Econometrics I (Advanced Probability and Statistics) 2012 Fall

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General Information

  • Lectures: Thursdays 14:00-16:45.
  • Classroom: South Bld 308
  • Office Hour: Wednesday 2:00-3:00pm or by appointment
  • Office: North Building #413
  • Phone: 021-52301191

Prerequisites

  • Calculus, linear algebra, undergraduate probability and statistics

Overview

This course is mainly intended for doctoral students majoring in economics and finance. We introduce key concepts such as probability, expectation, conditional expectation, distribution, etc., in a measure-theoretical way. It follows by basic asymptotic theory and the theory of hypothesis testing. If time allows, we also study adanced topics such as martingales and stochastic integration.

Textbooks

The above book and additional problem sets will be enough, but the following books would also be useful. The scope of Bierens (2005) will be the most similar to this course. Rosenthal (2006) and Williams (2001) both are very readable. Dudley (2003) is for more advanced reading on probability theory.

  1. Bierens (2005), Introduction to the Mathematical and Statiscal Foundations of Econometrics, Cambridge University Process.
  2. Rosenthal (2006), A First Look at Rigorous Probability Theory (2nd Ed.) World Scientific.
  3. Williams (2001), Probability with Martingales, Cambridge University Process.
  4. Dudley (2003), Real Analysis and Probability (2nd Ed.), Cambridge University Process.

Outline

  • Introduction to probability
  • Random variable
  • Expectation
  • Distributions and transformations
  • Hypothesis tests
  • Asymptotic theory

Problem Sets

  • We will have 6 problem sets.

Grading

Homework (40%), Final Exam (60%).

 

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Last updated: Sep 7, 2012