Econometrics of Cross Section Data

Course Description

The course accentuates primary data collection via surveys and experimental design. Unlike traditional econometrics courses that rely on secondary data, students will develop and execute binary-response surveys, conduct straightforward randomized experiments, and acquire comprehensive skills in sampling, coding, and estimation. The key models discussed include the linear probability model, logit, probit, and fundamental discrete choice models. Practical laboratory sessions are designed to equip students with essential syntax skills for analyzing real-world data. An early introduction to the conceptual distinction between binary and Likert scale formats is provided to establish foundational understanding. The practical emphasis is on binary and experimental survey methodologies.

Econometrics of Cross Section Data

Evaluation Tools (Active Term)

No evaluation items have been defined.

Course outcomes

No course outcomes have been defined yet.

Course Syllabus

Reference Books & Course Materials

1. 01 Jeffery Wooldridge, Introductory Econometrics: A modern Approach-7thEd, 2020.
2. 02 Alan Agresti, Categorial Data Analysis, 2013.

Learning Outcomes

1. L01 To define quantitative survey meachanisms SOLO 2
2. L02 To categorize primary data and secondary data SOLO 4
3. L03 To process binary and categorical outcomes SOLO 3
4. L04 To illustrate the logic of survey and experimental data, code and interpret binary variables SOLO 2
5. L05 To estimate and interpret causal reasoning, with applied skills rather than mathematical derivations SOLO 5

Program Outcomes

1. P01 1- To have advanced theoretical and practical knowledge supported by textbooks, application tools and other resources including current information in the field of Accounting and Finance.
2. P02 2- To be able to use advanced theoretical and practical knowledge acquired in the field of Accounting and Finance.
3. P03 3- To be able to interpret and evaluate data, identify problems, analyze and develop solutions based on research and evidence by using advanced knowledge and skills acquired in the field of Accounting and Finance.
4. P04 4- To be able to take responsibility as an individual and a team member in order to solve complex and unpredictable problems in accounting and finance applications.
5. P05 5- To be able to plan and manage activities for the development of employees under the responsibility of a project.
6. P06 6- To be able to determine the learning requirements in the field of Accounting and Finance and to direct their learning.
7. P07 7- To be able to inform people and institutions about issues related to the field of accounting and finance, and to be able to transfer their ideas and solution proposals in writing and orally.
8. P08 8- To be able to use information and communication technologies together with computer software at the European Computer Driving License Advanced Level required by the field of Accounting and Finance.
9. P09 9- To act in accordance with social, scientific, cultural and ethical values in the stages of collecting, interpreting, applying and announcing the results related to the field of accounting and finance.

Po-Lo Matrix