COURSE UNIT TITLE

: MICRO ECONOMETRICS II

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
EKO 6054 MICRO ECONOMETRICS II ELECTIVE 3 0 0 6

Offered By

Econometrics

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

ASSOCIATE PROFESSOR HAMDI EMEÇ

Offered to

Econometrics

Course Objective

Be able to evaluate and make interpretation of econometric cross-sectional and pooled data.

Learning Outcomes of the Course Unit

1   1- To explain microeconomic data and micro econometric model concepts,
2   2- Establishing binary and multinomial panel models, interpreting models and testing their validity
3   3- Knowing and setting up panel ordered models estimation methods and interpreting model estimates,
4   4- Using panel count data models,
5   5- Estimating and applying survival analysis models.
6   6- Estimating and interpreting structural equation models

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 1- Panel Data Model of Binary Choice: Random Effects Probit and Logit Models
2 2- Panel Data Model of Binary Choice: Fixed Effects Probit and Logit Models
3 3- Panel Data Model of Multinomial Choice - Random Effects Multinomial Probit Model, Random Effects Multinomial Model Logit Model
4 4- Ordered categorical variables using panel data: Random Effects Ordered Probit Model, Random Effects Ordered Logit Model
5 5- Regression Analysis of Panel Count Data- Week 1: Panel Poisson Models, Sample Mean Panel Poisson Model, Fixed Effects Panel Poisson Model
6 6- Regression Analysis of Panel Count Data - Week II: Random Effects Panel Poisson Model, Panel Negative Binomial Models, Sample Mean Panel Negative Binomial Model Fixed Effects Panel Negative Binomial Model, Random Effects Panel Negative Binom Model
7 7- Panel Tobit Model: Random Effects Panel Tobit Model, Fixed Effects Panel Tobit Model
8 8- Midterm
9 9- Survival Analysis and Applications- Week 1: Censored Data Types Used in Survival Analysis, Functions Used in Survival Analysis
10 10- Survival Analysis and Applications- Week II: Survival Analysis Methods, Nonparametric Analysis Methods, Survival Chart (ST) Analysis
11 11- Survival Analysis and Applications- Week III: Kaplan Meier (KM) Method, Cox Regression Model
12 12- Structural Equation Models- Week I: Maximum Likelihood Estimation Method (MLM)
13 13- Structural Equation Models- Week II: Unweighted Least Squares, Generalized Least Squares Method
14 14- Structural Equation Models- Week III: Weighted Least Squares Method, Standardized and Non-Standardized Coefficients

Recomended or Required Reading

Seda Şengül-Şenay Üçdoğruk Birecikli /Editörler), Uygulamalarla Mikro Ekonometri, Nobel Yayınevi 2021.
Cameron, A. C. ve Trivedi, P. K. (2005). Microeconometrics: Methods and Applications. New York: Cambridge University Press.
Cameron, A. C. ve Trivedi, P. K. (2009). Microeconometrics Using Stata. Vol. 5. College Station, TX: Stata Press.
Long, J. S. ve Freese, J. (2014). Regression Models for Categorical Dependent Variables Using Stata. USA: Stata press. Third Edition.
Long, J. S. (1997). Regression Models for Categorical and Limited Dependent Variables. USA: SAGE Publications.

Planned Learning Activities and Teaching Methods

This course will be presented using class lectures, class discussions, overhead projections, and demonstrations, Econometric package programs, Stata program.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 STT TERM WORK (SEMESTER)
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 + STT * 0.20 + FIN* 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + STT * 0.20 + RST* 0.50


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)
TOTAL WORKLOAD (hours) 0

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9
LO.1111111111
LO.2222222222
LO.3111111112
LO.4222222222
LO.5222222222
LO.6222222222

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

Copyright 2015 DEÜ. BİD

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