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fs2000.mod: provide actual replication 

Closes https://git.dynare.org/Dynare/dynare/-/issues/1905
mr#2177
Johannes Pfeifer 2023-09-13 21:15:31 +02:00 committed by Stéphane Adjemian (Guts)
parent 81cd0f1cb5
commit 162813225d
Signed by: stepan
GPG Key ID: 295C1FE89E17EB3C
3 changed files with 282 additions and 29 deletions
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91
examples/fs2000.mod
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@ -3,20 +3,20 @@
* 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 in file "fsdat_simul.m", and have been artificially generated.
* They are therefore different from the original dataset used by Schorfheide.
* 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, except for parameter rho. In the paper, the elicited beta prior for rho
* 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. Some optimizers, for instance
* mode_compute=12 (Mathworks' particleswarm algorithm) may find a posterior mode
* with rho equal to zero. We lowered the value of the prior standard deviation
* (changing .223 to .100) to remove the asymptote.
* recommended to avoid this extreme type of prior.
*
* 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
* implications of long-run neutrality for monetary business cycle models",
* Journal of Applied Econometrics, 9, S37-S70.
* Journal of Applied Econometrics, 9, S37-S70, NC in the following.
* Note that there is an initial minus sign missing in equation (A1), p. S63.
*
* This implementation was originally written by Michel Juillard. Please note that the
@ -25,7 +25,7 @@
*/
/*
* Copyright © 2004-2017 Dynare Team
* Copyright © 2004-2023 Dynare Team
*
* This file is part of Dynare.
*
@ -43,33 +43,71 @@
* along with Dynare. If not, see <https://www.gnu.org/licenses/>.
*/
var m P c e W R k d n l gy_obs gp_obs y dA;
varexo e_a e_m;
var m ${m}$ (long_name='money growth')
P ${P}$ (long_name='Price level')
c ${c}$ (long_name='consumption')
e ${e}$ (long_name='capital stock')
W ${W}$ (long_name='Wage rate')
R ${R}$ (long_name='interest rate')
k ${k}$ (long_name='capital stock')
d ${d}$ (long_name='dividends')
n ${n}$ (long_name='labor')
l ${l}$ (long_name='loans')
gy_obs ${\Delta \ln GDP}$ (long_name='detrended capital stock')
gp_obs ${\Delta \ln P}$ (long_name='detrended capital stock')
y ${y}$ (long_name='detrended output')
dA ${\Delta A}$ (long_name='TFP growth')
;
varexo e_a ${\epsilon_A}$ (long_name='TFP shock')
e_m ${\epsilon_M}$ (long_name='Money growth shock')
;
parameters alp bet gam mst rho psi del;
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')
;
% roughly picked values to allow simulating the model before estimation
alp = 0.33;
bet = 0.99;
gam = 0.003;
mst = 1.011;
rho = 0.7;
psi = 0.787;
phi = 0.787;
del = 0.02;
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;
[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']
W = l/n;
-(psi/(1-psi))*(c*P/(1-n))+l/n = 0;
[name='NC eq. (A2), intratemporal labour market condition']
-(phi/(1-phi))*(c*P/(1-n))+l/n = 0;
[name='NC below eq. (A2), credit market clearing']
R = P*(1-alp)*exp(-alp*(gam+e_a))*k(-1)^alp*n^(-alp)/W;
[name='NC eq. (A3), credit market optimality']
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;
[name='NC eq. (18), aggregate resource constraint']
c+k = exp(-alp*(gam+e_a))*k(-1)^alp*n^(1-alp)+(1-del)*exp(-(gam+e_a))*k(-1);
[name='NC eq. (19), money market condition']
P*c = m;
[name='NC eq. (20), credit market equilibrium condition']
m-1+d = l;
[name='Definition TFP shock']
e = exp(e_a);
[name='Implied by NC eq. (18), production function']
y = k(-1)^alp*n^(1-alp)*exp(-alp*(gam+e_a));
[name='Observation equation GDP growth']
gy_obs = dA*y/y(-1);
[name='Observation equation price level']
gp_obs = (P/P(-1))*m(-1)/dA;
end;
@ -84,12 +122,12 @@ steady_state_model;
m = mst;
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 = psi*mst^2/( (1-alp)*(1-psi)*bet*gst^alp*khst^alp );
nust = phi*mst^2/( (1-alp)*(1-phi)*bet*gst^alp*khst^alp );
n = xist/(nust+xist);
P = xist + nust;
k = khst*n;
l = psi*mst*n/( (1-psi)*(1-n) );
l = phi*mst*n/( (1-phi)*(1-n) );
c = mst/P;
d = l - mst + 1;
y = k^alp*n^(1-alp)*gst^alp;
@ -104,17 +142,18 @@ steady_state_model;
gy_obs = dA;
end;
steady;
steady;
check;
% Table 1 of Schorfheide (2000)
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, 0.100;
psi, beta_pdf, 0.65, 0.05;
rho, beta_pdf, 0.129, 0.223;
phi, 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;
@ -122,14 +161,8 @@ end;
varobs gp_obs gy_obs;
estimation(order=1, datafile=fsdat_simul, nobs=192, loglinear, mh_replic=2000, mh_nblocks=2, mh_jscale=0.8, mode_check);
estimation(order=1, datafile=fs2000_data, loglinear,logdata, mh_replic=2000, mh_nblocks=2, mh_jscale=0.8, mode_check);
/*
* The following lines were used to generate the data file. If you want to
* generate another random data file, comment the "estimation" line and uncomment
* the following lines.
