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Texts
Part 1
The text, which will be followed closely, is:
Casella, George, and Roger Berger. Statistical Inference . 2^{nd} ed. Pacific Grove, CA: Thomson Learning, 2002. ISBN: 9780534243128.
This book covers all of the material in Part 1 and provides many problems for practice as well as excellent references.
Part 2
Greene, William. Econometric Analysis. 5^{th} ed. Upper Saddle River, NJ: PrenticeHall, 2003. ISBN: 9780130661890.
Errors in the 5th edition may be found here.
You can also find the material in any standard text on regression.
Readings by Topic
Part I
Course readings.
TOPICS 
READINGS 
A. Brief review of probability 
Brief review of probability 
Casella and Berger. Statistical Inference. Chapters 14. 
B. Random samples and asymptotic methods 
Sampling and sums of random variables 
Casella and Berger. Statistical Inference. Sections 5.15.3. 
Laws of large numbers and central limit theorem 
Casella and Berger. Statistical Inference. Section 5.5. 
C. Statistical Theory 
Point estimation 
Casella and Berger. Statistical Inference. Sections 7.2 and 6.2.1. 
Evaluation of estimators: Unbiasedness, sufficiency, consistency, and the CramerRao theorem 
Casella and Berger. Statistical Inference. Sections 7.3, 6.2.1, 6.2.2, and 10.1. 
Interval estimation 
Casella and Berger. Statistical Inference. Chapter 9 and section 10.4. 
Part II
Course readings.
TOPICS 
READINGSS 
D. Fundamentals of regression 
Regression in economics 
Greene. Econometric Analysis. Chapters 2 and 3 (skim chapters 7 and 8.)
Varian, H. "Econometrics." Chapter 12 in Microeconomic Analysis. 3^{rd} ed. New York, NY: W.W. Norton and Company, 1992, pp. 198214. ISBN: 9780393957358.
Newey, W. "Convergence Rates and Asymptotic Normality for Series Estimators." Journal of Econometrics 79 (1997): 147168.
Judd, K. "Approximation Methods." Chapter 6 in Numerical Methods in Economics. Cambridge, MA: MIT Press, 1998, pp. 195249. ISBN: 9780262100717.

Best linear predictor 
Best linear approximation 
Conditional expectation function 
Building functional forms 
E. Regression in finite samples 
Basic regression algebra 
Greene. Econometric Analysis. Chapters 4 and 6. 
GaussMarkov optimality 
Finitesample inference under normality and nonnormality 
F. Regression in large samples 
Consistency 
Greene. Econometric Analysis. Chapters 5, 6, 11, and 12.
Newey, W. "Asymptotic Theory of Least Squares." 14.382 Lecture Notes, Spring 2000.
Remarks on normality (PDF)

Asymptotic Normality 
Heteroscedasticity 
Autocorrelation 
G. Special topics (if time permits) 
Additional Readings
Appendices in Greene collect background material on matrices and large sample theory. See also the lecture notes.