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
Lecturer and Office Hours: Moustapha Daouda Dala By appointment
Second Lecturer(s): 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.
MSc BAF Program
1 The students are gained the ability to look at the problems of daily life from a broader perspective. They gain the needed skills not only to understand economic problems in banking and finance but also to construct a model and defend in meaningful way.
2 They have knowledge about the finance and banking.
3 They have knowledge about the money and banking.
4 They have knowledge about the international finance and banking.
5 They have ability to use mathematical and statistical methods in banking and finance.
6 They know how to use computer programs in both daily office usage and statistical data evaluations in banking and finance department.
7 They have necessary banking and finance skills that needed in private and public sector.
8 They are intended to be specialist in one of departmental fields that they choose from the list of general economics, finance economics, public finance, corporate finance, finance management, international finance markets and institutions, banking and central banking, international finance and banking, money and banking, international trade and banking.
9 They have ability to utilize fundamental economic theories and tools to solve economic problems in banking and finance.
10 They are aware of the fact that banking and finance is a social science and they respect the social perspectives and social values of the society’s ethics.
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