Related:

Roadmap  

[As of June, 2021]

Gekko 3.0 was released as a stable version in the spring of 2019, and new users are advised to use versions in the 3.1.x series, which can be thought of as a “stable” development series (cf. the versions overview page). A stable version 2.4 exists, but in general, the work on the 2.x series is discontinued. Development-wise, at the moment the focus is on stabilization of the 3.1.x version, including help systems etc. If some syntax or other choices turn out to be unfortunate, this will be dealt with in a future “risky” 3.3.x development series that is not even at the drawing board yet (and may not be until 2022).

Aims regarding the further development of the 3.1.x series:

  • Stabilizing 3.1.x, continuing to fix bugs and glitches.
  • Better error messages in Gekko 3.1.x.
  • Improved solver capabilities. Blocks of equations, equation objects, model objects. More means than goals. Improved tracking when simulations fail. (Handling blocks of equations has been implemented in the 2.5.x series, but regarding the 3.1.x version, this will be built differently, using equation objects etc. Still, the experiences from model blocks in 2.5.x will be useful).
  • Static simulation possibilities (in a sense removing lags and solving the model for one period to obtain long-run values).
  • Improving daily frequency, and implementing weekly frequency.
  • Release the “new” DECOMP capabilities (pivot table approach), including guides.
  • More advanced PLOT windows.
  • Better translator from Gekko 2.0/2.2/2.4 to 3.0 and 3.1.x.
  • Databank API? It would be nice to be able to separate the databank read/write part of Gekko into a clean API that can be called from .NET languages like C#, but maybe also from languages like Python, R or other.
  • Implementing some of the “missing” functions/procedures from AREMOS that deal with holes in data, interpolation, extrapolation, or conversion between frequencies.
  • Better temporal disaggregation, for instance via the R tempdisagg package.
  • More advanced seasonal correction (JDemetra+ etc.), perhaps via the R RJDemetra package.
  • Better Python and R interfaces. Dataframe objects in Gekko would facilitate communication with Python and R.
  • Better Apache Arrow interface for data interchange.