the data and get started. The data are a random sample of 3000 babies born in Pennsylvania in 1989. The data include the baby's birth weight together with various characteristics of the mother, including whether she smoked during pregnancy. The variables are: birthweightbaby's birthweight in grams smoker = 1 if mother smoked during pregnancy, 0 otherwise unmarried = 1 if mother is unmarried, 0 otherwise nprevist =total number of prenatal visits alcohol = 1 if mother drank alcohol during pregnancy, 0 otherwise a) Estimate the following three regression models: \text { birthweight }_{i}=\beta_{0}+\beta_{1} \text { smoker }_{i}+u_{i} \text { birthweight }_{i}=\beta_{0}+\beta_{1} \text { smoker }_{i}+\beta_{2} \text { alcohol }_{i}+\beta_{3} \text { nprevist }_{i}+u_{i} \text { birthweight }_{i}=\beta_{0}+\beta_{1} \text { smoker } i+\beta_{2} \text { alcohol }_{i}+\beta_{3} \text { rerevist }_{i}+\beta_{4} \text { unmarried }_{i}+u_{i} and construct 95% confidence intervals for the estimated effect of smoking on birth weight using each of the three regressions. b) Does the coefficient on smoker in the first and second regressions suffer from omitted variables bias? Explain. c) Consider the coefficient on unmarried in the third regression. A family advocacy group notes that the large coefficient suggests that public policies that encourage marriage will lead, on average, to healthier babies. Do you agree?Hint: is unmarried a regressor or a control variable? Discuss some of the various factors that unmarried might be controlling for and how this affects the interpretation of its coefficient.

Fig: 1

Fig: 2

Fig: 3

Fig: 4

Fig: 5

Fig: 6

Fig: 7

Fig: 8

Fig: 9

Fig: 10

Fig: 11

Fig: 12

Fig: 13

Fig: 14