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General-to-Specific (GETS) Modelling And Indicator Saturation With The R Package Gets

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  • James Reade
  • Genaro Sucarrat

Abstract

This paper provides an overview of the R-package 'gets’, which contains facilities for General-to-Specific (GETS) modelling of the mean and variance of a regression, and Indicator Saturation (IS) methods for the detection and modelling of structural breaks and outliers. The mean can be specified as an autoregressive model with covariates (an 'AR-X' model), and the variance can be specified as an autoregressive log-variance model with covariates (a 'log-ARCH-X' model). The covariates in the two specifications need not be the same, and the classical regression model is obtained as a special case when there is no dynamics, and when there are no covariates in the variance equation. The four main functions of the package are arx, getsm, getsv and isat. The first function estimates an AR-X model with log-ARCH-X errors. The second function undertakes GETS model selection of the mean specification of an arx object. The third function undertakes GETS model selection of the log-variance specification of an arx object. The fourth function undertakes GETS model selection of an indicator saturated mean specification allowing for the detection of structural breaks and outliers. Examples of how LaTeX code of the estimation output can be generated is given, and the usage of two convenience functions for export of results to EViews and STATA are illustrated.

Suggested Citation

  • James Reade & Genaro Sucarrat, 2016. "General-to-Specific (GETS) Modelling And Indicator Saturation With The R Package Gets," Economics Series Working Papers 794, University of Oxford, Department of Economics.
    • Handle: RePEc:oxf:wpaper:794
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    References listed on IDEAS

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    More about this item

    Keywords

    general-to-specific; model selection; indicator saturation; log-variance; R;
    All these keywords.

    JEL classification:

    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software

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