sap course 1429220833

Course Code & Number:

ECON 331_O

Course Title:

Econometrics I

Level of Course:

BS

Credits:

(3+0+0) 3 TEDU Credits, 6 ECTS Credits

Catalog Description:

Interactions between economic problems and the assumptions of statistical theory. Formulation, estimation and testing of economic models. Single variable and multiple variable regression techniques. Theory of identification and issues relating to inference. Functional forms and specification error analysis. Detection of multicollinearity and heteroscedasticity. Use of dummy variables.

Pre-requisites & Co-requisites:

Pre-requisites: MATH 232
Co-requisites: NONE
Year of Study: 
Junior
Semester: 
Fall
Mode of Delivery: 
Face-to-face
Language of Instruction: 
English
Course Type: 
Compulsory
Required Reading: 
1. Wooldridge. J., Introductory Econometrics: A Modern Approach. 4th Edition, South-Western College Pub., Cincinnati, 2008.
Course Objective: 

The main objectives of this course to revise and strengthen students’ knowledge of univariate and multivariate statistics; to obtain a full understanding of the classical linear regression model; to provide students with a working knowledge of regression analysis under non-classical assumptions on the disturbance; to provide the necessary mathematical and statistical tools needed to conduct theoretical econometric analysis at an advanced level.

Extended Description: 

What is Econometrics? Types of Economic Data. Causality vs. Correlation. Review of Statistical Concepts. Introduction to Stata. The Simple/Multiple Linear Regression Model. Model and Assumptions. Ordinary Least Squares (OLS) Estimator. Goodness-of-fit and R-squared. Properties of OLS. Omitted Variables Bias. Multicollinearity. Gauss-Markov Theorem: Efficiency of OLS. Statistical Inference for OLS. Confidence Intervals. Functional Forms And Selection Of Regressors. Dummy Explanatory Variables. Heteroskedasticity and Weighted Least Squares.

Computer Usage: 
Students will use Stata 12, MS Office applications (Word, Excel, Access, Powerpoint) to work on their weekly assignments about 2 hours a week.
Learning Outcomes: 

Upon succesful completion of this course, a student will be able to
1. Demonstrate understanding of verbal, graphical, mathematical and econometric representation of economic ideas and analysis, including the relationship between them. 
2. Demonstrate more extensive knowledge and skills of quantitative economics and econometrics. 
3. Apply complex ideas to solve problems; reason logically and work analytically; perform with high levels of accuracy. 
4. Apply mathematical, statistical and graphical techniques in an appropriate manner and analyse and solve complex problems accurately. 
5. Relate economic questions to empirical observations and try to deal with those using econometric models based on sound hypotheses. 
6. Have a working knowledge of a statistical software and use it to address empirical questions. 
7. Demonstrate the ability to apply econometric principles by writing a quality paper and giving oral presentations of the findings of the paper as an individual and as a group member. 

Planned Learning Activities and Teaching Methods: 
Telling/Explaining
Discussion/Debate
Questioning
Reading
Demonstrating
Problem Solving
Case Study/Scenarion Analysis
Oral Presentation
Hands-on Activities
Web Searching
Assessment Methods and Criteria: 
Test / Exam
Quiz/Homework
Labrotary Work
Presentation (Oral/Poster)

Student Workload:

Lab Application
24
hrs
Quizzes /Homeworks
16
hrs
Midterm Exam 1
16
hrs
Final Exam
16
hrs
Research Review
24
hrs

Prepared By:

Jülide Yıldırım Öcal

Revised By:

sap_editor