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

2.7
Illustrative Examples
45
Summary and Conclusions
48
Exercises
48
CHAPTER 3
Two-Variable Regression Model: The
Problem of Estimation
55
3.1
The Method of Ordinary Least Squares
55
3.2
The Classical Linear Regression Model: The
Assumptions Underlying the Method 
of Least Squares
61
A Word about These Assumptions
68
3.3
Precision or Standard Errors 
of Least-Squares Estimates
69
3.4
Properties of Least-Squares Estimators: 
The Gauss–Markov Theorem
71
3.5
The Coefficient of Determination 
r
2
: 
A Measure of “Goodness of Fit”
73
3.6
A Numerical Example
78
3.7
Illustrative Examples
81
3.8
A Note on Monte Carlo Experiments
83
Summary and Conclusions
84
Exercises
85
Appendix 3A
92
3A.1
Derivation of Least-Squares Estimates
92
3A.2
Linearity and Unbiasedness Properties 
of Least-Squares Estimators
92
3A.3
Variances and Standard Errors 
of Least-Squares Estimators
93
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Contents
vii
3A.4
Covariance Between 
β
ˆ
1
and 
β
ˆ
2
93
3A.5
The Least-Squares Estimator of 
σ
2
93
3A.6
Minimum-Variance Property 
of Least-Squares Estimators
95
3A.7
Consistency of Least-Squares Estimators
96
CHAPTER 4
Classical Normal Linear Regression