Ruhr Economic Papers

Ruhr Economic Papers #309

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

by Manuel Frondel and Colin Vance

RWI, RUB, 01/2012, 24 S./p., 8 Euro, ISBN 978-3-86788-356-6 DOI: 10.4419/86788356



Interaction effects capture the impact of one explanatory variable x1 on the marginal effect of another explanatory variable x2. To explore interaction effects, socalled 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 specifi cations (AI, NORTON, 2003). This paper provides for a general derivation of interaction effects in both linear and non-linear models and calculates the formulae of the interaction effects resulting from HECKMAN’s sample selection model as well as the Two-Part Model, two regression models commonly applied to data with a large fraction of either missing or zero values in the dependent variable, respectively. 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.

JEL-Classification: C34

Keywords: Truncated regression models; interaction terms

Published as:

Frondel, M. and C. Vance (2013), On Interaction Effects: The Case of Heckit and Two-part Models. Jahrbücher für Nationalökonomie und Statistik 233 (1): 22-38.