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Course Description Course Name : Applied Econometrics II Course Code : EM 409 Course Type : Compulsory Level of Course : Second Cycle Year of Study : 4 Course Semester : Fall (16 Weeks) ECTS : 6 Name of Lecturer(s) : Asst.Prof.Dr. CEVAT BİLGİN Assoc.Prof.Dr. MEHMET ÖZMEN Learning Outcomes of the Course : Builds a macroeconomic model Investigates time series properties of the variables involved in the model. Estimates a proper model and evaluates estimation results. Analyzes short and long term relationships between variables. Discusses of student´s estimation results for a model of Turkish economy. Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : Modelling economic relations by using econometric methods, their computer based applications and interpreting the models. Course Contents : DF and ADF unit root tests, Engel-Granger and Johansen cointegration tests, estimation of VEC model, estimation of ARIMA models, estimation of VAR model Language of Instruction : Turkish Work Place : Classroom   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 İntroduction to time series Reading Lecture 2 Some Basic Concepts, Difference Equations, White Noise Process, AR, MA, ARMA and ARIMA models Readings ,Problem Set and Application Lecture, Problem Session and Application 3 Box-Jenkins Forecasting Models (application) Readings ,Problem Set and Application Lecture, Problem Session and Application 4 Random Walk Hypothesis, deterministic and stochastic trend, superious regression Readings ,Problem Set and Application Lecture, Problem Session and Application 5 Non-Stationary Stochastic Processes Readings ,Problem Set and Application Lecture, Problem Session and Application 6 Elimination of Time Series Trend: The Difference and Trend Stationarity Processes Readings ,Problem Set and Application Lecture, Problem Session and Application 7 Testing of Stationarity , Stationarity Testing with the help of Autocorrelation Function (ACF) Readings ,Problem Set and Application Lecture, Problem Session and Application 8 Midterm Exam 9 Testing of Stationarity with help of partial autocorrelation function (PACF), the Q statistic, LB, IDW Readings ,Problem Set and Application Lecture, Problem Session and Application 10 Unit Root Tests for Stationarity: DF, ADF, PP, KPSS, DF-GLS, etc. and applications Readings ,Problem Set and Application Lecture, Problem Session and Application 11 VAR analysis and applications Readings ,Problem Set and Application Lecture, Problem Session and Application 12 Cointegration (co-integration) Analysis Introduction to Testing the Existence of co-integration Readings ,Problem Set and Application Lecture, Problem Session and Application 13 Engle-Granger test, Engle-Granger and Yoo Approach, Johansen trace test statistic and the maximum eigenvalue statistics Readings ,Problem Set and Application Lecture, Problem Session and Application 14 Error Correction Models and Applications Readings ,Problem Set and Application Lecture, Problem Session and Application 15 Causality Analysis, Variance Decomposition and Impulse Response applications related functions Readings ,Problem Set and Application Lecture, Problem Session and Application 16/17 Final exam   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  Ekonometrik zaman serileri analizi, M.sevüktekin ve M.Nargeleçekenler,2010,nobel yayın dağıtım,3.baskı.  Ekonometri, R.Tarı, 2010, umuttepe yayınları,6.baskı Required Course Material(s)   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 60     Homeworks/Projects/Others 2 40 Total 100 Rate of Semester/Year Assessments to Success 40   Final Assessments 100 Rate of Final Assessments to Success 60 Total 100   Contribution of the Course to Key Learning Outcomes # Key Learning Outcome Contribution* 1 Models problems with Mathematics, Statistics, and Econometrics 4 2 Explains Econometric concepts 5 3 Estimates the model consistently and analyzes & interprets its results 4 4 Acquires basic Mathematics, Statistics and Operation Research concepts 4 5 Equipped with the foundations of Economics, and develops Economic models 4 6 Describes the necessary concepts of Business 0 7 Acquires the ability to analyze, benchmark, evaluate and interpret at conceptual levels to develop solutions to problems 4 8 Collects, edits, and analyzes data 5 9 Uses a package program of Econometrics, Statistics, and Operation Research 5 10 Effectively works, take responsibility, and the leadership individually or as a member of a team 4 11 Awareness towards life-long learning and follow-up of the new information and knowledge in the field of study 3 12 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 13 Uses Turkish and at least one other foreign language, academically and in the business context 3 14 Good understanding, interpretation, efficient written and oral expression of the people involved 3 15 Questions traditional approaches and their implementation while developing alternative study programs when required 4 16 Recognizes and implements social, scientific, and professional ethic values 2 17 Follows actuality, and interprets the data about economic and social events 4 18 Improves himself/herself constantly by defining educational requirements considering interests and talents in scientific, cultural, art and social fields besides career development 0 * Contribution levels are between 0 (not) and 5 (maximum).   Student Workload - ECTS Works Number Time (Hour) Total Workload (Hour) Course Related Works     Class Time (Exam weeks are excluded) 14 3 42     Out of Class Study (Preliminary Work, Practice) 14 3 42 Assesment Related Works     Homeworks, Projects, Others 2 10 20     Mid-term Exams (Written, Oral, etc.) 1 16 16     Final Exam 1 18 18 Total Workload: 138 Total Workload / 25 (h): 5.52 ECTS Credit: 6