Introduction
This course introduces the regression methods for analyzing data in economics. This is an introductory course in the theory and practice of classical econometric methods. The main components of the course deal with Single Equation Models, Dynamic Equation Models, Instrumental Variable Estimation and Multiple Equation Models. This course emphasizes both the theoretical and the practical aspects of statistical analysis, focusing on techniques for estimating econometric models of various kinds and for conducting tests of hypotheses of interest to economists. Some basic knowledge of matrix algebra and elementary statistical theory will be assumed, but a lot of it will be reintroduced during the lectures. The goal of this course is to help the students to develop a solid theoretical background in introductory level econometrics, the ability to implement the techniques and to critique empirical studies in economics. The computer is a fundamental tool in this course and students will be required to become familiar with some statistical software such as R, Eviews, STATA to analyze the econometric data and fitting of econometric models.
Learning outcomes
Textbooks
Course Plan
Week 
Topics and Reading. 
Books 
1 
Introduction to econometrics and its types. Econometrics data types 
Basic Econometrics 
2 
Review of the linear regression model assumptions 
Basic Econometrics 
3 
Multicollinearity: Definition, nature, consequences 
Basic Econometrics 
4 
Multicollinearity:Tests and solutions. 
Basic Econometrics 
5 
Heteroscedasticity: Definition, nature, consequences 
Basic Econometrics 
6 
Heteroscedasticity: Tests and solutions 
Basic Econometrics 
7 
Autocorrelation: Definition, nature, consequences 
Basic Econometrics 
8 
Autocorrelation: Tests and solutions 
Basic Econometrics 
9 
Specifications Tests 
Basic Econometrics 
10 
Error in variables problem: Reasons, Consequences, Tests and Solutions 
Basic Econometrics 
11 
Autoregressive and distributed lagged models. 
Basic Econometrics 
12 
Simultaneous Equation System 
Basic Econometrics 
13 
Identification 
Basic Econometrics. (388408) 
14 
Twostage and threestage Least Squares. 
Linear Models in Matrix form. (341348) Basic Econometrics. (441447) 
15 
Econometrics modeling with eviews and R 
The R book 

Description of system of Evaluation
Exam: Mid (30%), Final (50%), Sessional (20%): Assignments, Presentations, Quizzes, Class Participation.
Lecture Time (Regular) :
Tuseday (8:00 AM9:00 AM), Wensday (11:00 AM12:00 PM), Thursday (10:00 AM11:00 AM), Friday (10:00 AM11:00 AM)