Hi everyone,
I am evaluating the effects of the different monetary policies on the households’ and entrepreneurs’ value functions in my two sector model. To do this I ran the code by taking second approximations to the value functions. However, I have some problems with this.
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It takes too long (1 hour on average) to run the code when I do the 2nd order approximations to the value functions compared to 14 seconds when I do the first order approximation.
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For some values of m, the parameter in front of the borrowing constraint, dynare is not able to calculate autocorrelation, correlation, variance, or mean for the both value functions. However, I do not have any problem when I run the code with first order approximation of the variables. In any scenario the model converges to true steady state but there is only problem with var-covariance matrix and correlations and means.
I did some research and the only information I get as to why this problem might occur is that this is caused by non-stationarity of the
resulting decision rule. I do not need to know autocorrelation, var, covar, etc. of those variables that are approximated by second order, however the problem I am facing is weird anyway.
I am wondering if anyone had any experience with a situation similar to what I described above.
Any help is greatly appreciated.
Thanks in advance.
This is how dynare output looks like ( ve: the value function of the entrepreneurs). At the very end you will see that the mean, std dev, etc. of the value function is not defined.
STEADY-STATE RESULTS:
mu 0.84069
ce -0.84069
lambda -3.76448
gint 1.0101
ginf 1
q -0.0731779
y 1.30886
x 0.154151
ke 4.48104
l -0.253566
w 1.00779
be 4.11013
a 0
c 1.51492
k 2.45729
fk 0.245729
z 1.60553
pnew 0
pb 3.64439
pa 4.25179
xss 0.154151
yss 1.30882
kess 4.481
lss -0.2536
kss 2.45763
fkss 0.245763
zss 1.60551
ue -0.84069
ve -42.0345
EIGENVALUES:
Modulus Real Imaginary
4.476e-016 4.476e-016 0
9.073e-016 -9.073e-016 0
8.628e-009 -2.192e-015 8.628e-009
8.628e-009 -2.192e-015 -8.628e-009
0.8063 0.8063 0
0.95 0.95 0
1.014 1.014 0
1.02 1.02 9.835e-009
1.02 1.02 -9.835e-009
1.347 1.347 0
1.417 1.253 0.6628
1.417 1.253 -0.6628
Inf Inf 0
Inf Inf 0
Inf Inf 0
There are 9 eigenvalue(s) larger than 1 in modulus
for 9 forward-looking variable(s)
The rank condition is verified.
MODEL SUMMARY
Number of variables: 29
Number of stochastic shocks: 2
Number of state variables: 6
Number of jumpers: 9
Number of static variables: 14
MATRIX OF COVARIANCE OF EXOGENOUS SHOCKS
Variables eps epsm
eps 0.000074 0.000000
epsm 0.000000 0.000074
POLICY AND TRANSITION FUNCTIONS
ke k l q fk y z be ginf
Constant 4.481044 2.457291 -0.253566 -0.073178 0.245729 1.308856 1.605528 4.110134 1.000000
gint (-1) -10.407361 78.749069 -1.780409 -3.015897 0 -1.192874 -0.886648 -12.744440 -0.294715
ke (-1) 14.565943 -110.215687 2.257207 4.349435 0 1.842329 1.369380 17.965318 0.348255
be (-1) -10.512486 79.544514 -1.798393 -3.046360 0 -1.204923 -0.895604 -12.873172 -0.297692
a (-1) 7.768978 -58.785298 1.403521 3.015120 0 1.890359 1.405081 10.284924 0.184154
k (-1) 0.038475 -0.291126 -0.024002 0.021590 0.100000 -0.016081 0.013718 0.057555 -0.004131
eps 8.177872 -61.879261 1.477391 3.173811 0 1.989852 1.479032 10.826236 0.193847
epsm -8.463208 64.038302 -2.464620 -2.958880 0 -1.651295 -1.227387 -10.870077 -0.486475
MOMENTS OF SIMULATED VARIABLES (HP filter, lambda = 1600)
VARIABLE MEAN STD. DEV. VARIANCE SKEWNESS KURTOSIS
ke 4.482616 0.171177 0.029302 0.000471 -0.003151
k 2.445400 1.295243 1.677654 -0.000471 -0.003151
l -0.253263 0.034630 0.001199 0.001145 0.005314
q -0.072554 0.072996 0.005328 -0.002562 0.009921
