Print

COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
CEKO 428QUANTITATIVE METHODS IN LABOUR ECONOMICS3 + 06th Semester5

COURSE DESCRIPTION
Course Level Bachelor's Degree
Course Type Elective
Course Objective The aims of the course are threefold. The first aim is to introduce students to applications of data analysis widely used in Labour Economics based on Micro-econometric techniques. The second aim is to instruct students in the basics of survey methodology, including issues such as attrition, response rates, sampling frames and weighting. The third aim is to develop an understanding of the links between the predictions of economic theory and empirical implementation of such theory using cross-section and longitudinal data. With this course, it is aimed to improve skills of the students who will graduate as labour market experts in analysing labour markets, understanding structural problems, developing solutions to these problems and comparing them globally.
Course Content Week 1 and Week 2: Topics covered: Different types of panel datasets in Labour Economics; the British Household Panel Survey, Income Living Conditions Panel Dataset; introduction to STATA and to data management using STATA; how to estimate cross-sectional models Week 3: Topics covered: How to combine data files to obtain a panel dataset for analysis; theory and models about partnership formation Week 4: Topics covered: Theory and models of economic gains from partnerships – marriage and cohabitation; theory and models of unemployment scarring Week 5 Topics covered: Theory and models unemployment persistence; theory and models of unemployment and life satisfaction Week 6: Topics covered: Survey sample design, non-response, weighting; using weights in STATA Week 7 and Week 8: Topics covered: Event History Models: Data Preparation and Analysis; Introduction to Duration Analysis Week 9: Topics covered: Analysis of Event History Data Week 10: Application Class in the Lab Week 11: Presentations of Student Projects Week 12: Presentations of Student Projects Week 13: Presentations of Student Projects
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES
1Students will accomplish data analysis and understanding of quantitative methods in Labour Economics. Students will be equipped with knowledge and understanding to grasp the methods of empirical research and will be able to creatively use these methods in their own research or professional work. Additionally, they will learn a software widely used in data analysis. By presenting their projects, they will increase their analytical and critical evaluations, statistical skills and independent inquiry.

COURSE'S CONTRIBUTION TO PROGRAM
Data not found.

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)14342
Hours for off-the-classroom study (Pre-study, practice)14342
Assignments21020
Mid-terms11010
Final examination11616
Total Work Load

ECTS Credit of the Course






130

5
COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2022-2023 Spring1NURSEL DURMAZ BODUR


Print

Course Details
Course Code Course Title L+P Hour Course Code Language Of Instruction Course Semester
CEKO 428 QUANTITATIVE METHODS IN LABOUR ECONOMICS 3 + 0 1 Turkish 2022-2023 Spring
Course Coordinator  E-Mail  Phone Number  Course Location Attendance
Assoc. Prof. Dr. NURSEL DURMAZ BODUR ndurmaz@pau.edu.tr İİBF AB108 %70
Goals The aims of the course are threefold. The first aim is to introduce students to applications of data analysis widely used in Labour Economics based on Micro-econometric techniques. The second aim is to instruct students in the basics of survey methodology, including issues such as attrition, response rates, sampling frames and weighting. The third aim is to develop an understanding of the links between the predictions of economic theory and empirical implementation of such theory using cross-section and longitudinal data. With this course, it is aimed to improve skills of the students who will graduate as labour market experts in analysing labour markets, understanding structural problems, developing solutions to these problems and comparing them globally.
Content Week 1 and Week 2: Topics covered: Different types of panel datasets in Labour Economics; the British Household Panel Survey, Income Living Conditions Panel Dataset; introduction to STATA and to data management using STATA; how to estimate cross-sectional models Week 3: Topics covered: How to combine data files to obtain a panel dataset for analysis; theory and models about partnership formation Week 4: Topics covered: Theory and models of economic gains from partnerships – marriage and cohabitation; theory and models of unemployment scarring Week 5 Topics covered: Theory and models unemployment persistence; theory and models of unemployment and life satisfaction Week 6: Topics covered: Survey sample design, non-response, weighting; using weights in STATA Week 7 and Week 8: Topics covered: Event History Models: Data Preparation and Analysis; Introduction to Duration Analysis Week 9: Topics covered: Analysis of Event History Data Week 10: Application Class in the Lab Week 11: Presentations of Student Projects Week 12: Presentations of Student Projects Week 13: Presentations of Student Projects
Topics
WeeksTopics
1 Labour market concepts
2 Labour market concepts
3 To examine the data of national official institutions on the labor market (TURKSTAT, Social Security Institution)
4 To examine the data of national official institutions on the labor market (Trade Unions)
5 To examine the data of international official institutions on the labor market (EUROSTAT, OECD)
6 To examine the data of international official institutions on the labor market (World Bank, EUROFOUND)
7 Reporting to national and international data banks
8 Mid-term exam
9 Introduction of SPSS and descriptive analysis
10 Introduction of TURKSTAT household labour force survey micro datasets
11 Analyzing and reporting micro data sets with SPSS
12 Analyzing and reporting micro data sets with SPSS
13 Presentations of student projects
14 Presentations of student projects
Materials
Materials are not specified.
Resources
ResourcesResources Language
Kuvvet Lordoğlu ve Nurcan Özkaplan, Çalışma İktisadı, Der Yayınları (35-73) Türkçe
Berrin Ceylan Ataman, Çalışma Ekonomisi Teori ve Politikalar, İmaj Yayınevi (116-128, 184-203)Türkçe
Şener Büyüköztürk, Sosyal Bilimler İçin Veri Analizi El Kitabı, Pegem Akademi.Türkçe
Course Assessment
Assesment MethodsPercentage (%)Assesment Methods Title
Final Exam60Final Exam
Midterm Exam40Midterm Exam
L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes