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Forecasting a large set of disaggregates with common trends and outliers

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2015-09-01
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Abstract
This paper deals with macro variables which have a large number of components and our aim is to model and forecasts all of them. We adopt a basic statistical procedure for discovering common trends among a large set of series and propose some extensions to take into account data irregularities and small samples issues. The forecasting strategy consists on estimating single-equation models for all the components, including the restrictions derived from the existence of common trends. An application to the disaggregated US CPI shows the usefulness of the procedure in real data problems.
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This paper is a more elaborated version of a part of a previous paper distributed as "The pairwise approach a large set of disaggregates with common trends"
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Cointegration, Pairwise testing, Disaggregation, Forecast model selection, Outliers treatment, Inflation
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