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The causal relationship between money and income (output) has been an important topic and has been extensively studied. However, those empirical studies are almost entirely on Granger-causality in the conditional mean. Compared to conditional mean, conditional quantiles give a broader picture of an economy in various scenarios. In this paper, we explore whether forecasting conditional quantiles of output growth can be improved using money growth information. We compare the check loss values of quantile forecasts of output growth with and without using past information on money growth, and assess the statistical significance of the loss-differentials. Using U.S. monthly series of real personal income or industrial production for income and output, and M1 or M2 for money, we find that out-of-sample quantile forecasting for output growth is significantly improved by accounting for past money growth information, particularly in tails of the output growth conditional distribution. On the other hand, money–income Granger-causality in the conditional mean is quite weak and unstable. These empirical findings in this paper have not been observed in the money–income literature. The new results of this paper have an important implication on monetary policy, because they imply that the effectiveness of monetary policy has been under-estimated by merely testing Granger-causality in conditional mean. Money does Granger-cause income more strongly than it has been known and therefore information on money growth can (and should) be more utilized in implementing monetary policy.

The purpose of this paper is to examine the causal relationship between inward foreign direct investment (FDI) and economic growth in Southern African Development Community (SADC) countries over the period 1980-2012. It also investigates whether the causal relationship between FDI inflows and economic growth is dependent on the level of income.

In order to assess whether the causal relationship between FDI inflows and economic growth is dependent on the level of income, the study divided the SADC countries into two groups, namely, the middle-income countries and the low-income countries. The study used the recent panel-data analysis methods to examine this linkage. The Granger causality test for the middle-income countries was conducted within a vector-error correction mechanism framework; while that of the low-income countries was conducted within a vector autoregressions framework.

The results for the middle-income countries’ panel show that there is a uni-directional causal flow from GDP to FDI, and not vice versa. However, for the low-income countries’ panel, there was no evidence of causality in either direction. The study concludes that the FDI-led growth hypothesis does not apply to SADC countries.

Methodology applied in this study is a bivariate framework which is likely to suffer from the omission of variable bias (Odhiambo, 2008, 2011). Second, the Granger causality analysis employed in this only investigates the direction of causality and whether each variable can be used to explain another, but does not directly test for the mechanisms through which FDI leads to economic growth and economic growth leads to FDI.

Future studies may include a third variable such as domestic savings, exports, or financial development in a trivariate or multivariate panel causality model. A more complete analysis which seeks to explain the channels through which FDI impacts growth is suggested for future studies. Lastly, sector level analysis will help policy makers draft effective industrial policies, which can guide allocation of incentives.

The results of this study support the Growth-led FDI hypothesis, but not the FDI-led growth hypothesis. In other words, it is economic growth that drives FDI inflows into the SADC region and into Southern Africa, and not vice versa. This implies that the recent high economic growth rates that have been recorded in some of the SADC countries, especially the middle-income countries, have led to a massive inflow of FDI into this region.

At the regional level, SADC as a regional bloc has been actively pursuing policies and strategies aimed at attracting FDI into the region. Despite the important role of FDI in economic development, and the increase in FDI inflows into SADC countries in particular, there is a significant dearth of literature on the causal relationship between FDI and economic growth. The study used the recent panel-data analysis methods to examine the causal relationship between FDI and economic growth in SADC countries.

A number of recent papers have raised serious questions about the validity of the German dominance hypothesis, using Granger (temporal) causality tests. If Germany dominates within the European Monetary System, then German monetary policy, measured by either money stocks or interest rates should Granger (temporally) cause other EMS countries’ monetary policies, but not vice versa. Empirical evidence leads analysts to conclude that the German dominance hypothesis is invalid, or at a minimum, in need of significant reformulation. Explores similar Granger causality tests, using the recent cointegration and error‐correction modelling strategy, for the US and a group of developing countries during the Bretton Woods period, where conventional wisdom suggests that US policy dominated. Finds significant evidence of two‐way causality between the US money stock and the money stocks of a large number of developing countries. These findings raise a serious questions about the interpretation and/or appropriateness of the Granger causality test for investigating policy dominance hypotheses.

The purpose of this paper is twofold. First, the paper examines the risk transmission between crude oil and petroleum product prices of Japan’s oil futures market. Second, it compares the performance of two tests for Granger causality using realized variance (RV) and the exponential generalized autoregressive conditional heteroscedasticity (EGARCH) model.

