Machine Learning vs Traditional Forecasting Methods: An Application to South African GDP

Stellenbosch Working Paper Series No. WP12/2019
 
Publication date: August 2019
 
Author(s):
[protected email address] (Department of Economics, Stellenbosch University)
 
Abstract:

This study employs traditional autoregressive and vector autoregressive forecasting models, as well as machine learning methods of forecasting, in order to compare the performance of each of these techniques. Each technique is used to forecast the percentage change of quarterly South African Gross Domestic Product, quarter-on-quarter. It is found that machine learning methods outperform traditional methods according to the chosen criteria of minimising root mean squared error and maximising correlation with the actual trend of the data. Overall, the outcomes suggest that machine learning methods are a viable option for policy-makers to use, in order to aid their decision-making process regarding trends in macroeconomic data. As this study is limited by data availability, it is recommended that policy-makers consider further exploration of these techniques.

 
JEL Classification:

C32, C45, C53, C88

Keywords:

Machine learning, Forecasting, Elastic-net, Random Forests, Support Vector Machines, Recurrent Neural Networks

Download: PDF (762 KB)

Login

(for staff & registered students)



Need a password?
Forgot your password?

Upcoming Seminars

No seminars are currently listed. Please check back soon.
 
More...

BER Weekly

14 Jun 2024
As has been common this year, politics and interest rates were in the spotlight this week. Locally, a government of national unity (GNU) is taking shape. The international focus was on the aftermath of the European Parliamentary election, which led French President Emmanuel Macron to call for a snap election. Across the Atlantic Ocean, market participants...

Read the full issue
 

Upcoming Seminars

No seminars are currently listed. Please check back soon.
 
More...

BER Weekly

14 Jun 2024
As has been common this year, politics and interest rates were in the spotlight this week. Locally, a government of national unity (GNU) is taking shape. The international focus was on the aftermath of the European Parliamentary election, which led French President Emmanuel Macron to call for a snap election. Across the Atlantic Ocean, market participants...

Read the full issue