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The purpose of the paper is to investigate the causal relationships and speed of adjustment of stock prices to changes in macroeconomic information (MEI) in Ghana from 1996 to 2018 using monthly data. The paper seeks to conduct the investigation at individual MEI level rather than the composite MEI.

Quantitative approach was used in this paper. Monthly data span of 1996–2018 was used. The delay and half-life technique was used to determine the speed with which the information resulting from the changes in the macroeconomic are evident in the stock price. Thereafter, Toda–Yamamoto Granger no-causality approach was used to examine the causal relationship amongst variables.

The paper revealed that although the market adjustment to MEI has improved, the speed is till slow. The exchange rate exhibited the slowest speed in respect of the market reaction while the market reaction to money supply was the fastest. Toda–Yamamoto Granger no-causality estimation also revealed a bi-directional causality between MEI (gross domestic product, interest rate and money supply) and stock price and uni-directional relationship flowing from MEI (the exchange rate and foreign direct investment) to stock price. The paper also found no causality between inflation and stock price.

The findings although revealed improved level of market efficiency in comparison with the earlier data, the speed of adjustment is still undesirable. Rigorous approach should be adopted for the implementation of major reforms such as alternative market so as to increase the number of share listing and to increase the scope of investors' participation to enhancing trading volume and marketability and ultimately speed up information diffusion.

The practical implication of the low level of information processing rate of Ghana Stock Exchange (averagely more than a month) is that astute investors and market analysts could employ MEI to outperform the market prior to their infusion onto the stock market.

This study is one of the few studies in the Ghanaian literature that has extended the investigation of the speed of adjustment beyond composite or aggregate macroeconomic level estimation to estimation at individual variable level. This contribution is very relevant since each macroeconomic variable has unique characteristics and require specific policy framework, it is important to consider the speed of adjustment from the perspective of each of the individual variables.

The purpose of this paper is to develop a new framework to test the hypothesis that portfolio model predicts a negative correlation between stock prices and exchange rates in a trivariate transmission channel for foreign portfolio equity investment.

This paper utilizes panel data for eight economies to extend the Dumitrescu and Hurlin (2012) Granger non-causality test of heterogeneous panels to a trivariate model by integrating the Toda and Yamamoto (1995) approach to Granger causality.

The evidence suggests that stock prices Granger-cause exchange rates and portfolio equity flows Granger-cause exchange rates. However, the overall panel evidence casts doubt on the explicit trivariate model of portfolio balance model. The study shows that Indonesia may be the only case where stock prices affect exchange rates through portfolio equity flows.

The proposed test does not account for potential asymmetries or structural shifts associated with the crisis period. To isolate the impact of the Asian Financial crisis, this paper rather splits the sample period into two sub-periods: pre- and post-crises. The sample period and countries are also limited due to the use of the balance of payment statistics.

The study casts doubt on the maintained hypothesis of a trivariate transmission channel, as posited by the portfolio model. Policy makers of an economy may integrate capital market and fiscal policies in order to maintain stable exchange rate.

This paper integrates a portfolio equity inflow variable into a single framework with stock price and exchange rate variables. It extends the Dumitrescu and Hurlin’s (2012) bivariate stationary Granger non-causality test in heterogeneous panels to a trivariate setting in the framework of Toda and Yamamoto (1995).

The purpose of this paper is to analyze cointegration and causality relationships between spot and futures markets in Turkish foreign‐exchange markets.

The research employs Bounds cointegration test and Toda‐Yamamoto causality test to detect a possible risk transmission between spot and futures markets. Time series of Turkish spot and futures foreign‐exchange markets from January 2, 2006 to March 25, 2008 on a daily basis are used for empirical analysis.

The empirical tests suggest that there is unidirectional causality running from future exchange‐rate market to spot market implying that foreign‐exchange markets have informational efficiency in Turkey.

The paper has originality in both employing Bounds test and Toda‐Yamamoto test to examine the relationship between spots and derivative markets, and in being one of the first empirical papers examining Turkish futures markets. In addition, the paper presents a guide on how Bounds and Toda‐Yamamoto tests can be applied to detect interactions among markets without data stationarity.

This study aims to determine whether there is an effect of internal and public debt on income inequality in Kenya for the period 1970–2018.

