COURSE INFORMATION
Course Title: ECONOMETRICS II
Code Course Type Regular Semester Theory Practice Lab Credits ECTS
ECO 312 B 6 4 0 0 4 6
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 , Tuesdays (8:30 - 12:00)
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: Elective
Classroom and Meeting Time: Thursdays (computer lab)
Course Description: Theory and Economic application f the linear multiple regression model, identification and structural estimation in simultaneous models, analyzing of economic policy and forecasting.
Course Objectives: To provide students with the skills required to research in economics and finance using more advanced econometric practices and models. Real Life applications are analyzed via the E-VIEWS econometric package. Laboratory sessions help students to gain knowledge and new skills in demonstrating and interpreting the results of various static and dynamic models.
COURSE OUTLINE
Week Topics
1 Introduction to the: Course, Syllabus, Textbook and Evaluation Method.
2 Regression with Dummy Variables
3 Binary Dependent Variable, Discrete Dependent Variable
4 Heteroskedasticity
5 Weighted Least Square Estimation & Functional Form Misspecification
6 Application Exam Nr:1 (Computer-Based)
7 Midterm (Paper - Based)
8 Examples of Time Series Regression Models
9 Trends and Seasonality
10 Stationary and Weakly Dependent Time Series
11 Using Highly Persistent Time Series in Regression Analysis
12 Dynamic Complete Models and the Absence of Serial Correlation
13 Application Exam Nr:2 (Computer-Based)
14 Review for Final Exam
Prerequisite(s): Financial Econometrics I
Textbook: Wooldridge J.M.(2015). Introduction to Econometrics. Cengage Learning
Other References: Lectures, Practical Sessions, Exercises
Laboratory Work: Yes
Computer Usage: Yes (E-views Software)
Others: No
COURSE LEARNING OUTCOMES
1 To have skills to set up robust parsimonious econometric models.
2 To have the ability of testing specification of the model.
3 To have the required skills to analyze financial time series and related regressions.
4 To model multivariate relationships using either dynamic or static form.
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 5
2 Students describe key economic theories 5
3 Students critically discuss current developments in economics 5
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 4
6 Students apply appropriate analytical methods to address economic problems 4
7 Students use effective communication skills in a variety of academic and professional contexts 3
8 Students effectively contribute to group work 5
9 Students conduct independent research under academic supervision 5
10 Students uphold ethical values in data collection, interpretation, and dissemination 5
11 Students critically engage with interdisciplinary innovations in social sciences 5
12 Student explain how their research has a broader social benefit 5
COURSE EVALUATION METHOD
Method Quantity Percentage
Midterm Exam(s)
1
25
Project
1
15
Quiz
2
10
Final Exam
1
30
Other
1
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 3 48
Hours for off-the-classroom study (Pre-study, practice) 16 3 48
Mid-terms 1 16 16
Assignments 1 10 10
Final examination 1 18 18
Other 1 10 10
Total Work Load:
150
Total Work Load/25(h):
6
ECTS Credit of the Course:
6