova_compute {return token::COVA_COMPUTE;}
<DYNARE_STATEMENT>discretionary_tol {return token::DISCRETIONARY_TOL;}
<DYNARE_STATEMENT>analytic_derivation {return token::ANALYTIC_DERIVATION;}
<DYNARE_STATEMENT>[\$][^$]*[\$] {
strtok(yytext+1, "$");
......
......@@ -64,6 +64,7 @@ MODFILES = \
fs2000/fs2000d.mod \
fs2000/fs2000_cmaes.mod \
fs2000/fs2000_calib.mod \
fs2000/fs2000_analytic_derivation.mod \
homotopy/homotopy1_test.mod \
homotopy/homotopy2_test.mod \
homotopy/homotopy3_test.mod \
......
// Tests the analytic_derivation option
var m P c e W R k d n l gy_obs gp_obs y dA;
varexo e_a e_m;
parameters alp bet gam mst rho psi del;
alp = 0.33;
bet = 0.99;
gam = 0.003;
mst = 1.011;
rho = 0.7;
psi = 0.787;
del = 0.02;
model;
dA = exp(gam+e_a);
log(m) = (1-rho)*log(mst) + rho*log(m(-1))+e_m;
-P/(c(+1)*P(+1)*m)+bet*P(+1)*(alp*exp(-alp*(gam+log(e(+1))))*k^(alp-1)*n(+1)^(1-alp)+(1-del)*exp(-(gam+log(e(+1)))))/(c(+2)*P(+2)*m(+1))=0;
W = l/n;
-(psi/(1-psi))*(c*P/(1-n))+l/n = 0;
R = P*(1-alp)*exp(-alp*(gam+e_a))*k(-1)^alp*n^(-alp)/W;
1/(c*P)-bet*P*(1-alp)*exp(-alp*(gam+e_a))*k(-1)^alp*n^(1-alp)/(m*l*c(+1)*P(+1)) = 0;
c+k = exp(-alp*(gam+e_a))*k(-1)^alp*n^(1-alp)+(1-del)*exp(-(gam+e_a))*k(-1);
P*c = m;
m-1+d = l;
e = exp(e_a);
y = k(-1)^alp*n^(1-alp)*exp(-alp*(gam+e_a));
gy_obs = dA*y/y(-1);
gp_obs = (P/P(-1))*m(-1)/dA;
end;
initval;
k = 6;
m = mst;
P = 2.25;
c = 0.45;
e = 1;
W = 4;
R = 1.02;
d = 0.85;
n = 0.19;
l = 0.86;
y = 0.6;
gy_obs = exp(gam);
gp_obs = exp(-gam);
dA = exp(gam);
end;
shocks;
var e_a; stderr 0.014;
var e_m; stderr 0.005;
end;
steady;
check;
estimated_params;
alp, beta_pdf, 0.356, 0.02;
bet, beta_pdf, 0.993, 0.002;
gam, normal_pdf, 0.0085, 0.003;
mst, normal_pdf, 1.0002, 0.007;
rho, beta_pdf, 0.129, 0.223;
psi, beta_pdf, 0.65, 0.05;
del, beta_pdf, 0.01, 0.005;
stderr e_a, inv_gamma_pdf, 0.035449, inf;
stderr e_m, inv_gamma_pdf, 0.008862, inf;
end;
varobs gp_obs gy_obs;
options_.solve_tolf = 1e-12;
estimation(order=1,analytic_derivation,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=2000,mh_nblocks=2,mh_jscale=0.8);
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