EC828 Econometric Theory II         Spring 2004          Boston College    
Prof. Arthur Lewbel, Dept. of Economics, Admin. bldg 491,  617-552-3678   

                                  OVERVIEW
This course is intended for advanced (2nd year) graduate students in economics. The aim is to cover a range of important topics in modern econometric theory. The focus is on the construction, analysis, and theory of linear and nonlinear models with stationary (usually iid) data, using asymptotic methods. The course will not cover bayesian or time series topics. Students are assumed to have training in calculus, probability, statistics, matrix algebra, and linear regression models. 

Most of the material in this course will come from the following 5 sources:

(G)   Greene, W. H. (2000), "Econometric Analysis," 4th or 5th edition, Prentice Hall. 

(S)   Serfling, R.J., (1980) "Approximation Theorems of Mathematical Statistics," Wiley. Only the first few chapters will be used.

Engle, R.F. and D. L. McFadden (1994) "Handbook of Econometrics, vol. IV," North-Holland, and Heckman, J.J. and E. Leamer (2001), "Handbook of Econometrics, vol. V," North-Holland. The following chapters from this handbook will be used. They can be downloaded for free from http://www.elsevier.com/hes/books/02/menu02.htm 

(NM)   "Large Sample Estimation and Hypothesis Testing," by Newey, W.K., and McFadden, D., Chapter 36. 

(HL)   "Applied Nonparametric Methods," by Hardle, W. and Linton, O., Chapter 38.

(P)    "Estimation of Semiparametric Models," by Powell, J., Chapter 41. 

(H)    "The Bootstrap," by Horowitz, J.L., Chapter 52. 

Other books you may find useful for additional reading are:
  Primarily for the earlier parts of the term:
Amemiya, T. (1985) Advanced Econometrics.
Spanos, A., (1990) Statistical Foundations of Econometric Modeling.
Mittelhammer, R.C., G.G. Judge, and D.J. Miller, (2000) Econometric Foundations. 
  Primarily for the later parts of the term:
Lee, M.J., (1996) Methods of Moments and Semiparametric Econometrics For Limited Dependent Variables Models.
Pagan, A. and A. Ulah, (1999) Nonparametric Econometrics. 
  
GRADING: midterm: 50%, Final: 50%. 

          			           SYLLABUS
1. Properties of Estimators, Asymptotic Theory
S 1, 2 G 4,

2. Linear Models - OLS and GLS Estimation
G 6, 11.1-11.4, 9, 11, 12.

3. Consistency 
NM 2-2.3, 2.7

4. Maximum Likelihood Estimation
G 4.5, 19, NM 2.4, 3.0-3.2

5. Nonlinear Least Squares, Extremum Estimation
G 10, 5, NM 2.2, 3.1-3.5 

6. Least Absolute Deviations and other Extremum Estimators
G 9.8, NM 2.8, 7

7. The Generalized Method of Moments
G. 4.7, 11.5-11.6, NM 2.5, 3.3

8. Two Step Estimators, Generated Regressors, and Nuisance Parameters 
NM 6, G. 4.6

9. Latent Variable, Index, and Limited Dependent Variable Models
G 19, 20, and skim P 3, will cover that more deeply later.

10. Nonparametric Density Estimation
HL 1,2 

11. Nonparametric Regression
HL 3,4,5 

12. Semiparametric Estimators 
HL 6, P 1, 2.5, 3

-if time permits, will also cover

13. General hypothesis Testing for Extremum, GMM, and related estimators
NM 9, G 4.8, 4.9, 6.8, 7, 9.6, 10.4, 11.6 

14. The Bootstrap and other Resampling Techniques
B 1, 2, 3.