Model Solve - smooth transition from historical to forecast?

[gg_pse]

I am fairly new to eviews and would appreciate any help on this topic. I have a system of equations in the MODEL object that I am trying to solve simultaneously and create forecasts of. The problem is that for the starting value of the forecast of a given endogenous variable there is an anomalous dip which throws off the entire series and subsequently all the other variables that are dependent on it. For example a variable showing population growth which has historical data till 2011, suddenly turns negative in 2012. I am trying to figure out how this first forecasted value for an endogenous variable is created, and how I can modify it? Is there a way to use add factors to get a smooth transition from historical data to forecast?

The simulation type I am using is deterministic (dynamic solution) and the solver is set to Preferred solution starting values - "Actuals" and Forward Solution "User supplied in Actuals".


I would greatly appreciate any help. Thanks.

[EViews Gareth]

Hard to say without knowing more about the specification of the model/equations

[gg_pse]

I am attaching 2 txt files here. The first has all the text view of the entire model. The second has the equations defined which do not display in the text view in the first file.
Thanks

[EViews Gareth]

Could you post the workfile?

[gg_pse]

Unfortunately I can't post the workfile because it has forecast data from a third party that is proprietary. I was wondering if Icould get some ideas on how to proceed, based on the equations and Solve properties of my model that I have posted.

Currently if I set the scenario to "Baseline" it shows bad values in the first period of forecasts leadig to a sharp dip in every forecasted variable. If I change the settings to "Actual" and check "Exclude for periods where Actuals exist", then I get the forecast to be a straight line where the last historical value is repeated throughout the entire forecast period.

[EViews Gareth]

What happens if you do a solo forecast from the equation, rather than using the model object?

[gg_pse]

In that case it creates forecasted values over the historical period, but cannot forecast out in the future since the independent variables also do not have values in the future periods.

[EViews Chris]

It's very hard to give any specific advice.

If your model is producing forecasts that you don't like, you can either:
1) change the equations of the model
2) change the forecasted future paths of any exogenous variables
3) include 'add factors' in the model (really just exogenous variables with a special purpose) that reflect tweaks to the model that reflect your judgement as to why the model is not adequately matching up to reality

If you think a particular equation seems to be the cause of the problems, you could verify that by dropping the equation from the model and temporarily treating the endogenous variable of the equation as an exogenous variable and then entering a future path for that variable by hand. If that makes everything in the forecast look sensible, then you've narrowed down the problem to the equation that has been dropped and you can try to investigate further why it is forecasting poorly. That might give you somewhere to start.

[gg_pse]

thank you, i will give these a try