The relationship is examined by using the Autoregressive Distributed Lag (ARDL) model by Pesaran et al. (2001) and Toda Yamamoto causality by Toda and Yamamoto (1995).

Our findings suggest that both internal and public debt harm inequality in Kenya in the long term. Furthermore, a one-way causality from internal debt to income inequality is also obtained while no causality relationship is found to exist between public debt and income inequality. Based on these findings, the study recommends that to reduce income inequality levels in Kenya, other methods of financing other than debt financing should be preferred because debt financing is not pro-poor.

This study is unique based on the fact that no previous paper has analysed the debt and inequality relationship in Kenya. To the best of our knowledge, this will be the first study to analyse the applicability of redistribution effect of debt in Kenya. The study is also different in that it provides separate analysis for public debt and internal debt on their effects on income inequality.

The study aims to find the synchronization between foreign agriculture investment (FAI) and Sustainable Development Goals (SDGs) related to agriculture as classified by the Food and Agriculture Organization (FAO). The study tries to find such an association in India over 2 decades from 2001.

The Toda-Yamamoto Granger using the M-Wald test for the non-causality procedure is applied to find the synchronization. Stationarity is tested using the Augmented Dickey-Fuller, Phillips-Perron and Kwiatkowski, Phillips, Schmidt and Shin (KPSS) tests. The Johanson methodology with MacKinnon-Haug-Michelis P-value is employed for the Cointegration test.

The empirical results indicate that the FAI Granger cause SDG2 “Zero hunger” and “Overall sustainability”, but SDG13 “Climate Change”, SDG6 “Clean water and sanitation”, SDG12 “Responsible production and consumption” and SDG15 “Life on Land” granger cause global investments. Notwithstanding, SDG5 “Gender equality” and SDG14 “Life below water” found no-way causality with FAI.

Host governments should prioritize sector-level sustainable development, notably agricultural SDGs, to attract global investments. Foreign agriculture investment is influenced differently by various SDGs; thus, policymakers should concentrate on specific agricultural SDGs to enhance the flow of capital into the agriculture sector. Global investors should take sustainability into account while framing foreign investment plans, and the supra-national organization may consider global agricultural investments while addressing the problems related to global food security.

The distinguishing feature of the study is that SDGs classified by the FAO from a global investment perspective have not been studied so far.

The purpose of this study is to investigate the dynamic relationship that exists between energy consumption, environmental pollution and per capita economic growth in Tanzania. The energy consumption is represented by electricity usage in kilowatt hours (kWh) per capita, while environmental pollution is represented by carbon emission per metric tons and economic growth by gross domestic product (GDP) per capita.

This investigation is made based on the Environmental Kuznets Curve using time series annual data from 1975 to 2013 by applying the more robust causality technique of Toda and Yamamoto non-Causality test (1995), Impulse response and Variance Decomposition, Augumented and Dickey–Fueller test and Philips and Perron Test of unit root tests.

Economic growth rate (LGDP) and energy consumption per capita (LENGY), both being unidirectional, cause environmental pollution through carbon emission (LCO₂) in Tanzania. Interestingly, after using impulse response, a significant and positive economic growth (GDP per capita) was found due to shocks from electricity per capita (energy consumption) and carbon emission (LCO₂) with time. The Variance Decomposition suggested that the percentage of the variations due to shocks or innovations of economic growth (LGDP) and energy consumption (LENGY) to carbon emission is very high and significant, accounting to 46 and 41 per cent, respectively, in 10 years to come.

The study recommends that, in the future, the relationship be examined using super-exogeneity causality tests that takes into consideration the changes in policy or regime in contrast to Toda and Yamamoto. Furthermore, the addition of other variables such as fixed capital formation and labor force, which were not considered in this study, may result in strong correlation.

The results imply that the government of Tanzania can adopt environment conservation and energy saving policies without affecting its economic growth. As a matter of fact, to put a stop to persistent environmental pollution in Tanzania, the energy saving policy should be put in place rather quickly. It is imperative that the government implements policies and strategies that ensure continuous economic growth without forsaking the environment.

Despite the increase in carbon emissions, energy consumption and economic growth in Tanzania since 2000, to date, no previous work has been done to investigate their multivariate relationship. This is the first study that uses the Toda and Yamamoto non-Causality test, Impulse Response and Variance Decomposition Analysis to investigate a trivariate relationship of the variables mentioned above.

