SLN Dummy Variables Spring 2007

# SLN Dummy Variables Spring 2007 - Dummy(or Binary...

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Dummy (or Binary) Explanatory Variables Supplementary Lecture Notes: Spring 2007 Dummy variables are qualitative (non-numerical measures) variables as opposed to quantitative (numerical measures). A dummy variable characterizes an observation in terms of one of two possible disjoint categories or ‘qualities’. In other words, if X is a dummy variable, then it is a qualitative variable with two categories. For example, X can represent gender where observations have the "quality" of being male or the "quality" of being female. X = gender Î X = male or X = female Some other examples of Dummy variables: X = employment status Î X= employed or X = not employed X = Home ownership status Î X = owns home or X = does not own home X = Education Î X = college grad or X = non-college grad In general if X is a Dummy variable then either X exhibits a certain ‘quality’ or X does not exhibit that quality. The categories or qualities are non-numerical. To deal with this, we impose a "quantification" or coding scheme so that the variable takes on numerical values. A dummy variable is assigned the value either 0 or 1. These are numerical codes to distinguish between two disjoint categories. Consider the following model E(Y) = β o + β 1 X 1 + β 2 X 2 Where Y = annual salary of professors (\$) X 1 = teaching experience (years) X 2 = gender = 1 if male and 0 if female Recall that in general the beta coefficient on a variable, X, tells us the expected change in Y of a one unit change in X, assuming all other X variables in the model are held constant, i.e., controlling for the other X variables in the model. Thus

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SLN Dummy Variables Spring 2007 - Dummy(or Binary...

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