Social Ingredients and Conditional Convergence in the Study of Sectoral Growth

In this research article, we investigate the improved modelling ability and the outstanding policy advocacy of infusing health and education in sectoral growth equations of the South African economy. Our findings not only include improved and dependable modelling results but also provide distinct estimates of the returns on investment in health and education per sector using Iterative Seemingly Unrelated Regressions techniques. Additionally, this paper provides a theoretical description of the productivity effects of HIV/AIDS using sectoral equations. Also, this research investigates the diffusion process in the technological progress at the South African sectoral level and its impact on the study of social ingredients. Using a fixed effects model, some features of the diffusion process are explained.Coefficient of effectiveness, Diffusion process, Fixed effects model, Seemingly Unrelated Regressions

Social Ingredients and Conditional Convergence in the Study of Sectoral Growth

In this research article, we investigate the improved modelling ability and the outstanding policy advocacy of infusing health and education in sectoral growth equations of the South African economy. Our findings not only include improved and dependable modelling results but also provide distinct estimates of the returns on investment in health and education per sector using Iterative Seemingly Unrelated Regressions techniques. Additionally, this paper provides a theoretical description of the productivity effects of HIV/AIDS using sectoral equations. Also, this research investigates the diffusion process in the technological progress at the South African sectoral level and its impact on the study of social ingredients. Using a fixed effects model, some features of the diffusion process are explained.Coefficient of effectiveness; Diffusion process; Fixed effects model; Seemingly Unrelated Regressions

The impact of economic shocks in the rest of the world on South Africa : evidence from a global VAR

The substantial change in South Africa’s trade patterns over the past two decades has affected the impact of economic shocks in major world economies on South Africa. To investigate the effect, we use a global vector autoregression (GVAR) model with time-varying trade weights to account for changing international trade linkages. We show that the long-term impact of a shock to Chinese GDP on South African GDP is much stronger in 2009 than in 1995, due to the substantial increase in South Africa’s trade with China since the mid-1990s. At the same time, the importance of the U.S. economy to South Africa diminished considerably. The results indicate one of the possible reasons why the recent global crisis did not affect South Africa as much as it affected developed economies. It also stresses the increased risk, to the South African and other economies, should China experience slower GDP growth.Commonwealth Scholarship Commission in the UK and the Cambridge Commonwealth Trust.http://www.tandfonline.com/loi/mree202017-09-30hb2016Economic

Monetary policy and inflation in South Africa : a VECM augmented with foreign variables

We develop a structural cointegrated vector autoregressive (VAR) model with weakly exogenous foreign variables, known as an augmented VECM or VECX*, suitable for a small open economy like South Africa. This model is novel for South Africa in two ways: it is the first VECX* developed to analyse monetary policy and the first model that uses time-varying trade weights to create the foreign series.We impose three significant long-run relations (augmented purchasing power parity, uncovered interest parity and Fisher parity) to investigate the effect of a monetary policy shock on inflation. The results suggest the effective transmission of monetary policy.http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1813-6982hb201

Non-linearities in inflation-growth nexus in the SADC region : a panel smooth transition regression approach

The main objective of central banks around the world is the achievement and maintenance of price stability, which actually creates an environment conducive for faster economic growth. Therefore, it is important for policy makers to understand the relationship between inflation and economic growth in order to make sound policies. If inflation is detrimental to economic growth, then policy makers should aim for low rates of inflation. This leads to a question; how low should the inflation rate be? Previous research in the non-linearities of the inflation–growth relationship has found that a positive relationship exists when the inflation rate is low and a negative relationship when the inflation rate is high. This implies the existence of a threshold level of inflation at which the sign switches. In this paper we use panel data for the period 1980– 2008 to examine the inflation–growth nexus in the Southern African Development Community (SADC) region and to endogenously determine the threshold level of inflation. To deal with problems of endogeneity and heterogeneity, the paper uses the Panel Smooth Transition Regression (PSTR) method developed by González et al. (2005) to examine the non-linearities in the inflation–growth nexus. This technique further estimates the smoothness of the transition from a low inflation to a high inflation regime. The findings reveal a threshold level of 18.9%, above which inflation is detrimental to economic growth in the SADC region.http://www.elsevier.com/locate/ecmodhb201

Exchange rate puzzles : a review of the recent theoretical and empirical developments

This paper presents a comprehensive literature review of the theoretical and empirical developments that have taken place over the last two decades in an attempt to address the exchange rate puzzles. Specifically, we discuss non-linear and Bayesian econometric techniques, Dynamic General Equilibrium models, and the Market Microstructure approach that has been designed to address three exchange rate puzzles, namely, the Purchasing Power Parity (PPP) puzzle, the exchange rate disconnect puzzle and the exchange rate determination puzzle. We conclude that the exchange rate puzzles are likely to be less puzzling, if researchers decide to move to non-linear econometric frameworks and microfounded general equilibrium models.http://www.iupindia.org/ijmoe.as

Do we need a global VAR model to forecast inflation and output in South Africa?

