1 Introduction
I Regression
2 Conditional Expectation and Projection
3 The Algebra of Least Squares
4 Least Squares Regression
5 Normal Regression
II Large Sample Methods
6 A Review of Large Sample Asymptotics
7 Asymptotic Theory for Least Squares
8 Restricted Estimation
9 Hypothesis Testing
10 Resampling Methods
III Multiple Equation Models
11 Multivariate Regression
12 Instrumental Variables
13 Generalized Method of Moments
IV Dependent and Panel Data
14 Time Series
15 Multivariate Time Series
16 Nonstationary Time Series
17 Panel Data
18 Difference in Differences
V Nonparametric Methods
19 Nonparametric Regression
20 Series Regression
21 Regression Discontinuity
VI Nonlinear Methods
22 M-Estimators
23 Nonlinear Least Squares
24 Quantile Regression
25 Binary Choice
26 Multiple Choice
27 Censoring and Selection
28 Model Selection, Stein Shrinkage, and Model Averaging
29 Machine Learning
Appendixes
A Matrix Algebra
B Useful-Inequalities
Hansen, Bruce [Àú]
Bruce Hansen lives in Portland, Oregon and spends most of the good weather riding and writing about the best motorcycling roads in the Pacific Northwest. He is a contributor to Morotcycle Cruiser, Rider, RoadBike, American Iron, and Motorcycle Voyager magazines. When he''s not on his bike, behind his camera, or in front of his computer, he teaches a distance writing class through Portland State University.