From 1983dc13a3df86d0df0499f6d7bb983c300c4c29 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?St=C3=A9phane=20Adjemian=20=28Guts=29?= <stepan@adjemian.eu>
Date: Thu, 14 Dec 2023 12:09:09 +0100
Subject: [PATCH] Make examples/fs2000.mod closer to the original code.
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- Use (old default) mode_compute=4 which is closer to the algorithm
used by Frank Schorfheide and ensures that the hessian matrix is well
behaved (contrary to the new default, because of the asymptote at 0
in the beta prior for autoregressive parameter Ï).
- Change parameterization for mst. A normal prior on mst is not
equivalent to a normal prior on log(mst) (which is done the
parameterization in the JAE paper).
Closes #2177.
---
examples/fs2000.mod | 50 +++++++++++++++++++++---------------------
examples/fs2000_data.m | 8 +++----
2 files changed, 29 insertions(+), 29 deletions(-)
diff --git a/examples/fs2000.mod b/examples/fs2000.mod
index 391fc2f1c3..13b95f0714 100644
--- a/examples/fs2000.mod
+++ b/examples/fs2000.mod
@@ -1,17 +1,17 @@
/*
- * This file replicates the estimation of the cash in advance model (termed M1
- * in the paper) described in Frank Schorfheide (2000): "Loss function-based
+ * This file replicates the estimation of the cash in advance model (termed M1
+ * in the paper) described in Frank Schorfheide (2000): "Loss function-based
* evaluation of DSGE models", Journal of Applied Econometrics, 15(6), 645-670.
*
- * The data are taken from the replication package at
+ * The data are taken from the replication package at
* http://dx.doi.org/10.15456/jae.2022314.0708799949
*
* The prior distribution follows the one originally specified in Schorfheide's
* paper. Note that the elicited beta prior for rho in the paper
* implies an asymptote and corresponding prior mode at 0. It is generally
- * recommended to avoid this extreme type of prior.
+ * recommended to avoid this extreme type of prior.
*
- * Because the data are already logged and we use the loglinear option to conduct
+ * Because the data are already logged and we use the loglinear option to conduct
* a full log-linearization, we need to use the logdata option.
*
* The equations are taken from J. Nason and T. Cogley (1994): "Testing the
@@ -62,20 +62,20 @@ varexo e_a ${\epsilon_A}$ (long_name='TFP shock')
e_m ${\epsilon_M}$ (long_name='Money growth shock')
;
-parameters alp ${\alpha}$ (long_name='capital share')
- bet ${\beta}$ (long_name='discount factor')
- gam ${\gamma}$ (long_name='long-run TFP growth')
- mst ${m^*}$ (long_name='long-run money growth')
- rho ${\rho}$ (long_name='autocorrelation money growth')
- phi ${\phi}$ (long_name='labor weight in consumption')
- del ${\delta}$ (long_name='depreciation rate')
+parameters alp ${\alpha}$ (long_name='capital share')
+ bet ${\beta}$ (long_name='discount factor')
+ gam ${\gamma}$ (long_name='long-run TFP growth')
+ logmst ${\log(m^*)}$ (long_name='long-run money growth')
+ rho ${\rho}$ (long_name='autocorrelation money growth')
+ phi ${\phi}$ (long_name='labor weight in consumption')
+ del ${\delta}$ (long_name='depreciation rate')
;
% roughly picked values to allow simulating the model before estimation
alp = 0.33;
bet = 0.99;
gam = 0.003;
-mst = 1.011;
+logmst = log(1.011);
rho = 0.7;
phi = 0.787;
del = 0.02;
@@ -84,7 +84,7 @@ model;
[name='NC before eq. (1), TFP growth equation']
dA = exp(gam+e_a);
[name='NC eq. (2), money growth rate']
-log(m) = (1-rho)*log(mst) + rho*log(m(-1))+e_m;
+log(m) = (1-rho)*logmst + rho*log(m(-1))+e_m;
[name='NC eq. (A1), Euler equation']
-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;
[name='NC below eq. (A1), firm borrowing constraint']
@@ -119,25 +119,25 @@ end;
steady_state_model;
dA = exp(gam);
gst = 1/dA;
- m = mst;
+ m = exp(logmst);
khst = ( (1-gst*bet*(1-del)) / (alp*gst^alp*bet) )^(1/(alp-1));
- xist = ( ((khst*gst)^alp - (1-gst*(1-del))*khst)/mst )^(-1);
- nust = phi*mst^2/( (1-alp)*(1-phi)*bet*gst^alp*khst^alp );
+ xist = ( ((khst*gst)^alp - (1-gst*(1-del))*khst)/m )^(-1);
+ nust = phi*m^2/( (1-alp)*(1-phi)*bet*gst^alp*khst^alp );
n = xist/(nust+xist);
P = xist + nust;
k = khst*n;
- l = phi*mst*n/( (1-phi)*(1-n) );
- c = mst/P;
- d = l - mst + 1;
+ l = phi*m*n/( (1-phi)*(1-n) );
+ c = m/P;
+ d = l - m + 1;
y = k^alp*n^(1-alp)*gst^alp;
- R = mst/bet;
+ R = m/bet;
W = l/n;
ist = y-c;
q = 1 - d;
e = 1;
-
+
gp_obs = m/dA;
gy_obs = dA;
end;
@@ -151,7 +151,7 @@ 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;
+logmst, normal_pdf, 0.0002, 0.007;
rho, beta_pdf, 0.129, 0.223;
phi, beta_pdf, 0.65, 0.05;
del, beta_pdf, 0.01, 0.005;
@@ -161,8 +161,8 @@ end;
varobs gp_obs gy_obs;
-estimation(order=1, datafile=fs2000_data, loglinear,logdata, mh_replic=2000, mh_nblocks=2, mh_jscale=0.8, mode_check);
+estimation(order=1, datafile=fs2000_data, loglinear,logdata, mode_compute=4, mh_replic=20000, nodiagnostic, mh_nblocks=2, mh_jscale=0.8, mode_check);
%uncomment the following lines to generate LaTeX-code of the model equations
%write_latex_original_model(write_equation_tags);
-%collect_latex_files;
\ No newline at end of file
+%collect_latex_files;
diff --git a/examples/fs2000_data.m b/examples/fs2000_data.m
index 9c4ea3d6d1..281b2d8eb1 100644
--- a/examples/fs2000_data.m
+++ b/examples/fs2000_data.m
@@ -1,6 +1,6 @@
%This file is a direct Matlab implementation of the loaddata.g and data.prn files
-%of Schorfheide, Frank (2000): Loss function-based evaluation of DSGE models
-%(replication data). Version: 1. Journal of Applied Econometrics. Dataset.
+%of Schorfheide, Frank (2000): Loss function-based evaluation of DSGE models
+%(replication data). Version: 1. Journal of Applied Econometrics. Dataset.
%http://dx.doi.org/10.15456/jae.2022314.0708799949
% Copyright: 2000-2022 Frank Schorfheide
% Copyright: 2023 Dynare Team
@@ -210,6 +210,6 @@ data_q=[18.02 1474.5 150.2
%Compute growth rates: from 1950:I to 1997:IV
gy_obs=1000*data_q(:,2)./data_q(:,3); %real GDP per capita
-gy_obs=diff(log(gy_obs));
+gy_obs=diff(log(gy_obs));
-gp_obs = diff(log(data_q(:,1))); %GDP deflator inflation
\ No newline at end of file
+gp_obs = diff(log(data_q(:,1))); %GDP deflator inflation
--
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