COURSE INFORMATION Course Title: TIME SERIES IN ECONOMETRICS

Code	Course Type	Regular Semester	Theory	Practice	Lab	Credits	ECTS
ECO 402	B	2	3	0	0	3	7.5

Academic staff member responsible for the design of the course syllabus (name, surname, academic title/scientific degree, email address and signature)	NA
Lecturer (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	Moustapha Daouda Dala , By appointment
Second Lecturer(s) (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	NA
Teaching Assistant(s) and Office Hours:	NA
Language:	English
Compulsory/Elective:	Compulsory
Classroom and Meeting Time:
Course Description:	The course consists of econometric models which are employed in time series analyses. It covers the topics such as time series regression, exploratory data analysis, ARMA/ARIMA models, model identification/estimation/linear operators, GARCH family models, Co-integration, VAR analysis, Causality, Panel Data analyses. The Analyses are performed using E-views software program.
Course Objectives:	- to teach applied Time Series methodologies with an emphasis on model building and accurate prediction in order to apply to real life situations. - to provide the ability to bring together and flexibly apply knowledge to characterize, analyses and solve a wide range of social, economic and scientific problems. - to provide students skills required to research in economics and finance with exposure to more advanced econometric practices and models.

COURSE OUTLINE

Week	Topics
1	Introduction
2	The Nature of Time Series Data
3	Finite Sample Properties of OLS under Classical Assumptions
4	Trends and Seasonality
5	Stationary and Weakly Dependent Time Series
6	Dynamically Complete Models and the Absence of Serial Correlation
7	The Homoskedasticity Assumption for Time Series Models
8	Midterm Exam
9	Serial Correlation and Heteroskedasticity in Time Series Regressions
10	Infinite Distributed Lag Models
11	Spurious Regression
12	Cointegration and Error Correction Models
13	Forecasting
14	Review

Prerequisite(s):	Introductory course in statistics and econometrics.
Textbook:	Wooldridge J.M.(2015). Introduction to Econometrics. Cengage Learning
Other References:	Vogelvang B. (2015). Econometrics Theroy and Applications with E-views. Printice Hall.
Laboratory Work:	Yes
Computer Usage:	E-views software program
Others:	No

COURSE LEARNING OUTCOMES

1	Provide skill to apply economic models in econometrics
2	Provide skill to set up econometric models
3	Provide ability for testing specification of the model
4	Provide skill to apply time series econometric methods in academic research

COURSE CONTRIBUTION TO... PROGRAM COMPETENCIES (Blank : no contribution, 1: least contribution ... 5: highest contribution)

No	Program Competencies	Cont.
Master of Science in Economics Program
1	Students apply advanced knowledge in economics
2	Students explain the interaction between related disciplines and economics
3	Students apply scientific methods to address economic problems
4	Students define existing theory in a specialized branch of economics
5	Students critically evaluate knowledge in economics and carry out advanced research independently
6	Students develop economic models and formulate policy options
7	Students make an original contribution to the discipline
8	Students effectively communicate in a variety of professional and academic contexts
9	Students will develop new strategic approaches for unexpected, complicated situations in economics and take responsibility in solving them
10	Students uphold and defend ethical values data collection, interpretation and dissemination
11	Students use advanced empirical analyses to address social problems
12	Students interact with professional networks in their field of specialization

COURSE EVALUATION METHOD

Method	Quantity	Percentage
Midterm Exam(s)	1	35
Quiz	2	10
Final Exam	1	40
Attendance		5
	Total Percent:	100%

ECTS (ALLOCATED BASED ON STUDENT WORKLOAD)

Activities	Quantity	Duration(Hours)	Total Workload(Hours)
Course Duration (Including the exam week: 16x Total course hours)	16	3	48
Hours for off-the-classroom study (Pre-study, practice)	16	5	80
Mid-terms			0
Assignments	1	29.5	29.5
Final examination			0
Other	1	30	30
Total Work Load:			187.5
Total Work Load/25(h):			7.5
ECTS Credit of the Course:			7.5