When The Last Tree Dies, The Last Man Dies: Do Forests Hold The Key To Survival In Ghana? A Critical Analysis Using The Bootstrapped Rolling Window Granger Causality Test Approach

This paper investigates the role of forests in the life expectancy of people in Ghana. We test whether the extinction of forests will inevitably lead to extinction of people in Ghana. We first examined the causal relationship between life expectancy and deforestation using the full sample bootstrap Granger causality test approach and find causality to run from deforestation to life expectancy with no feedback from life expectancy to deforestation. Testing for parameter stability, we found the short run and long run parameters of the estimated Vector Auto Regressive models to be unstable. A time-varying approach, the rolling window bootstrapped Granger causality test was then employed to investigate the causal relationship between life expectancy and deforestation. The results showed that deforestation has a negative effect on life expectancy, confirming the widely accepted saying that the health of forests is inextricably linked to the health of mankind. The empirical results further show that, on trend higher life expectancy increases the rate of deforestation in Ghana. Highlighting the importance of the role of forests in influencing life expectancy in Ghana, we recommend awareness creation on the role of forests in supporting human life and also extensive afforestation programs to reduce the rate of deforestation in Ghana. This, we believe, will reduce the spread of vector borne diseases such as malaria and reduce the surge in respiratory diseases which shorten the life span of Ghanaians.JEL codesQ23, Q50, Q53, Q58, Q58

Corruption – Poverty Nexus: Evidence from Panel ARDL Approach for SAARC Countries

The article intends to investigate the relationship between corruption and poverty based on the panel data of SAARC countries over the period 1996–2019. We employed the panel ARDL of pooled mean group (PMG) technique to analyze the data and focus on capability poverty, using the human development index (HDI) as a proxy for poverty. The empirical findings of PMG of the ARDL model suggest that an increase in corruption score (COC) (i.e. decrease in corruption) and increase in women’s labor force participation rate (WLFPR) seem to have a significant impact either in eradicating poverty or increasing social welfare in the long run as well as in the short run. A random effect (RE) model also identified a significant positive relationship between corruption score and HDI, and WLFPR and HDI. A Dumitrescu-Hurlin pairwise panel Granger non-causality test detected a bilateral causality relationship between COC and HDI, and WLFPR and HDI, while unilateral causality ran from WLFPR to COC. The article contributes to examining the dynamics between corruption and poverty from the governance aspect, taking South Asia as a case study.

Exchange rate and Export of Bangladesh: Does Marshall-Lerner condition holds?

Export is expected to have a favorable impact on GDP growth, and the exchange rate is expected to have a major impact on export and thus export earnings. The relationship between exchange rate and export is a hotly debated topic in macroeconomics, and the goal of this research is to see if the Marshall-Lerner condition holds incase of Bangladesh that is if devaluation of domestic currency increase export earnings. Explanatory variables of the model in the study are the exchange rate, foreign income (WGDP), and domestic income (DGDP). Cointegration approaches; Error Correction model, Granger Causality test are used in this study to estimate the long and short-run impacts. With time series data from 1973Q3 to 2018Q2, we used the Error Correction Model and the Granger Causality Test. The findings of VECM support short-run exchange rate and export adjustments. The bidirectional causality between exchange rate and export is established using the Granger causality test.

Research on the Spatial Spillover Effect of Provincial Final Consumption Level in China Based on the Complex Network

A spatial spillover correlation network is an excellent representation for expressing the relationship of consumption levels among regions, which provides a way to study the evolution mechanism of the spatial influence of the consumption level. Using data on the consumption levels of 29 provinces (or municipalities or autonomous regions) during the global stage (1978–2020) and two separated stages (1978–2001 and 2002–2020) after China’s reform and opening up, this paper analyzes the topological characteristics and driving factors of provincial residents’ consumption level spatial spillover network by applying the Granger causality test of Vector Autoregression (VAR) model and a complex network analysis method. The results show that the number of spatial spillover relationships of provincial residents’ consumption level in the second stage increases significantly in comparison with that in the first stage and the scope of mutual influence among provinces increases rapidly in the second stage; that eastern coastal regions play a net spillover role in the network and some central and western provinces play an increasingly important broker role; and that the members of the network compose four communities with different gradients, with Beijing, Shanghai, and Jiangsu in the leading positions. The network shows neighborhood spillover and club convergence, and these characteristics are more evident in the second stage; moreover, spatial adjacency, residents’ disposable income, urbanization level, consumer credit, and consumption environment similarity have significant driving effects on the spillover correlation of the consumption level.

Causal Relationship Between Economic Growth and Energy Consumption in Jordan

Due to the current situation of the Jordanian economy, this paper aims to evaluate the impacts of economic growth on energy consumption in a developing country like Jordan, a country with limited resources such as oil, agricultural land, and water. This study is very important since the energy bill reflects a notable share in the GDP for Jordan, especially in the recent decade that witnessed energy bills rising due to different political and financial crisis events. The study investigates the causal relationship between the per capita energy consumption and economic growth (proxied by real gross domestic product per capita in constant prices) over the 1975-2011 period. A Granger causality test is utilized on annual time series data. The results of the study confirm a neutral relationship between real GDP and energy consumption, indicating that per capita increase in economic growth may not cause any perpetual rise in energy consumption in Jordan.

