Factor-Based Forecasting in the Presence of Outliers: Are Factors Better Selected and Estimated by the Median than by The Mean?

Johannes Kristensen

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

Abstract: Macroeconomic forecasting using factor models estimated by principal components has become a popular research topic with many both theoretical and applied contributions in the literature. In this paper we attempt to address an often neglected issue in these models: The problem of outliers in the data. Most papers take an ad-hoc approach to this problem and simply screen datasets prior to estimation and remove anomalous observations.We investigate whether forecasting performance can be improved by using the original unscreened dataset and replacing principal components with a robust alternative. We propose an estimator based on least absolute deviations (LAD) as this alternative and establish a tractable method for computing the estimator. In addition to this we demonstrate the robustness features of the estimator through a number of Monte Carlo simulation studies. Finally, we apply our proposed estimator in a simulated real-time forecasting exercise to test its merits. We use a newly compiled dataset of US macroeconomic series spanning the period 1971:2–2011:4. Our findings suggest that the chosen treatment of outliers does affect forecasting performance and that in many cases improvements can be made using a robust estimator such as our proposed LAD estimator.

Keywords: Forecasting; FactorsModels; Principal Components Analysis; Robust Estimation; Least Absolute Deviations (search for similar items in EconPapers)
JEL-codes: C38 C53 E37 (search for similar items in EconPapers)
Pages: 36
Date: 2012-06-08
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Journal Article: Factor-based forecasting in the presence of outliers: Are factors better selected and estimated by the median than by the mean? (2014)
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