(Econometrics) Hi would you mind answering the question? Thank you. The goal of
ID: 3061827 • Letter: #
Question
(Econometrics)
Hi would you mind answering the question?
Thank you.
The goal of the theory assignment is to reinforce your understanding of the theory of econometric models. We will emphasize the understanding of model and data set up, model equations, model assumptions and tests, estimation procedures, and interpretation of results. Please answer the following questions Binary outcome models a) b) Compare and contrast the probit and logit specifications for binary choice variables. Explain why the linear probability model is inadequate as a specification for binary dependent variable estimation. c) Why do we need to exercise caution when interpreting the coefficients of a probit or logit model?Explanation / Answer
a)
A binary choice variable as the name suggests gives us only 2 possible outcomes which are generally labled 1 and 0
The Logit model derives its name from logistic function
The logit model is actually a inverse sigmoidal logistic function
The general representation is given by =1/(1+exp(-x))
The probit model is actually a function associated with the standard normal cumulative distribution
b)
A linear probability model is inadequate for a binary dependent variable estimation because of the fact that unless and otherwise restrictions are placed for the coefficient values in linear probability model the value of the coefficients can go beyond the probability threshold of 1 which makes no sense
Hence probit or logit models are used
c)
The coefficients of the logit function or the probit function are always in terms of odd ratio or ratio of probabilities
We need to take the value and substitute and reconvert it into the desired quantity for interpreting in the correct manner
If the coefficients of the model are used without convrsion then the final interpretation will be misleading
Related Questions
Navigate
Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.