Dear all, i’m doing the replication of the paper “Shadow Banking & Financial Regulation” by Fevé 2019. The authors have defined some equations inside the model such that three shocks are endogeneous: epsilonm (shock to labour market), epsilon (shock to loans) and epsilond (shock to household deposits).
As consequence of that, i could simulate the model, as you can see in the dynare code, but i couldn’t estimate the parameters on the bayesian mode.
My question are:
- Dynare offers or not an alternative method to estimate a (bayesian) dsge with endogeneous shocks?
- The authors were fitting the bayesian model with dynare following the parameters described in table 2 and 3 of the paper; but i don’t know if they were assuming the endogeneous shocks as state variables. On the stoch simulation i had a singularity problem, that could be the problem for the bayesian estimation?
I appreciate any advice to manage this kind of endogeneous structures. Thanks a lot!
test.mod (7.0 KB)
>> dynare test.mod
Starting Dynare (version 5.4).
Calling Dynare with arguments: none
Starting preprocessing of the model file ...
Found 26 equation(s).
Evaluating expressions...done
Computing static model derivatives (order 1).
Computing dynamic model derivatives (order 1).
Processing outputs ...
done
Preprocessing completed.
MODEL_DIAGNOSTICS: The Jacobian of the static model is singular
MODEL_DIAGNOSTICS: there is 1 colinear relationships between the variables and the equations
Colinear variables:
x
f
k
h
w
ll
ii
s
rk
c
aabs
n
d
pi_b
pi_s
costx
ra
rd
Colinear equations
2 3 4 8 9 10 17 18 19 20
MODEL_DIAGNOSTICS: The singularity seems to be (partly) caused by the presence of a unit root
MODEL_DIAGNOSTICS: as the absolute value of one eigenvalue is in the range of +-1e-6 to 1.
MODEL_DIAGNOSTICS: If the model is actually supposed to feature unit root behavior, such a warning is expected,
MODEL_DIAGNOSTICS: but you should nevertheless check whether there is an additional singularity problem.
MODEL_DIAGNOSTICS: The presence of a singularity problem typically indicates that there is one
MODEL_DIAGNOSTICS: redundant equation entered in the model block, while another non-redundant equation
MODEL_DIAGNOSTICS: is missing. The problem often derives from Walras Law.
Residuals of the static equations:
Equation number 1 : 0 : f
Equation number 2 : 0 : 2
Equation number 3 : 0 : 3
Equation number 4 : 0 : k
Equation number 5 : 0 : 5
Equation number 6 : 0 : x
Equation number 7 : 0 : costx
Equation number 8 : 0 : pi_b
Equation number 9 : 0 : 9
Equation number 10 : 0 : pi_s
Equation number 11 : 0 : lambda
Equation number 12 : 0 : 12
Equation number 13 : 0 : 13
Equation number 14 : 0 : 14
Equation number 15 : 0 : 15
Equation number 16 : 3.687e-07 : 16
Equation number 17 : 0 : 17
Equation number 18 : 0 : 18
Equation number 19 : 0 : q
Equation number 20 : 0 : 20
Equation number 21 : 0 : 21
Equation number 22 : 0 : 22
Equation number 23 : 0 : 23
Equation number 24 : 0 : 24
Equation number 25 : 0 : 25
Equation number 26 : 0 : epsilona
MODEL SUMMARY
Number of variables: 26
Number of stochastic shocks: 6
Number of state variables: 14
Number of jumpers: 7
Number of static variables: 9
MATRIX OF COVARIANCE OF EXOGENOUS SHOCKS
Variables shockz shockl shocka shockd shockm shocki
