EC828 Econometric Theory II         Fall 2006          Boston College    
Prof. Arthur Lewbel, Dept. of Economics, Admin. bldg 491,  617-552-3678   

                                  OVERVIEW
This is a course in asymptotic theory for econometric estimation and inference, with emphasis on nonlinear, cross section models. Topics include forms of convergence, consistency and limiting distribution theory, maximum likelihood, linear and nonlinear least squares, generalized method of moments, extremum estimators, nonparametric kernel estimators, and semiparametric estimators. 

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 econometric models with stationary (usually iid) data, using asymptotic methods. The course will not cover bayesian or time series topics. 

Prerequisites: EC 827 or equivalent. Students are assumed to have training in calculus, probability, statistics, matrix algebra, and linear regression models. 

You do not need to buy a textbook for this class. Most of the course material will come from the following 5 sources:

(G)   Greene, W. H. (2000), "Econometric Analysis," 4th or 5th edition, Prentice Hall. These will mainly be back up readings, material in class will mostly be covered at a more advanced level than Greene.

(Z)   Zivot, Eric (2005) "A Primer on Asymptotics,"
http://faculty.washington.edu/ezivot/econ583/econ583asymptoticsprimer.pdf

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

(NM)   "Large Sample Estimation and Hypothesis Testing," by Newey, W.K., and McFadden, D., Chapter 36 of Engle, R.F. and D. L. McFadden (1994) "Handbook of Econometrics, vol. IV," North-Holland.

(HL)   "Applied Nonparametric Methods," by Hardle, W. and Linton, O., Chapter 38 of Handbook of Econometrics vol. IV as above.

(P)    "Estimation of Semiparametric Models," by Powell, J., Chapter 41 of Handbook of Econometrics vol. IV as above.

Other books you may find useful for alternative coverage of these topics:
Wooldridge, J. M. (2002) Econometric Analysis of Cross Section and Panel Data.
Spanos, A., (1990) Statistical Foundations of Econometric Modeling.
Mittelhammer, R.C., G.G. Judge, and D.J. Miller, (2000) Econometric Foundations. 
Pagan, A. and A. Ullah, (1999) Nonparametric Econometrics. 
  
GRADING: midterm: 50%, Final: 50%. 

          			           SYLLABUS
1. Properties of Estimators, Asymptotic Theory
Z 1-3; S 1-2; G 4,

2. Linear Models - OLS and GLS Estimation
 G 6, 11.1-11.4, 9, 11, 12; Z 4

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
Sections 1, 2, and 3 of "The Bootstrap," by Horowitz, J.L., Chapter 52. Heckman, J.J. and E. Leamer (2001), "Handbook of Econometrics, vol. V," North-Holland.