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While the relationship between natural resource rent and economic growth is well documented in the literature, not much robust analysis has been done to estimate the causative relationship between oil resource rent and economic growth in Ghana. This might be due to the fact that commercial production of crude oil started not long ago in Ghana. This paper aims to examine the causal relationship between oil resource rent and economic growth for the period of 2011 to 2020 in Ghana.

The study incorporates economic growth as a function of oil resource rent, non-oil revenue, foreign direct investment, capital and interest rate in a Cobb–Douglass production function/model. The study used four different estimation strategies including the autoregressive distributed lags model, Toda–Yamamoto test approach, nonlinear autoregressive distributed lags model and nonlinear Granger causality.

The main finding revealed that 1% increase in oil resource rent generates 0.84% increase in economic growth of Ghana in the long run. Contrary, the authors find an insignificant positive effect of oil resource rent on economic growth of Ghana in the short run for the period under study. The result from the Toda–Yamamoto test approach also showed a unidirectional causality running from oil resource rent to economic growth of Ghana, providing evidence in support of the resource blessing hypothesis in Ghana. The results are robust to two different alternative estimation strategies.

The causal relationship between crude oil resource rent and economic growth is examined.

The purpose of this research is to examine the validity of the agriculture-induced environmental Kuznets curve (EKC) hypothesis with evidence from an autoregressive distributed lag (ARDL) approach with a structural break including real income and energy consumption in the model for Ghana over the period 1980–2014.

The ARDL approach with a structural break was used to analyze the agriculture-induced EKC model which has not been studied in Ghana. The dynamic ordinary least squares (DOLS), canonical cointegration regression (CCR) and fully modified ordinary least squares (FMOLS) econometric methods were further used to validate the robustness of the estimates, and the direction of the relationship between the study variables was also clarified using the Toda–Yamamoto Granger causality test.

The ARDL results revealed that GDP, energy consumption and agricultural value added have significant positive effects on CO₂ emissions, while GDP² reduces CO₂ emissions. The Toda-Yamamoto causality test results show a bidirectional causality running from GDP and energy consumption to CO₂ emissions whereas a unidirectional long-term causality runs from GDP² and agriculture value-added to CO₂ emissions.

This finding validated the presence of the agriculture-induced EKC hypothesis in Ghana in both the short run and long run, and the important role of agriculture and energy consumption in economic growth was confirmed by the respective bidirectional and unidirectional causal relationships between the two variables and GDP. Thus, a reduction in unsustainable agricultural practices is recommended through specific policies to strengthen institutional quality in Ghana for a paradigm shift from rudimentary technology to modern sustainable agrarian technologies.

This study is novel in the EKC literature in Ghana, as no study has yet been done on agriculture-induced EKC in Ghana, and the other EKC studies also failed to account for structural breaks which have been done by this study. This study further includes a causality analysis to examine the direction of the relationship which the few EKC studies in Ghana failed to address. Finally, dynamic ordinary least squares (DOLS), canonical cointegration regression (CCR) and fully modified ordinary least squares (FMOLS) methods are used for robustness check, unlike other studies with single methodologies.

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 current wave of decreasing electricity supply to meet the immediate demand of the populace is influencing not only economic growth but also the industrial productivity of the ECOWAS sub-region. In this context, this paper investigates the long-run and causal relationships between electricity consumption and industrial output in selected ECOWAS countries over the period 1971–2017.

The Autoregressive Distributed Lag (ARDL) bound testing approach is employed to determine the existence of relationships among the variables. The causal nexus between electricity consumption and industrial output is examined using both the Toda-Yamamoto causality test and the bootstrap-corrected causality technique.