shockz 0.000100 0.000000 0.000000 0.000000 0.000000 0.000000
shockl 0.000000 0.000100 0.000000 0.000000 0.000000 0.000000
shocka 0.000000 0.000000 0.000100 0.000000 0.000000 0.000000
shockd 0.000000 0.000000 0.000000 0.000100 0.000000 0.000000
shockm 0.000000 0.000000 0.000000 0.000000 0.000100 0.000000
shocki 0.000000 0.000000 0.000000 0.000000 0.000000 0.000100
POLICY AND TRANSITION FUNCTIONS
c f k h rd rk ra
Constant 0.325569 0.439243 1.351351 0.250000 0 0.108563 0
k(-1) 0.068726 0.112429 1.030074 0.003304 0.016834 -0.052549 0.220324
ll(-1) 0.069706 -0.023764 -0.158466 -0.020309 -0.087833 -0.005873 -0.354305
epsilonz(-1) 0.065460 0.290494 0.180771 0.023030 0.031512 0.071799 0.018449
epsilonl(-1) 0.107207 -0.016371 -0.412085 -0.013990 -0.558934 -0.004046 -0.529156
epsilona(-1) 0 0 0 0 0 0 0.600000
epsilond(-1) -0.049344 0.014229 -0.109943 0.012160 0.011487 0.003517 0.019431
epsiloni(-1) -0.112506 0.025577 0.056617 0.021858 0.287450 0.006322 0.283359
h(-1) 0.174384 0.773877 0.481573 0.661353 0.083947 0.191272 0.049148
epsilonm(-1) -0.002207 -0.005789 -0.002777 -0.004947 -0.001477 -0.001431 -0.001276
shockz 0.109099 0.484157 0.301284 0.038384 0.052519 0.119664 0.030748
shockl 0.014111 -0.002155 -0.054240 -0.001841 -0.073569 -0.000533 -0.069649
shocka 0 0 0 0 0 0 1.000000
shockd -0.007908 0.002280 -0.017620 0.001949 0.001841 0.000564 0.003114
shockm -0.042032 -0.110264 -0.052888 -0.094231 -0.028129 -0.027253 -0.024307
shocki -0.187510 0.042629 0.094361 0.036430 0.479083 0.010536 0.472265
MOMENTS OF SIMULATED VARIABLES
VARIABLE MEAN STD. DEV. VARIANCE SKEWNESS KURTOSIS
c 0.325546 0.003947 0.000016 0.208570 -0.132038
f 0.439234 0.008084 0.000065 0.094046 -0.331300
k 1.351108 0.017536 0.000308 -0.074628 -0.385568
h 0.249734 0.002471 0.000006 -0.052040 -0.525197
rd -0.000083 0.006163 0.000038 0.016972 -0.214100
rk 0.108584 0.001777 0.000003 0.034912 -0.063291
ra 0.001719 0.013117 0.000172 0.022846 -0.196848
CORRELATION OF SIMULATED VARIABLES
VARIABLE c f k h rd rk ra
c 1.0000 0.6544 0.7192 0.3411 -0.5595 0.1873 -0.2615
f 0.6544 1.0000 0.6954 0.6786 0.1647 0.7262 0.0276
k 0.7192 0.6954 1.0000 0.4213 0.0698 0.0133 -0.0332
h 0.3411 0.6786 0.4213 1.0000 0.2950 0.5475 0.0976
rd -0.5595 0.1647 0.0698 0.2950 1.0000 0.2185 0.3772
rk 0.1873 0.7262 0.0133 0.5475 0.2185 1.0000 0.0871
ra -0.2615 0.0276 -0.0332 0.0976 0.3772 0.0871 1.0000
AUTOCORRELATION OF SIMULATED VARIABLES
VARIABLE 1 2 3 4 5
c 0.7913 0.6353 0.5106 0.4003 0.3128
f 0.7414 0.5293 0.3680 0.2393 0.2107
k 0.9643 0.8910 0.7984 0.7010 0.6075
h 0.8683 0.6590 0.4576 0.2940 0.1873
rd 0.6096 0.3834 0.2082 0.1112 0.0161
rk 0.6171 0.3273 0.1240 -0.0203 -0.0091
ra 0.5951 0.2615 0.1179 0.0458 -0.0280
VARIANCE DECOMPOSITION SIMULATING ONE SHOCK AT A TIME (in percent)
shockz shockl shocka shockd shockm shocki Tot. lin. contr.
c 52.35 0.82 0.00 0.11 12.91 31.16 97.35
f 79.44 0.09 0.00 0.00 12.40 2.99 94.92
k 67.77 2.76 0.00 0.11 14.64 11.76 97.03
h 12.25 0.20 0.00 0.06 71.14 11.22 94.87
rd 2.94 2.57 0.00 0.01 0.68 92.88 99.08
rk 81.88 1.04 0.00 0.07 9.34 2.83 95.15
ra 1.98 0.48 86.50 0.01 0.42 19.27 108.66
Note: numbers do not add up to 100 due to non-zero correlation of simulated shocks in small samples
Total computing time : 0h00m16s