**YORK
UNIVERSITY**

**GRADUATE STUDIES**

**DEPARTMENT OF ECONOMICS**

__ECONOMICS____ 5025__

**ECONOMETRICS**

Course Director: Joann Jasiak

Office: 1062 Vari Hall

E-mail: jasiakj@yorku.ca, phone: 416
736-2100 ext. 77045

http://www.jjstats.com

Office hours: Mon, Wed 3:4

Teaching Assistant: TBA

TA phone , TA e-mail:

__Course Description__

This
is an intermediate course for students who have already taken an introductory
course(s) in econometrics or regression analysis. The objective is to introduce
students to the estimation and testing methods used in practice, and to provide
sufficient theoretical background for the extensions of the general linear
model. Those extensions will include the heteroscedasticity, error-in-variables
models, mulivariate linear models and their
estimators. Nonlinear models such as the Poisson, logit and probit
models, and the maximum likelihood estimator will also be covered. This course
will be focused on the analysis of cross-section data. Time series methods will
be discussed in Winter in the Econ5220 course. All theoretical concepts will be
illustrated in class by empirical examples. Additional examples and problems
will be provided to students in assignments. Students will be allowed to work
in teams of two or (maximum) three. Suggested software are SAS, STATA and R.
Students who are not familiar with any of these can use SAS codes available
from this website. The prerequisites for this course are basic calculus,
mathematical statistics and matrix algebra. Detailed instructions on how to use
SAS on WEBFAS are provided on the ECON website. In order to access SAS go to:
https://webfas.yorku.ca/Citrix/WEBFASWeb/

__Requirements, Evaluation and Other
Details__

1. Mid-term exam 30%: date of exam, October 25

2. Final exam 50% (date to be determined later)

3. Assignments 20%: to be handed in on
October 18, November 15 and 29.

__Books and Other Materials__

**Required: Greene, W.H.
"Econometric Analysis", Prentice Hall editions 6 ^{th}, 7th
or 8th**

**Suggested:**

lecture notes for Econ 5025 at http://www.jjstats.com

Ajmani, V.B. "Applied Econometrics Using the SAS
System", Wiley 2009.

Davidson, R., and J. MacKinnon
"Estimation and Inference in Econometrics", Oxford University Press,
1993

Gourieroux, C., and A. Monfort
"Statistics and Econometric Models", Vol I and II, Cambridge
University Press 1995

__Course Content__

1. Review: General Linear Regression
Model and OLS (Greene 2,3)

2. Small sample properties of the
OLS (Greene 4)

3. Asymptotic theory and the
asymptotic properties of the OLS (Greene 4)

4. Maximum Likelihood (ML)
estimator-properties, examples: linear, binomial and Poisson models (Greene 16)

5. Restricted estimation, asymptotic
tests: Wald, LM, LR; (Greene 5)

6. Heteroscedasticity and Seemingly
Unrelated Regression (SUR) model (Greene 10)

7. Panel data, the Generalized Least
Squares (GLS) estimator (Greene 11)

8. Error-in-variable model, the Method of Moments (MM) and Instrumental
Variables (IV) estimators (Greene 12)

9. Simultaneous equations model and
the Two-Stage Least Squares (2SLS) estimator (Greene 13)

10. Probit
and Logit models for qualitative variables, ML (Greene 16)