*/
//stoch_simul(periods=200, order=1);
//datatomfile('fsdat_simul', {'gy_obs', 'gp_obs'});
%uncomment the following lines to generate LaTeX-code of the model equations
%write_latex_original_model(write_equation_tags);
%collect_latex_files;

215
examples/fs2000_data.m Normal file
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@ -0,0 +1,215 @@
%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.
%http://dx.doi.org/10.15456/jae.2022314.0708799949
% Copyright: 2000-2022 Frank Schorfheide
% Copyright: 2023 Dynare Team
% License: CC BY 4.0
% (https://creativecommons.org/licenses/by/4.0/legalcode)
% Time series, extracted 05/04/00
% columms are quarterly data from 1949:IV to 1997:IV
% 1: GDPD = GROSS DOMESTIC PRODUCT:IMPLICIT PRICE DEFLATOR (INDEX,92=100)(T7.1)
% 2: GDPQ = GROSS DOMESTIC PRODUCT
% 3: GPOP = POPULATION, NIPA basis (THOUS.,NSA)
data_q=[18.02 1474.5 150.2
17.94 1538.2 150.9
18.01 1584.5 151.4
18.42 1644.1 152
18.73 1678.6 152.7
19.46 1693.1 153.3
19.55 1724 153.9
19.56 1758.2 154.7
19.79 1760.6 155.4
19.77 1779.2 156
19.82 1778.8 156.6
20.03 1790.9 157.3
20.12 1846 158
20.1 1882.6 158.6
20.14 1897.3 159.2
20.22 1887.4 160
20.27 1858.2 160.7
20.34 1849.9 161.4
20.39 1848.5 162
20.42 1868.9 162.8
20.47 1905.6 163.6
20.56 1959.6 164.3
20.62 1994.4 164.9
20.78 2020.1 165.7
21 2030.5 166.5
21.2 2023.6 167.2
21.33 2037.7 167.9
21.62 2033.4 168.7
21.71 2066.2 169.5
22.01 2077.5 170.2
22.15 2071.9 170.9
22.27 2094 171.7
22.29 2070.8 172.5
22.56 2012.6 173.1
22.64 2024.7 173.8
22.77 2072.3 174.5
22.88 2120.6 175.3
22.92 2165 176.045
22.91 2223.3 176.727
22.94 2221.4 177.481
23.03 2230.95 178.268
23.13 2279.22 179.694
23.22 2265.48 180.335
23.32 2268.29 181.094
23.4 2238.57 181.915
23.45 2251.68 182.634
23.51 2292.02 183.337
23.56 2332.61 184.103
23.63 2381.01 184.894
23.75 2422.59 185.553
23.81 2448.01 186.203
23.87 2471.86 186.926
23.94 2476.67 187.68
24 2508.7 188.299
24.07 2538.05 188.906
24.12 2586.26 189.631
24.29 2604.62 190.362
24.35 2666.69 190.954
24.41 2697.54 191.56
24.52 2729.63 192.256
24.64 2739.75 192.938
24.77 2808.88 193.467
24.88 2846.34 193.994
25.01 2898.79 194.647
25.17 2970.48 195.279
25.32 3042.35 195.763
25.53 3055.53 196.277
25.79 3076.51 196.877
26.02 3102.36 197.481
26.14 3127.15 197.967
26.31 3129.53 198.455
26.6 3154.19 199.012
26.9 3177.98 199.572
27.21 3236.18 199.995
27.49 3292.07 200.452
27.75 3316.11 200.997
28.12 3331.22 201.538
28.39 3381.86 201.955
28.73 3390.23 202.419
29.14 3409.65 202.986
29.51 3392.6 203.584
29.94 3386.49 204.086
30.36 3391.61 204.721
30.61 3422.95 205.419
31.02 3389.36 206.13
31.5 3481.4 206.763
31.93 3500.95 207.362
32.27 3523.8 208
32.54 3533.79 208.642
33.02 3604.73 209.142
33.2 3687.9 209.637
33.49 3726.18 210.181
