Syllabus system

2005年度上智大学シラバス

◆BUSINESS AND ECONOMIC FORECASTING　－　（後）

OZAKI VALERIE

○講義概要

One of the most important uses of statistics in business and economics is to forecast future economic conditions. This course considers economic forecasting using various approaches such as multiple regression models, seasonal adjustment, exponential smoothing, Box-Jenkins ARIMA modeling, and simultaneous equation econometric models. Prerequisite: IBE 340.

○評価方法

レポート(40%)、後期学期末試験(定期試験期間中)(25%)、中間試験(25%)
Case Study 10%

○テキスト

Hanke and Wichern『Business Forecasting (8th edition)』 Prentice-Hall
Mendenhall, Beaver and Beaver『A Brief course in Business Statistics』 Brooks/Cole
Newbold and Bos『Introductory Business and Economic Forecasting』

○参考書

Walter Enders『Applied Econometric Time Series』Wiley, 2003

○必要な外国語

English

○他学部・他学科生の受講

可

○ホームページURL

www.fcc.sophia.ac.jp/academic/syllabus/IBE476_Ozaki.pdf

○授業計画

1	Introduction to Time Series
2	Simple Linear Regression (Chapter 6) Review and extensions of material studied in IBE340
3	Multiple Regression Analysis (Chapter 7) Review and extensions of material studied in IBE340
4	Multiple Regression Analysis (Chapter 7) Review and extensions of material studied in IBE340
5	Regression with Time Series data (Chapter 8) Autocorrelated errors, spurious regression
6	Regression with Time Series data (Chapter 8) Autocorrelated errors, spurious regression
7	Time Series and their Components (Chapter 5)
8	MID-TERM Time Series and their Components (Chapter 5)
9	Introduction to Box-Jenkins ARIMA Methodology (Chapter 9) Stationarity,autocorrelation function
10	Box-Jenkins ARIMA Methodology (Chapter 9) Autoregressive and moving average processes
11	Box-Jenkins ARIMA Methodology (Chapter 9) ARMA models, model fitting and checking
12	Box-Jenkins ARIMA Methodology (Chapter 9) Trends, seasonality, test for unit roots
13	Vector Autoregressive (VAR) models and Granger Causality(Chapter 5, Enders)
14	Volatility – ARCH and GARCH models (Chapter 3, Enders) Panel Data Analysis (PcGive manual) Econometric Modeling – cointegration and error-correction models (Chapter 6, Enders)