You are working on a data set which contains the following variables for 753 women Variable Description Average inlf = 1 if in the labour force and zero otherwise 0.56 nwifeinc household income earned by other household 20.12 members annually (thousands of dollars) age age of the woman 42.5 educ years of education completed 12.3 exper years of experience in the labour market 10.6 kidslt6 number of children aged less than 6 0.23 kidsge6 number of children aged 6 or older 1.35 A logit regression has been estimated to determine how the variables affect the decision for a woman to be in the labour force or not. Call : glm(formula = inlf ~ nwifeinc + age + educ + exper + kidslt6 + kidsge6, family = "binomial", data = mroz, maxit = 1000) Deviance Residuals : Min 1Q Median 3Q Max -2. 5261 -0.9223 0. 4489 0. 8978 2.3170 Coefficients : Estimate Std. Error z value Pr(> |z|) (Intercept) 0. 837909 0. 840933 0. 996 0. 3191 nwifeinc -0. 020216 0. 008264 -2. 446 0. 0144 * age -0. 091088 0. 014321 -6.361 2. 01e-10 *** educ 0. 226977 0. 043295 5. 243 1. 58e-07 *** exper 0. 119746 0. 013626 8.788 1 (Dispersion parameter for binomial family taken to be 1)Null deviance: 1029.75 on 752 degrees of freedom Residual deviance: 812.29 on 746 degrees of freedom (a) Estimate the impact of having an extra child, aged less than 6, on the probability that the woman will be in the labour force? [13 MARKS] (b) Explain whyr the logit regression had to be estimated by maximum likelihood and provide some intuition to explain how this technique differs from Ordinary Least Squares. [12 MARKS]