Information Package / Course Catalogue
Time Series Econometrics
Course Code: ECON427
Course Type: Area Elective
Couse Group: First Cycle (Bachelor's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 3
Prt.: 0
Credit: 3
Lab: 0
ECTS: 5
Objectives of the Course

The purpose of the Time Series Econometrics course is to equip undergraduate students with the theoretical knowledge and practical skills necessary to analyze and interpret time-dependent economic data.

Course Content

Some of the main topics to be covered in the course are as follows: Introduction to time series econometrics, time series components (trend and seasonality), autocorrelation function (correlogram), stationarity and non-stationarity, Dickey-Fuller and ADF unit root tests, Cointegration concept and analysis, Error Correction Model, ARDL Analysis, Causality concept and analysis. In addition, macroeconomic and financial data will be analysed using software packages such as Eviews, Stata and R.

Name of Lecturer(s)
Learning Outcomes
1.Students are able to apply stationarity tests and decide whether a series is stationary or not.
2.Students construct VAR models and interpret impulse-response functions and variance decomposition results.
3.Students can perform Engle-Granger or Johansen Cointegration Tests.
4.Students can perform Vector Error Correction model and interpret the outputs.
5.Students are able to establish and estimate the ARDL model, and interpret the outputs.
6.Students are able to apply all topics with the help of package programmes and interpret the outputs.
Recommended or Required Reading
1.Enders, W. (2014). Applied Econometric Time Series. Wiley.
2.Mert, M. ve Çağlar, A. E. (2023). Eviews ve Gauss Uygulamalı Zaman Serileri Analizi. Detay Yayıncılık.
3.Göktaş, P., Pekmezci, A. ve Bozkurt, K. (2019). Ekonometrik Serilerde Uzun Dönem Eşbütünleşme ve Kısa Dönem Nedensellik. Gazi Kitabevi.
4.Bozkurt, H. Y. (2013). Zaman Serileri Analizi. Ekin Yayınevi.
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction to time series econometric, basic concepts, time series components: trend, seasonality, stationarity, non-stationarity
Week 2 - Theoretical
Autocorrelation Function (ACF), Partial Autocorrelation Function (PACF), Correlogram Graphs, Autocorrelation tests (Bartlett, Box-Pierce Q, Ljung-Box Q)
Week 3 - Theoretical
Deterministic and Stochastic Trend
Week 4 - Theoretical
Random Walk Model and Unit Root Test
Week 5 - Theoretical
AR, MA and ARIMA Models
Week 6 - Theoretical
Basic Approaches to Unit Root Tests: Dickey Fuller and Augmented Dickey Fuller
Week 7 - Theoretical
Unit Root Tests: Phillips Perron, Ng-Perron ve KPSS Tests
Week 8 - Theoretical
Vector Autoregressive Models (VAR),
Week 9 - Theoretical
Impulse-Response Analysis and Variance Decomposition Analysis
Week 10 - Theoretical
Cointegration: Engle-Granger
Week 11 - Theoretical
Cointegration: Johansen
Week 12 - Theoretical
Error Correction Model
Week 13 - Theoretical
Causality Analysis
Week 14 - Theoretical
ARDL Model
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%40
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory143384
Midterm Examination110313
Final Examination120323
TOTAL WORKLOAD (hours)120
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
PÇ-11
PÇ-12
OÇ-1
3
2
3
2
3
2
2
2
3
3
OÇ-2
3
2
4
3
2
4
3
2
4
3
OÇ-3
4
3
2
3
4
2
3
4
2
3
OÇ-4
2
2
3
2
3
4
2
3
2
4
OÇ-5
3
3
3
4
2
2
3
2
5
4
OÇ-6
3
3
2
4
2
3
2
5
4
3
Adnan Menderes University - Information Package / Course Catalogue
2026