Lecture 15 Dummy variables

# Lecture 15 Dummy variables - Economics 326 Methods of...

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Economics 326 Methods of Empirical Research in Economics Lecture 15: Dummy variables Vadim Marmer University of British Columbia March 24, 2011

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Interval, Ordinal, and Categorical Variables I Interval variable: is one where the di/erence between two values is meaningful. in years. There is a meaning to the di/erence between 12 and 10 years of education. I In some data sets, education is reported as an ordinal variable: only the order between its values matters, but the di/erence has no meaning. Example: The following two variables are equivalent. Education i = 8 < : 1 if high-school graduate, 2 if college graduate, 3 if advanced degree. Education i = 8 < : 1 if high-school graduate, 10 if college graduate, 234 if advanced degree. 1²21
Interval, Ordinal, and Categorical Variables I Categorical variable is one that has one or more categories, but there is no natural ordering to the categories Examples: Gender, race, marital status, geographic location. I The following two variables are equivalent: Gender i = 1 if observation i corresponds to a woman , 2 if observation i corresponds to a man . Gender i = 1 if observation i corresponds to a man , 2 if observation i corresponds to a woman . I Categorical and ordinal variables are also called qualitative. I Qualitative variables cannot be simply included in regression, because the regression technique assumes that all variables are interval. 2/21

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Dummy variables I A dummy variable is a binary zero-one variable which takes on condition fails: I Female i = 1 if observation i corresponds to a woman, 0 if observation i corresponds to a man. I Male i = 1 if observation i corresponds to a man, 0 if observation i corresponds to a woman. I Note that Female i + Male i = 1 for all observations i . I Married i = 1 if married, 0 otherwise. 3/21
Example 4/21

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A single dummy independent variable I Consider the following regression: Wage i = β 0 + δ 0 Female i + β 1 Educ i + β 3 Exper i + β 4 Tenure i + U i , and assume that conditionally on all independent variables, E ( U i ) = 0 . I If observation i corresponds to a woman, Female i = 1, and E ( Wage i j Female i = 1 , Educ i , Exper i , Tenure i ) = = β 0 + δ 0 + β 1 Educ i + β 3 Exper i + β 4 Tenure i . I
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Lecture 15 Dummy variables - Economics 326 Methods of...

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