# Module Information

Module Identifier
EC30900
Module Title
Introduction to Econometrics
2020/2021
Co-ordinator
Semester
Semester 1 (Taught over 2 semesters)
Pre-Requisite
Pre-Requisite
Other Staff

#### Assessment

Due to Covid-19 students should refer to the module Blackboard pages for assessment details

Assessment Type Assessment length / details Proportion
Semester Exam 3 Hours   Unseen written examination  60%
Semester Assessment 1 hour class based unseen test (Michaelmas term)  10%
Semester Assessment Coursework project (Lent-Easter term)  30%
Supplementary Exam 3 Hours   Unseen written examination  60%
Supplementary Assessment Repeat failed element or equivalent 1  10%
Supplementary Assessment Repeat failed element or equivalent 2  30%

### Learning Outcomes

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

* Demonstrate familiarity with and an appreciation of the need for statistical foundations behind regression analysis;

* Perform regression analysis using a statistical package and recognise a set of results from an OLS regression;

* Interpret and critically evaluate results of regression analysis;

* Utilise and recognise key diagnostic tests;

* Describe remedies of problems associated with violation of assumptions underlying the CNLRM;

* Critically assess the policy implications of econometric models in a range of contexts.

### Aims

This module is a core module in Economics Single Honours and Major degree schemes. The understanding of econometrics is an essential element of training in economics and is required for appreciation of empirical implementations of microeconomic, macroeconomic and other strands of economic theory.

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 understand the implications of the failure of the Ordinary Least Squares Gauss-Markov assumptions. Students are also introduced to what to do to fix the problems when the assumptions are violated.

### Brief description

This module introduces students to essential quantitative tools used in economic research to analyse economic data and model economic phenomena. The module presents a detailed and in-depth treatment of the method of ordinary least squares (OLS) used in estimating quantitative relationship between economic variables, the assumptions behind the appropriate use of OLS, the implications of the violation of such assumptions and the remedial measures that can be taken to remedy the problems arising from the violation of the assumptions behind OLS estimation. The module is taught over two semesters. There are thirty hours of lectures and twelve hours of seminar and/or practical sessions over the two semesters.

### Content

• Introduction to Econometrics
• Basics and a primer to regression analysis
• OLS and the CNLRM
• Simple Linear Regression Models Multiple Linear Regression Models
• Hypothesis Testing
• Models with qualitative regressors
• Violation of the assumptions underlying the CNLRM
• Multicollinearity Heteroscedasticity Autocorrelation Model misspecification Normality Assumption

### 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 modules
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

### Notes

This module is at CQFW Level 6