The Economic Determinants of Budget Deficits in South Africa

Abstract

Since 1980, South Africa recorded massive budget deficits except in 2007 and 2008 when the budget surpluses as a percentage of GDP respectively stood at 0.3 per cent and 0.7 per cent. This stirred a great debate on whether budget deficits in South Africa are a result of poor governance or are due to the magnitude of the economic problems that the government seeks to alleviate. Therefore, this study examines the economic determinants of budget deficits in South Africa for the period 1980 -2010. Specifically, the study seeks to ascertain if budget deficits in South Africa are a result of the fight against economic problems. The Vector Error Correction Model (VECM) was used to determine the impact of selected macroeconomic variables on budget deficits in South Africa. The results revealed that all the determinants have a positive impact on budget deficits except for foreign debt. However, foreign reserves explain the largest component variation of budget deficit followed by foreign debt, unemployment, economic growth and government investment, in that order.

Budget Deficit and Economic Growth in Ethiopia: Evidence from ARDL-VAR Model Approach

“…The study result is inconsistent from Freidman and Neo-classical paradigm, but it supports the Keynesians postulates. The study result also consistent from (Farajova, 2011;Murwirapachena, Maredza, & Choga, 2013;Al-Qudah & Jaradat, 2018), but it is inconsistent with the study of (AbdRahman, 2012; Tung, 2018). As the study result shows when economic growth increase budget deficit also increase but Ethiopian economic growth is not much responsible to increase budget deficit, as the time series data shows Ethiopia highly experienced with budget deficit from 1974/75 -2019/202, this budget deficit is not due to economic growth.…”

The Significance of Mining Infrastructural Development on South African Economy from 1980–2013: An Econometric Approach

“…To select the lag order under VAR, the information criteria is provided as the direction to choose the appropriate lag order. In this present paper, the maximum lag of 3 was employed to allow adjustments in the model and undertake well behaved residuals (Murwirapachena, Maredza, Choga, 2013). However, according to Liew (2004) and Mah, Petersen, Miruka and Petersen (2013) argue that it is important to focus more on Akaike Information Criteria and Final prediction Error are superior when having less than 60 observations.…”

“…Both the trace and maximum eigenvalue tests do confirm the long run relationship of mining sector and economic growth in South Africa. Murwirapachena, Maredza and Choga (2013) in their paper declare that, the VECM allows to distinguish both the long run and short run variables and also to establish the influence of explanatory variables towards and explanator variable. The VECM permits to separate long run and short run effect of on the model.…”

The Impact of Budget Deficit on Economic Growth in an Emerging Market: An Application of the ARDL Technique

“…The USA is among few countries that run deficit yearly and still maintain a yearly economic growth rate. Murwirapachena, Maredza, and Choga (2013) employing unit root test such as; DF, and ADF, Johansen co-integration test, VECM, and VAR try to get to the bottom of what determines budget deficit in South Africa and using annual data covering 30 years' period (1980 to 2010). The author's outcome reveals the cointegration among the variables in the long run and Deficit-Growth relationship is positive and significant.…”