Dear professors,

I am a beginner in the study of New Keynesian models. I recently discovered this tool (Dynare) and I am trying to use it along with Octave.

I would like to know if Dynare is capable of estimating coefficients and unobservable variables present in the semi-structural model presented in the link below:

ri202112b7p.pdf (bcb.gov.br)

Unfortunately, the text is in Portuguese. The idea is that the model consists of 5 equations containing observable variables, unobservable variables, and coefficients. The author claims to estimate the coefficients and unobservable variables using Bayesian methods and the Kalman filter. Before you ask, I cannot contact the author. He does not respond to me.

I am going in circles. Could someone help me?

Is there any Dynare and semi-structural model course for beginners?

Are there any courses on how to build Bayesian algorithms and Kalman filters?

Thank you in advance for any assistance you can provide.

Best regards

Yes, Dynare does Bayesian estimation with a Kalman filter. See e.g.

Thank you very much, professor, it helped a lot.

I saw on the Dynare website that there are summer courses about the package. I live in Latin America. Could I be a student in the course? If yes, how can I register?

Unfortunately, the deadline for the Dynare summer school has already passed.

I am trying to simulate a semi-structural model proposed by the IMF. The parameters are fixed (they have already been estimated - I just copied them) and I tried to find suitable initial values to solve it. When I run the model in Dynare on Octave, the following error appears:

DYNARE_SOLVE (solve_algo=2|4): the Dulmage-Mendelsohn decomposition returned a non-square block. This means that the Jacobian is s

ingular. You may want to try another value for solve_algo.

error: Impossible to find the steady state (the sum of squared residuals of the static equations is 2.2661). Either the model does

n’t have a steady state, there are an infinity of steady states, or the guess values are too far from the solution

error: called from

print_info at line 33 column 5

stoch_simul at line 119 column 5

driver at line 1022 column 27

dynare at line 310 column 5

I am a beginner in this area. I can’t find my mistake. Could someone help me?

