Consider a linear probability model under the Gauss-Markov assumptions without assuming homoskedasticity. This is sufficient to identify a causal effect in the model. True False A problem of the linear probability model is that an OLS estimation of it can generate fitted values that are negative or greater than one. True False
Consider a linear probability model under the Gauss-Markov assumptions without assuming homoskedasticity. This is sufficient to identify a causal effect in the model. True False A problem of the linear probability model is that an OLS estimation of it can generate fitted values that are negative or greater than one. True False
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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Problem 1P
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Consider a linear probability model under the Gauss-Markov assumptions without
assuming homoskedasticity. This is sufficient to identify a causal effect in the model.
True
False
A problem of the linear probability model is that an OLS estimation of it can generate
fitted values that are negative or greater than one.
True
False
And both.. otherwise don't ans
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