Section_10 - Section 10 - Econ 140 GSIs: Hedvig, Tarso,...

Info iconThis preview shows pages 1–2. Sign up to view the full content.

View Full Document Right Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: Section 10 - Econ 140 GSIs: Hedvig, Tarso, Xiaoyu * 1 Binary Dependent Variables ( Y i = 1 or Y i = 0 ) 1.1 General model Y i = + 1 X 1 i + ... + k X ki + u i E [ Y | X 1 ,...,X k ] = 1 Pr ( Y = 1 | X 1 ,...,X k ) + 0 Pr ( Y = 0 | X 1 ,...,X k ) Pr ( Y = 1 | X 1 ,...,X k ) = F ( + 1 X 1 + ... + k X k ) , where F ( . ) is the cumulative distribution function 1.2 Interpretation Predicted probabilities: c Pr ( Y = 1 | X 1 ,...,X k ) = F ( b + b 1 X 1 + ... + b k ) E ect of a change in a regressor (example: in X 1 ) : INFERENCE HERE! e ect = c Pr ( Y = 1 | X 1 + X 1 ,X 2 ,...,X k )- c Pr ( Y = 1 | X 1 ,X 2 ,...,X k ) * continuous variable: e ect = c Pr ( Y =1 | X 1 ,...,X k ) X 1 = b 1 .f b + b 1 X 1 + ... + b k X k , where f ( . ) is the density function * discrete variable: e ect = c Pr ( Y = 1 | 1 ,X 2 ,...,X k )- c Pr ( Y = 1 | ,X 2 ,...,X k ) 1.3 Estimation Nonlinear Least Squares (NLLS): b NLLS = argmin...
View Full Document

Page1 / 2

Section_10 - Section 10 - Econ 140 GSIs: Hedvig, Tarso,...

This preview shows document pages 1 - 2. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online