PcGive Professional

PcGive Professional aims to give an operational and structured approach to econometric modelling using the most sophisticated yet user-friendly software. The accompanying books transcend the old ideas of extbooks and computer manuals by linking the learning of econometric methods and concepts to the outcomes achieved when they are applied.

The econometric techniques of the PcGive system can be divided by the type of data to which they are (usually) applied. The documentation is comprised of three volumes, and the overview below gives in parenthesis whether the method is described in Volume I, II or III or V. Volume IV refers to the PcNaive book. PcGive is also part of OxMetrics Enterprise Edition.

PcGive uses OxMetrics for data input and graphical and text output. OxMetrics has its own help system. Even though PcGive is largely written in Ox Professional, it does not require Ox to function.

PcGive includes Autometrics

Autometrics is the automatic econometric model selection procedure that is available in PcGive. Autometrics is a revolutionary new approach to model building, based on recent advances in the understanding of model selection procedures. Experiments show that Autometrics outperforms even the most experienced econometrician. Starting from an initial model, Autometrics will find the best simplified model. Thus removing the drudgery of model selection, allowing you to concentrate on the variable choice and interpretation of the model(s).

New features in PcGive 14

Version 14.0 is a major upgrade of PcGive and includes a new volume of material: Volume V: Econometrics Analysis with Markov-Switching Models.

• New book on Markov-switching models;
• PDF files of five books now included in help;
• Autometrics related:
  • Autometrics default now set to 0.01 instead of 0.05;
  • Added SIS, IIS+SIS, DIIS, DIIS+IIS dummy saturation;
  • Now have PcGive batch command createinterventions and Ox function PcGive::CreateInterventions to construct intervention dummies from saturation in the database;
  • Reclassification of lagged dependent variables from X,U to Y,I is now done at a later stage. This allows forcing of lagged dependent variables when running Autometrics on a system (OLS) or single equation (OLS, IVE);
  • Additional instruments for IVE (denoted with an A) now is different from unrestricted (U). U is used for unrestricted: not to be removed by automatic model selection;
  • Removed variables from an IVE model are only made into additional instruments if reduction of the reduced form was used first (which is the default);
  • Writing initial GUM when entering k>T.
• Much extended dynamic forecasting:
  • Automatic detection of certain types of transformations of the dependent variable Y:
    • fn(Y), Dfn(Y), DDfn(Y), DD_sfn(Y), D_sfn(y);
    • Where fn(Y): Y, log(Y), logit(Y);
    • Also detects on rhs corresponding fn(Y), Dfn(Y), D_sfn(y).
  • Based on this a levels forecast will be available in two forms:
    1. Median forecasts: inverse transformation (exp(y), logistic(y));
    2. Mean forecasts: based on lognormal and logitnormal distribution.
    The 5% and 95% quantiles, based on two standard errors simply arise from the transformation,e.g. for log(Y): exp(y-2SE), exp(y+2SE);
  • Robust forecasts. Robust forecast are derived from using the model on the differenced data, which is then reintegrated;
  • Optionally, forecasting can start a specified number of observations after the end of the estimation sample;
  • Hedgehog graphs: forecasts starting from each observation in the estimation sample:
    1. fixed parameters: the same parameters are used for each forecast;
    2. recursive parameters: if the model is estimated recursively, the recursive parameter estimates are used. So the model is re-estimated each time for the new forecasts.
  • Estimating an empty model now does not give an error message anymore, facilitating DDD;
  • Add documentation to header files, DoForecasting doesn store SEs, nor are there functions to extract forecasts.
• Added X12-ARIMA;
• Markov-switching models:
  • MS_Component: Markov-switching with component structure for mean and variance;
  • MS_GARCH: Markov-switching GARCH;
  • MS_MV: Multifractal volatility models;
  • MS_VAR: Multivariate Markov switching;
  • Refactored code to implement improvements in structure;
  • Removed singularity in analytical derivatives when probability is (very close to) zero;
  • Changed starting values for transition probabilities;
  • Probability mask: avoid diagonal when setting 1-sum element;
  • Ability to set lower pound for probability of staying in same regime (if this is zero, we have identified an outlier - this can be on the boundary of the parameter space with a lower log-likelihood than the interior solution. Default minimum for diagonal of transition matrix (probability of staying) is 0.01;
  • Reporting sdev(y) not var(y);
  • Updated NBER info;
  • Forecasts: not reporting naive forecasts anymore;
  • Forecast se: only simulating for dynamic models;
  • Impulse responses with standard errors.

Fixed in PcGive 14

• Exit batch command crashes OxMetrics;
• Fixed infinite reload loop in when loading help in Chrome;
• CFIML: not forcing rows/columns of restricted parameters to zero anymore in VarCovar matrix (fixes problem with forecast se when parameter uncertainty is included);
• IVE withholding forecast, store fitted in database gave concatenation warning (but worked fine);
• Recursive IVE: default no inits was zero, which didn work for IVE;
• CFIML then FIML: was still estimating CFIML;
• Dummy saturation (IIS) would go haywire if a dummy is already in the model.

Supported Platforms

PcGive 14 supports the latest versions of Microsoft Windows, Mac OS and Linux. See below to see if your machine is compliant with the latest version:

• Microsoft Windows:
  • Windows 8, 7, Vista, XP, 2000 (32-bit)
  • Windows 8, 7, Vista (64-bit)
• Mac OS:
  • OS X 10.4 (Tiger)
  • OS X 10.5 (Leopard)
  • OS X 10.6 (Snow Leopard)
  • OS X 10.7 (Lion)
  • OS X 10.8 (Mountain Lion)
• Linux:
  • 32-bit
  • 64-bit