Introduction to Econometrics

Overview

Understanding data is at the heart of economics. Data on different processes or events are often noisy and impossible to predict with complete accuracy. However, most data variables have patterns, and econometrics is about understanding and helping to explain these patterns. Do last year’s sales figures help me predict what my sales figures will be this year? Do taller people live longer? Does lecture attendance cause students to achieve better grades? These are the kind of questions that econometrics can answer.



First, we will look at data variables in isolation and see how univariate distributions can be used to make inferences. We will then look at how to model relationships between data variables and test for associations. Eventually, we will see how to model individual data variables as functions of several variables in the multivariate linear regression model. Interpretation plays a huge role in econometric understanding. A large part of the module will focus on interpreting econometric results and being able to identify potential flaws in econometric applications.



The course is practical. Throughout the lectures, we will see why econometrics helps us model data and also how this is performed in practice. In tutorials, you will be allowed to put these econometric skills into practice whilst receiving feedback from the module tutor. The module requires students to submit two projects. Tutorials teach introductory statistical programming techniques.

Learning Objectives

This module furthers knowledge of statistical methods used in the economics discipline. It expands the understanding of statistical methods and focuses on the techniques used in scenarios faced by economists. On completion, students should be able to distinguish how and why econometric theory helps in practical applications.

Students should be aware of the potential of econometrics to explain a wide range of economic and social phenomena. They should be able to critically assess econometric results, understand the implications of these results, and be aware of the importance of econometric modelling assumptions in the process.

Skills

Students will develop the quantitative skills necessary to undertake econometric analysis. This module fosters computer software and programming skills. All students are required to perform data handling, visualisation, and modelling exercises using econometric software. The ability to disseminate econometric analyses cogently will be emphasised and students will also develop their communication skills. The skills acquired by students in this module are particularly useful for those intending to pursue further study in economics (3rd year and postgraduate) or related disciplines, and also for those wishing to work in a profession involving quantitative analyses.

Assessment

Students must achieve an overall mark of 40% in the module to pass.