The content of the .mod file is as follows:

```
var L_GDP
L_GDP_GAP
L_GDP_BAR
DLA_GDP_BAR
MCI
L_CPI
DLA_CPI
E_DLA_CPI
D4L_CPI
D4L_CPI_TAR
RMC
RS
RSNEUTRAL
RR
RR_GAP
RR_BAR
L_S
PREM
L_Z
L_Z_GAP
L_Z_BAR
DLA_Z_BAR
L_GDP_RW_GAP
RS_RW
RR_RW_BAR
L_CPI_RW
DLA_CPI_RW
;
varexo SHK_L_GDP_GAP
SHK_DLA_CPI
SHK_L_S
SHK_RS
SHK_RR_BAR
SHK_DLA_Z_BAR
SHK_DLA_GDP_BAR
SHK_D4L_CPI_TAR
SHK_L_GDP_RW_GAP
SHK_RS_RW
SHK_DLA_CPI_RW
SHK_RR_RW_BAR
;
parameters b1
b2
b3
b4
a1
a2
a3
e1
g1
g2
g3
rho_D4L_CPI_TAR
rho_DLA_Z_BAR
rho_RR_BAR
rho_DLA_GDP_BAR
rho_L_GDP_RW_GAP
rho_RS_RW
rho_DLA_CPI_RW
rho_RR_RW_BAR
ss_D4L_CPI_TAR
ss_DLA_Z_BAR
ss_RR_BAR
ss_DLA_GDP_BAR
ss_DLA_CPI_RW
ss_RR_RW_BAR
;
b1 = 0.8;
b2 = 0.3;
b3 = 0.5;
b4 = 0.7;
a1 = 0.7;
a2 = 0.2;
a3 = 0.7;
e1 = 0.4;
g1 = 0.7;
g2 = 0.5;
g3 = 0.5;
rho_D4L_CPI_TAR = 0.5;
rho_DLA_Z_BAR = 0.8;
rho_RR_BAR = 0.8;
rho_DLA_GDP_BAR = 0.8;
rho_L_GDP_RW_GAP = 0.8;
rho_RS_RW = 0.8;
rho_DLA_CPI_RW = 0.8;
rho_RR_RW_BAR = 0.8;
ss_D4L_CPI_TAR = 2;
ss_DLA_Z_BAR = -1.5;
ss_RR_BAR = 0.5;
ss_DLA_GDP_BAR = 2.5;
ss_DLA_CPI_RW = 2;
ss_RR_RW_BAR = 0.75;
model;
L_GDP_GAP = b1*L_GDP_GAP(-1) - b2*MCI + b3*L_GDP_RW_GAP + SHK_L_GDP_GAP;
MCI = b4*RR_GAP + (1-b4)*(-L_Z_GAP);
DLA_CPI = a1*DLA_CPI(-1) + (1-a1)*DLA_CPI(+1) + a2*RMC + SHK_DLA_CPI;
RMC = a3*L_GDP_GAP + (1-a3)*L_Z_GAP;
E_DLA_CPI = DLA_CPI(+1);
RS = g1*RS(-1) + (1-g1)*(RSNEUTRAL + g2*(D4L_CPI(+4) - D4L_CPI_TAR(+4)) + g3*L_GDP_GAP) + SHK_RS;
RSNEUTRAL = RR_BAR + D4L_CPI(+1);
L_S = (1-e1)*L_S(+1) + e1*(L_S(-1) + 2/4*(D4L_CPI_TAR - ss_DLA_CPI_RW + DLA_Z_BAR)) + (-RS + RS_RW + PREM)/4 + SHK_L_S;
RR = RS - D4L_CPI(+1);
L_Z = L_S + L_CPI_RW - L_CPI;
L_CPI = L_CPI(-1) + DLA_CPI/4;
L_Z_BAR = L_Z_BAR(-1) + DLA_Z_BAR/4;
D4L_CPI = L_CPI - L_CPI(-4);
L_GDP_BAR = L_GDP_BAR(-1) + DLA_GDP_BAR/4;
L_GDP = L_GDP_GAP + L_GDP_BAR;
RR = RR_BAR + RR_GAP;
L_Z = L_Z_GAP + L_Z_BAR;
DLA_GDP_BAR = rho_DLA_GDP_BAR*DLA_GDP_BAR(-1) + (1-rho_DLA_GDP_BAR)*ss_DLA_GDP_BAR + SHK_DLA_GDP_BAR;
D4L_CPI_TAR = rho_D4L_CPI_TAR*D4L_CPI_TAR(-1) + (1-rho_D4L_CPI_TAR)*ss_D4L_CPI_TAR + SHK_D4L_CPI_TAR;
DLA_Z_BAR = rho_DLA_Z_BAR*DLA_Z_BAR(-1) + (1-rho_DLA_Z_BAR)*ss_DLA_Z_BAR + SHK_DLA_Z_BAR;
RR_BAR = rho_RR_BAR*RR_BAR(-1) + (1-rho_RR_BAR)*ss_RR_BAR + SHK_RR_BAR;
DLA_Z_BAR(+1) = RR_BAR - RR_RW_BAR - PREM;
L_GDP_RW_GAP = rho_L_GDP_RW_GAP*L_GDP_RW_GAP(-1) + SHK_L_GDP_RW_GAP;
RS_RW = rho_RS_RW*RS_RW(-1) + (1-rho_RS_RW)*(RR_RW_BAR + DLA_CPI_RW) + SHK_RS_RW;
DLA_CPI_RW = rho_DLA_CPI_RW*DLA_CPI_RW(-1) + (1-rho_DLA_CPI_RW)*ss_DLA_CPI_RW + SHK_DLA_CPI_RW;
RR_RW_BAR = rho_RR_RW_BAR*RR_RW_BAR(-1) + (1-rho_RR_RW_BAR)*ss_RR_RW_BAR + SHK_RR_RW_BAR;
L_CPI_RW = L_CPI_RW(-1) + DLA_CPI_RW/4;
end;
initval;
L_GDP = 0;
L_GDP_GAP = 0;
L_GDP_BAR = ss_DLA_GDP_BAR/4;
DLA_GDP_BAR = ss_DLA_GDP_BAR;
DLA_CPI = 0;
L_CPI = 0;
D4L_CPI_TAR = ss_D4L_CPI_TAR;
RR = ss_RR_BAR;
RS = ss_RR_BAR;
D4L_CPI = 0;
RR_GAP = 0;
RR_BAR = ss_RR_BAR;
L_S = e1*(2/4*(ss_D4L_CPI_TAR - ss_DLA_CPI_RW + ss_DLA_Z_BAR)) + (-ss_RR_BAR + (1-rho_RS_RW)*(ss_RR_RW_BAR + ss_DLA_CPI_RW) + ss_RR_BAR - ss_RR_RW_BAR - ss_DLA_Z_BAR)/4;
L_Z = e1*(2/4*(ss_D4L_CPI_TAR - ss_DLA_CPI_RW + ss_DLA_Z_BAR)) + (-ss_RR_BAR + (1-rho_RS_RW)*(ss_RR_RW_BAR + ss_DLA_CPI_RW) + ss_RR_BAR - ss_RR_RW_BAR - ss_DLA_Z_BAR)/4 + ss_DLA_CPI_RW/4;
L_Z_GAP = 0;
L_Z_BAR = ss_DLA_Z_BAR/4;
L_Z = ss_DLA_Z_BAR/4;
PREM = ss_RR_BAR - ss_RR_RW_BAR - ss_DLA_Z_BAR;
DLA_Z_BAR = ss_DLA_Z_BAR;
RS_RW = (1-rho_RS_RW)*(ss_RR_RW_BAR + ss_DLA_CPI_RW);
L_GDP_RW_GAP = 0;
RR_RW_BAR = ss_RR_RW_BAR;
DLA_CPI_RW = ss_DLA_CPI_RW;
MCI = 0;
RMC = 0;
E_DLA_CPI = 0;
RSNEUTRAL = ss_RR_BAR;
D4L_CPI = 0;
L_CPI_RW = ss_DLA_CPI_RW/4;
end;
shocks;
var SHK_L_GDP_GAP; stderr 1;
var SHK_DLA_CPI; stderr 1;
var SHK_L_S; stderr 1;
var SHK_RS; stderr 1;
var SHK_RR_BAR; stderr 1;
var SHK_DLA_Z_BAR; stderr 1;
var SHK_DLA_GDP_BAR; stderr 1;
var SHK_D4L_CPI_TAR; stderr 1;
var SHK_L_GDP_RW_GAP; stderr 1;
var SHK_RS_RW; stderr 1;
var SHK_DLA_CPI_RW; stderr 1;
var SHK_RR_RW_BAR; stderr 1;
end;
stoch_simul(order=1,irf=20) L_CPI;
```

It seems your model has one or more unit roots. In that case, there are infinitely many steady states and they cannot be endogenously computed. Please provide an analytical steady state.

Thank you very much, professor, for the response. You are helping me a lot to understand this new world I am studying. In order to better understand the subject, could you please provide me with an example of a model with one or more unit root that contains the mathematical expressions of the analytical steady state?

Equations like

look like a unit root with drift. If `DLA_CPI=0`

, any value for `L_CPI`

would be a steady state. If `DLA_CPI`

is different from 0, no steady state will exist.