Weighted Least Squares and Adaptive Least Squares: Further Empirical Evidence
نویسنده
چکیده
This paper compares ordinary least squares (OLS), weighted least squares (WLS), and adaptive least squares (ALS) by means of a Monte Carlo study and an application to two empirical data sets. Overall, ALS emerges as the winner: It achieves most or even all of the efficiency gains of WLS over OLS when WLS outperforms OLS, but it only has very limited downside risk compared to OLS when OLS outperforms WLS. DOI: https://doi.org/10.1007/978-3-319-50742-2_9 Posted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: https://doi.org/10.5167/uzh-136112 Accepted Version Originally published at: Sterchi, Martin; Wolf, Michael (2017). Weighted least squares and adaptive least squares: further empirical evidence. In: Kreinovič, Vladik; Sriboonchitta, Songsak; Huynh, Van-Nam. Robustness in Econometrics. Cham: Springer, 135-167. DOI: https://doi.org/10.1007/978-3-319-50742-2_9 Weighted Least Squares and Adaptive Least Squares: Further Empirical Evidence Martin Sterchi Department of Economics University of Zurich 8032 Zurich, Switzerland [email protected] Michael Wolf Department of Economics University of Zurich 8032 Zurich, Switzerland [email protected]
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