Empirical Methods II (API-202) Kennedy School of Government Harvard University 1 LECTURE NOTES 3 - REGRESSION WITH DUMMY VARIABLES I - INTRODUCTIONQualitative information can sometimes be captured by defining a binary variable(i.e. a zero-one variable), commonly called a dummy variable. Examples: female = 1 if person is female 0 if person is male male = 1 if person is male 0 if person is female In these lecture notes, we will study SRs with dummy variable among the RHS variables. In future classes, we will study SRs with a dummy variable as LHS variable. To illustrate the use of dummies in RA we are going to think about the following question: Do women earn less than men?How much less? Data: person Wage per hour educexperfemalemarried 1 5.25 9 2 0 1 2 6.20 12 4 1 1 3 5.85 10 2 0 0 . . . . . . . . . . . . 526 6.15 12 3 1 0
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