JOURNAL ARTICLE

INTERACTION TERMS IN POISSON AND LOG LINEAR REGRESSION MODELS

Shengwu ShangErik NessonMaoyong Fan

Year: 2017 Journal:   Bulletin of Economic Research Vol: 70 (1)   Publisher: Wiley

Abstract

ABSTRACT This paper develops a difference‐in‐semielasticities (DIS) interpretation for the coefficients of dichotomous variable interaction terms in nonlinear models with exponential conditional mean functions, including but not limited to Poisson, Negative Binomial, and log linear models. We show why these interaction term coefficients cannot be interpreted as a DIS or semielasticity in the same manner as continuous coefficients, which has been overlooked by some empirical researchers. Then we show how interaction terms can be easily transformed into a DIS and derive the asymptotic distribution of this estimator. We illustrate the discrepancy between the interaction term coefficient and the DIS using an empirical example evaluating the relationship between employment, private health insurance and physician office visits. Our results can be applied in treatment effect models when the outcome variable is logged and the dichotomous variables indicating treatment participation and the post‐treatment time period.

Keywords:
Negative binomial distribution Estimator Poisson distribution Econometrics Mathematics Poisson regression Term (time) Statistics Variables Linear regression Conditional expectation Linear model Variable (mathematics) Economics Medicine Mathematical analysis

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34
Cited By
4.10
FWCI (Field Weighted Citation Impact)
14
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0.93
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Citation History

Topics

Advanced Causal Inference Techniques
Physical Sciences →  Mathematics →  Statistics and Probability
Healthcare Policy and Management
Social Sciences →  Economics, Econometrics and Finance →  Economics and Econometrics
Health Systems, Economic Evaluations, Quality of Life
Social Sciences →  Economics, Econometrics and Finance →  Economics and Econometrics

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