Forecasting issue in SVAR with Exogenous variable

[essa]

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!

[EViews Gareth]

Hard to say without having the workfile.

[essa]

Hard to say without having the workfile.

[EViews Gareth]

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

[essa]

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