Course Information Undergraduate prospectus

Quantitative Methods and Econometrics

Course summary

Course code: ECON1142
Level: 5
Credits: 30
School: Business Faculty
Department: International Bus and Economics
Course Coordinator(s): Edna Solomon

Specification

Pre and co requisites

ECON 1010

Aims

The objective of this course is to provide students with an understanding of how various economic
situations can be modelled effectively by using statistical and econometrics techniques, and to
provide them with solid skills required for other economic courses as well as prepare them for their
final project. The specific aims of the course are to integrate economic theory, statistical methods
and the interpretation of data to analyse business and economic issues. The course provides an
opportunity to engage the students in deductive and inductive reasoning to enhance problem
solving and decision‐making skills. The course will also offer an opportunity to develop an ability in
establishing logical argument, numeric analyse and data interpretation critical for evaluating
alternative perspectives by introducing concepts relating to random variables and analysis of
variants, co‐variants and correlation and simple regression analysis. The students will learn about
the properties of two variable regression coefficients and hypothesis testing and the assumptions of
the classical linear regression model. The course will cover interval estimation and hypothesis testing.
They will also learn how to deal with regression analysis when the assumptions of the simple
regression model have been removed.

Learning outcomes

On successful completion of this course a student will be able to:
Learning
Outcome
1 Appreciate statistical thinking and reasoning for solving business and economic
problems
2 Present, interpret and analyse information in numerical form and draw statistical
inference and use appropriate computer software for this purpose
3 Plan and manage time effectively in relation to deadlines whilst displaying individual
initiative and enterprise in collecting interpreting and analysing data.
4 Conduct data analysis, interpret empirical results and access policy implications by
using econometrics methodology, building on economic theory specifying
econometrics models, estimating the parameters of the model, hypothesis testing,
forecasting and using the model for control or policy purposes.
5 Understand and critically evaluate the assumptions of the classical model and of data
(that may be incomplete), to make judgements, and to frame appropriate questions
to achieve a solution ‐ or identify a range of solutions ‐ to a problem
6 Identify and be able to propose corrections to situations when the error terms are
correlated as is often the case with economic and financial data over time.

Indicative content

Rules of differentiation, vectors, matrices and matrix manipulation
 Systems of linear equations
 functions of two variables and partial differentiation
 unconstrained optimization of functions of two variables
 constrained optimization and Lagrange multiplier
 probability measure and combinatorial analysis
 conditional probabilities
 discrete and continuous random variables and their distributions
 normal distribution and how to standardize a normal random variable
 the sampling distribution of the sample mean and the Central Limit Theorem
 Point and interval estimation
 Statistical inference on population mean
 Test hypotheses and errors in testing hypotheses
 Two sample z‐test and t‐test
 One‐way analysis of variance
 Simple linear regression
 Multiple linear regression
 Multicollinearity and heteroscedesticity
 Autocorrelation and model specification
 Discrete choice modelling or univariate time‐series: modeling and forecasting

Teaching and learning activity

Learning and teaching activities include lectures, tutorials, computer lab workshops and independent
study. Lectures will introduce students to mathematical and statistical methods that can be used to
solve problems and analyse data. Lectures also demonstrate how certain methods can be used to model
economic activity and how the models can be tested with empirical evidence. Independent study should
be geared towards preparatory work before lectures and further practical work in the form of solving
exercises and reporting any areas of difficulty. Students are expected to solve a range of exercises
before they come to tutorials, which will enable students to: (i) demonstrate how they solve problems;
(ii) indicate the relevance of their work for the study of economics; and (iii) communicate their findings
to their tutors and peers.

Assessment

In class Test 1 15%
50 Minutes
Outcome 1,2 & 4

In class Test 2 15%
50 Minutes
Outcome 1,2,4,5,6

Group Coursework Project 20%
Outcome 4,5,6
1500 Words

Final Examination 50%
Outcome 1,2,3,5,6
3 hrs

Pass Mark 40%