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 ()
Additional contact information
Wolfgang Hess: Department of Economics, Lund University, Postal: Department of Economics, School of Economics and Management, Lund University, Box 7082, S-220 07 Lund, Sweden, http://www.nek.lu.se/en/contact
Stephanie Rubenbauer: Department of Statistics, Ludwig-Maximilians-University Munich
Jan Gertheiss: Department of Statistics, Ludwig-Maximilians-University Munich

No 2013:5, Working Papers from Lund University, Department of Economics

Abstract: 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.

Keywords: Penalized Regression; Lasso-type Penalties; Varying Coefficient Models; Gravity; Death of Distance; Missing Globalization Puzzle (search for similar items in EconPapers)
JEL-codes: C23 C52 F10 (search for similar items in EconPapers)
Pages: 30 pages
Date: 2013-02-19
New Economics Papers: this item is included in nep-ecm and nep-geo
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Citations: View citations in EconPapers (1)

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Related works:
Working Paper: 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 (2013)
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