Using Twitter to measure policy uncertainty in South Africa

Abstract

Policy uncertainty affects economies around the world through the impact that it has on employment, stock markets, consumption, inflation, production, investment, and exports, which ultimately affects economic growth. Due to these economic consequences, policy uncertainty has been receiving increased attention in recent years. Since policy uncertainty impacts developing countries more severely than developed countries, it is an especially important concern to policymakers in countries such as South Africa. The South African economy — already affected by poverty, inequality, and high unemployment — is troubled further by an environment of high policy uncertainty that causes weak confidence and low economic growth. The severity of the effects of policy uncertainty, not only in South Africa but all over the world, has highlighted the importance of addressing this issue. However, in order to be able to solve the problem of policy uncertainty, its causes, effects, and magnitude must first be understood. To facilitate an understanding of policy uncertainty, it is important that an accurate measure be obtained of the concept. This will provide support to economists and policymakers in terms of economic forecasting, evaluating the reception of policies and in implementing the lessons learned from previous policies. In South Africa, the North-West University (NWU) has developed a policy uncertainty index (PUI) based on uncertainty in the news media, the Bureau of Economic Research's (BER) manufacturing survey and the expert opinions of leading South African economists about economic policy uncertainty. However, the rise of social media has provided a new source of data that holds numerous benefits for sentiment analysis, which include the fact that data can be acquired in real time; that communication takes place in a dialogue format which enables the public to directly voice their opinions; and that it is easily accessible and provides a larger pool of data than was previously possible with traditional sources, such as surveys. This study used Twitter as a source of data to determine if social media can provide information about policy uncertainty in South Africa. This was done by calculating the correlation coefficients between measures of policy uncertainty derived from Twitter and various indicators of uncertainty, such as short-term interest rates, inflation, stock market prices, employment, investment, and household consumption. The Twitter uncertainty measures were also compared to two benchmark tests of policy uncertainty measures, namely Gross Domestic Product (GDP) and the NWU's policy uncertainty index. The results were obtained via two methods of data analysis. The first method demonstrated that a Twitter measure of uncertainty coincides with occurrences of major political events, while the second method indicated that a Twitter measure of conviction has significant relationships with stock market prices, employment, investment, and household consumption. The Twitter conviction variable also has a strong and significant relationship with GDP and, although no significant relationship exists with the second benchmark – the NWU's policy uncertainty index – this is attributed to the low amount of data observations available for the index. Although among the various indicators of uncertainty the Twitter uncertainty measure only shows a weak relationship with the Consumer Price Index (CPI), a strong, significant relationship was found with the benchmark GDP. Based on the results from these two methods, a simple Twitter-based index was constructed to measure policy uncertainty from a South African perspective. This study contributes to the knowledge base on policy uncertainty by showing that social media, especially Twitter, can and should be used to obtain information about policy uncertainty. In this regard, the recommendations to policymakers entail using measurements of policy uncertainty to judge the suitability and timing of their policy announcements and to make use of the functionalities provided by social media to mitigate policy uncertainty.