Applied Microeconomics (ECON504) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Applied Microeconomics ECON504 General Elective 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language Turkish
Course Type Elective Courses
Course Level Ph.D.
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Discussion, Question and Answer, Brain Storming.
Course Coordinator
Course Lecturer(s)
  • Assoc. Prof. Dr. Dersin Öğretim Üyesi
Course Assistants
Course Objectives 1. To introduce the applications in Microeconomics 2. To endow the students with the required statistical and econometric tools
Course Learning Outcomes The students who succeeded in this course;
  • To learn the applications in microeconomics
  • To gain the required statistical and econometric tools to analyze microeconomic issues
Course Content Introduction to Stata, applied analyses in regression models, applied analyses in qualitative information, applied analyses in heterosckedasticity, basic regression analysis with time series data, serial correlation in time series regressions, applications of simple panel data methods, applications of advanced panel data methods.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction to Stata I Handouts
2 Introduction to Stata II Handouts
3 Introduction to Stata III Handouts
4 Applied Analyses in Regression Models I Wooldridge, p. 22-100
5 Applied Analyses in Regression Models II Wooldridge, p. 100-167
6 Applied Analyses in Qualitative Information Wooldridge, p. 225-264
7 Applied Analyses in Heterosckedasticity Wooldridge, p. 264-300
8 Midterm
9 Basic Regression Analysis with Time Series Data I Wooldridge, p. 340-360
10 Basic Regression Analysis with Time Series Data II Wooldridge, p. 360-377
11 Serial Correlation in Time Series Regressions Wooldridge, p. 408-443
12 Applications of Simple Panel Data Methods I Wooldridge, p. 444-460
13 Applications of Simple Panel Data Methods II Wooldridge, p. 460-481
14 Applications of Advanced Panel Data Methods I Wooldridge, p. 481-495
15 Applications of Advanced Panel Data Methods II Wooldridge, p. 495-506.

Sources

Course Book 1. Introductory Econometrics, Jeffrey Wooldridge; South-Western; 2009.
Other Sources 2. An Introduction to Stata Programming, Christopher F. Baum; Stata Press, 2009.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 10 5
Presentation 1 15
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 35
Final Exam/Final Jury 1 45
Toplam 13 100
Percentage of Semester Work
Percentage of Final Work 100
Total 100

Course Category

Core Courses X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 To compare main theories and/or approaches in political economy and make a critical evaluation of each
2 To compare main macroeconomic theories and/or approaches and make a critical evaluation of each
3 To use complementary approaches from other relevant disciplines (e.g. political science, sociology) in order to solve problems requiring scientific expertise
4 To develop the skills for establishing a micro-macro link in human and social sciences
5 To analyze the main economic indicators and comment on them
6 To acquire theoretical knowledge through literature survey and derive empirically testable hypothesis
7 To be able to develop new approaches/theories for complex problems in political economy
8 To apply critical thinking, statistical/econometric tools or other relevant quantitative and qualitative tools to new areas/problems
9 To make a research design and carry it out within predetermined time frames
10 To formulate and present policy recommendations based on academic research
11 To continue learning and undertake advanced research independently

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours)
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 16 4 64
Presentation/Seminar Prepration
Project
Report
Homework Assignments 10 1 10
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 10 10
Prepration of Final Exams/Final Jury 1 15 15
Total Workload 99