We used linear regression to model state per capita alcohol consumption as a function of cigarette prices (log-transformed) and SFA score. All models included state and year fixed effects and the covariates described above. We used natural log-transformed per capita alcohol and beverage-specific consumption as our dependent variables. Thus, the beta coefficient for cigarette price can be interpreted as the price elasticity of demand for alcohol with respect to cigarette prices (percent change in alcohol consumption associated with a 1% increase in cigarette price per pack). The beta coefficient for SFA policy score, multiplied by 100, can be interpreted as the percent change in alcohol consumption associated with a one point increase in the SFA policy score. The joint effect of both tobacco policies was examined using a 2 degree-of-freedom F-test to evaluate the change in explained variance upon simultaneous addition of both policy variables compared to a more restricted model including only the other covariates. In each model, all three alcohol excise tax variables (beer, wine, and spirits) were included as covariates. Some states have state-run retail and/or wholesale
