Effect of Cigarette Price and Tax Increases on Smoking in Europe: A Difference-in-Differences Study with Double Machine Learning

2026-04-07

AI Summary

This study evaluates the causal impact of cigarette price and tax increases on smoking prevalence in Europe. Leveraging Eurobarometer data from 27 European Union countries between 2012 and 2020, the authors employ a difference-in-differences design combined with double machine learning to estimate policy effects under relaxed parametric assumptions. They systematically compare the robustness of estimates under alternative definitions of treatment—binary versus continuous—highlighting the sensitivity of causal inference to variable construction. The findings indicate that higher tobacco taxes significantly reduce both monthly and daily smoking rates, with effects concentrated among individuals aged 15–24. While the results prove robust to functional form specifications, they are notably sensitive to how the treatment variable is defined, underscoring the critical role of precise measurement in causal analysis.

Technology Category

• Machine Learning: Causal Learning
• Reasoning under Uncertainty: Causality
• Game Theory and Economic Paradigms: Social Choice / Voting

Application Category

• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets
• Responsible Web: Data and user privacy-enhancing technologies for the Web
• Web Mining and Content Analysis: Robustness and generalizability of Web mining methods

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.

Problem

• cigarette price
• tax increases
• smoking rates
• Europe
• difference-in-differences

Innovation

• Double Machine Learning
• Difference-in-Differences
• Causal Inference
• Tax Policy Evaluation
• Nonparametric Estimation