Panel Count Data Analysis of Determinants of Cigarette Smoking: Evidence from British Household Panel Survey, 2001-2009

Abstract

Count Datasets contain relatively larger number of realizations of nonnegative integer-valued random variable. The nature necessitates application of regression models based on binomial probability distributions including Poisson, Zero-Inflated Poisson or Zero-Inflated Negative Binomial distributions to infer valid predictions. This paper will use micro-dataset from the British Household Panel Survey (Abbreviated and Well-known as BHPS) to identify factors determining the participation decisions to smoke at the individual level. It is evident from the results that the educated and married person’s participation to smoke is lower than the participation of divorced and separated individuals. Congruent participation to smoke of unemployed or newly employed is higher. The empirical results persuade a more details investigation in a comparable theme to contribute to scarcity of research in health economics to determine causal factors of smoking and formulate more effective health policies.

Keywords: Panel Count Data, Binomial Distribution, Poisson distribution, Zero-Inflated Poisson Distribution, Zero-Inflated Negative Binomial Distribution, Smoking

JEL Classification: C23, C51, C52, I19