The author measures the daily RV of crude oil, kerosene and gasoline futures listed on the Tokyo Commodity Exchange using high-frequency data, and he examines the Granger causality in variance between these variables using the vector autoregression model. Further, the author estimates the EGARCH model based on daily data and test for Granger causality in variance between commodity futures using Hong’s (2001) approach.

The results of the RV approach reveal that the hypothesis on the existence of a mutual volatility spillover between crude oil and petroleum product markets is accepted. However, the results of the conventional approach indicate that all the hypotheses on Granger causalities in variance are rejected. The methodology based on intraday high-frequency data exhibits higher power than the conventional approach based on daily data.

This is the first paper to investigate Japan’s oil market using RV. The authors conclude that the approach based on RV is universally adoptable when testing for Granger causality in variance.

The purpose of this paper is to investigate the dynamic relationship among Gold, Crude oil, Indian Rupee-US Dollar and Stock market-Sensex (gold, oil, dollar and stock market (GODS)) in the pre-crisis, the crisis and the post-crisis periods in the Indian context.

The authors use Johansen’s cointegration technique, Vector Error Correction Model (VECM), Vector Auto Regression, VEC Granger Causality/Block Exogeneity Wald Test, and Granger Causality and Toda Yamamoto modified Granger causality to study long-run relationship and causality.

Johansen’s cointegration test results indicate that there is a long-run equilibrium relationship among the variables in the pre-crisis and the crisis periods but not in post-crisis period. VECM results report that none of four models of the variables show long-run causality in the pre-crisis period. During the crisis period, both crude oil and Sensex models show long-run causality. However, in some cases, results indicate short-run causality. The authors find one-way causality from USD and Sensex to crude oil, and from gold and Sensex to USD. Thus, the authors conclude that the relationship among GODS is dynamic across global financial crisis.

The research findings of this study are vital to the large group of stakeholders and participants of gold, crude oil, US dollar and stock market in emerging economies like India. The results are useful to importers, exporters, government, policy makers, corporate houses, retail investors, portfolio managers, commodity traders, treasury and fund managers, other commercial traders, etc.

This study is one of its kinds as it investigates the relationship among GODS in India in different sub-periods like before, during and after the global financial crisis of 2008. None of the studies compare phase-wise relationship among GODS in the Indian context. The study contributes to the economic theory and the body of knowledge. It highlights the need to revisit the economic theory to explain the interplay mechanism among GODS.

The nature of price volume relationship in asset market has been an interesting subject in financial research as it reveals a very important aspect which has implications for market efficiency. The purpose of this paper is to examine price volume relationships in Indian commodity futures market.

There are two competing models in price volume relationship. Mixture of distribution hypothesis, suggesting a positive contemporaneous relationship and sequential information arrival hypothesis (SIH), suggesting a positive intertemporal causal relationship. Both are tested using correlation coefficient and Granger causality test with vector auto regressive methodology.

Though there exists contemporaneous correlation between volume and price change in some of the cases, but in general on the basis of the presence of Granger causality it follows that SIH is supported.

As only three commodities futures have been studied in this paper, this study can be extended to include more number of commodities currently being traded so as to make it more exhaustive.

The research has been done with the data of MCX Gold, MCX Silver and MCX Crude. The results of causality suggest that inefficiency level is maximum in Silver which may be attributed to informational asymmetry.

The Indian commodity futures market is of very recent origin. Hence, very little research work has been undertaken in this space. The paper presents an assessment of the existence of informational asymmetry among the three commodity futures under the study.

The purpose of this study is to attempt to analyze Granger causality in the frequency domain framework between producers' prices measured by wholesale price index (WPI) and consumers' prices measured by consumer price index (CPI) in the context of India.

Analysis was carried out in the framework of time series and for analysis Johansen and Juselius's maximum likelihood approach for cointegration was applied after confirming that variables are integrated of order one, i.e. I(1) through the Lee and Strazicich unit root test. Finally, Granger causality was tested in the frequency domain by utilizing a recently developed approach of Lemmens et al. over the period January 1957‐February 2009.

The paper finds that CPI Granger cause WPI at a lower, intermediate as well as higher levels of frequency, reflecting very long‐run, intermediate as well as short‐run cycles. By contrast WPI Granger cause CPI at 5 percent level of significance was found at intermediate frequencies, reflecting significant intermediate cycles.

