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PcGive 12: enhancements and solved problems
Fixed and improved in PcGive 12.1
- General cointegration restrictions with restriction on alpha, but not in all rows:
could give indexing run-time error.
- Logit estimation did not take selected sample (start,end)
into account. It only did sample selection using a Select by variable.
Store predictions in database gave run-time error.
- Generated Ox code when specifying `less forecasts'
as part of the estimation sample: this is not taken into account
when writing the SetSelSample command in the Ox code.
- PcGive now installs Arfima and DPD packages
- Autometrics name for combined dummies are wrong (the values
of the created variables are right, but the S and D names are misleading).
Now just writing the name as the sum or difference of the two dummies,
- Forecasting beyond the end of the database with 52 weeks/year
as frequency and Seasonals goes wrong, because when the database is extended,
the wrong seasonal is constructed.
- Generated GARCH code would try to load garch.dll,
which doesn't exist.
- PcNaive: ability to use PcGive and Autometrics.
- PcNaive loading experiment from file: would lose
some parameters if there are no lagged Z's in the DGP.
New in PcGive 12.0
- Now a module in the new OxMetrics 5 system.
- Autometricstm for automatic model selection.
- Generate Ox code. The required oxo files are now installed, and the
generated code can be run with Ox Professional.
- Enhanced status handling in Formulate dialog.
- Improved output when variable names are very long.
- Autometrics GUM now stored in history for recall (removed checkbox about
Use final model in next formulation dialog).
Problems in PcGive 11.1 that have been fixed in PcGive 12
- PcNaive: SetPcGiveDimensions didn't check rows in Pi.
Start formulating matrix DGP, cancel, switch to PcFiml DGP: would forget
to allow for constant and trend.
- Garch: could not have lagged Y in variance.
- Batch nonlinear/ml estimation would fail if there is a variable
in the database that has all missing values (or the sample size could
be restricted if some variable(s) have shorter sample).
- Further output, LaTeX of nonlinear model should use \&
- Restricted cointegration: in some cases wrongly decided that
restrictions on alpha were simple, in which case rescaling was applied when
it shouldn't be. As a consequence, the alpha matrix would not reflect the
This file last changed .