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2. The following table summarizes some regressions using data from a random

sample of babies born in Pennsylvania in 1989. The data include the baby’s

birthweight (the dependent variable) together with various characteristics of

the mother, including whether she smoked during the pregnancy.

Birthweight=birth weight of infant (in grams)

Smoker=1 if the mother smoked during pregnancy, 0 otherwise.

Alcohol=1 if mother drank alcohol during pregnancy, 0 otherwise

Nprevist=total number of prenatal visits

Unmarried=1 if mother is unmarried, 0 otherwise

Age=age in years

Educ=years of educational attainment (more than 16 years coded as 17)

Each column contains results from regression estimates from a model explaining

Birthweight. An empty cell means that the variable was not included in the model for

that column. For example in column 1 Birthweight was the dependent variable and an

intercept and the smoking dummy variable were the only regressors. Robust Standard

errors are reported in brackets underneath the parameter estimates.

Regressor

Smoker

(1)

-253.2

(26.8)

Alcohol

(2)

-217.6

(26.1)

-30.5

(72.6)

34.1

(3.6)

(3)

– 175.4

(26.8)

-21.1

(73.0)

29.6

(3.6)

-187.1

(27.7)

(4)

– 177.0

(27.3)

– 14.8

(72.9)

29.8

(3.6)

-199.3

(31.0)

Nprevist

Unmarried

Age

Educ

-2.5

(2.4)

-0.238

(5.53)

3199.4

(90.6)

Intercept

3432.1

(11.9)

3051.2

(43.7)

3134.4

(44.1)

SER

583.7

0.028

3000

570.5

0.072

3000

565.7

0.087

3000

565.8

0.087

3000

n

a) What is the value of the estimated effect of smoking on birthweight in each of

the regressions? (include units)

b) Construct a 95% confidence interval for the effect of smoking on birthweight,

using each of the regressions.

c) Is it likely that the coefficient on Smoker in regression (1) suffers from omitted

variables bias? Explain.

d) Is it likely that the coefficient on smoker in regression (2) suffers from omitted

variable bias? Explain.

e) Consider the coefficient on Unmarried in regression (3).

(i) Construct a 95% confidence interval for the coefficient.

(ii) is the coefficient statistically significant? Explain.

(iii) is the magnitude of the coefficient large? Explain.

(iv) A family advocacy group notes that the large coefficient suggests that

public policies that encourage marriage will, on average, lead to healthier

babies. Do you agree?

(Hint: Review the discussion of control variables in section 7.5 of SW 3rd

updated edition or section 6.8 of the 4th edition. Think of the various factors

that Unmarried may be controlling for and how this affects the interpretation

of its coefficient. Is it likely that the coefficient on Unmarried represents a

causal effect of marriage or is it controlling for other factors?)

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Statistics Knowledge

APPLIED ECONOMETRICS

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