# Assignment #5 Simple Regression Model

Assignment #5 Simple Regression Model

1. Let kids denote the number of children ever born to a woman, and let educ denote years of education for the woman. A simple model relating fertility to years of education is

where u is the unobserved error.

(i)  What kinds of factors are contained in u? Are these likely to be correlated with level

of education?

(ii)  Will a simple regression analysis uncover the ceteris paribus effect of education

on fertility? Explain.

1. The data set in CEOSAL2 contains information on chief executive officers for U.S. corporations. The variable salary is annual compensation, in thousands of dollars, and ceoten is prior number of years as company CEO.

(i)  Find the average salary and the average tenure in the sample.

(ii)  How many CEOs are in their first year as CEO (that is, ceoten = 0)? What is the longest tenure as a CEO?

(iii)  Estimate the simple regression model

and report your results in the usual form. What is the (approximate) predicted percentage increase in salary given one more year as a CEO?

3.  Use the data in SLEEP75 from Biddle and Hamermesh (1990) to study whether there is a tradeoff between the time spent sleeping per week and the time spent in paid work. We could use either variable as the dependent variable. For concreteness, estimate the model

where sleep is minutes spent sleeping at night per week and totwrk is total minutes worked during the week.

(i)  Report your results in equation form along with the number of observations and

R2. What does the intercept in this equation mean?

(ii)  If totwrk increases by 2 hours, by how much is sleep estimated to fall? Do you find

this to be a large effect?

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