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Neil R. Ericsson

Federal Reserve Board



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288 – Economic and Business Applications in High-Dimensional and Big Data Contexts

Inherently High-Dimensional Analysis with Indicator Saturation

Sponsor: Business and Economic Statistics Section
Keywords: Autometrics, high-dimensional analysis, impulse indicator saturation, model selection, robust estimation, structural breaks

Neil R. Ericsson

Federal Reserve Board

Indicator saturation is a generic approach to robust estimation, and to the detection and quantification of structural breaks. Saturation techniques are inherently high-dimensional and require automated model selection with non-standard inference. This paper characterizes several roles for saturation techniques and proposes extensions of impulse indicator saturation that have greater power to detect empirically common structural breaks. A model for the Brazilian inflation rate illustrates saturation techniques.

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