Beatrice Desiree Simo-Kengne

The Impact of House Prices on Consumption in South Africa: Evidence from Provincial-Level Panel VARs

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 approach to provincial level panel data covering the period of 1996–2010. With the shocks being identified using the standard recursive identification scheme, we find that the response of consumption to house prices shock is positive, but short-lived. In addition, we find that a positive shock to house price growth has a positive and significant effect on consumption, while the negative impact of a house price decrease causes an insignificant reduction in consumption. This suggests that house prices exhibit an asymmetric effect on consumption, with the positive effect following an increase in house prices being dominant in magnitude in comparison to a decline in consumption resulting from a negative shock to house prices.

The Causal Relationship between Imports and Economic Growth in the Nine Provinces of South Africa: Evidence from Panel Granger Causality Tests

This paper examines the causal relationship between imports and growth in nine provinces of South Africa for the period 1996-2011, using panel causality analysis, which accounts for cross-section dependency and heterogeneity across regions. Our empirical results support unidirectional causality running from economic growth to imports for Gauteng, Mpumalanga, North West, and Western Cape; a bi-directional causality between imports and economic growth for KwaZulu-Natal; and no causality in any direction between economic growth and imports for the rest of provinces. This suggests that import liberalisation might not be an efficient strategy to improve provincial economic performance in South Africa. Indeed, provincial imports tend to increase in some provinces as economic growth improves.

Can the Sharia-based Islamic stock market returns be forecasted using large number of predictors and models?

This study employs 14 global economic and financial variables to predict the return of the Islamic stock market as identified by the Dow Jones Islamic Stock Market (DJIM). It implements alternative forecasting methods and allows for nonlinearity in the multivariate predictive regressions by estimating time-varying parameter models. All the methods fail to forecast the returns of the Sharia-based DJIM index over the out-of-sample period. The forecasts are weak at best, with only four predictors, the 3-month Treasury bill rate, inflation, oil price and return on the S&P500 Index, outperforming the benchmark autoregressive model of order one. The study suggests that the DJIM return is best predicted by an autocorrelation(1) model, and that future research should aim at analysing whether the performance of the linear autoregressive model can be improved by using nonlinear methods.

The dynamic relationship between house prices and output: evidence from US metropolitan areas

This paper investigates the long-run and short-term dynamics of 351 US metropolitan statistical area housing prices in relation to personal income. We apply a panel cointegration approach on annual data from 1993 to 2011 and find a long-run relationship between local house prices and per capita personal income. The causal direction is then assessed based on an autoregressive distributed lag specification that also accommodates for error-correction. Results from Granger-causality tests reveal the existence of a bi-directional causality between real house prices and real per capita personal income over both long and short-horizons. Our results continue to be robust, when our bivariate system is extended to include additional MSA-level (employment and population) and national-level variables (real stock price and mortgage interest rate). We conclude that changes in personal income can predict house price movements and vice versa.

Causal Relationship between Asset Prices and Output in the United States: Evidence from the State-Level Panel Granger Causality Test

Emirmahmutoglu F., Balcilar M., Apergis N., Simo-Kengne B. D., Chang T. and Gupta R. Causal relationship between asset prices and output in the United States: evidence from the state-level panel Granger causality test, Regional Studies. This paper investigates the causal relationship between asset prices and output across US states using a bootstrap panel Granger causality approach which allows not only for heterogeneity and cross-sectional dependence to be accounted for but also interdependency between asset markets. Empirical results from a trivariate vector autoregression (VAR) comprising real house prices, real stock prices and real per capita personal income over 1975–2012 reveal the existence of a unidirectional causality running from both asset prices to output. This confirms the leading indicator property of asset prices for the real economy, while also substantiating the wealth and/or collateral transmission mechanism.

The causal relationship between natural gas consumption and economic growth: evidence from the G7 countries

Abstract This article re-examines the nature of the causality between natural gas consumption and economic growth in G7 countries over the period from 1965 to 2011. We employ the Granger causality procedure proposed by Emirmahmutoglu and Kose (2011) which takes into account cross-sectional dependency and heterogeneity across countries. Our overall empirical results support the neutrality hypothesis for the panel while the individual country results confirm the same result with the exception of the case of UK, where the conservation hypothesis is confirmed, showing that GDP causes natural gas consumption in the country. These results make policies that promote the consumption of natural gas risk-free with regard to their effects to the economic growth and development levels.

The causal relationship between coal consumption and economic growth in the BRICS countries: Evidence from panel Granger causality tests

ABSTRACT This paper empirically analyzes the causal linkages between coal consumption and economic growth in the BRICS countries (Brazil, Russia, India, China, and South Africa) using annual data from 1985 to 2009. Due to the common directions and principals of the BRICS countries with regard to energy, the employed panel causality methodology is chosen to account for both cross-section dependence and heterogeneity across countries. Empirical results provide evidence of no causal relationship between the two variables, suggesting that neither coal consumption nor economic growth is sensitive to each other. While this finding vindicates the neutrality hypothesis overall for the BRICS countries, the individual country results provide support for a unidirectional causality running from coal consumption to economic growth for China; the opposite is true for South Africa and bidirectional for India. Policies to reduce coal consumption will have a detrimental effect on India’s economy. However, in the rest of the countries, policy makers should aim to step further from fossil-fuel generation – and specifically coal – of energy without the potential risks of having an impact to the economic growth and development.

The causal relationship between exports and economic growth in the nine provinces of South Africa: evidence from panel-granger causality test

This paper examines the causal relationship between exports and growth in nine provinces of South Africa for the period 1995-2011, using panel causality analysis, which accounts for cross-section dependency and heterogeneity across regions. Our empirical results support unidirectional causality running from economic growth to exports for Mpumalanga only; a bi-directional causality between exports and economic growth for Gauteng; and no causality in any direction between economic growth and exports for the rest of provinces. This suggests that export expansion might not be an efficient strategy to improve provincial economic performance in South Africa as neither exports nor economic growth is sensitive to each other in almost all provinces.

Evolution of Monetary Mechanism in the U.S.: The Role of Asset Returns

This paper investigates whether changes in the monetary transmission mechanism as captured by the interest rate respond to variations in asset returns. We distinguish between low-volatility (bull) and high-volatility (bear) markets and employ a TVP-VAR approach with stochastic volatility to assess the evolution of the interest rate in relation to housing and stock returns. We measure the relative importance of housing and stock returns in the movements of the interest rate and their possible feedback effects over both time and horizon and across regimes. Empirical results from annual data on the US spanning the period from 1890 to 2012 indicate that the interest rate responds more strongly to asset returns during low-volatility (bull) regimes. While the bigger interest-rate effect of stock-return shocks occurs prior to the 1970s, the interest rate appears to respond more strongly to housing-return than stock return shocks after the 1970s. Similarly, a higher interest rate exerts a larger effect on both asset categories during low-volatility (bull) markets. Particularly, larger negative responses of housing return to interest-rate shocks occur after the 1980s, corresponding to the low-volatility (bull) regime in the housing market. Conversely, the stock-return effect of interest-rate shocks dominates before the 1980s, where stock-market booms achieved more importance.