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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS EKO 6042 ECONOMETRIC ANALYSIS II ELECTIVE 3 0 0 7

Offered By

Econometrics

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

PROFESSOR DOCTOR ŞENAY ÜÇDOĞRUK BIRECIKLI

Offered to

Econometrics

Course Objective

Be able to make statistical evaluation of economics and business data, to comment, to give skills to use basic calculations and formulations, and statistical results, to develop statistical reasoning.

Learning Outcomes of the Course Unit

1   To reveal the relationship between micro-econometric methods. 2   To consider the differences between the methods. 3   To classify dependent variables according to their characteristics. 4   Model building. 5   To reveal the relationships. 6   To make a comment

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Nominal Output: Multinomial Logit and related models, Introduction to multinomial Logit model 2 MNLM as a difference model, multinomial Logit model as a discrete choice model 3 Test whether a variable has no effect, Test whether can be combined the two output, Interpretation 4 Estimated Probabilities, Partial Change, Discrete Change, Interpretation of Difference Ratios 5 Conditional Logit model, Independence of unrelated (irrelevant) alternatives and Testing 6 Nominal Output: Multinomial Logit and Applications with Related Models 7 Sequential Output: Ordered Logit and Ordered Probit Analysis 8 Mid-term 9 Distribution assumptions, probabilities of the observed values 10 Identification, Estimation, Interpretation, Probabilities of Estimation 11 Partial Change in the Estimation Probabilities, Discrete Change, Parallel Regression Assumption 12 Models for Sequential Data 13 Sequential Output: Related Applications with Ordered Logit and Ordered Probit Analysis 14 Sequential Output: Related Applications with Ordered Logit and Ordered Probit Analysis

Recomended or Required Reading

1- Scott Long, Regression Models for Categorical and Limited Dependent Variables

Planned Learning Activities and Teaching Methods

Lecture Method, Question-Answer Method, Method Discussion and Problem Solving Method

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 FCG FINAL COURSE GRADE 3 FCGR FINAL COURSE GRADE MTE * 0.40 + FCG* 0.60 4 RST RESIT 5 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.40 + RST* 0.60 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 13 3 39 Preparations before/after weekly lectures 13 3 39 Preparation for midterm exam 1 40 40 Preparation for final exam 1 40 40 Midterm 1 3 3 Final 1 3 3 TOTAL WORKLOAD (hours) 164

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 LO.1 1 LO.2 1 LO.3 1 LO.4 1 LO.5 1 LO.6 1