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Hi everyone. I am estimating SVAR with exogenous variable using model. However, the model solution does not forecast the model over the workfile range and gives the following error message:
Sample: 1976Q1 2028Q4
Solve Options:
Dynamic-Deterministic Simulation
Solver: Broyden
Max iterations = 5000, Convergence = 1e-08

Scenario: Baseline
Solve begin 21:19:04
2020Q2 NA generated for LNEXP
Solve terminated - Unable to compute due to missing data in "LNEXP = @COEF(1) * LNEXP(-1) + @COEF(2) * LNEXP(-2) + @COEF(3) ...

Further, I have used lags of exogenous variable on the right side of the equation and the data set does not contain any missing value. I need help over how to solve the model for the forecasted period. Thanks in advance!

Hard to say without having the workfile.

You have debt as an exogenous variable, and have no data for debt during those solution periods.

You have debt as an exogenous variable, and have no data for debt during those solution periods.

Thank you for the reply. Yes, I used debt as an identity and added it into the model as :
m_baseline.append debt_0 = (1+ir_0)/(1+inf_0)/(1+dy)*debt_0(-1) - (lnexp_0-lntax_0)/lngdp
where all the variables are endogenous and for the left out exogenous variable dy I added values, still the model solution does not forecast and gives the following error message:

Unable to compute due to missing data in "DEBT_0 =
(1+IR_0)/(1+INF_0)/(1+DY)*DEBT_0(-1) - (LNEXP_0-LNTAX_0)
/LNGDP" in "M_BASELINE.SOLVE" on line 13.

The work file is attached. Please suggest me how to solve this issue. Thank you so much