## LUBS2570 Introduction to Econometrics

### 10 creditsClass Size: 300

Module manager: Dr Sandra Lancheros
Email: S.P.LancherosTorres@leeds.ac.uk

Taught: Semester 2 (Jan to Jun) View Timetable

Year running 2017/18

### Pre-requisite qualifications

LUBS1280 - Mathematical Economics

Or

LUBS1260 Mathematics for Economics and Business 1

Or

MATH1710 - Probability and Statistics I
And
MATH1712 - Probability and Statistics II

### Pre-requisites

 LUBS1260 Mathematics for Economics and Business 1 LUBS1280 Mathematical Economics MATH1710 Probability and Statistics I MATH1712 Probability and Statistics II

### This module is mutually exclusive with

 LUBS2225 Credit and Financial Analytics LUBS2925 Modelling Techniques for Business Analytics

This module is not approved as a discovery module

### Module summary

This module provides you with an introductory knowledge of applied econometric techniques and relevant software. The module introduces the basic assumptions and interpretation of the linear regression with one regressor. It extends this model to incorporate additional regressors in the multivariate regression analysis. Additionally this module assesses the particular problems that may arise in regression analysis such as, multicollinearity, autocorrelation, heteroskedasticity and omitted variable bias.

### Objectives

The aim of this module is to introduce students to the basic tools of econometrics to enable them to use these techniques to test economic theory It also provides the basic explanation of the analysis of modern time series economic data.

Learning outcomes
Upon completion of this module students will be able to:
- Explain and identify basic applied econometric techniques, and econometric theories and methodologies
- Interpret the outcomes of econometric analysis
- Assess the reliability of the results from a regression analysis, namely to evaluate the external and internal validity of a regression analysis

Skills outcomes
Upon completion of this module students will be able to:
Transferable
- Apply analytical and problem solving skills

Subject specific
- Apply econometric techniques and appropriate software to economic, accounting and financial analysis

### Syllabus

Indicative content:
- The nature of econometrics
- The basic linear regression model
- Ordinary least squares (OLS)
- Interpretation & assumptions of basic models
- Multivariate regression analysis
- Problems in regression analysis
- Multicollinearity
- Autocorrelation
- Heteroscedasticity
- Omitted variables

### Teaching methods

 Delivery type Number Length hours Student hours Computer Class 1 1.00 1.00 Computer Class 5 1.00 5.00 Lecture 22 1.00 22.00 Tutorial 4 2.00 8.00 Private study hours 64.00 Total Contact hours 36.00 Total hours (100hr per 10 credits) 100.00

### Opportunities for Formative Feedback

Progress monitoring will take place through the following routes:

- Individual feedback given in assignments for periodic seminars and computer sessions;

- Active communication using Announcements on the VLE;

- Practice exams (final exam) available via the VLE;

- Past exam papers with detailed solutions (final exam) available via the VLE;

### Methods of assessment

Coursework
 Assessment type Notes % of formal assessment Computer Exercise Continually assessed computer lab workshops and seminars 30.00 Total percentage (Assessment Coursework) 30.00

Resit will be 100% by exam.

Exams
 Exam type Exam duration % of formal assessment Standard exam (closed essays, MCQs etc) 1 hr 00 mins 70.00 Total percentage (Assessment Exams) 70.00

Resit will be 100% by exam.