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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS EKO 5081 SPATIAL ECONOMETRICS ELECTIVE 3 0 0 5

Offered By

Econometrics

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSISTANT PROFESSOR ÖZLEM KIREN GÜRLER

Offered to

Econometrics

Course Objective

The main objective of the course is to give the student the ability to form a spatial econometric model based on economic theory.

Learning Outcomes of the Course Unit

1   Understanding and analyzing the concept of spatial econometrics 2   Define the objectives of spatial econometric models 3   Understand the concepts of spatial dependence and heterojenity. 4   Select appropriate models of econometric methods for spatial data 5   With the help of econometric computer software package is to guess the appropriate econometric analysis of the spatial data.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction to Spatial Analysis and Econometrics, Difference between classical econometrics and Spatial econometrics 2 Spatial Effects, Spatial Dependence ve Spatial heterogeneity 3 Spatial weights matrices 4 Spatial autoregressive models 5 Spatially Lagged Model , Spatially Lagged Dependent Variables 6 Estimation and Interpretion of Spatial SAR, SDM, SEM and SAC Models 7 Estimation and Interpretion of Spatial SAR, SDM, SEM and SAC Models (Continue) 8 Mid-term 9 Mid-term 10 Specification Tests 11 Estimating the spatial models using econometrics software 12 Estimating the spatial models using econometrics software (Continue) 13 Introduction to panel spatial econometrics 14 Estimating the panel spatial models using econometrics software

Recomended or Required Reading

1- Spatial Econometrics, Statistical Foundation and Application to Regional Converge, Advances in Spatial Science, 2009. Giuseppe Arbia 2. Spatial Econometrics: Methods and Models, 1988, Luc Anselin 3. Intorduction to Spatial Econometrics, 2009, LeSage J., Pace R. K.,

Planned Learning Activities and Teaching Methods

verbal lecture

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 * 0.30 + FIN* 0.40 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + STT * 0.30 + RST* 0.40 *** 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 2 26 Preparation for midterm exam 1 30 30 Preparation for final exam 1 30 30 Midterm 1 3 3 Final 1 3 3 TOTAL WORKLOAD (hours) 131

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 LO.1 1 1 1 LO.2 1 1 1 LO.3 1 1 1 LO.4 1 1 1 LO.5 1 1 1