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An Application of Unconditional Quantile Regression to Cigarette Taxes
This study investigates heterogeneous response to state cigarette tax increases using unconditional quantile regression (UQR). We make two contributions to the empirical policy analysis literature. First, we argue that UQR provides more policy-relevant information than conventional quantile regressi...
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Published in: | Journal of policy analysis and management 2014, Vol.33 (1), p.188-210 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | This study investigates heterogeneous response to state cigarette tax increases using unconditional quantile regression (UQR). We make two contributions to the empirical policy analysis literature. First, we argue that UQR provides more policy-relevant information than conventional quantile regression in most empirical state policy analyses. Second, we document cigarette tax elasticity across a sample of adult smokers in the Current Population Survey Tobacco Use Supplements between 1992 and 2011. Our ordinary least squares regression show an imprecise negative relationship between taxes and cigarettes smoked in the past 30 days, while UQR reveals a U-shaped relationship: Only moderate smokers reduce their smoking following a cigarette tax increase, and the magnitude of the effect is small. A $1.00 (135 percent) increase in the cigarette tax leads to a 3.5 percent reduction in the number of cigarettes smoked in the past 30 days among the most responsive smokers (implied tax elasticity = -0.03). © 2013 by the Association for Public Policy Analysis and Management. |
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ISSN: | 0276-8739 1520-6688 |
DOI: | 10.1002/pam.21724 |