CGE-Core v0.6 ↔ GAMS workflow crosswalk#
This is a practitioner-intuition and design-sanity aid, not a requirement that Python imitate GAMS. A public operation should have either a recognizable GAMS counterpart or a short explanation of why the Python object model improves on the serial GAMS discipline.
CGE-Core v0.6 |
GAMS idiom |
Manual discipline automated |
|---|---|---|
|
sets/data/parameters/equations declared before solve |
Configures the static economy and its data source. |
|
|
Applies the Hosoe closure, solves the SAM-replicating benchmark, and protects it behind an |
|
benchmark |
Makes the benchmark structurally read-only at the public API. |
|
begin/reset an experiment block |
Creates an isolated counterfactual without manual reset bookkeeping. |
|
parameter assignment; for a Var, |
Applies a scenario shock. |
|
release a Var previously fixed in the experiment |
Releases only a Var fixed earlier by this Scenario; this is not a general GEMPACK-style closure swap. |
|
second |
Solves the counterfactual and returns an immutable snapshot. |
|
|
Reads a solved level without traversing the live model. |
|
hand-built report table |
Computes |
multiple live |
no direct serial-script equivalent without manual state management |
Python object ownership keeps counterfactuals simultaneously live and isolated. |
Terminology layer rule#
benchmark: the SAM-replicating static equilibrium;
scenario / counterfactual / experiment: a static policy solve derived from that benchmark;
baseline: reserved for a reference path in dynamic/forecast contexts rather than the static benchmark solve.