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Year/Semester of Study | 3 / Spring Semester | ||||
Level of Course | 1st Cycle Degree Programme | ||||
Type of Course | Compulsory | ||||
Department | ECONOMICS | ||||
Pre-requisities and Co-requisites | None | ||||
Mode of Delivery | Face to Face | ||||
Teaching Period | 14 Weeks | ||||
Name of Lecturer | ANIL BÖLÜKOĞLU (anil.bolukoglu@nevsehir.edu.tr) | ||||
Name of Lecturer(s) | |||||
Language of Instruction | Turkish | ||||
Work Placement(s) | None | ||||
Objectives of the Course | |||||
It is aimed to learn to student that how micro and macro models are commented. |
Learning Outcomes | PO | MME | |
The students who succeeded in this course: | |||
LO-1 | Use models for panel data. |
PO-8 have ability on working with quantitative data about economics and using the tools about statistically data analysis. |
Examination |
LO-2 | Use simultaneous equation models, identification, and the indirect and twostep least squares methods; dynamic models with timedelayed explanatory variables; Granger causality test. |
PO-4 have theoretical and empirical information to analyze how to authorities, consumers and firms effect each other and how to make decision. |
Examination |
LO-3 | Estimate nonlinear models. |
PO-10 have ability on modeling the economic theories mathematically. |
Presentation |
LO-4 | Select and apply appropriate statistical models pertaining to various subject areas in economics. |
PO-11 have ability on defining economic variables and comment on the relationships between these variables. |
Performance Project |
PO: Programme Outcomes MME:Method of measurement & Evaluation |
Course Contents | ||
Multivariate regression models and clasical asumptions about econometrics, econometric problems such as: serial correlation, Heteroskedasticity and functional form. | ||
Weekly Course Content | ||
Week | Subject | Learning Activities and Teaching Methods |
1 | Problem for forecasting | Given a presentation and then lead discussion |
2 | Linear regression model | Given a presentation and then lead discussion |
3 | Matrix Approach | Given a presentation and then lead discussion |
4 | Multiple linear connection | Given a presentation and then lead discussion |
5 | Heteroscedasticity | Given a presentation and then lead discussion |
6 | Serial correlation I | Given a presentation and then lead discussion |
7 | Serial correlation II | Given a presentation and then lead discussion |
8 | mid-term exam | |
9 | Modelling | Given a presentation and then lead discussion |
10 | Dummy Variables | Given a presentation and then lead discussion |
11 | Linear probability model | Given a presentation and then lead discussion |
12 | Probit model | Given a presentation and then lead discussion |
13 | AR model | Given a presentation and then lead discussion |
14 | Lag models I | Given a presentation and then lead discussion |
15 | Lag models II | Given a presentation and then lead discussion |
16 | final exam | |
Recommend Course Book / Supplementary Book/Reading | ||
1 | Basic Econometrics , Damodar N. Gujarati, 3. Baskı | |
Required Course instruments and materials | ||
course book |
Assessment Methods | |||
Type of Assessment | Week | Hours | Weight(%) |
mid-term exam | 8 | 1 | 40 |
Other assessment methods | |||
1.Oral Examination | |||
2.Quiz | |||
3.Laboratory exam | |||
4.Presentation | |||
5.Report | |||
6.Workshop | |||
7.Performance Project | |||
8.Term Paper | |||
9.Project | |||
final exam | 16 | 1 | 60 |
Student Work Load | |||
Type of Work | Weekly Hours | Number of Weeks | Work Load |
Weekly Course Hours (Theoretical+Practice) | 3 | 14 | 42 |
Outside Class | |||
a) Reading | 2 | 14 | 28 |
b) Search in internet/Library | 0 | ||
c) Performance Project | 0 | ||
d) Prepare a workshop/Presentation/Report | 0 | ||
e) Term paper/Project | 0 | ||
Oral Examination | 0 | ||
Quiz | 0 | ||
Laboratory exam | 0 | ||
Own study for mid-term exam | 3 | 7 | 21 |
mid-term exam | 1 | 1 | 1 |
Own study for final exam | 3 | 7 | 21 |
final exam | 1 | 1 | 1 |
0 | |||
0 | |||
Total work load; | 114 |