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 aim of the study is to evaluate role of trade war between the United States and China on oil price. For this purpose, global oil price and US trade balance with China are selected as variables. In addition to this issue, monthly data of these variables for the periods between 1990 and 2019 are taken into consideration. In the evaluation process, both Engle–Granger cointegration and Toda–Yamamoto causality analysis are considered. The results of Engle–Granger cointegration analysis indicates that there is a ­relationship between trade war and oil prices. Nevertheless, according to the results of Toda–Yamamoto causality analysis, it is identified that trade war does not cause oil prices. While looking at these results, it is determined that trade war between the United States and China has an influence on the oil price changes. However, it is also understood that it is not the main factor of this volatility. Thus, it is recommended that in order to identify the main indicator of the oil price volatility, some different factors should also be taken into consideration.

This study aims to examine the influence of socioeconomic development on inflation in South Asia using the foreign exchange rate and money supply as control variables.

The study uses annual panel data for five South Asian economies, namely, Bangladesh, India, Nepal, Pakistan and Sri Lanka over the period 1990–2018, applies cointegrating regression techniques, namely, the panel dynamic ordinary least square (OLS) and fully modified OLS estimators to examine the long-run relations and conducts the Toda-Yamamoto Granger causality test to detect the direction of causality among variables.

The cointegrating regression estimations have documented that the socioeconomic development proxied by the human development index (HDI) has no significant impact on inflation. Although economic development represented by gross domestic product (GDP) growth causes inflation, socioeconomic development represented by HDI has no impact on inflation and has demonstrated as a better macroeconomic indicator, and thus creates no inflationary pressure in the economy. The foreign exchange rate has a positive impact on inflation. The broad money supply has the usual positive effect on domestic inflation that endorses the monetarist view about prices. The Toda-Yamamoto Granger causality test has confirmed several unidirectional causalities: inflation causes HDI, money supply causes both inflation and HDI and the foreign exchange rate causes HDI.

The study has practical implications for policymakers in South Asia, to improve HDI, particularly GDP per capita, education and health-care facilities to realize continuous socioeconomic development, which will take care of inflation. Moreover, these counties may follow a conservative monetary policy to control inflationary pressure in their economies.

The study is original and claims to be the first to examine the impact of socioeconomic development on inflation. The findings have socioeconomic values regarding controlling inflation in South Asia.

The purpose of this paper is to study the market efficiency, unbiasedness and the direction of causality among four agricultural commodity futures contracts for a forecasting horizon of 28 days, 56 days and 84 days which are traded at National Commodity and Derivatives Exchange Ltd.

To analyse the efficiency of futures market in Indian scenario, we focus on maize, chickpea, soybean and wheat which are among the most important agricultural commodities traded in India. In the first step, Augmented Dickey-Fuller test and nonparametric Phillips-Perron approaches have been used to examine the stationarity of all futures and spot price series. After testing the presence of cointegration in futures and spot series using Johansen’s Cointegration approach, the joint restrictions of β ₀=0, β ₁=1 and β ₁=1 on the cointegrating vectors were imposed to test whether the futures price is an unbiased predictor of spot at contract maturity. In the next step, linear Toda and Yamamoto (1995) and the nonparametric Diks and Panchenko (2006) causality tests were applied to examine the direction of causality. Finally, nonlinear test were applied on the vector error correction model (VECM) residuals to investigate whether any remaining causality is strictly nonlinear in nature.

The results of cointegration tests between futures and spot prices of the selected agricultural commodities indicated a long term relationship do exist in three out of four futures contracts. However, the Wald tests results on the cointegrating vectors indicate markets as inefficient and biased. Further, analysis of short-term relationship using alternate tests of causality do not give consistent results for same commodity series indicating that results may vary due to alternate measures and specifications. Finally, if we consider the results of Diks-Panchenko test on the filtered VECM-residuals, results provide evidence that if cointegration is taken into account; neither spot nor future leads or lags the other consistently.

The results are based on the sample of four agricultural futures commodity contracts. The study can be extended to a larger sample of contracts and relative efficiency of each contract can be explored.

There are very few studies that have explored the efficiency, unbiasedness and direction of causality using both linear and nonlinear techniques for Indian agriculture commodity futures market for different forecasting horizons.