On Interaction Effects: The Case of Heckit and Two-Part Models
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.
|Date of creation:||Jan 2012|
|Date of revision:|
|Contact details of provider:|| Postal: Hohenzollernstraße 1-3, 45128 Essen|
Web page: http://www.rwi-essen.de/
More information through EDIRC
|Order Information:||Web: http://www.rwi-essen.de/publikationen/|
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- William H. Greene, 2009.
"Testing Hypotheses About Interaction Terms in Nonlinear Models,"
09-08, New York University, Leonard N. Stern School of Business, Department of Economics.
- Greene, William, 2010. "Testing hypotheses about interaction terms in nonlinear models," Economics Letters, Elsevier, vol. 107(2), pages 291-296, May.
- Edward C. Norton & Hua Wang & Chunrong Ai, 2004. "Computing interaction effects and standard errors in logit and probit models," Stata Journal, StataCorp LP, vol. 4(2), pages 154-167, June.
- Manuel Frondel & Colin Vance, 2009.
"Do High Oil Prices Matter? Evidence on the Mobility Behavior of German Households,"
Environmental & Resource Economics,
European Association of Environmental and Resource Economists, vol. 43(1), pages 81-94, May.
- Frondel, Manuel & Vance, Colin, 2008. "Do High Oil Prices Matter? – Evidence on the Mobility Behavior of German Households," Ruhr Economic Papers 72, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
- Frondel, Manuel & Peters, Jörg & Vance, Colin, 2007.
"Identifying the Rebound - Evidence from a German Household Panel,"
Ruhr Economic Papers
32, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
- Manuel Frondel & Jorg Peters & Colin Vance, 2008. "Identifying the Rebound: Evidence from a German Household Panel," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 145-164.
- Ai, Chunrong & Norton, Edward C., 2003. "Interaction terms in logit and probit models," Economics Letters, Elsevier, vol. 80(1), pages 123-129, July.
- White, Michelle J, 1986. "Sex Differences in Urban Commuting Patterns," American Economic Review, American Economic Association, vol. 76(2), pages 368-72, May.
- repec:zbw:rwidps:0039 is not listed on IDEAS
When requesting a correction, please mention this item's handle: RePEc:rwi:repape:0309. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sabine Weiler)
If references are entirely missing, you can add them using this form.