Stochastic Scenario Modelling of Tobacco Taxation in Nepal: Evaluating 5–10 Year Pathways to Achieve a 75 Percent Tax Share

Tobacco consumption is a major public health and economic burden in Nepal, and taxation is a central policy tool for its reduction while increasing fiscal revenue. However, the most effective pathway to achieve the WHO-recommended 75 percent tax share under different reform timelines remains unclear. This study assesses whether 5-, 7-, or 10-year tobacco tax reform scenarios best achieve this benchmark while reducing consumption and prevalence in Nepal. Secondary data from the Cost Recovery and Revenue Estimator (CoRRE) from The Tobacco Atlas were used to construct baseline price and consumption pathways. A Monte Carlo simulation with 10,000 iterations was implemented in STATA v14 to incorporate uncertainty in key parameters, from most recent empirical evidence of price elasticity of demand, income elasticity of demand, inflation, income growth, and tax passthrough rates. Consumption was projected as a function of these variables, while prevalence was derived as a proportional transformation of consumption change. Results reveal that the 5-year accelerated scenario produces the largest and most consistent reductions in consumption and prevalence across all uncertainty bounds. The 7-year scenario yields moderate reductions but with uncertainty intervals crossing zero, indicating possible weak or non-significant effects. The 10-year scenario shows the weakest impact, with a high likelihood of negligible or positive consumption changes due to income growth offsetting price effects. In conclusion, faster tax escalation is more robust and effective in achieving the WHO 75 percent benchmark and reducing tobacco use in Nepal. Gradual reforms are more feasible politically but less reliable in public health impact. Policy should prioritize accelerated tax increases, alongside stronger enforcement against substitution and illicit trade, and future models should incorporate socioeconomic heterogeneity for improved precision.