33.95 3790.44 210.737
34.36 3892.22 211.192
34.94 3919.01 211.663
35.61 3907.08 212.191
36.29 3947.11 212.708
37.01 3908.15 213.144
37.79 3922.57 213.602
38.96 3879.98 214.147
40.13 3854.13 214.7
41.05 3800.93 215.135
41.66 3835.21 215.652
42.41 3907.02 216.289
43.19 3952.48 216.848
43.69 4044.59 217.314
44.15 4072.19 217.776
44.77 4088.49 218.338
45.57 4126.39 218.917
46.32 4176.28 219.427
47.07 4260.08 219.956
47.66 4329.46 220.573
48.63 4328.33 221.201
49.42 4345.51 221.719
50.41 4510.73 222.281
51.27 4552.14 222.933
52.35 4603.65 223.583
53.51 4605.65 224.152
54.65 4615.64 224.737
55.82 4644.93 225.418
56.92 4656.23 226.117
58.18 4678.96 226.754
59.55 4566.62 227.389
61.01 4562.25 228.07
62.59 4651.86 228.689
64.15 4739.16 229.155
65.37 4696.82 229.674
66.65 4753.02 230.301
67.87 4693.76 230.903
68.86 4615.89 231.395
69.72 4634.88 231.906
70.66 4612.08 232.498
71.44 4618.26 233.074
72.08 4662.97 233.546
72.83 4763.57 234.028
73.48 4849 234.603
74.19 4939.23 235.153
75.02 5053.56 235.605
75.58 5132.87 236.082
76.25 5170.34 236.657
76.81 5203.68 237.232
77.63 5257.26 237.673
78.25 5283.73 238.176
78.76 5359.6 238.789
79.45 5393.57 239.387
79.81 5460.83 239.861
80.22 5466.95 240.368
80.84 5496.29 240.962
81.45 5526.77 241.539
82.09 5561.8 242.009
82.68 5618 242.52
83.33 5667.39 243.12
84.09 5750.57 243.721
84.67 5785.29 244.208
85.56 5844.05 244.716
86.66 5878.7 245.354
87.44 5952.83 245.966
88.45 6010.96 246.46
89.39 6055.61 247.017
90.13 6087.96 247.698
90.88 6093.51 248.374
92 6152.59 248.928
93.18 6171.57 249.564
94.14 6142.1 250.299
95.11 6078.96 251.031
96.27 6047.49 251.65
97 6074.66 252.295
97.7 6090.14 253.033
98.31 6105.25 253.743
99.13 6175.69 254.338
99.79 6214.22 255.032
100.17 6260.74 255.815
100.88 6327.12 256.543
101.84 6327.93 257.151
102.35 6359.9 257.785
102.83 6393.5 258.516
103.51 6476.86 259.191
104.13 6524.5 259.738
104.71 6600.31 260.351
105.39 6629.47 261.04
106.09 6688.61 261.692
106.75 6717.46 262.236
107.24 6724.2 262.847
107.75 6779.53 263.527
108.29 6825.8 264.169
108.91 6882 264.681
109.24 6983.91 265.258
109.74 7020 265.887
110.23 7093.12 266.491
111 7166.68 266.987
111.43 7236.5 267.545
111.76 7311.24 268.171
112.08 7364.63 268.815];
%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));
gp_obs = diff(log(data_q(:,1))); %GDP deflator inflation

5
license.txt
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@ -245,6 +245,11 @@ Copyright: 2005-2010 Pascal Getreuer
2017 Dynare Team
License: BSD-2-clause
Files: examples/fs2000_data.m
Copyright: 2000-2022 Frank Schorfheide
Copyright: 2023 Dynare Team
License: CC-BY-SA-4.0
Files: doc/*.rst doc/*.tex doc/*.svg doc/*.pdf doc/*.bib
Copyright: 1996-2022 Dynare Team
License: GFDL-NIV-1.3+