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Flashcards in lecture 6 key terms Deck (6)
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1
Q

binary indicator

A

random variable that takes the value of 0 or 1

2
Q

linear probability model

A

marginal effect of a change in explanatory variable equal to a constant

3
Q

logit model

A

probability of the binary indicator being equal to 1 is given by exp(Xi’B)/[1 + exp(Xi’B)]

4
Q

probit model

A

probability of the binary indicator being equal to 1 given by the standard normal cumulative distribution

5
Q

method of max likelihood

A

a way of obtaining estimates of the parameters in logit and probit models

6
Q

max likelihood estimator

A

a type of estimator obtained by maximising thv log likelihood of a model