The long run results indicated that increasing electricity supply enhances industrial output only in Benin, Cote d'Ivoire, Gambia, Guinea, Liberia, Nigeria, Senegal, and Sierra Leone. Furthermore, the causality test results confirmed the presence of all four hypotheses in this study, but the two causality tests agree, particularly in the evidence of growth and neutrality hypotheses. In the cases of Benin, Burkina Faso, Gambia, Ghana, Nigeria, and Sierra Leone, a unilateral causality running from electricity consumption to industrial output is found. However, no evidence of causality between electricity consumption and industrial production has been confirmed in Cote d'Ivoire, Guinea Bissau, Liberia and Niger.

The relevant energy stakeholders in the subregion need to reprioritize their policy framework to focus more on the electricity sector of their economies since electricity consumption is identified as an important driver of industrial growth in the West African countries.

This is the first study to provide a comparative and country-specific investigation of the nexus between electricity consumption and industrial output in Africa, particularly in the West African region.

The “resource curse phenomenon” has received a lot of attention from researchers; however, there has not been any sound explanation to back this phenomenon since the main reason why natural resource should restrain economic growth instead of boosting economic growth remains unanswered. This paper contributes to literature on “resource curse hypothesis” by examining the role of government effectiveness in influencing the impact of gas resource rent on economic growth.

The study adopted the Cobb-Douglass production and incorporated gas resource rent, institutional quality (government effectiveness), inflation and exchange rate as additional variables that influences total output (gross domestic product). The author estimated the empirical form of the Cobb-Douglass production using autoregressive distributed lag model (ARDL) and Toda and Yamamoto (1995) as the main estimation strategies while other time series approaches were used as a robustness check.

The estimates from the ARDL short-run and the long-run dynamics suggest that the direct impact of gas resource rent on economic growth was positive but not statistically significant. At the same time, the interacting of gas resource rent and government effectiveness showed a positive and statistically significant effect of nearly 0.4123 and 0.8724 on economic growth in the long run and short run, respectively. The results from the Toda and Yamamoto (1995) also indicated that economic growth has a strong influence on gas resource rent while government effectiveness drives economic growth and not vice versa.

The findings from this study imply that government effectiveness plays a crucial role in averting the “resource curse phenomenon”. Hence, improving government effectiveness and efficiency through minimizing corruption among state institutions would be imperative in curbing the “resource curse phenomenon” in developing countries.

The influential role of government effectiveness on the relationship between gas resource rent on economic growth is examined.

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.

This study investigates the causal relationship between financial innovation (FI) as proxied by the bank credits to private sector, as percentage of GDP and economic growth in case of Azerbaijan using annual data covering the period from 1992 to 2018. For this purpose, the Toda–Yamamoto causality test with the framework of vector autoregressive (VAR) model is utilized to test causal relationship between the variables. The estimation results reveal that there is bidirectional causal relationship between FI and economic growth. The findings of the study suggest the researchers and policy makers to understand the role of FI in economic growth for macroeconomic stability and sustainable development purposes in Azerbaijan and other developing oil-rich countries.

This paper empirically examines the impact of financial development on domestic investment in India for the period 1989–2017.

This study employs the autoregressive distributed lag (ARDL) bounds testing approach to co-integration to test the long-run relationship between financial development and domestic investment. To test the direction of causality, Toda–Yamamoto causality test and vector error correction model (VECM) Granger causality/Block Exogeneity Wald test have been employed. Investment has been measured by Gross Capital Formation. To capture various aspects of financial development in India, eight alternative indicators (both bank based and market based) have been used. With the help selected indicators, a composite index (FINDEX) of financial development has been constructed using principal component analysis (PCA).

The estimated result finds evidence in favour of positive, short-run and long-run impact of financial development on investment in the Indian economy. Both bank-based and market-based indicators are found to significantly affect the level of investment. The significant effect of efficiency-based financial development indicators (both bank based and market based) upon domestic investment implies that there is a need to implement policies that ensure the efficiency of financial intermediation.

To the best of authors' knowledge, not much research has been done to explore the relationship between financial development and domestic investment, especially in the case of Indian economy. This study also tries to find the impact of bank-based and market-based financial development indicators upon domestic investment to explore banks vs market issue.

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.