Enhancing the Model Object Functionality - updated list

[tvonbrasch]

Thank you for the great work on improving the model object in EViews. There are some important functionalities that should be added:

Optimal policy: It should be possible to run optimal policy experiments where the simulations determine the paths of one or more instrument variables that minimize the value of a specified loss function (see, for example, viewtopic.php?f=10&t=21565 and viewtopic.php?p=70635&hilit=filter#p70635)

Improved algorithm for solving forward-looking models: The current algorithm does not yet include some of the special handling found in the FRB/US implementation—most notably for linear rational expectations models with a maximum lead of +1.

Built-in Feature for Estimating Polynomial Adjustment Cost (PAC): PAC models are dynamic adjustment models that specify how agents gradually adjust a decision variable, such as investment or prices, toward a target, while minimizing both deviations from the target and the costs of changing the variable and its growth rates. The PAC methodology is now widely used in leading policy models, e.g. the Federal Reserve Board’s FRB/US model and the European Central Bank’s ECB-BASE and ECB-(RE)BASE models: viewtopic.php?t=22000

Scenario gap decomposition: Create a routine that attribute differences between a counterfactual and a baseline scenario for selected endogenous targets to specific drivers, covering both exogenous variables and add-factors. For instance, within a macroeconomic model, the routine could rapidly quantify how much of a change in the interest rate is driven by international price impulses, international demand, or shifts in public consumption: viewtopic.php?p=71752#p71752

Keep up the great work!