Working Paper No. 961

Using Lasso-Type Penalties to Model Time-Varying Covariate Effects in Panel Data Regressions – A Novel Approach Illustrated by the ‘Death of Distance’ in International Trade

Published: March 13, 2013Pages: 29Keywords: Penalized Regression; Lasso-type Penalties; Varying Coefficient Models; Gravity; Death of Distance; Missing Globalization PuzzleJEL-codes: C23; C52; F10

Using Lasso-Type Penalties to Model Time-Varying Covariate Effects in Panel Data Regressions – A Novel Approach Illustrated by the ‘Death of Distance’ in International Trade Wolfgang Hess, Maria Persson, Stephanie Rubenbauer and Jan Gertheiss


When analyzing panel data using regression models, it is often reasonable to allow for time-varying covariate effects. We propose a novel approach to modelling timevarying coefficients in panel data regressions, which is based on penalized regression techniques. To illustrate the usefulness of this approach, we revisit the well-known empirical puzzle of the ‘death of distance’ in international trade. We find significant differences between results obtained with the proposed estimator and those obtained with ‘traditional’ methods. The proposed method can also be used for model selection, and to allow covariate effects to vary over other dimensions than time.

Maria Persson

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Sick of Inequality?

An Introduction to the Relationship between Inequality and Health

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In this book Andreas Bergh, Therese Nilsson, IFN and Lund University, and Daniel Waldenström, IFN and Paris School of Economics, France, review the latest research on the relationship between inequality and health. What does inequality mean for our health? Does increasing income inequality affect outcomes such as obesity, life expectancy and subjective well-being?

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