EconPapers    
Economics at your fingertips  
 

A Comparison Study of Least Squares and Ridge Estimators in the Presence of Heteroscedasticity and Multicollinearity Under Normal and Nonnormal Disturbances

George S. Donatos () and George C. Michailidis
Additional contact information
George S. Donatos: University of Athens
George C. Michailidis: University of Florida

Chapter Chapter 10 in Money, Trade and Finance, 2021, pp 195-221 from Springer

Abstract: Abstract In this chapter the sample properties of the least squares (LS) and of some ridge estimators (and predictors) are studied for alternative models of heteroscedasticity at various levels of multicollinearity, under normal and non-normal disturbances with small and large variances. The present simulation study shows that when the regression coefficient vector β is aligned to the normalized eigenvector corresponding to thelargest eigenvalue of the X’X matrix the Generalized Cross-Validation estimator in almost all cases is superior to the other estimators examined in the study. It is also “confirmed” that the LS estimator exhibits a poor performance independent of the level of multicollinearity for all the examined criteria with the notable exception of the multiple correlation coefficient.

Date: 2021
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-73219-6_10

Ordering information: This item can be ordered from
http://www.springer.com/9783030732196

DOI: 10.1007/978-3-030-73219-6_10

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-28
Handle: RePEc:spr:sprchp:978-3-030-73219-6_10