lec32v2_1up

# lec32v2_1up - Stat 104 Quantitative Methods for Economists...

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Stat 104: Quantitative Methods for Economists Class 33: Dummy Variables 1

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Dummy variables What is 2+2 ? 5 ? X Y 2
Dummy Variables s Many variables in the world are fundamentally discrete -- - e.g., you are male or female, have a your tonsils or not, eat/drink Four Loko or not, etc. ummy variable r dicator variable is a variable s A dummy variable (or indicator variable ) is a variable that takes on a value of zero or one. Note : This section considers X variables that are indicator variables. When Y is an indicator variable, least-squares is not the appropriate method (logistic regression is, which we get to in a bit). 3

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Some Examples b categorical variable (e.g., 1 if female, 0 if not) b temporal variable (e.g., 1 if Monday, 0 if not) b spatial variable (e.g., 1 if Midwest, 0 if not) b qualitative variable (e.g., 1 if “good at beer pong,” 0 if not) 4
Example: Sexual Discrimination s Simple regression model: s Salary i = β 0 + β 1 Male i + ε i s How do you interpret this model? ammer Time! s Hammer Time! 5 Break it down, break it down.

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s The model says Salary i = β 0 + β 1 Male i + ε i s We are really fitting two models at once. s So for females (male variable = 0) b E[Salary | male = 0] = β 0 s And for males (male variable = 1) b E[Salary | male = 1] = β 0 + β 1 s So, β 1 is the expected difference between a male’s salary and a male’s salary. s For instance, β 1 = 10,000 means that females earn \$10,000 less (on average). 6
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lec32v2_1up - Stat 104 Quantitative Methods for Economists...

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