COURSE INFORMATION
Course 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