Evaluation of dynamic capital structures for the JSE technology sectors

Abstract: There is insufficient research on capital structure of firms in South Africa and none that we are aware of that focuses on the technology sector of the Johannesburg Stock Exchange (JSE), despite the critical role this sector plays in the economy. The current study bridges this gap in the literature. The modern-day need for speedy dissemination of information and technology transfer expects the technology sector to be dynamic and progressive. Therefore, the technology sector is conjectured to have an evolving capital structure in tandem with the digitalisation process in the economy. This study empirically examines if firms listed on the JSE technology sector engage in capital rebalancing and partial adjustment. Accordingly, appropriate conceptual frameworks are used to model capital rebalancing (on the one hand) as well as partial capital adjustment (on the other). Methodologically, two econometric models are applied. Balanced panel data is used to investigate capital rebalancing, while an unbalanced Generalised Method of Moments (GMM) is used to analyse partial capital adjustment. Relevant procedures for pre- and post-estimation validation were conducted, including tests for stationarity, normality, multicollinearity and the Hausman model selection process. The study findings show that firms practise capital rebalancing over time to maintain target debt-to-equity levels. Further, the results show that firms engage in partial capital adjustment to achieve certain target debt-to-equity ratios. In this regard, the speed of adjustments ranges between 45% and 57% per year for total debt and long-term debt respectively. The results of the current study concur with prior evidence on speed of adjustment for emerging economies. With regard to the partial adjustment model, and for the purpose of computing the mentioned speed of adjustment, the commonly applied capital structure determinants were employed (as covariates), namely, profitability, asset tangibility, total assets, and tax value. The variables used in this study are consistent with prior literature for trade-off theory, pecking order and market timing theory, especially the dynamic configurations of these models. The findings of this study should be beneficial to business and policy makers. One area of application is in recognising the advantages of utilising leverage for organisational growth in contrast to using internal sources of finance. Furthermore, by studying the interplay between leverage and firm speed of adjustment, government and policymakers can use the findings of this study to determine optimal interest rates to 6 support sustainable growth. Nevertheless, there are some limitations in the study, such as data availability, where owing to the nature of firms involved, the sector only has a modest population of 63 entities before data clean-up. Also, owing to other data restrictions, the study only considers firms listed on the JSE. Recommendations for further study include the incorporation of quantitative and qualitative methods in the study of capital structure to capture the driving elements in capital structure decision making at managerial level. The application of longer periods of study in capital structure may provide a clearer view for improved econometric modelling. This study has successfully modelled and investigated the question of whether firms in the JSE technology sector are involved in dynamic capital structure practice. The study findings show that firms, over time, carry out capital rebalancing and capital adjustment processes to maintain optimal capital structures. This study concludes that listed technology firms on the JSE follow dynamic capital structures...M.Com. (Investment Management