QUANTITATIVE METHODS
TERM: Fall, 2006
COURSE TIME: Thursday (10:35-12:05 & 13:20-14:50) and Friday (13:20-14:50)
INSTRUCTOR: Kei Kajisa (kajisa@grips.ac.jp) Room C-1209 (ext. 6226) TEACHING ASSISTANT: Yuko Nakano (doc05010@grips.ac.jp) Room C-601 E (ext. 5208) OFFICE HOURS: Kajisa: 17:00-18:00 on Thu and Fri or by appointment. Nakano: 17:00-18:00 on Wed. COURSE DESCRIPTION: The course objective is to provide students with a solid understanding of statistics and econometrics so that they can integrate these quantitative methods with economic theories for the analysis of development issues. rather than theory itself. PREREQUISITES: Pre-acquisition of basic knowledge on calculus, and algebra is highly recommended. TEXTBOOKS: The course relies mainly on the following textbooks: Thomas Wannacott and Ronald Wannacott, Introductory Statistics for Business This course emphasizes application Examples use data on economic growth and development.
and Economics, 4th edition, John Wiley & Sons, 1990. (for statistics part)
Damodar Gujarati, Essentials of Econometrics, 2nd edition, McGraw-Hill, 1999. (for econometrics part) Supplementary textbooks for advanced studies and practical applications are: Jeffrey M. Wooldridge, Introductory Econometrics: A Modern Approach, 2nd edition, South-Western College Publishing, 2003 Damodar Gujarati, Basic Econometrics, 3rd edition, McGraw-Hill, 1995 Peter Kennedy, A Guide to Econometrics, 4th edition, Blackwell, 1998.
1
COURSE WEB SITE: Announcements about this course are posted on the website. source web sites, etc. http://www3.grips.ac.jp/~kajisa/courses.htm SOFTWARE: This course uses the statistical software STATA® to analyze data. available at the computer lab. This software is Students The manuals are available at GRIPS library. The site also provides you with syllabus, handouts, problem sets materials, links to useful economics and data
who are familiar with other statistical software may use it in their homework. COURSE STRUCTURE: The course consists of lectures and laboratory sections. used for exercises and computational work. PROBLEM SETS: Problem sets, which include problem solving and computer tasks, will be passed out in class and posted on the Course Web site. Data sets used for computational tasks will be placed on the Course Web site. Credit will NOT be given for late submission. The laboratory sections will be
Getting the “right” answer is often less important than knowing how to obtain the correct answer. Show your work in your homework, or you will not get full points. If you hand in printouts of spreadsheets (e.g. Excel or Lotus) as a part of your answers, you have to explain how you calculate either by words or formulas in your answers. You may work together with other classmates on problem sets (I encourage you to do so.) However, you must always write up your own answers independently. Also, your answer sheet must be legible. COURSE GRADING: Course grading is based on problem sets, and two exams. Problem Sets 10%, Midterm exam 40%, Final exam 50%. score. The allocation is as follows: The numerical score will be
converted to the letter grades (A, B and C) according to the relative position of your If the numerical score is below 60, however, the letter grade D will be given.
2
COURSE SHEDULE AND READINGS: *indicates supplementary readings. Date 10/6 Topic and Readings INTRODUCTION W Ch. 1 10/12, 13 *G Ch. 1
I. DESCRIPTIVE STATISTICS
I-1. Descriptive Statistics
W Ch. 2 *G Ch. 2 & 3
I-2. Applications of Descriptive Statistics: Measures of inequality
Gills, Malcolm, Dwight H. Perkins, Michael Roemer, and Donald R. Snodgrass, Economics of Development, 4th edition, Ch. 4, pp. 70 – 76. *Debraj Ray, Development Economics, Chapter. 6 Section 3, Measuring economic inequality, pp. 173-192. 10/19, 20
I-3. Index Numbers
W Ch. 22
I-4. Applications of Index Numbers: (1) Price indexes, Production indexes, (2) Real exchange rates and PPP (3) Measurement of poverty, (4) The Human development index
Gills, Malcolm, Dwight H. Perkins, Michael Roemer, and Donald R. Snodgrass, Economics of Development, 4th edition, Ch. 3, pp37 – 41 Debraj Ray, Development Economics, Ch. 2 Sect. 4, The Many faces of underdevelopment, pp. 25-33. *UNDP, Human Development Report, 2004, pp. 139-142 and pp. 258-264.
II. PROBABILITY AND STATISTICAL INFERENCE
10/26, 27
II-1. Probability
W Ch. 3 and 4 W Ch. 5 *G Ch. 2 and 3
II-2. Two Random Variables
11/2
II-3. Sampling
W Ch. 6 W Ch. 7 *G Ch. 2 and 3
II-4. Point Estimation
3
11/9, 10
II-5. Confidence Interval
W Ch. 8 W Ch. 9 *G Ch. 4
II-6. Hypothesis Testing
11/16, 17
II-6. Hypothesis Testing (cont.)
W Ch. 9
II-7. Analysis of Variance (ANOVA)
W Ch. 10 Section 10-1 11/24 11/30 12/1+ 12/14, 15 12/21, 22 12/28 Midterm Exam
III. REGRESSION ANALYSIS
III-1. Two-Variable Linear Regression: Estimation
G Ch. 5
III-2. Two-Variable Linear Regression: Hypothesis Testing
G Ch. 6 G Ch. 7 G Ch. 9 *W Ch. 11 and 12 *W Ch. 13 *W Ch. 14
III-3. Multiple Regression: Estimation and Hypothesis Testing III-4. Dummy Explanatory Variables III-5. Application of Regression Analysis and Simultaneous Equation Models
G Ch. 7, 8, 15
1/4, 5
III-6. Basic Time Series Analysis
Jeffrey M. Wooldridge, Introductory Econometrics: A Modern
Approach, South-Western College Publishing, Ch. 10.
G Ch. 14.2, 14.3, 14.6 1/11, 12
III-7. Basic Panel Data Analysis
Jeffrey M. Wooldridge, Introductory Econometrics: A Modern
Approach, South-Western College Publishing, Ch. 13 & Ch. 14
1/19 Final Exam
4