Interpreting Expectiles
Collin Philipps (collin.philipps@afacademy.af.edu)
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Collin Philipps: Department of Economics and Geosciences, US Air Force Academy
No 2022-01, Working Papers from Department of Economics and Geosciences, US Air Force Academy
Abstract:
This article establishes how expectiles should be understood. An expectile is the minimizer of an asymmetric least squares criterion, making it a weighted average. This also means that an expectile is the conditional mean of the distribution under special circumstances. Specifically, an expectile of a distribution is a value that would be the mean if values above it were more likely to occur than they are. Expectiles summarize distributions in a manner comparable to quantiles, but quantiles are expectiles in location models. The reverse is true in special cases. Expectiles are m-estimators, m-quantiles, and Lp-quantiles, families which connect them to the majority of statistics commonly in use.
Keywords: Expectile regression; Generalized Quantile Regression (search for similar items in EconPapers)
JEL-codes: C0 C21 C46 (search for similar items in EconPapers)
Pages: 40 pages
Date: 2022-01
New Economics Papers: this item is included in nep-ecm
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Persistent link: https://EconPapers.repec.org/RePEc:ats:wpaper:wp2022-1
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