Researchers focus more on the relationship between research output and economic growth. The study of such a relationship is not only of theoretical interest, but it can also influence specific policies to improve the quality, and probably the quantity of research output. This paper has studied...

This study applies the bootstrap panel causality test proposed by Kónya (2006), which accounts for both dependency and heterogeneity across countries, to test the causal link between population growth and economic growth in 21 countries over the period of 1870-2013. With regards to the...

This paper compares the forecasting ability of five alternative types of models in predicting four key macroeconomic variables, namely, per capita growth rate, the CPI inflation, the money market rate, and the growth rate of the nominal effective exchange rate for the South African economy....

This paper provides an empirical analysis of the role of house prices in determining the dynamic behaviour of consumption in South Africa using a panel vector autoregression (PVAR) approach to provincial level panel data covering the period of 1996 to 2010. With the shocks being identified using...

This paper empirically examines the effect of house price changes on economic growth across provinces in South Africa. The economic impact of house prices is estimated using a panel data set that covers all nine provinces in South Africa from 1996 to 2010. We find that when heterogeneity,...

This paper uses a predictive regression framework to examine the out-of-sample predictability of South Africa’s equity premium, using a host of financial and macroeconomic variables. Past studies tend to suggest that the predictors on their own fail to deliver consistent out-of-sample forecast...

This paper empirically examines the causal linkages between policy uncertainty and house prices in a panel of seven advanced countries including Canada, France, Germany, Italy, Spain, the UK and the US. We implement a bootstrap panel causality test on quarterly data from 2001Q1 to 2013Q1, which...

This paper analyzes whether a wealth of information contained in 126 monthly series used by large-scale Bayesian Vector Autoregressive (LBVAR) models, as well as Factor Augmented Vector Autoregressive (FAVAR) models, either Bayesian or classical, can prove to be more useful in forecasting real...

This paper develops large-scale Bayesian Vector Autoregressive (BVAR) models, based on 268 quarterly series, for forecasting annualized real house price growth rates for large-, medium- and small-middle-segment housing for the South African economy. Given the in-sample period of 1980:01 to...

This paper analyzes the ability of principal component regressions and Bayesian regression methods under Gaussian and double-exponential prior in forecasting the real house price of the United States (US), based on a monthly dataset of 112 macroeconomic variables. Using an in-sample period of...