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Course Description Course Name : Time Series Models II Course Code : EM 403 Course Type : Compulsory Level of Course : First Cycle Year of Study : 4 Course Semester : Fall (16 Weeks) ECTS : 5 Name of Lecturer(s) : Res.Asst. FELA ÖZBEY Learning Outcomes of the Course : Detects deterministic and stochastic trend. Analizes multivariate time series models. Detects interrelationship among economic time series. Establishes statistical model that best fits the time series data. Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : The aim of this course is to give the students a good theoretical and empirical understanding of statistical methods used in multivariate time series analysis. Course Contents : This course involves the study of stochastic and deterministic trends,Unit root tests, VAR models, Granger Causality, error correction model, cointegration. 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 Nonstationary Processes - Forms of Nonstationarity, Trend Elimination Reading the textbook Lecture 2 Nonstationary Processes - Dickey-Fuller Tests Reading the textbook Lecture 3 Nonstationary Processes - The Phillips-Perron Test, Unit Root Tests and Structural Breaks, KPSS test Reading the textbook Lecture 4 Vector Autoregressive Processes: Represantation of the System Reading the textbook Lecture 5 Vector Autoregressive Processes - Error Correction Represantation, , FPE, AIC, BIC, HQ criteria Reading the textbook Lecture 6 Vector Autoregressive Processes - Granger Causality, Impulse Response Analysis Reading the textbook Lecture 7 Problem Solving Solving related problems problem session 8 Midterm Exam 9 Vector Autoregressive Processes - Variance Decomposition Reading the textbook Lecture 10 Cointegration - Definition and Properties of Cointegrated Processes Reading the textbook Lecture 11 Cointegration - Cointegration in Single Equation Models: Represantation, Estimation and Testing Reading the textbook Lecture 12 Cointegration - Cointegration in Single Equation Models: Represantation, Estimation and Testing (continue) Reading the textbook Lecture 13 Cointegration - Cointegration in Vector Autoregressive Models: (i) The Vector Error Correction Representation, (ii) The Johansen Approach Reading the textbook Lecture 14 Cointegration - Cointegration in Vector Autoregressive Models: (iii) Analysis of Vector Error Correction Models, Cointegration and Economic Theory Reading the textbook Lecture 15 General Review Solving related problems problem session 16/17 Final Exam   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  Introduction to Modern Time Series Analysis, G.Kirchgassner - J.Wolters, Springer-Verlag, Berlin Heidelberg, 2007 Required Course Material(s)   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 100     Homeworks/Projects/Others 0 0 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 5 2 Explains Econometric concepts 5 3 Estimates the model consistently and analyzes & interprets its results 5 4 Acquires basic Mathematics, Statistics and Operation Research concepts 5 5 Equipped with the foundations of Economics, and develops Economic models 3 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 5 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 1 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 0 13 Uses Turkish and at least one other foreign language, academically and in the business context 5 14 Good understanding, interpretation, efficient written and oral expression of the people involved 1 15 Questions traditional approaches and their implementation while developing alternative study programs when required 0 16 Recognizes and implements social, scientific, and professional ethic values 2 17 Follows actuality, and interprets the data about economic and social events 2 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 0 0 0     Mid-term Exams (Written, Oral, etc.) 1 20 20     Final Exam 1 30 30 Total Workload: 134 Total Workload / 25 (h): 5.36 ECTS Credit: 5