A Case Study: El Paso Smoking Ban

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Multiple linear regression analysis was used to examine the effect of the El Paso smoking ban on changes in revenue over time. The following independent variables were considered: a variable indicating whether the smoking ban was in force, an ordinal variable to represent secular time, and three variables to indicate during which one of four calendar quarters the revenue data were collected. Two regression models were created for each of the following primary dependent variables: 1) revenue subject to sales tax from all restaurants and bars, restaurants only, and bars only; and 2) revenue subject to the mixed-beverage tax. For each category, the first model examined the association between the smoking ban and revenue, and the second examined

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