Interpreting the outcomes of two-part models
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Date
2011-03-23
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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 effects resulting from the Two-Part Model, a commonly
employed censored regression model. Drawing on a survey of automobile use from
Germany, we illustrate several subtleties inherent to the substantive interpretation of
interaction effects gleaned from non-linear models.
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Keywords
censored regression models, interaction terms, marginal and interaction effects