(Prerequisite: ECO 102 and MAT 300)
COURSE DESCRIPTION
Examines applications of statistical techniques to economic data, regression analysis, and estimation of economic models. Includes violations of the regression model and analysis of variance.
INSTRUCTIONAL MATERIALS
Required Resources
Gujarati, D.N. (2010). Essentials of econometrics (4th ed.). Boston: McGraw Hill.
Supplemental Resources
Kennedy, Peter. (1998). A Guide to Econometrics (4th ed.). Massachusetts: MIT Press.
Mirer, Thad W. (1995). Economic Statistics and Econometrics (3rd ed.). New Jersey: Prentice-Hall.
Woolridge, Jeffrey M. (2000). Introductory Econometrics United States: South-Western Publishing.
COURSE LEARNING OUTCOMES
- Apply econometrics to conduct and present the analysis of economic data to support business and public policy decisions.
- Apply regression analysis to interpret the characteristics of populations and test hypotheses.
- Select and apply the appropriate model to analyze economic data.
- Explain how to resolve issues of multicollinearity, heteroscedasticity, and autocorrelation in variables.
- Use technology and information resources to research issues in econometrics.
- Write clearly and concisely about econometrics using proper writing mechanics.
WEEKLY COURSE SCHEDULE
The standard requirement for a 4.5 credit hour course is for students to spend 13.5 hours in weekly work. This includes preparation, activities, and evaluation regardless of delivery mode.
| Week | Preparation, Activities, and Evaluation | Points |
| 1 | Preparation
• Reading(s) • Chapter 1: The Nature and Scope of Econometrics • e-Activity • Use the Internet to research current applications of econometrics. Be prepared to discuss. Activities • Introduction Discussion • Discussions Evaluation • None |
20 20 |
| 2 | Preparation
• Reading(s) • Chapter 2: Basic Ideas of Linear Regression: The Two-Variable Model • Chapter 3: The Two Variable Model: Hypothesis Testing • e-Activity • Use the Internet to identify and learn about common uses of regression analysis. Be prepared to discuss. Activities • Discussions Evaluation • Homework: Chapter 2 • Problems: 2.8, 2.10, 2.13, and 2.22 • Homework: Chapter 3 • Problems: 3.7, 3.9, 3.10, and 3.18 |
20
48
48 |
| 3 | Preparation
• Reading(s) • Chapter 4: Multiple Regression: Estimation and Hypothesis Testing • e-Activity: • Use the Internet to find and research a current example of how estimation and hypothesis testing were used to solve a problem. Be prepared to discuss. Activities • Discussions Evaluation • Homework: Chapter 4 • Questions 4.5 and 4.6 • Problems 4.11, 4.12, 4.13, and 4.21 • Assignment 1: The Two-Variable Model |
20
16 48 240 |
| 4 | Preparation
• Reading(s) • Chapter 5: Functional Forms of Regression Models • e-Activity • Use the Internet to research how the concepts discussed in Chapter 5 may be applied to a better understanding of the U.S. economic recession of the late 2000s. Be prepared to discuss. Activities • Discussions Evaluation • Homework: Chapter 5 • Question: 5.3 • Problems: 5.10, 5.13, 5.14, and 5.27 • Assignment 2: Multiple Regression |
20
8 48 280 |
| 5 | Preparation
• Reading(s) • Chapter 6: Dummy Variable Regression Models Activities • Discussions Evaluation • Homework: Chapter 6 • Questions: 6.3, 6.6, and 6.7 • Problems 6.11 (a-c) and 6.28 (a-g) |
20
24 24 |
| 6 | Preparation
• Reading(s) • Chapter 7: Model Selection: Criteria and Tests Activities • Discussions Evaluation • Homework: Chapter 7 • Questions: 7.1 and 7.6 • Problems 7.11, 7.17, and 7.20 • Assignment 3: Course Project – Prospectus |
20
16 36 240 |
| 7 | Preparation
• Reading(s) • Chapter 8: Multicollinearity: What Happens if the Explanatory Variables Are Correlated? • e-Activity • Use the Internet to identify and research a recent economic issue that resulted from multicollinearity. Be prepared to discuss. Activities • Discussions Evaluation • Homework: Chapter 8 • Question: 8.3 • Problems 8.14, 8.15, 8.16, and 8.22 |
20
8 48 |
| 8 | Preparation
• Reading(s) • Chapter 9: Heteroscedasticity: What Happens if the Error Variance Is Nonconstant? Activities • Discussions Evaluation • Homework: Chapter 9 • Question: 9.1 • Problems 9.8, 9.10, 9.14, and 9.19 • Assignment 4: Model Selection and Specification Errors |
20
8 48 240 |
| 9 | Preparation
• Reading(s) • Chapter 10: What Happens if Error Terms Are Correlated? Activities • Discussions Evaluation • Homework: Chapter 10 • Problems 10.10, 10.12, 10.13, and 10.17 |
20
48 |
| 10 | Preparation
• Reading(s) • Chapter 11: Simultaneous Equation Models • Chapter 12: Selected Topics in Single Equation Regression Models Activities • Discussions Evaluation • Homework: Chapter 11 • Question 11.5 • Problems 11.16 (a-c), 11.18, and 11.19 • Homework: Chapter 12 • Problems 12.8 and 12.13 • Assignment 5: Course Project |
20
8 36
24 320 |
