The Asymptotic Equivalence of Ridge and Principal Component Regression with Many Predictors

De Mol, Christine, Giannone, Domenico and Reichlin, L (2024) The Asymptotic Equivalence of Ridge and Principal Component Regression with Many Predictors. Econometrics and Statistics. ISSN 24523062 (In Press)

Abstract

The asymptotic properties of ridge regression in large dimension are studied. Two key results are established. First, consistency and rates of convergence for ridge regression are obtained under assumptions which impose different rates of increase in the dimension n between the first n1 and the remaining n−n1 eigenvalues of the population covariance of the predictors. Second, it is proved that under the special and more restrictive case of an approximate factor structure, principal component and ridge regression have the same rate of convergence and the rate is faster than the one previously established for ridge.

More Details

[error in script]
Item Type: Article
Subject Areas: Economics
Date Deposited: 02 Apr 2024 11:44
Subjects: Time series
Regression
Last Modified: 25 Apr 2024 08:34
URI: https://lbsresearch.london.edu/id/eprint/3658
[error in script] More

Export and Share


Download

Full text not available from this repository.

Statistics

Altmetrics
View details on Dimensions' website

Downloads from LBS Research Online

View details

Actions (login required)

Edit Item Edit Item