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Information
| Unit | FACULTY OF ECONOMICS AND ADMINISTRATIVE SCIENCES |
| ECONOMETRICS PR. | |
| Code | EKMZ401 |
| Name | Econometrics III |
| Term | 2018-2019 Academic Year |
| Semester | 7. Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 3 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Lisans Dersi |
| Type | Normal |
| Label | C Compulsory |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. SEDA ŞENGÜL |
| Course Instructor |
Prof. Dr. SEDA ŞENGÜL
(Güz)
(A Group)
(Ins. in Charge)
Prof. Dr. SEDA ŞENGÜL (Güz) (B Group) (Ins. in Charge) |
Course Goal / Objective
The aim of this course is to provide students with the basic concepts of econometrics and to strengthen econometric background. This course also aims to equip students with skills to carry out independent applied research and be able to apply certain econometric methods to economic problems.
Course Content
This course, which is the continuation of econometrics I and econometrics II, will focus on topics such as simultaneous equations estimation methods, dynamic models, discrete choice models, limited dependent variable models, panel data analysis, time series analysis.
Course Precondition
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | The basic subjects of econometrics are well known |
| LO02 | The student is able to estimate and interpret econometric models. |
| LO03 | The student gaines skills to carry out independent applied research as well as to develop new econometric methods |
| LO04 | The student can identify any econometric problems and to develop the solutions. |
| LO05 | The student can produce solutions to any econometric problems in an econometric model. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | - | Explains Econometric concepts | 5 |
| PLO02 | - | Acquires basic Mathematics, Statistics and Operation Research concepts | 4 |
| PLO03 | - | Equipped with the foundations of Economics, and develops Economic models | 5 |
| PLO04 | - | Describes the necessary concepts of Business | 2 |
| PLO05 | - | Models problems with Mathematics, Statistics, and Econometrics | 5 |
| PLO06 | - | Estimates the model consistently and analyzes & interprets its results | 5 |
| PLO07 | - | Acquires the ability to analyze, benchmark, evaluate and interpret at conceptual levels to develop solutions to problems | 5 |
| PLO08 | - | Collects, edits, and analyzes data | 3 |
| PLO09 | - | Uses a package program of Econometrics, Statistics, and Operation Research | 5 |
| PLO10 | - | Effectively works, take responsibility, and the leadership individually or as a member of a team | 4 |
| PLO11 | - | Awareness towards life-long learning and follow-up of the new information and knowledge in the field of study | 4 |
| PLO12 | - | Develops the ability of using different resources in the form of academic rules, synthesis the information gathered, and effective presentation in an area which has not been studied | 4 |
| PLO13 | - | Uses Turkish and at least one other foreign language, academically and in the business context | 4 |
| PLO14 | - | Good understanding, interpretation, efficient written and oral expression of the people involved | 4 |
| PLO15 | - | Improves himself/herself constantly by defining educational requirements considering interests and talents in scientific, cultural, art and social fields besides career development | 3 |
| PLO16 | - | Questions traditional approaches and their implementation while developing alternative study programs when required | 3 |
| PLO17 | - | Recognizes and implements social, scientific, and professional ethic values | 3 |
| PLO18 | - | Follows actuality, and interprets the data about economic and social events | 3 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Model specification, model specifation error and types of model specification error | Students will be prepared by studying relevant subjects from source books according to the weekly program. | |
| 2 | Tests of model specification error , errors of measurement and model selection criteria. | Students will be prepared by studying relevant subjects from source books according to the weekly program. | |
| 3 | Dynamanic models: Estimation of Distributed -Lag models. The Koyck Approach, Adaptive expectation, Partial adjustment | Students will be prepared by studying relevant subjects from source books according to the weekly program. | |
| 4 | Estimation of Autoregressive models: Almon approach, polinominal spline distrubuted lags, exogeneity tests, the wu-hausman test | Students will be prepared by studying relevant subjects from source books according to the weekly program. | |
| 5 | Simultaneous equation models:specifation and identification in Simultaneous equation models | Students will be prepared by studying relevant subjects from source books according to the weekly program. | |
| 6 | Estimation and inference in simultaneous equation models: indirect least squares, generalized least squares, the two-stage least squares estimator, the limited information maximum likelihood, the full information maximum likelihood | Students will be prepared by studying relevant subjects from source books according to the weekly program. | |
| 7 | Maximum likelihood (ML): properties of ML estimators. ML estimation of linear model, | Students will be prepared by studying relevant subjects from source books according to the weekly program. | |
| 8 | Mid-Term Exam | Students prepare for mid-term exam | |
| 9 | aximum likelihood (ML): likelihood ratio test, wald test, lagrange multiplier tests | Students will be prepared by studying relevant subjects from source books according to the weekly program. | |
| 10 | Discrete choice models: Linear probability model, probit and logit models | Students will be prepared by studying relevant subjects from source books according to the weekly program. | |
| 11 | Limited dependent variables: truncating, censoring, and sample selection | Students will be prepared by studying relevant subjects from source books according to the weekly program. | |
| 12 | Tobit model, Heckman model | Students will be prepared by studying relevant subjects from source books according to the weekly program. | |
| 13 | Panel data analysis: general terms of panel data, advantages of panel data, pooled least squares | Students will be prepared by studying relevant subjects from source books according to the weekly program. | |
| 14 | panel data analysis fixed effects models and random effects models | Students will be prepared by studying relevant subjects from source books according to the weekly program. | |
| 15 | Time series modeling: ARMA processes, testing and estimation for stationarity, forecast | Students will be prepared by studying relevant subjects from source books according to the weekly program. | |
| 16 | Term Exams | Students prepare for final exam | |
| 17 | Term Exams | Students prepare for final exam |
Assessment (Exam) Methods and Criteria
| Assessment Type | Midterm / Year Impact | End of Term / End of Year Impact |
|---|---|---|
| 1. Midterm Exam | 100 | 40 |
| General Assessment | ||
| Midterm / Year Total | 100 | 40 |
| 1. Final Exam | - | 60 |
| Grand Total | - | 100 |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 2 | 28 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 6 | 6 |
| Final Exam | 1 | 10 | 10 |
| Total Workload (Hour) | 86 | ||
| Total Workload / 25 (h) | 3,44 | ||
| ECTS | 3 ECTS | ||