時間數列分析 - 國立中山大學經濟學研究所

國立中山大學 099學年度第2學期課程教學大綱

中文名稱

時間數列分析

課號

M6041006

英文名稱

TIME SERIES ANALYSIS

課程類別

講授類

必選修

選修

系所

經濟學研究所碩士班

授課教師

李慶男

學分

課程網頁

尚未建置

課程大綱

This is a course in Macro econometrics. Econometrics is concerned with the systematic study of economic phenomena using observed data. We will mainly concern on the treatment of parametric modeling. (Therefore, there is a field called Nonparametric Econometrics—see Pagan and Ullah, 1999, Nonparametric Econometrics)
To study the econometrics parametrically, we will first discuss regression analysis. The regression analysis put some variables (especially economic variables) to be some function (linear or nonlinear) of other economic variables and verse vise. These constitute the study of multiple regression and simultaneous equations model.
On the other hand, time series analysis of econometrics, we regard the economics variable is coming from some stochastic mechanism of her own past and new innovation (unit variable time series analysis) and even stochastic function of other variables past value and innovation (vector time series analysis). These two views of econometrics is now somewhat merging. (See Granger, 2001, Macro Econometrics –Past and Future, Journal of Econometrics, 100). With this statistical background, I hope you will have the basic skill to read modern therical Journal article.

課程目標

Let student be more familiar with Time Series Analysis

授課方式

An oral instruction will be employed within all class

評分方式﹝評分標準及比例﹞

1.Home-Work：20%
2.Mid-Term：30%
3.Final Exam：50%

參考書/教科書/閱讀文獻〔請遵守智慧財產權觀念，不可非法影印〕

序號	作者	書名	出版社	出版年	出版地	ISBN#
1	Greene, W. H.	Econometric Analysis, 4th Edition, (Required)	Prentice Hall	2000
2	Hamilton, J. D.	Time Series Analysis(Required)	Princeton University Press	1994
3	White, H.	Asymptotic Theory For Econometricians(Recommended)	Academic Press.	2001
4	Spanos, A	Statistical Foundations of econometric Modeling	Cambridge University press	1986

每週課程內容及預計進度

週次	日期	授課內容及主題
1	2011/02/21~2011/02/27	Statistical Review: sample space, random variable, parametric probability model, sampling, estimation, hypothesis testing. (Spanos)
2	2011/02/28~2011/03/06	Difference equation
3	2011/03/07~2011/03/13	Lag Operators
4	2011/03/14~2011/03/20	Stationary ARMA Model (Hamilton, Ch.3, 5) (i). Population Characteristics (ii). Estimation.
5	2011/03/21~2011/03/27	Stationary ARMA Model (Hamilton, Ch.3, 5) (i). Population Characteristics (ii). Estimation.
6	2011/03/28~2011/04/03	Stationary ARMA Model (Hamilton, Ch.3, 5) (i). Population Characteristics (ii). Estimation.
7	2011/04/04~2011/04/10
8	2011/04/11~2011/04/17	Asymptotic Distribution Theory: i.i.d. process, serially correlated process, and Martingale Difference process. (Hamilton, Ch. 7, White) (i). Law of large number. (ii). Central Limit Theorem
9	2011/04/18~2011/04/24	期中考
10	2011/04/25~2011/05/01	Stationary Vector Time Series (Hamilton, Ch. 10, 11)(i). Law of large number.(ii). Central Limit Theorem
11	2011/05/02~2011/05/08	Stationary Vector Time Series (Hamilton, Ch. 10, 11))(i). Law of large number.(ii). Central Limit Theorem
12	2011/05/09~2011/05/15	Models of Nonstationary Time Series (Hamilton, Ch. 15) (i). Trend Stationary Process (ii). Difference Stationary Process
13	2011/05/16~2011/05/22	Models of Nonstationary Time Series (Hamilton, Ch. 15) (i). Trend Stationary Process (ii). Difference Stationary Process
14	2011/05/23~2011/05/29	Univariate Process with Unit Roots: (Hamilton, Ch. 17) (i). Brownian Motion(ii). Functional Central Limit Theorem (iii). Dickey-Fuller test (iv). Phillips-Perron Tests(v). Augmented Dickey-Fuller Test
15	2011/05/30~2011/06/05	Spurious Regression: (Hamilton, Ch. 18)
16	2011/06/06~2011/06/12	Cointegration: (Hamilton, Ch. 19) (i). Granger Representation Theorem (ii). Engle-Granger Two Step method
17	2011/06/13~2011/06/19	Johansen’s Maximum Likelihood Analysis of Cointegrated System
18	2011/06/20~2011/06/29	期末考

課業討論時間

時段1:
時間：星期一15:10~17:00
地點：社4037
時段2：
時間：星期四15:10~17:00
地點：社4037