The impact of mobile communications infrastructure investment on economic growth in South Africa

Mobile telecommunications networks provide the ability to access the internet and use telephony services, where the infrastructure exists. Because of its mobile nature a customer can always connect to the internet, even when not in the comfort of their home, unlike the case with fixed-line services....

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Bibliographic Details
Main Author: Sookha, Keshal
Other Authors: Alhassan, Abdul Latif
Format: Dissertation
Language:English
Published: University of Cape Town 2018
Subjects:
Online Access:http://hdl.handle.net/11427/28372
Description
Summary:Mobile telecommunications networks provide the ability to access the internet and use telephony services, where the infrastructure exists. Because of its mobile nature a customer can always connect to the internet, even when not in the comfort of their home, unlike the case with fixed-line services. This paper studies the impact of mobile telecommunications investment on economic growth in South Africa. To test the impact of mobile telecommunications investment on economic growth, the dissertation examines the development of mobile telecommunications infrastructure in South Africa and the relationship between mobile communications infrastructure investment (MCII) on economic growth. It is hypothesised that MCII has a relationship with economic growth. The methodology employed by this study is the autoregressive distributed lags (ARDL) approach with secondary data sourced from the World Bank Group and Global System Mobile Association (GSMA) databases over the period 1994 to 2016. To model the relationship, the study used a neoclassical growth model with proxies for economic growth as gross domestic product (GDP); capital as mobile operator capital expenditure and gross capital formation; and labour as the labour force and the unemployment rate. Results of the study showed that there was a unidirectional Granger causality between GDP and MCII and therefore no bidirectional causal relationship between MCII and GDP. Furthermore, using the ARDL approach found no cointegration between the variables and consequently no long run relationship. Producing the short run model as a VAR (2) model using the Akaike information criteria (AIC) lag selection also resulted in no significant relationship between MCII and GDP. This result has very important implications for policy recommendations to government and for development. Firstly, government should investigate why there is no significant impact of MCII on GDP because this relationship does exist in other markets. From these findings, government can develop and adopt policies which could produce a positive effect of MCII on GDP.