EPOKA UNIVERSITY
FACULTY OF ECONOMICS AND ADMINISTRATIVE SCIENCES
DEPARTMENT OF ECONOMICS
COURSE SYLLABUS
COURSE INFORMATIONCourse Title: ECONOMETRICS I |
Code | Course Type | Regular Semester | Theory | Practice | Lab | Credits | ECTS |
---|---|---|---|---|---|---|---|
ECO 311 | B | 5 | 4 | 0 | 0 | 4 | 5 |
Academic staff member responsible for the design of the course syllabus (name, surname, academic title/scientific degree, email address and signature) | NA |
Lecturer (name, surname, academic title/scientific degree, email address and signature) and Office Hours: | Egis Zaimaj , 8:30 - 17:30 (12:30-13:30 break time) |
Second Lecturer(s) (name, surname, academic title/scientific degree, email address and signature) and Office Hours: | NA |
Teaching Assistant(s) and Office Hours: | NA |
Language: | English |
Compulsory/Elective: | Compulsory |
Classroom and Meeting Time: | Computer Lab II & Computer Lab I |
Course Description: | Econometrics I: Techniques of Econometrics, estimating the basic linear model and hypothesis testing, empirical illustrations to contemporary economic issues |
Course Objectives: | The primary objective of this course is to teach students fundamental econometric techniques in a highly empirical but theoretically rigorous context. This course presents an applied introduction to econometric techniques with some derivations of their properties, but leaves more theoretical treatment to future courses. For all groups, the course provides practical experience in the use of econometric software EVIEWS. |
COURSE OUTLINE
|
Week | Topics |
1 | Intro; Evaluation Method; Term Project & A brief Lecture on Types of Data |
2 | Chapter 1: Types and Nature of Economic Data |
3 | Chapter 2: Simple Linear Regression Models |
4 | Chapter 3: Multiple Linear Regression Models (Estimation and Interpretation) |
5 | Chapter 4: Further concepts on M.L.R Models |
6 | Chapter 5: OLS Estimation |
7 | Application Nr:1 (Computer-Based) |
8 | Midterm (Paper - Based) |
9 | Chapter 6: Further Issues MLRM |
10 | Chapter 7: Linear Probability Models |
11 | Chapter 8: Heteroscedasticity (Causes and Remedies) |
12 | Project Presentation |
13 | Application Nr:2 (Computer-Based) |
14 | Revision prior to the Final Exam |
Prerequisite(s): | na |
Textbook: | Introduction to Econometrics, J.M. Wooldridge, Cengage Learning. Analysis of Economic Data. Gary Koop, Second Edition. |
Other References: | na |
Laboratory Work: | yes |
Computer Usage: | yes (Eviews Software) |
Others: | No |
COURSE LEARNING OUTCOMES
|
1 | The student should be able to understand the nature of Econometrics and apply the basic econometric techniques in different studies. |
2 | The student should be able to estimate and interpret econometric models. |
3 | The student should be able to check the robustness and specification of the econometric models. |
4 | The student should be able to apply fundamental econometric principles to real life and scientific problems as well as test economic theories. |
COURSE CONTRIBUTION TO... PROGRAM COMPETENCIES
(Blank : no contribution, 1: least contribution ... 5: highest contribution) |
No | Program Competencies | Cont. |
Bachelor in Economics (3 years) Program | ||
1 | Students define the fundamental problems of economics | 4 |
2 | Students describe key economic theories | 5 |
3 | Students critically discuss current developments in economics | 4 |
4 | Students appropriately use software for data analysis | 5 |
5 | Students critically contextualize the selection of an economic problem for research within scholarly literature and theory on the topic | 5 |
6 | Students apply appropriate analytical methods to address economic problems | 5 |
7 | Students use effective communication skills in a variety of academic and professional contexts | 4 |
8 | Students effectively contribute to group work | 4 |
9 | Students conduct independent research under academic supervision | 4 |
10 | Students uphold ethical values in data collection, interpretation, and dissemination | 4 |
11 | Students critically engage with interdisciplinary innovations in social sciences | 4 |
12 | Student explain how their research has a broader social benefit | 4 |
COURSE EVALUATION METHOD
|
Method | Quantity | Percentage |
Midterm Exam(s) |
1
|
25
|
Project |
1
|
15
|
Lab/Practical Exams(s) |
2
|
10
|
Final Exam |
1
|
30
|
Attendance |
10
|
|
Total Percent: | 100% |
ECTS (ALLOCATED BASED ON STUDENT WORKLOAD)
|
Activities | Quantity | Duration(Hours) | Total Workload(Hours) |
Course Duration (Including the exam week: 16x Total course hours) | 16 | 4 | 64 |
Hours for off-the-classroom study (Pre-study, practice) | 16 | 2 | 32 |
Mid-terms | 1 | 6 | 6 |
Assignments | 0 | ||
Final examination | 1 | 10 | 10 |
Other | 1 | 13 | 13 |
Total Work Load:
|
125 | ||
Total Work Load/25(h):
|
5 | ||
ECTS Credit of the Course:
|
5 |