The McGraw-Hill Series Economics essentials of economics brue, McConnell, and Flynn Essentials of Economics

Empirical Exercises
6.14. You are given the data in Table 6.7.
**
Fit the following model to these data and obtain
the usual regression statistics and interpret the results:
100
100
−
Y
i
=
β
1
+
β
2
1
X
i
guj75772_ch06.qxd 27/08/2008 10:41 AM Page 178

---

Chapter 6
Extensions of the Two-Variable Linear Regression Model
179
b.
Based on this plot, do you think the following models might fit the data equally
well?
Invrate
i
=
β
1
+
β
2
Savrate
i
+
u
i
ln Invrate
i
=
α
1
+
α
2
ln Savrate
i
+
u
i
c.
Estimate both of these models and obtain the usual statistics.
d.
How would you interpret the slope coefficient in the linear model? In the log–
linear model? Is there a difference in the interpretation of these coefficients?
e.
How would you interpret the intercepts in the two models? Is there a difference in
your interpretation?
f.
Would you compare the two 
r
2
coefficients? Why or why not?
g.
Suppose you want to compute the elasticity of the investment rate with respect to
the savings rate. How would you obtain this elasticity for the linear model? For
the log–linear model? Note that this elasticity is defined as the percentage change
in the investment rate for a percentage change in the savings rate.
h.
Given the results of the two regression models, which model would you prefer?
Why?
6.16. Table 6.9* gives the variable definitions for various kinds of expenditures, total
expenditure, income, age of household, and the number of children for a sample of
1,519 households drawn from the 1980–1982 British Family Expenditure Surveys.