SYLLABUS OF ECONOMETRICS
Instructor: ZHOUJIA
Email: maxwelljoel@sina.com
REQUIRED TEXT
1. BASIC ECONOMETRICS, FOURTH EDITION, DAMODAR GUJARATI, MCGRAW-HILL EDUCATION. 2013
DESCRIPTION
This course covers the statistical tools needed to understand empirical economic research and to plan and execute independent research projects. Topics include statistical inference, regression, generalized least squares, instrumental variables, simultaneous equations models, and evaluation of government policies and programs.
PREREQUISITES:
It is expected that you have a good understanding of the intermediate level econometrics before taking this course. The purpose of this course is to survey the more advanced econometric methodology used in modern empirical research; therefore we will not spend much time on the derivation of basic models.
OBJECTIVES
This course provides you with an in-depth understanding of the methodologyand econometric modeling tools that are frequently used in the empirical economic research.
Upon satisfactory completion of the course, students should:
Be able to understand the concepts and principles of econometrics
Enhance their ability to analyze data and solve problems
Familiarize the students with the approaches, techniques of data analysis
COURSE ASSESSMENT
Class Attendance: 10%. Responsible attendance is expected of each individual enrolled in this course. Iwill circulate a sign-up sheet every day that we are scheduled to meet and you will forfeit one full percentagepoint for every unexcused absence beyond three. If you miss a lecture you are responsible for obtaining anymissed notes and/or handouts on your own unless you are officially excused.
You may be officially excused from a class meeting for one of four reasons: (1) You have an illness that prevents you from attending class and a doctor's note to that effect; (2) You have a personal emergency like a death in the family and are either excused before class or can document the emergency afterwards; (3) You have a university sponsored obligation (participation in a sporting event or student organization sponsored project)and are excused before the examination or case presentation; or, (4) You have the absence officially excused in writing by the Dean of Economics & Management.
Group/individual presentation & Class discussion: 20%. During the semester, the students need to conduct an independent research project using the econometric models taught in the course. The topic of your research can be related to any fields within economics, but the project must be empirical, which means data analysis and econometric modeling must be employed. During the 30 minutes presentation, you should clearly introduce your original research question, survey the relevant literature, describe the data and sample, lay out the appropriate model, and summarize the results and implications. Your grade will be based on the originality and rigorousness of your study as well as your presentation performance.
Assignment: 20%. The students should finish the assignments such as key concepts, questions for review, problems and application in the related chapters, and hand in them on time.
Examinations: 50%. There will be 2 examinations (please note specific days and dates listed in the calendar) including the Midterm and Final examinations during this semester. Midterm Exam will be worth 20%, while the Final will be worth 30%. The questions will come from the assigned reading material, the lecture notes, as well as classdiscussions and exercises. Test paper will be presented withdefining, multiple choice, true/false, short essay, and long essay questions.
COURSE CONTENTS
Topics | Class Hours | |
Week 1-2 | The Nature of Regression Analysis
| 6 |
Week 3-4 | Two-Variable Regression Analysis: SomeBasic Ideas
| 6 |
Week 5-6 | Two-Variable Regression Model:TheProblem of Estimation
| 6 |
Week 7-8 | Classical Normal Linear Regression Model (CNLRM) 4.1 The Probability Distribution of Disturbances ui 4.2 The Normality Assumption for ui Why the Normality Assumption? 4.3 Properties of OLS Estimators under the Normality Assumption 4.4 The Method of Maximum Likelihood (ML) | 6 |
Week 9-10 | Two-Variable Regression: Interval Estimation and Hypothesis Testing 5.1 Statistical Prerequisites 5.2 Interval Estimation: Some Basic Ideas 5.3 Confidence Intervals for Regression 5.4 Confidence Interval for σ2 5.5 Hypothesis Testing: General Comments 5.6 Hypothesis Testing: | 6 |
Week 11-12 | Extensions of the Two-Variable LinearRegression Model 6.1 Regression through the Origin 6.2 Scaling and Units of Measurement 6.3 Regression on Standardized Variables 6.4 Functional Forms of Regression Models 6.5 How to Measure Elasticity: The Log-LinearModel
| 6 |
Week 13-14 | Multiple Regression Analysis:The Problem of Estimation 7.1 The Three-Variable Model: Notationand Assumptions 7.2 Interpretation of Multiple Regression Equation 7.3 The Meaning of Partial RegressionCoefficients 7.4 OLS and ML Estimation of the Partial Regression Coefficients | 6 |
Week 15 | Multiple Regression Analysis:The Problemof Inference 8.1 The Normality Assumption Once Again 8.2 Hypothesis Testing in Multiple Regression: General Comments 8.3 Hypothesis Testing about IndividualRegression Coefficients 8.4 Testing the Overall Significance of the SampleRegression | 3 |
Week 16-17 | Dummy Variable Regression Models 9.1 The Nature of Dummy Variables 9.2 ANOVA Models 9.3 ANOVA Models with Two Qualitative Variables 9.4 Regression with a Mixture of Quantitative and Qualitative Regressors: The ANCOVA Models 9.5 The Dummy Variable Alternative to the Chow Test 9.6 Interaction Effects Using Dummy Variables 9.7 The Use of Dummy Variables in SeasonalAnalysis 9.8 Piecewise Linear Regression | 6 |
Week 18 | General Review and Final Examination | 3 |
Total Hours | 54 |