Readings

Texts

Part 1

The text, which will be followed closely, is:

Casella, George, and Roger Berger. Statistical Inference . 2nd 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. 5th ed. Upper Saddle River, NJ: Prentice-Hall, 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

TOPICS READINGS
A. Brief review of probability
Brief review of probability Casella and Berger. Statistical Inference. Chapters 1-4.
B. Random samples and asymptotic methods
Sampling and sums of random variables Casella and Berger. Statistical Inference. Sections 5.1-5.3.
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 Cramer-Rao 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

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. 3rd ed. New York, NY: W.W. Norton and Company, 1992, pp. 198-214. ISBN: 9780393957358.

Newey, W. "Convergence Rates and Asymptotic Normality for Series Estimators." Journal of Econometrics 79 (1997): 147-168.

Buy at MIT Press Judd, K. "Approximation Methods." Chapter 6 in Numerical Methods in Economics. Cambridge, MA: MIT Press, 1998, pp. 195-249. 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.
Gauss-Markov optimality
Finite-sample inference under normality and non-normality
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.