Least trimmed squares: cointegration and outliers

Journal article

Abstract:: When applying the cointegrated autoregressive distributed lag model it is common to include indicator variables for outliers. This is often done in a somewhat ad hoc way. Least Trimmed Squares estimation provides a more systematic approach. This estimator is robust to a large number of outliers of many types. We analyse the estimator in a model that allows a range of contamination and show that it has the same asymptotic properties as the infeasible Ordinary Least Squares estimator applied to a model generated by the good errors.

Files:: Berenguer-Rico_and_Nielsen_2026_Least_trimmed_squares.pdf

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Publisher:: Wiley
Journal:: Oxford Bulletin of Economics and Statistics More from this journal
Publication date:: 2026-04-29
Acceptance date:: 2026-04-08
DOI:: 10.1111/obes.70077
EISSN:: 1468-0084
ISSN:: 0305-9049

Language:: English
Keywords:: asymptotic theory

cointegration

least trimmed squares

outliers
Pubs id:: 2403358
Local pid:: pubs:2403358
Deposit date:: 2026-04-08
ARK identifier:: ark:/29072/ora_e9ed4a9471fd4883bbb1cd417afab2c2

Copyright holder:: Berenguer-Rico and Nielsen
Rights statement:: © 2026 The Author(s). Oxford Bulletin of Economics and Statistics published by Oxford University and John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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