Econ 627
Econometric Theory II
2013-14 Winter Session
Vadim Marmer
Office: BuTo 1016
Phone: (82)2-8217
Email: vadim.marmer@gmail.com
Time and Location: Tuesdays & Thursdays, 9:30AM - 10:50PM, Buch D222.
Office Hours: Wednesdays 11AM-noon.
Course web-page: http://www.econ.ubc.ca/vmarmer/econ627
TA: Jutong Pan, panjutong@gmail.com
Discussion group: Mondays, 1PM-2:30PM, Neville Scarfe, 203.
Office hours: Mondays, 3:00PM-4:00PM, BuTo, 1099C.
Web-page: https://sites.google.com/site/jutongpan/ta-courses/econ627
Textbooks:
I will provide lecture notes that will cover the essential part of the material. The main textbook for the
course is Econometrics by Fumio Hayashi, Princeton University Press, New Jersey, 2000 (required). Answers
to selected questions, data sets for empirical exercises and other accompanying materials are available on
the web from http://fhayashi.fc2web.com/hayashi_econometrics.htm . Additional textbooks/sources that
students might find helpful include:
• J. Davidson, Stochastic Limit Theory: An Introduction for Econometricians, Advanced Texts in Econometrics, Oxford University Press, New York, 1994.
• J.R. Magnus and H. Neudecker, Matrix Differential Calculus with Applications in Statistics and Econometrics, John Wiley & Sons, New York, 1999.
• H. White, Asymptotic Theory for Econometricians, Revised Edition, Academic Press, 2001.
• Bruce Hansen’s Lectures on Econometrics, available online at
http://www.ssc.wisc.edu/~bhansen/econometrics/
• Peter Phillips’ Lecture Notes on Stationary and Nonstationary Time Series and Unit Roots and Cointegration, see http://cowles.econ.yale.edu/korora/phillips/teach/lec-notes.htm
Course Description:
This course is a continuation of Econ 626. We will start with a discussion linear econometric models,
linear simultaneous equations, and system estimation methods. Nonlinear models will be covered in the
context of extremum estimation. We will cover a general theory of extremum estimators with the main focus
on generic approaches for establishing consistency and asymptotic normality of extremum estimators. The
course will conclude with various topics in stationary and nonstationary time series econometrics. Students
will receive analytical and practical exercises. The practical questions will require handling and analyzing
data with MATLAB, Gauss, or similar software. Grading: There will be regular (weekly) assignments
(20% of the final grade), a midterm exam (30%), and a final exam (50%).
Topics:
1. Linear simultaneous equations. Identification and estimation methods: GMM, 2SLS, 3SLS, FIML
and LIML.
2. Extremum estimators. Asymptotic normality and consistency of extremum estimators including
MLE, GMM estimator for nonlinear models, Classical Minimum Distance estimator, and quantile
regression.
3. Time series. Dependence structure, ergodicity, stationarity, mixing processes, LLNs and CLTs for
weakly dependent data, linear regression with weakly dependent data, HAC variance estimation, Wold
decomposition, linear processes.