Effect of Cigarette Price and Tax Increases on Smoking in Europe: A Difference-in-Differences Study with Double Machine Learning
TLDR
Cigarette tax hikes in Europe reduce smoking rates, especially among young adults, using a novel double machine learning diff-in-diff approach.
Key contributions
- Employs a difference-in-differences approach with double machine learning on EU data (2012-2020).
- Shows cigarette tax increases reduce smoking rates among monthly and daily smokers.
- Identifies the 15-24 age group as the primary driver of this reduction.
- Findings are robust to functional form assumptions but sensitive to treatment definition.
Why it matters
This study provides robust evidence on the effectiveness of tobacco taxation policies in Europe, particularly highlighting their impact on youth. The use of double machine learning offers a more flexible and reliable estimation method than traditional approaches, informing public health strategies.
Original Abstract
We estimate the effect of cigarette price and tax increases on smoking rates using Eurobarometer survey data from 27 European Union countries between 2012 and 2020. Following a difference-in-differences approach, we compare individuals exposed to large price and tax increases with those in stable price and tax environments. Estimation is based on a difference-in-differences estimator with double machine learning, which relaxes the functional form assumptions typically imposed by parametric approaches such as two-way fixed effects. Our results indicate that tax increases reduce smoking rates among individuals who smoke at least once per month and among daily smokers. The reduction is primarily driven by individuals aged 15-24. We examine the sensitivity of our findings to functional form assumptions and treatment definitions. While estimates are robust to alternative functional form assumptions, they are sensitive to whether the treatment is defined as binary or continuous.
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