Explain the marginal effect and consider the following: D=1 woman looking for jo

Question

Explain the marginal effect and consider the following: D=1 woman looking for job, 0 otherwise M=1 woman is married, 0 otherwise S=Number of years of schooling for each woman

- probit D H S Iteration 0: Iteration 1: Iteration 2: Iteration 3: Iteration 4: log likelihood = -20-19035 log likelihood - -13.446805 log likelihood =-13.301194 log likelihood - -13.30OB33 log likelihood =-13-300833 30 13-76 0.0010 0.3412 Probit regreasion Humber af aba LR chi2 (2) Prob > chi2 Pseudo R2 Log likelihood - -13.30OB33 Coef. Std. Err [95% Conf. Interval] -6225214 -1.44393B -3976043 -3-4392 15 0.020 0.020 0.066 -2.664057 -.2236183 - 732976 -2272679 2-32 2.32 -0622326 conS 1-870689 -7-105698

Explanation / Answer

D(Dependent variable) = Categorical variable - It can only take value 0 or 1

M(Independent variable) = Categorical Variable - It can only take value 0 or 1

S(Independent variable) = Continous variable - It can take any positive value

Marginal effect gives you the information about the change in response variable (D) is related to change in other variables. It's interpretation for categorical and continous independent variable is different

Marginal effect for categorical variables computes, how probability of response variable changes as categorical variable changes from 0 to 1 keeping all other independent variables at their means.

M is the categorical variable and can take value 0 or 1. In above case, M changes from zero to one, the probability for the variable D taking the value one decrease by 0.467.

Marginal effect for continuous variables measures the rate of change.

S is the continuous variable so one unit change in year, increases the probability of for the variable D taking the value one rises by 14.35%.

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