This study determines whether the global vector autoregressive (GVAR) approach provides better forecasts of key South African variables than a vector error correction model (VECM) and a Bayesian vector autoregressive (BVAR) model augmented with foreign variables. The article considers both a small GVAR model and a large GVAR model in determining the most appropriate model for forecasting South African variables. We compare the recursive out-of-sample forecasts for South African GDP and inflation from six types of models: a general 33 country (large) GVAR, a customized small GVAR for South Africa, a VECM for South Africa with weakly exogenous foreign variables, a BVAR model, autoregressive (AR) models and random walk models. The results show that the forecast performance of the large GVAR is generally superior to the performance of the customized small GVAR for South Africa. The forecasts of both the GVAR models tend to be better than the forecasts of the augmented VECM, especially at longer forecast horizons. Importantly, however, on average, the BVAR model performs the best when it comes to forecasting output, while the AR(1) model outperforms all the other models in predicting inflation. We also conduct ex ante forecasts from the BVAR and AR(1) models over 2010:Q1–2013:Q4 to highlight their ability to track turning points in output and inflation, respectively.Commonwealth Scholarship Commission in the UK and the Cambridge Commonwealth Trust.http://www.tandfonline.com/loi/raec202016-08-31hb201

Testing the out-of-sample forecasting ability of a financial conditions index for South Africa

The importance of financial instability for the world economy has been severely demonstrated since the 2007–8 global financial crisis, highlighting the need for a better understanding of financial conditions. We consider a financial conditions index (FCI) for South Africa that is constructed from sixteen financial variables and test whether the FCI does better than its individual financial components in forecasting the key macroeconomic variables of output growth, inflation, and interest rates. Two sets of out-of-sample forecasts are obtained—one from a benchmark autoregressive (AR) model and one from a nested autoregressive distributed lag (ARDL) model that includes one financial variable at a time. This concept of forecast encompassing is used to examine the out-of-sample forecasting ability of these financial variables as well as of the FCI, while also controlling for data mining.http://www.tandfonline.com/loi/mree202016-12-31hb201

Can we beat the random-walk model for the South African Rand-US Dollar and South African Rand-UK Pound exchange rates? : Evidence from dynamic model averaging

Traditionally, the literature on forecasting exchange rates with many potential predictors have primarily only accounted for parameter uncertainty using Bayesian Model Averaging (BMA). Though BMA-based models of exchange rates tend to outperform the random walk model, we show that when accounting for model uncertainty over and above parameter uncertainty through the use of Dynamic model Averaging (DMA), the gains relative to the random walk model are even bigger. That is, DMA models outperform not only the random walk model, but also the BMA model of exchange rates. We obtain these results based on fifteen potential predictors used to forecast two South African Rand-based exchange rates. In the process, we also unveil variables, which tends to vary over time, that are good predictors of the Rand-Dollar and Rand-Pound exchange rates at different forecasting horizons.http://www.tandfonline.com/loi/mree202016-11-30hb201

Predictive ability of competing models for South Africa's fixed business non-residential investment spending

The study evaluates the forecasting ability of models of South Africa’s real fixed business non-residential investment spending growth over the recent 2003:1–2011:4 out-of-sample period. The forecasting models are based on the Accelerator, Neoclassical, Cash-Flow, Average Q, Stock Price and Excess Stock Return Predictors models of investment spending. The Average Q, Stock Price and Return Predictors models appear more important in forecasting the behaviour of South Africa’s business investment spending growth over the recent 2003:1–2011:4 out-of-sample period. The results from this study point to the important role of the stock market in promoting investment growth in South Africa, underscoring the need for stock market development. Also, stock market variables seem to play an increasingly important role in predicting investment spending behaviour in recent times.http://www.ecocyb.ase.ro/am201