Economics 388

This is a module in applied economics and does not form part of Economics taken as a major subject. It is particularly useful as a precursor to graduate studies in Economics, in terms of both the quantitative skills and the module content. It builds technical skills and also allows an opportunity to analyse in greater depth one area of application, viz. Labour Economics.

From 2022 onwards, this module consists of two parts:

Introduction to data science for economists: data scientific techniques applied to data in economics or finance. Topics include: programming, visualisation and elementary machine learning methods.

Labour economics and labour econometrics: this sub-module deals with some central policy concerns in South Africa. It consists of an introduction to Labour Economic theory and to South African labour market issues, while much attention is devoted to developing skills in analysing micro-level (labour market) datasets, e.g. estimating earnings functions or the determinants of labour force participation and employment.

Prerequisite Pass module (PP): Economics 214

Prerequisite module (P): Economics 244

Corequisite module (C): Economics 318

Continuous assessment

Credits: 24

Classes per week: 2 lectures, 2 tutorials

Module convenor: Dr Debra Shepherd (first semester)

Module convenor: Dr Eldridge Moses (second semester)

Work programme: Data Science for Economists

Work programme: Labour Economics