# Module Information

Module Identifier
EC30920
Module Title
INTRODUCTION TO ECONOMETRICS
2012/2013
Co-ordinator
Semester
Semester 2 (Taught over 2 semesters)
Pre-Requisite
Pre-Requisite
Other Staff

#### Course Delivery

Delivery Type Delivery length / details
Lecture 30 Hours.
Seminars / Tutorials 6 Hours.
Practical 6 Hours. 6 PC practical workshops

#### Assessment

Assessment Type Assessment length / details Proportion
Semester Assessment Assessment 1  10%
Semester Assessment Assessment 2  10%
Semester Assessment Assessment 3  2 pieces of coursework  20%
Semester Exam 3 Hours   3 Hour Examination  60%
Supplementary Assessment Repeat Assessment 1  Repeat Failed Elements or equivalent  10%
Supplementary Assessment Repeat Assessment 2  Repeat Failed Elements or equivalent  10%
Supplementary Assessment Repeat Assessment 3  Repeat Failed Elements or equivalent  20%
Supplementary Exam 3 Hours   3 Hour Examination  Repeat Failed Elements or equivalent  60%

### Learning Outcomes

On successful completion of this module students should be able to:

* Recognise a set of results from an OLS regression;

* Carry out a regression using microfit;

* Recognise key diagnostic tests;

* Describe the various remedies of these problems;

* Assess the policy implications of econometric models.

### Aims

This module introduces students to linear regression in economics, and the estimation, inference and hypothesis testing procedures involved. It builds from this introduction to help students to understand the implications of the failure of the Ordinary Least Squares Gauss-Markov aassumptions. Students are also introduced to how to correct these problems when they are present.

### Brief description

This module presents the basics of econometrics governing failure of the Gauss Markov assumptions and the remedy to these problems.

### Content

• Overview of Econometrics
• Causality versus Correlation
• Ordinary Least Squares regression
• Key Gauss-Markov assumptions
• Properties of the OLS Estimator
• Confidence Intervals
• Hypothesis Testing
• Violations of the Gauss-Markov Assumptions
• Multicollinearity
• Autocorrelation
• Heteroskedasticity
• Model Specification and Diagnostic Testing
• Time series econometrics: stochastic process, unit roots and stationarity, spurious regressions, cointegration, forecasting, diagnostic testing

### Module Skills

Skills Type Skills details
Application of Number * Development of quantitative (mathematical, statistical, econometric) skills
Communication * Development of oral and written communication including data responce
Improving own Learning and Performance * Development of quantitative analytical skills instrumental for learning in other moduls
Information Technology * Use of statistical (computer) software for data and regression analysis
Personal Development and Career planning * Development of quantitative analtyical skills useful in a wide range of professions and in further study
Problem solving * Identifying the problem to be solved * Finding pertinent data in order to solve the problem * Application of appropriate methods and statistical tools for solving the problem * Understanding and interpretation of results.
Research skills * Basic Research Skills pertaining to operationalization of economic theory into testable propositions * Testing these propositions using appropriate data and statistical techniques * Analysis of economic data
Subject Specific Skills * Use of statistical computer software to assess economic performance * Economic and policy analysis (in other subject areas of economics)
Team work * Team working skills through self-study working groups