課程資訊
課程名稱
計量經濟學一
ECONOMETRICS(I) 
開課學期
99-1 
授課對象
管理學院  財務金融學研究所  
授課教師
管中閔 
課號
Fin8036 
課程識別碼
723ED6000 
班次
 
學分
全/半年
半年 
必/選修
必修 
上課時間
星期一6,7,8(13:20~16:20) 
上課地點
管二204 
備註
本課程以英語授課。本課程以英語授課。
總人數上限:15人 
Ceiba 課程網頁
http://ceiba.ntu.edu.tw/991econometrics 
課程簡介影片
 
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課程概述

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.  

課程目標
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 
課程要求
 
預期每週課後學習時數
 
Office Hours
另約時間 備註: Tuesday 4-6 or by appointment 
參考書目
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. 
指定閱讀
R1. Kuan, C.-M., Introduction to Econometric Theory, Slides and Notes, available at: ceiba.ntu.edu.tw/991econometrics (for nance students)
ceiba.ntu.edu.tw/991econometrics3 (for economics and IB students)
homepage.ntu.edu.tw/ckuan

R2. White, H., Asymptotic Theory for Econometricians, revised ed., Academic Press, 1999.

R3. White, H., Estimation, Inference and Speci cation Analysis, Cambridge University Press, 1994.

R3. White, H., Estimation, Inference and Speci cation Analysis, Cambridge University Press, 1994.  
評量方式
(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
9/14  1. Syllabus 2. R Installation Instructions 3. Ch1: Linear and Matrix Algebra 4. Ch2: Statistical Concepts 5. Ch3: Classical Least Squares Theory  
第2週
9/20  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
9/28  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
10/05  Ch5: Elements of Probability Theory; Ch6: Asymptotic Least Squares Theory: Part I; Slides: Elements of Probability Theory (2010.10.04) 
第5週
10/12  R_HW_20101011 (2010.10.12 Update) 
第6週
10/19  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
11/02  Ch6: Asymptotic Least Squares Theory: Part I (2010.11.01 Update); R_HW_20101101 (2010.11.02 Update) 
第11週
11/23  Slides: Nonlinear Least Squares Theory (2010.11.22) 
第12週
11/30  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
12/20,12/21  Slides: Quasi Maximum Likelihood Theory (2010.12.20);Lec-TimeSeries_slide_Fall2010 (2010.12.20) 
第16週
12/28  Ch9: Quasi-Maximum Likelihood Theory (2010.12.27 Update); Ch10: Quasi-Maximum Likelihood: Applications (2010.12.27) 
第17週
1/04  Lec-TimeSeries_slide_Fall2010 (2011.1.10 Update)