Estimate a regression model for bweight

Reference no: EM133046970

Question 1: Does a mother's smoking affect the birthweight of her child? Using data in the file bweight,mall taken from Cattaneo (2010),3' we explore this question. The file bweight contains more observations.

a. Calculate the sample means of BWEIGHT for mothers who smoke (MBSMOKE = 1) and those who do not smoke (MBSMOKE = 0). Use the t-test of the equality of population means given in Appendix C.7.2, Case 1, to test whether the mean birthweight for smoking and nonsmoking mothers is the same. Use the 5% level of significance.

b. Estimate the regression BWEIGHT = 13, + 0,MBSMOKE + e. Interpret the coefficient of MBSMOKE. Can we interpret the coefficient as the "average treatment effect" of smoking? Test the null hypothesis that f3, > 0 against O, < 0 at the 5% level of significance.

c. Add to the model in (b) control variables MMARRIED, MACE, PRENATALI, and FBABY. Are any of these variables significant predictors of an infant's birthweight? Which signs of the sig¬nificant coefficients are consistent with your expectations? Does the estimate of the coefficient of MBSMOKE change much?

d. Estimate the regression of BWEIGHT on MMARRIED, MACE, PRENATAL1, and FBABY for mothers who smoke (MBSMOKE = 1) and those who do not smoke (MBSMOKE = 0). Carry out a Chow test of the equivalence of these two regressions at the 5% level.

e. Use equation (7.37) to obtain the estimate of the average treatment effect using the results from (d). compare this estimate of the average treatment effect to the estimates in (b) and (c).

Question 2: Does a mother's smoking affect the birthweight of her child? Using the data file bweight_small we explore this question. The file bweight contains more observations. The variable MSMOKE is the number of cigarettes smoked daily during pregnancy. Nonsmokers(MBSMOKE = 0)smoke zero daily. Among smokers (MBSMOKE = 1), the variable MSMOKE = 1 if 1-5 cigarettes are smoked daily; MSMOKE = 2 if 6-10 cigarettes are smoked daily; and MSMOKE = 3 if 11 or more cigarettes are smoked daily

a. Estimate a regression model for BWEIGHT. Include as explanatory variables MMARRIED, MAGE, PRENATAL1, and FBABY, along with MSMOKE. Interpret the estimated coefficient of MSMOKE.

b. From MSMOKE create three indicator variables, SMOKE2 = 1 if a mother smokes 1-5 cigarettes per day, 0 otherwise; SMOKE3 = 1 if a mother smokes 6-10 cigarettes per day, 0 otherwise; SMOKE4 = 1 if a mother smokes 11 or more cigarettes per day, 0 otherwise. Estimate a regression model for BWEIGHT. Include as explanatory variables MMARRIED, MAGE, PRENATAL1, and FBABY, along with SMOKE2, SMOKE3, and SMOKE4. Interpret the estimated coefficients of SMOKE2, SMOKE3, and SMOKE4. Does smoking 1-5 cigarettes per day have a statistically significant negative effect on infant birthweight?

c. Using the results in (b), test the null hypothesis that smoking 11 or more cigarettes per day reduces birthweight by no more than smoking 6-10 cigarettes per day, against the alternative that smoking 11 or more cigarettes per day reduces birthweight by more than smoking 6-10 cigarettes per day.

Question 3: The data file br2 contains data on 1080 house sales in Baton Rouge, Louisiana, during July and August 2005. The variables are: PRICE ($), SQFT (total square feet), BEDROOMS (number), BATHS (number), AGE (years), OWNER (= 1 if occupied by owner; 0 if vacant or rented), TRADI-TIONAL (= 1 if traditional style; 0 if other style), FIREPLACE (= 1 if present), WATERFRONT (= 1 if on waterfront).

a. Compute the data summary statistics and comment. In particular, construct a histogram of PRICE. What do you observe?

b. Estimate a regression model explaining ln(PR/CE/1000) as a function of the remaining variables. Divide the variable SQFT by 100 prior to estimation. Comment on how well the model fits the data. Discuss the signs and statistical significance of the estimated coefficients. Are the signs what you expect? Give an exact interpretation of the coefficient of WATERFRONT.

c. Create a variable that is the product of WATERFRONT and TRADITIONAL. Add this variable to the model and reestimate. What is the effect of adding this variable? Interpret the coefficient of this interaction variable and discuss its sign and statistical significance.

Note: Question 1 only need to do part D
Question 2 need to do part B and C
Question 3 only do part c

Reference no: EM133046970

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