Ahdi Noomen Ajmi

Oil prices and MENA stock markets:New evidence from nonlinear and asymmetric causalities during and after the crisis period

This article investigates the potential of nonlinear causal relationships between world oil prices and stock markets in Middle East and North Africa (MENA) countries during a black swan period that is characterized by rarity and devastating impacts. Our study is carried out using the daily data for 11 MENA countries over the period from 2 July 2007 to 27 August 2012. By using the nonlinear and asymmetric causality test of Kyrtsou and Labys (2006), we mainly find that: (i) the oil prices and MENA stock markets interact in a nonlinear manner; (ii) the signs of changes in the causing variables are important for detecting the true causality links between the variables and (iii) the nonlinear causality is more pronounced in the case of the Brent than West Texas Intermediate oil prices.

Carbon emissions - income relationships with structural breaks: the case of the Middle East and North African countries

This article revisits the carbon dioxide (CO2) emissions-GDP causal relationships in the Middle Eastern and North African (MENA) countries by employing the Rossi (Economet Theor 21:962–990, 2005) instability-robust causality test. We show evidence of significant causality relationships for all considered countries within the instability context, whereas the standard Granger causality test fails to detect causal links in any direction, except for Egypt, Iran, and Morocco. An important policy implication resulting from this robust analysis is that the income is not affected by the cuts in the CO2 emissions for only two MENA countries, the UAE and Syria.

Modelling the volatility of the Dow Jones Islamic Market World Index using a fractionally integrated time-varying GARCH (FITVGARCH) model

Appropriate modelling of the process of volatility has implications for portfolio selection, the pricing of derivative securities and risk management. Further, a large body of research has suggested that both long memory and structural changes simultaneously characterize the structure of financial returns volatility. Given this, in this article, we aim to model conditional volatility of the returns of the Dow Jones Islamic Market World Index (DJIM), interest on which has come to the fore following the need for renovation of the conventional financial system, in the wake of the recent global financial crisis. To model the conditional volatility of the DJIM returns, accounting for both long memory and structural changes, we allow the parameters in the conditional variance equation of the fractionally integrated generalized autoregressive conditional heteroscedasticity (FIGARCH) model to be time dependent, such that the parameters evolve smoothly over time based on a logistic smooth transition function, yielding a fractionally integrated time-varying generalized autoregressive conditional heteroscedasticity (FITVGARCH) model. Our results show that, in terms of model diagnostics and information criteria, as well as, portfolio allocation, the FITVGARCH model performs better than the FIGARCH model in explaining conditional volatility of the DJIM returns, thus, highlighting the need to model simultaneously long memory and structural changes in the volatility process of asset returns.

Causality between Exports and Economic Growth in South Africa: Evidence from Linear and Nonlinear Tests

This paper investigates the dynamic causal link between exports and economic growth using both linear and nonlinear Granger causality tests. We use annual South African data on real exports and real gross domestic product from 1911-2011. The linear Granger causality result shows no evidence of significant causality between exports and GDP. The relevant VAR is unstable, which undermines our confidence in the causality result identified by the linear Granger causality test. Accordingly we turn to the nonlinear methods to evaluate Granger causality between exports and GDP. First, we use Hiemstra and Jones (1994) nonlinear Granger causality test and find a unidirectional causality from GDP to exports. However, using a more powerful and less biased nonlinear test, the Diks and Panchenko (2006) test, we find evidence of significant bi-directional causality. These results highlight the risk of misleading conclusions based on the standard linear Granger causality tests which neither accounts for structural breaks nor uncover nonlinearities in the dynamic relationship between exports and GDP.

Causality between US economic policy and equity market uncertainties: Evidence from linear and nonlinear tests

This paper examines the causal relationship between economic policy uncertainty (EPU) and equity market uncertainty (EMU) in the US. We use daily data on the newly developed indexes by Baker et al. (2013a) covering 1985:01:01 to 2013:06:14. Results from the linear causality tests indicate strong bidirectional causality. However, the parameters stability tests show strong evidence of short-run parameter instability, thus invalidating any conclusion from the full sample linear estimations. Therefore we turn to nonlinear tests and observe a stronger predictive power from EMU to EPU than from EPU to EMU. Using sub-sample bootstrap rolling window causality tests to fully account for the existence of structural breaks, we find evidence that EPU can help predict the movements in EMU only around 1993, 2004 and, 2006. However, we find strong evidence that EMU can help predict the movements in EPU throughout the sample period barring around 1998, 2003 and 2005.

Research output and economic growth in G7 countries: new evidence from asymmetric panel causality testing

ABSTRACT Recent studies have shown increasing interest 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 article has studied this relationship in G7 countries using the asymmetric panel causality test of Hatemi-J (2011). Our results show that only the UK shows a causal relationship from the output of research to real GDP. However, when the signs of variations are taken into account, there is an asymmetric causality running from negative research output shocks to negative real GDP shocks.

Oil Price and Consumer Price Nexus in South Africa Revisited: A Novel Asymmetric Causality Approach

The relationship between oil and the price level has always garnered the attention from policy makers and researchers. Periods of high oil price volatility is thought to induce negative repercussions for domestic price levels in an oil importing country. Research in the past has revealed that there exists an asymmetric component in the causal relationship between oil prices and consumer prices. To this end, we opt for a novel asymmetric causality test developed by Hatemi-J (2012) to explore the relationship between international oil prices and the price level in South Africa for a period that runs from 1921: M02 to 2013: M10. This method disentangles the effects of positive shocks from negatives ones allowing to test for an asymmetric relationship. Our evidence are in favour of a causal relationship that runs from oil prices to the price level, but this relationship is observed only for the short term since there is no long run cointegrating relationship. The asymmetric tests reveal that both a positive and negative oil price shock leads to a positive price level shock, however the evidence in favour of a negative oil price shock is stronger.

Contagion versus Interdependence: The Case of the BRIC Countries During the Subprime Crises

This chapter contributes to the empirical finance literature on modeling co-movement in financial markets by considering the case of the BRIC countries during the subprime crises. To overcome the problem of the time-varying behavior of stock market volatility when calculating the adjusted correlation coefficients, we propose the SWARCH—Adjusted correlation approach that combines the univariate ARCH regime-switching model (SWARCH) of Hamilton and Susmel (1994) and the adjusted correlation approach of Forbes and Rigobon (2002) . The empirical results reveal the presence of high interdependence between the US and BRIC countries, mainly in high volatility periods. Moreover, empirical investigation shows the presence of a contagion phenomenon running from the US to Brazil.

Money Demand Causality for Ten Asian Countries: Evidence from Linear and Nonlinear Causality Tests

Abstract This chapter estimates causality properties between real money demand and a number of determinants, that is, real output, the lending rate and the real exchange rate, across 10 Asian economies through linear and nonlinear causality methodologies spanning the period 1990–2012. The results document both bidirectional and unidirectional causality between monetary aggregates (M1 and M2) and their determinants for different country groups. The empirical findings exemplify the role of the demand for money as a policy tool and can provide useful policy recommendations to the Asian monetary authorities in their vision of forming a future monetary union.