COURSE UNIT TITLE

: ECONOMETRICS II

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
EMT 3002 ECONOMETRICS II COMPULSORY 3 0 0 5

Offered By

Econometrics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR HAMDI EMEÇ

Offered to

Economics
Economics (Evening)

Course Objective

The main objective of the course is to provide How to get more knowledge and skill in the field of quantitative or theorical econometrics modelling.

Learning Outcomes of the Course Unit

1   To be able to identify theory of economics by using advanced econometrics techniques in modelling of econometrics
2   To be able to set up right functional form of model and related and unrelated variables in selection of identification of the ideal econometrics model
3   To be able to consitute dummy variables to measure effects of qualitative variables in regression analysis, explain usage of constant and slope with dummy variables
4   To be able to study short and long term economics affects via finite distributed lag models and infinite distributed lag models
5   To be able to identify how to be expectations with dynamic econometrics model
6   To be able to estimate system of two or more simultaneous equations
7   To be able to identify characteristics of time series variables to show effects of short and long term via dynamic econometrics models

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Model specification, specification error, distinction of incorrect specification error, types of specification error
2 Methods of identifying specification error, measuring error in variables
3 Models with dummy variables, models with one dummy variable(analysis of variance model), models with dummy variables and the other quantitative variables(analysis of co-variance model)
4 Dummy variables with more than two categories and how to affect these variables eachother, test of season effect, partial linear regression
5 Models with dependent dummy variables: logistic model
6 Models with dependent dummy variables: Probit model, maximum likelihood method
7 Distributed lag models, concepts of lag and different techniques about distributed lag models, Almon Polinomial Model
8 Different techniques (continue): Koyck Model, adaptive expectation model
9 Mid-term
10 Different techniques (continue): Partial improving model
11 Estimation Methods of Autoregressive Models: estimation of autoregressive models by using least square method, estimation of autoregressive models by using proxy variable method, identify autocorrelation in autoregressive models
12 Models with simultaneous equation, identify of models with simultaneous equation, expression of mathematics, systems of sequence equation
13 Distriction of structural and reduced models, deviation of simultaneous equation, estimations of simultaneous equation
14 Econometrics of time series: Stationarity, unit roots, causality in economics: Granger Test
15 Econometrics of time series: Causality in economics: Granger Test

Recomended or Required Reading

Fundamental Reference:
1. Ekonometri II, Şahin Akkaya, M .Vedat Pazarlıoğlu
Supplementary Reference:
1. Ekonometri Temel Kavramları, Selahattin Güriş, Ebru Çağlayan, DER Yayınları
2. Temel Ekonometri, Damodar N. Gujarati

Planned Learning Activities and Teaching Methods

This course will be presented using manner of telling method, question and answer method, discussion method and problem solving method.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 MTEG MIDTERM GRADE MTEG * 1
3 FIN FINAL EXAM
4 FCGR FINAL COURSE GRADE MTEG * 0.40 + FIN * 0.60
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTEG * 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)

Prof. Şenay ÜÇDOĞRUK
Room: 632
E-mail: s.ucdogruk@deu.edu.tr
Tel: 0 (232) 301 03 56 Int.: 10356

Asst.Prof. Hamdi EMEÇ
Room: 629
E-mail: hamdi.emec@deu.edu.tr
Tel: 0 (232) 301 03 58 Int: 10358

Asst.Prof. Özlem KIREN GÜRLER
Room: 633
E-mail: ozlem.kiren@deu.edu.tr
Tel: 0 (232) 301 04 08 Int: 10408

Asst.Prof. Emrah GÜLAY
Room: 627
E-mail: emrah.gulay@deu.edu.tr
Tel: 0 (232) 301 07 23 Int: 10723

Office Hours

Prof. Şenay ÜÇDOĞRUK Tuesday: 16:00-18:00
Asst.Prof. Hamdi EMEÇ Tuesday: 16:00-18:00
Asst. Prof. Özlem KIREN GÜRLER Monday: 16:00-18:00
Asst.Prof. Emrah GÜLAY Monday: 16:00-18:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 14 2 28
Preparation for midterm exam 1 20 20
Preparation for final exam 1 30 30
Preparation for quiz etc. 2 1 2
Midterm 1 1 1
Final 1 1 1
Quiz etc. 2 1 2
TOTAL WORKLOAD (hours) 126

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9
LO.11111
LO.21111
LO.31111
LO.41111
LO.51111
LO.61111
LO.71111

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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