課程資訊

Econometrics (Ⅰ)

102-1

Fin8036

723ED6000

Ceiba 課程網頁
http://ceiba.ntu.edu.tw/1021econometrics02

This is the rst course in econometric theory for Ph.D. students; well prepared Master students are also welcome to take this course. This course requires knowledge of probability theory, multivariate statistics, and linear (matrix) algebra; econometrics at master level is not a prerequisite, however. In this course, I will follow my own lecture notes, with some textbooks assigned as complementary reading. Unlike most econometrics textbooks that are organized according to models, my notes are arranged by theories (methods), with
applications to various models. What I hope is that, by introducing econometric theory in this way, students will learn how an econometric method is derived and why it works.

The lectures will be in English; classroom discussion may be in Mandrin if so desired. Students are also required to be familiar with at least one programming language. A senior student will introduce basic programming in R in the beginning lectures; some basic materials about R installation and introduction can be found in the class website (see below). You may choose to program in matlab or other languages.

Part I: Review of Classical and Generalized Least Squares Theory (Chapters 3-4 of R1; S2; S4)

Part II: Asymptotic Least Squares Theory (Chapters 5-7 of R1; R2; R3)
II.1 Elements of Probability Theory
II.2 Asymptotic Properties of the OLS Estimator
II.3 Consistent Estimation of Covariance Matrix
II.4 Large Sample Tests
II.5 Autoregression of an I(1) Variable and Unit-Root Tests
II.6 Tests of Stationarity against I(1)
II.7 Regressions of I(1) Variables and Cointegration

Part III: Nonlinear Least Squares (NLS) Theory (Chapter 8 of R1; S1)
III.1 Nonlinear speci cations
III.2 NLS estimator
III.3 Asymptotic properties of the NLS estimator
III.4 Large sample tests

Part IV: Quasi-Maximum Likelihood (QML) Theory (Chapters 9-10 of R1; R3; S3)
IV.1 Kullback-Leibler information criterion
IV.2 Asymptotic properties of the QML estimator
IV.3 Information matrix equality
IV.4 Large sample tests { Nested models
IV.5 Large sample tests { Non-nested models
IV.7 Applications: ARMA models
IV.8 Applications: Volatility models

Office Hours

S1. Davidson, R. and J. G. MacKinnon, Estimation and Inference in Econometrics, Oxford University Press, 1993.
S2. Greene, W. H., Econometric Analysis, 6th ed., Pearson Prentice Hall, 2008.
S3. Hamilton, J., Time Series Analysis, Princeton University Press, 1994.
S4. Kuan, C.-M., Elements of Matrix Algebra, Lecture Notes.

(僅供參考)

 No. 項目 百分比 說明 1. One midterm 40% 2. One final 45% 3. Homework 15%

 課程進度
 週次 日期 單元主題 第1週 09/09 Ch1: Linear and Matrix Algebra; Ch2: Statistical Concepts; Ch3: Classical Least Squares Theory; Ch4: Generalized Least Squares Theory; Ch5: Elements of Probability Theory; Ch6: Asymptotic Least Squares Theory:Part I; Ch8: Nonlinear Lest Squares Theory; Ch9: Quasi-Maximum Likelihood Theory; Ch10: Quasi-Maximum Likelihood:Applications; Slide 1: Classical Least Theory; Slide 2: Elements of Probability Theory; Slide 3: Asymptotic Least Squares Theory; Slide 4: Nonlinear Least Squares Theory; Slide 5: Quasi Maximum Likelihood Theory; Slide 6: Introduction to Time Series Analysis; 第2週 09/16 Slides: Classical Least Squares Theory (2010.09.23 Update, Note: the changes are mainly in the section of GLS); Ch4: Generalized Least Squares Theory (2010.09.23 Update, Note: only 4.3.3 and some home problems of Chap 4 in the notes have been modified.) 第3週 9/23 Note: R (2010.10.01 Update, 講義更新的部分是example 6 以及習題第四題) 第4週 09/30 Ch5: Elements of Probability Theory; Ch6: Asymptotic Least Squares Theory: Part I; Slides: Elements of Probability Theory (2010.10.04) 第5週 10/07 R_HW_20101011 (2010.10.12 Update) 第6週 10/14 Slides: Asymptotic Least Squares Theory (2010/10/19 Update); Ch3: Classical Least Squares Theory; Ch4: Generalized Least Squares Theory; Ch5: Elements of Probability Theory; Ch6: Asymptotic Least Squares Theory: Part I (2010.10.19 Update) 第8週 10/28 Ch6: Asymptotic Least Squares Theory: Part I (2010.11.01 Update); R_HW_20101101 (2010.11.02 Update) 第11週 11/18 Slides: Nonlinear Least Squares Theory (2010.11.22) 第12週 11/25 Slides: Quasi Maximum Likelihood Theory (2010.11.29); Lectures: Ch8: Nonlinear Least Squares Theory & Ch9: Quasi-Maximum Likelihood Theory (2010.11.29) 第15週 12/16 Slides: Quasi Maximum Likelihood Theory (2010.12.20);Lec-TimeSeries_slide_Fall2010 (2010.12.20) 第15週 12/16 Slides: Quasi Maximum Likelihood Theory (2010.12.20);Lec-TimeSeries_slide_Fall2010 (2010.12.20) 第16週 12/23 Ch9: Quasi-Maximum Likelihood Theory (2010.12.27 Update); Ch10: Quasi-Maximum Likelihood: Applications (2010.12.27) 第17週 12/30 Lec-TimeSeries_slide_Fall2010 (2011.1.10 Update)