On Marginal and Interaction Effects: The Case of Heckit and Two-Part Models

24 Pages Posted: 24 Oct 2009

See all articles by Manuel Frondel

Manuel Frondel

RWI Leibniz Institute for Economic Research ; Ruhr University Bochum (RUB)

Colin Vance

Rheinisch-Westfälisches Institut für Wirtschaftsforschung (RWI)

Date Written: September 1, 2009

Abstract

Interaction effects capture the impact of one explanatory variable x1 on the marginal effect of another explanatory variable x2. To explore interaction effects, so-called interaction terms x1x2 are typically included in estimation specifications. While in linear models the effect of a marginal change in the interaction term is equal to the interaction effect, this equality generally does not hold in non-linear specifications (AI, NORTON, 2003). This paper provides for a general derivation of marginal and interaction effects in both linear and non-linear models and calculates the formulae of the marginal and interaction eff ects resulting from Heckman’s sample selection model as well as the Two-Part Model, two commonly employed censored regression models. Drawing on a survey of automobile use from Germany, we argue that while it is important to test for the significance of interaction effects, their size conveys limited substantive content. More meaningful, and also more easy to grasp, are the conditional marginal effects pertaining to two variables that are assumed to interact.

Keywords: Censored regression models, interaction terms

JEL Classification: C34

Suggested Citation

Frondel, Manuel and Vance, Colin, On Marginal and Interaction Effects: The Case of Heckit and Two-Part Models (September 1, 2009). Ruhr Economic Paper No. 138. Available at SSRN: https://ssrn.com/abstract=1493156 or http://dx.doi.org/10.2139/ssrn.1493156

Manuel Frondel (Contact Author)

RWI Leibniz Institute for Economic Research ( email )

Hohenzollernstr. 1-3
45128 Essen
Germany

Ruhr University Bochum (RUB) ( email )

Universitätsstraße 150
Bochum, NRW 44780
Germany

Colin Vance

Rheinisch-Westfälisches Institut für Wirtschaftsforschung (RWI) ( email )

Hohenzollernstr. 1-3
Essen, 45128
Germany
0049-201-8149-237 (Phone)

HOME PAGE: http://www.rwi-essen.de

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