The study reveals that CPI is a leading indicator of producers' prices and inflation (i.e. WPI). This gives an indication that Indian policy analysts ought to control for factors affecting CPI in order to have control on WPI since WPI is used for making various macroeconomic indicators in real terms.

The main contribution of the paper is to show the evidence of bidirectional causality between WPI and CPI. Furthermore, use of a recent approach developed by Lemmens et al. for Granger causality in the frequency domain in this study is also relatively new. To the best of the author's knowledge there is no such study in this area either for developed or developing economy to date.

Proposes to re‐examine empirically the causal relationship between defence spending and economic growth in mainland China. First, using a VAR modelling technique with suitable diagnostics, e.g. Akaike’s FPE statistics and a likelihood ratio test for over‐ and under‐fitting the causal model, the results indicate a positive unidirectional causality flowing from defence spending to economic growth. Second, by evaluating a dynamic vector error‐correction model, variance decomposition and impulse response functions, then analyses the direction, duration and strength of Granger‐causality between defence spending and economic growth. The results broadly indicate that defence spending and economic growth did share a common trend over the sample period under analysis, but it was the former which stimulated the latter. Moreover, it is defence spending that has a much more perceptible and prolonged effect on economic growth, giving rise to implications that although expenditure on defence may have been politically motivated, over the long‐run this spending did play a significant indirect role in enhancing the growth potential of this, for many years, closed‐door economy.

This paper seeks to study the impact of bio‐fuel policies on oil and food futures prices from December 6, 2004 to August 1, 2008.

The daily closing prices of brent crude oil, light sweet crude oil, corn, wheat, soybeans, and rough rice futures from December 6, 2004 to August 1, 2008 are used in this research. The vector error correction model is applied in order to study the impact of bio‐fuel policies on oil and agricultural futures prices.

Unit root and cointegration tests show that the brent crude oil, light sweet crude oil, wheat, corn, soybeans, and rough rice futures are stationary and have a long‐run equilibrium relationship. Granger causality tests of the four periods shows that the causality relationship between oil futures and food futures changes over time. The first period result shows many Granger causes on several variables at a 5 percent significance level. The second period has more Granger causes at the 5 percent significance level. However, the Granger causality relationships become fewer and fewer in the third and fourth period.

This is the first paper to study the impact of the four major bio‐fuel policies of Brazil, the European Union, and the USA.

This paper examines the causal relationship between stock market performance and foreign exchange market in Egypt over the period 2009–2016. The study period is divided into two sub-periods: pre- and post-January 25th Egyptian revolution (ER). The reason is to examine how this revolution affects the causal relationship between the two markets' performance.

In this study, the daily basis data are used to enable good and effective observation changes in the foreign exchange rate and stock market performance over time. Stock market indexes and stock market capitalization are used as proxies for stock market performance. Further, the Egyptian pound to US$ exchange rate is used as a measure for foreign exchange market performance. The study analysis is done in stages. The first is to check the variables' stationarity for the pre- and post-revaluation. The second is to examine the cointegration among the variables. The third is to run vector autoregression (VAR) estimates, after which VAR Granger causality tests are employed.

The results show that the data are not stationary at their levels but stationary in their first difference level while there is no cointegration in the long-run among the variables in both sub-periods. Further, findings indicate that, in the pre-January 25th revolution period, there is a significant causal relationship between the foreign exchange market and stock market indexes and a significant causal relationship between market capitalization (CAP) and exchange rate at the 1% level. However, in the post-January 25th revolution period, the study does not find a significant causal relationship between foreign exchange market and stock market indexes and capitalization.

As this study focuses on the causal relationship between foreign exchange and stock markets before and after the 25th January Revolution, other macroeconomic variables such as consumer price index, interest rate and GDP were excluded for the comparison purposes with other studies. Further research is suggested to include them in the analysis to find out its effect on the performance of stock market and foreign exchange market.

The existence of long-run bidirectional causality means that portfolio managers and hedgers may have improved their understanding regarding the dynamic relationship between foreign exchange market and stock market performance as this may help them to plan and implement suitable hedging strategies to guard against currency risk in future crises or events. Investors, fund and portfolio managers and policymakers should give much attention to these event-specific interactions when they make capital budgeting decisions and implement regulation policies. Furthermore, our results may allow portfolio managers, investors and policymakers to assess the importance of informational efficiency for both markets.

This paper is an original contribution to the literature that concerns the causal relationship between stock market and foreign exchange market in the period of political instability and social unrest such as the January 25th Revolution in one of the emerging markets, namely Egypt.