fk 0.244541 0.129524 0.016776 -0.000501 -0.003136
y 1.309670 0.092961 0.008642 -0.003887 0.008082
z 1.605829 0.039560 0.001565 -0.003938 0.027749
be 4.112228 0.231530 0.053606 -0.000583 -0.000144
ginf 1.000010 0.004659 0.000022 0.004559 0.019301
CORRELATION OF SIMULATED VARIABLES (HP filter, lambda = 1600)
VARIABLE ke k l q fk y z be ginf
ke 1.0000 -1.0000 0.9747 0.9679 -0.8064 0.8989 0.8923 0.9968 0.3763
k -1.0000 1.0000 -0.9747 -0.9679 0.8064 -0.8989 -0.8923 -0.9968 -0.3763
l 0.9747 -0.9747 1.0000 0.9394 -0.6984 0.8299 0.8626 0.9703 0.5403
q 0.9679 -0.9679 0.9394 1.0000 -0.8246 0.9562 0.9771 0.9849 0.2498
fk -0.8064 0.8064 -0.6984 -0.8246 1.0000 -0.9391 -0.7997 -0.8178 0.1889
y 0.8989 -0.8989 0.8299 0.9562 -0.9391 1.0000 0.9574 0.9234 -0.0166
z 0.8923 -0.8923 0.8626 0.9771 -0.7997 0.9574 1.0000 0.9255 0.1297
be 0.9968 -0.9968 0.9703 0.9849 -0.8178 0.9234 0.9255 1.0000 0.3387
ginf 0.3763 -0.3763 0.5403 0.2498 0.1889 -0.0166 0.1297 0.3387 1.0000
AUTOCORRELATION OF SIMULATED VARIABLES (HP filter, lambda = 1600)
VARIABLE 1 2 3 4 5
ke 0.8064 0.6519 0.5254 0.4248 0.3435
k 0.8064 0.6519 0.5254 0.4248 0.3435
l 0.6790 0.5544 0.4489 0.3682 0.3006
q 0.8577 0.7241 0.6134 0.5234 0.4493
fk 0.8064 0.6519 0.5254 0.4248 0.3435
y 0.9181 0.7734 0.6548 0.5576 0.4782
z 0.9036 0.7943 0.7019 0.6246 0.5592
be 0.8214 0.6723 0.5498 0.4519 0.3724
ginf -0.0047 0.0086 0.0001 0.0109 0.0095
MODEL SUMMARY
Number of variables: 29
Number of stochastic shocks: 2
Number of state variables: 6
Number of jumpers: 9
Number of static variables: 14
MATRIX OF COVARIANCE OF EXOGENOUS SHOCKS
Variables eps epsm
eps 0.000074 0.000000
epsm 0.000000 0.000074
POLICY AND TRANSITION FUNCTIONS
c ce ve
Constant 1.434289 2.094342 -51.854272
(correction) -0.080635 2.935031 -9.819794
gint (-1) 0.487892 -15.380624 -75.691695
ke (-1) -0.554401 21.654871 106.065089
be (-1) 0.492820 -15.535984 -76.456257
a (-1) 0.379116 12.223465 69.888743
k (-1) 0.008637 0.067301 0.290264
eps 0.399069 12.866805 73.567098
epsm -0.109618 -13.013807 -62.058432
gint (-1),gint (-1) -20.559636 -727.990614 -5629.976881
ke (-1),gint (-1) 59.814170 1973.443426 15441.829721
ke (-1),ke (-1) -43.791968 -1323.873504 -10524.461352
be (-1),gint (-1) -41.046726 -1486.068733 -11449.382364
be (-1),ke (-1) 60.418353 1993.377198 15597.807799
be (-1),be (-1) -20.730670 -750.539764 -5782.516345
a (-1),gint (-1) 30.126793 1084.831414 8400.879073
a (-1),ke (-1) -44.274777 -1453.598765 -11439.036274
a (-1),be (-1) 30.431104 1095.789307 8485.736437
a (-1),a (-1) -11.120454 -398.818317 -3107.991244
k (-1),gint (-1) 0.168063 5.855970 43.838244
k (-1),ke (-1) -0.245318 -7.786665 -59.352158
k (-1),be (-1) 0.169761 5.915121 44.281054
k (-1),a (-1) -0.126944 -4.308191 -32.427026
k (-1),k (-1) 0.000237 -0.004677 -0.053599
eps ,eps -12.321832 -441.903952 -3443.757611
epsm,eps 25.600008 920.495212 7152.865745
epsm,epsm -12.699319 -468.310016 -3663.541431
gint (-1),eps 31.712414 1141.927804 8843.030603
gint (-1),epsm -32.519740 -1181.739080 -9149.187516
ke (-1),eps -46.605029 -1530.103963 -12041.090815
ke (-1),epsm 48.019066 1588.430627 12481.020385
be (-1),eps 32.032741 1153.462428 8932.354145
be (-1),epsm -32.848222 -1193.675838 -9241.603552
a (-1),eps -23.411482 -839.617509 -6543.139461
a (-1),epsm 24.320008 874.470451 6795.222458
k (-1),eps -0.133625 -4.534938 -34.133711
k (-1),epsm 0.151772 5.029169 36.874001
MOMENTS OF SIMULATED VARIABLES (HP filter, lambda = 1600)
VARIABLE MEAN STD. DEV. VARIANCE SKEWNESS KURTOSIS
ve NaN NaN NaN NaN NaN
CORRELATION OF SIMULATED VARIABLES (HP filter, lambda = 1600)
VARIABLE ve
ve NaN
AUTOCORRELATION OF SIMULATED VARIABLES (HP filter, lambda = 1600)
VARIABLE 1 2 3 4 5
ve NaN NaN NaN NaN NaN
Total computing time : 1h11m40s