ECON 501.2 (Spring 1999)
Introduction to Statistics and Econometrics
for Ph.D. Students in Economics
Instructor: Prof. Herman J. Bierens (Tel.: 865-4921, email: hbierens@psu.edu)
Office hours: Wednesday 2-4 pm (Kern 510)
T.A.: Sergei Izmalkov
Office hours: Wednesday 5-7 pm (Sparks 218)
Time: Tuesday-Thursday 9:45-11:00 am. Place: 319 Willard
The objective of this course is to prepare the first year Ph.D.
students in economics for the study of econometrics, by providing a
rigorous introduction to probability and measure theory,
mathematical statistics, and the classical multivariate linear regression
model. Each week a number of exercises from the text books will be assigned
as homework. At the end of the semester also some econometric exercises
may be assigned that require the use of a PC and econometrics software. The final grade is
determined by the homework (20%), a written closed-book mid-term exam (40%),
and a written closed-book final exam (40%).
Required textbooks
- [RG] A. Ronald Gallant, An Introduction to Econometric Theory, Princeton
University Press
- [HC] R.V. Hogg and A.T. Craig, Introduction to Mathematical Statistics (Fifth Ed.),
Macmillan
Topics
- Introduction to probability [RG, Ch. 1-3; HC, Ch. 1]
- Multivariate distributions [HC, Ch.2]
- Discrete distributions: Binomial and Poisson distributions [HC, Ch.3]
- Normal, t- and Chi-square distributions [HC, Ch. 3]
- Functions of random variables [RG, Ch.3; HC, Ch. 4]
- The multivariate normal distribution [Lecture notes; RG, Sec. 3.8; HC, Sec. 4.10, 10.8,
10.9]
- Modes of convergence, the law of large numbers and the central limit theorem [Lecture
notes; RG, Ch.4; HC, Ch. 5]
- Statistical inference [RG, Ch.5; HC, Ch. 6 + 9]
- Maximum likelihood estimation and testing [Lecture notes]
- The classical linear regression model [Lecture notes]
- Hypothesis tests with the multiple regression model [Lecture notes]
- Asymptotic theory of the linear regression model [Lecture notes]