1. (5 marks) The following equations were estimated using the data in bwght”: bwght=4.682 -0.005cigs, +0.155parity;+0.026male;+0.062white; (0.016) (0.0008) (0.006) (0.010) (0.012) n=1,388, R2=0.045, RP=0.043 and bwght=4.668 – 0.005cigs, +0.171parity;+0.033male;+0.049white;-0.002motheduc;+0.004fatheduci (0.036) (0.001) (0.006) (0.011) (0.015) (0.003) (0.003) n=1,191, R=0.048, RP=0.043 The variables’ definition can be found in the link: http://fmwww.bc.edu/ec-p/data/wooldridge/bwght.des. i (2 marks) Considering the second regression results, comment on the estimated effect and statistical significance of fatheduc.(i.e., comment on the practical and statistical significance of fatheduc’s partial effect separately) (3 marks) Recall the content we learned in Chapter 4 (4-5f Testing General Linear Restrictions). If two linear models are nested, it means that the restricted model is obtained from the full model by setting some constraints on the parameters). In this question, the first regression is the restricted model. It is obtained by restricting motheque =0 and Bfatheduc=0 in the full model. Usually we can compare nested models with the F test to see whether the restrictions are valid. In this questions, it means we need to compute the F statistic for joint significance of motheduc and fatheduc by using the formula 4.37 in the textbook. (SSR, SSRur)/q SSRur/(n – k-1) FE However, from the given information, why are you unable to compute the F statistic? What would you have to do to compute the F statistic?
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