The purpose of this document is to set a framework for forecasting and predictive modelling for South African Cultural and Creative industries and their impact on sustainable development of the national economy and society.
This document is based on the ideas laid out in the accompanying SACO report on statistical framework for cultural and creative industries prepared by Prof. Jen Snowball (Rhodes University) and Prof Alan Collins (Portsmouth University). Ideally we would expect that the reader is already familiar with the report Towards the Development of a Framework for Cultural Statistics for South Africa [17].
Firstly we provide an overview of data (already available and likely to be available in foreseen future) and data sources that may be valuable in the task. Broadly this data may be categorised into three sets: (a) previously collected and recoded data; (b) purposely collected data (e.g. via specialised surveys) and (c) open data.
Secondly we review potentially productive methodologies and techniques that are most likely to contribute to the task of the design of scientifically motivated statistical, mathematical and computational predictive models.
Finally we elaborate on visualising techniques that support better understanding both of the data and the results of the modelling.
