Iassopack: Model Selection and Prediction with Regularized Regression in Stata

55 Pages Posted: 28 Jan 2019

See all articles by Achim Ahrens

Achim Ahrens

Economic and Social Research Institute (ESRI)

Christian Hansen

University of Chicago - Booth School of Business - Econometrics and Statistics

Mark E. Schaffer

Heriot-Watt University - Centre for Economic Reform and Transformation; Centre for Economic Policy Research (CEPR); IZA Institute of Labor Economics

Abstract

This article introduces lassopack, a suite of programs for regularized regression in Stata. lassopack implements lasso, square-root lasso, elastic net, ridge regression, adaptive lasso and post-estimation OLS. The methods are suitable for the high-dimensional setting where the number of predictors p may be large and possibly greater than the number of observations, n. We offer three different approaches for selecting the penalization ('tuning') parameters: information criteria (implemented in lasso2), K-fold cross-validation and h-step ahead rolling cross-validation for cross-section, panel and time-series data (cvlasso), and theory-driven ('rigorous') penalization for the lasso and square-root lasso for cross-section and panel data (rlasso). We discuss the theoretical framework and practical considerations for each approach. We also present Monte Carlo results to compare the performance of the penalization approaches.

Keywords: lasso2, cvlasso, rlasso, lasso, elastic net, square-root lasso, cross-validation

JEL Classification: C53, C55, C87

Suggested Citation

Ahrens, Achim and Hansen, Christian and Schaffer, Mark E., Iassopack: Model Selection and Prediction with Regularized Regression in Stata. IZA Discussion Paper No. 12081. Available at SSRN: https://ssrn.com/abstract=3323196

Achim Ahrens (Contact Author)

Economic and Social Research Institute (ESRI)

Whitaker square Sir john Rogerson's Quay
Dublin 2
Dublin
Ireland

Christian Hansen

University of Chicago - Booth School of Business - Econometrics and Statistics ( email )

Chicago, IL 60637
United States
773-834-1702 (Phone)

Mark E. Schaffer

Heriot-Watt University - Centre for Economic Reform and Transformation ( email )

School of Management - Department of Economics
Edinburgh EH14 4AS
United Kingdom
+44 131 451 3494 (Phone)
+44 131 451 3008 (Fax)

HOME PAGE: http://www.hw.ac.uk/ecoWWW/cert

Centre for Economic Policy Research (CEPR)

London
United Kingdom

IZA Institute of Labor Economics

P.O. Box 7240
Bonn, D-53072
Germany

Register to save articles to
your library

Register

Paper statistics

Downloads
4
Abstract Views
18
PlumX Metrics