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10. Revisiting the linear probability model Suppose you are estimating the following linear probability model (LPM): y-Be+A₁₁+₂+ where Ply 21,22)=80+ B₁²s + B₂=₂ and Var (y|z)=P(z)(1-p(z)| Outline the steps needed to use weighted least squares (WLS) for estimating the LPM.

10. Revisiting the linear probability model Suppose you are estimating the following linear probability model (LPM): y-Be+A₁₁+₂+ where Ply 21,22)=80+ B₁²s + B₂=₂ and Var (y|z)=P(z)(1-p(z)| Outline the steps needed to use weighted least squares (WLS) for estimating the LPM.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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10. Revisiting the linear probability model Suppose you are estimating the following linear probability model (LPM): y Bot Bizet Byên tử where P(y 21, 22)=B0+ B₂z1+ B₂=₂ and Var (yz)=p(z)(1-p(z)) Outline the steps needed to use weighted least squares (WLS) for estimating the LPM. Outline the steps needed to use weighted least squares (WLS) for estimating the LPM. 1. Estimate the model using OLS and obtain the 2. Determine whether all of the values fit inside the unit interval. 3. Construct the estimated variance 4. Estimate the original model with using weights equal to 1/h. True or False: Suppose, for some i, -2. Although WLS involves multiplying observation i by √1/h, the WLS method will be viable without any V further adjustments. O True False Outline the steps needed to use weighted least squares (WLS) for estimating the LPM. 1. Estimate the model using OLS and obtain the 2. Determine whether all of the values fit inside the unit interval. 3. Construct the estimated variance 4. Estimate the original model with are inside the unit interval. If so, proceed to step 3. If not, adjust them so that all O True False are inside the unit interval. If so, proceed to step 3. If not, adjust them so that all True or False: Suppose, for some i, j,-2. Although WLS involves multiplying observation i by √/1/, the WLS method will be viable without any V further adjustments. = using weights equal to 1/h.
Transcribed Image Text:10. Revisiting the linear probability model Suppose you are estimating the following linear probability model (LPM): y Bot Bizet Byên tử where P(y 21, 22)=B0+ B₂z1+ B₂=₂ and Var (yz)=p(z)(1-p(z)) Outline the steps needed to use weighted least squares (WLS) for estimating the LPM. Outline the steps needed to use weighted least squares (WLS) for estimating the LPM. 1. Estimate the model using OLS and obtain the 2. Determine whether all of the values fit inside the unit interval. 3. Construct the estimated variance 4. Estimate the original model with using weights equal to 1/h. True or False: Suppose, for some i, -2. Although WLS involves multiplying observation i by √1/h, the WLS method will be viable without any V further adjustments. O True False Outline the steps needed to use weighted least squares (WLS) for estimating the LPM. 1. Estimate the model using OLS and obtain the 2. Determine whether all of the values fit inside the unit interval. 3. Construct the estimated variance 4. Estimate the original model with are inside the unit interval. If so, proceed to step 3. If not, adjust them so that all O True False are inside the unit interval. If so, proceed to step 3. If not, adjust them so that all True or False: Suppose, for some i, j,-2. Although WLS involves multiplying observation i by √/1/, the WLS method will be viable without any V further adjustments. = using weights equal to 1/h.
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