A commenter grumbles that it's "sloppy econometrics."[THUD]The survey question on alcohol asks respondents, “Do you ever have occasion to use any alcoholic beverages such as liquor, wine, or beer, or are you a total abstainer?” From this question we create a dummy variable where drinkers have a one and abstainers have a zero. The survey also asks respondents the frequency with which they go to a bar or tavern. Choices include the following: almost every day, once or twice a week, several times per month, about once per month, several times a year, about once a year, never, and don’t know. From this question we create a variable indicating whether an individual frequents a bar or tavern at least once per month. This somewhat crude measure attempts to capture whether one drinks in social or nonsocial settings.
We therefore estimate the following equation:
Yi = ?Xi+ ?Ai + ?Bi + ?I , (1)...where Y is the log of real earned income by individual i; X is a vector of personal and demographic characteristics; A is the drinking dummy variable; and B is the social vs. nonsocial drinking dummy variable.
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I'm inclined to agree. In many cases these "control" variables give the response functions different intercepts but the same slope: there is no way of establishing whether a Protestant who bar-hops (an interaction term) would do better than an agnostic who is a regular at some bar.Control variables in X include race, age, age squared, religion, schooling, marital status, parental education, number of siblings, and region of residence.*sigh*

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