Agricultural Water Use Efficiency: Is There Any Spatial Correlation between Different Regions?

Affected by global climate change and water shortages, food security continues to be challenged. Improving agricultural water use efficiency is essential to guarantee food security. China has been suffering from water scarcity for a long time, and insufficient water supply in the agricultural sector has seriously threatened regional food security and sustainable development. This study adopted the super-efficiency slack-based model (SBM) to measure the provincial agricultural water use efficiency (AWUE). Then, we applied the vector autoregression (VAR) Granger causality test and social network analysis (SNA) method to explore the spatial correlation of AWUE between different provinces and reveal the interprovincial transmission mechanism of spillover effects in AWUE. The results show the following: (1) In China, the provincial AWUE was significantly enhanced, and the gaps in provincial AWUE have widened in the past 20 years. (2) There were apparent spatial heterogeneity and correlations of provincial AWUE. The provinces with higher AWUE were mainly located in economically developed and coastal areas. (3) The correlation of AWUE between provinces showed significant network structure characteristics. Fujian, Hebei, Jiangsu, Shandong, and Hubei Qinghai were central to the network, with high centrality. (4) The AWUE spatial correlation network could be divided into four blocks. Each block played a different role in the cross-provincial transmission of spillover effects. Therefore, it is necessary to manage the agricultural water resources and improve water use efficiency from the perspective of the network.

Dynamic Linkages among Saudi Market Sectors Indices

This study aims to test the causal relationship between Saudi stock market index (TASI) and sectoral indices throughout the period from 2016–2020. The study data were extracted through the main index of the Saudi market and the indices of the available data of 19 sectors out of 21 sectors. The unit root test was used along with the Granger causality test, in addition to multiple regression tests in order to analyze the study hypotheses. The study shows that all index series were stationary at the zero level I (0), and the results also show that there were bidirectional and unidirectional causal relationships between TASI and sectoral indices, and that TASI effectively mirrors all the changes that occur in the Saudi stock market.

The Relationship Between Economic Growth and Banking Sector Development in Ukraine

The paper examines the relationship between economic growth and banking sector indicators in Ukraine. The constructed empirical model revealed a positive impact of bank deposits on real GDP growth. The causal relationships between economic growth in Ukraine and the performance of the banking sector are analyzed using the Granger Causality Test. It is established that banking deposits Granger-cause GDP, while banking credits do not, but GDP has an effect on banking credits. It is noted that the banking sector of Ukraine does not play a significant role in the redistribution of capital in the intersectoral and spatial dimensions. It is defined limiting factors of lending to the private sector and ways to increase the deposit base of banks.

Design of Portfolio using Multivariate Analysis

Stock markets are considered a barometer of the respective country’s economy around the world. Modern portfolio theory advocates diversification for risk management, which helps maintain returns as long as indices around the world are not perfectly correlated. The relationship exists across markets; as a result, co-movement has drawn the attention of individual investors and portfolio managers for the construction of their portfolios to maximize returns for a given level of risk. The study of co-movements provides inputs for portfolio construction and facilitates the identification of markets where indices may move in the same direction or the opposite direction and the country’s stock markets that are not correlated. A review of the literature revealed that statistical tools like Correlation, Factor analysis, and Granger causality test, etc., are some of the tools that can be used to understand co-movements of markets. Alan harper et al. (2012) study used principle component analysis and inferred that Indian stock returns are aligned with its trading partners and concluded that maximizing the investors’ returns by reducing the risk. Tak Kee Hui concluded that factor analysis provides inputs for selecting foreign markets for risk diversification. This study examines the potential for diversification using 22 world stock market indices using multivariate analysis.

A Symmetry and Asymmetry Investigation of the Nexus Between Environmental Sustainability, Renewable Energy, Energy Innovation, and Trade: Evidence From Environmental Kuznets Curve Hypothesis in Selected MENA Countries

The motivation of the study is to gauge the role of renewable energy consumption (REC), energy innovation (EI), and total trade (TR) on environmental sustainability (ES) in selected MENA (Middle East and North Africa) countries for the period 1980–2018 under the assumption of environmental Kuznets curve (EKC). The study implemented several econometrical tools, including structural break unit root test, Bayer–Hanck combined cointegration test, autoregressive distributed lag (ARDL), nonlinear ARDL, and Granger causality test under error correction term. Variables properties test detected that all the variables are stationary after the first difference but neither exposed to stationary after the second difference. The test statistics of the combined cointegration test documented a long-run association between ES, RE, EI, and TR, which is valid for both countries concerned. Regarding EKC concern, study findings with ARDL and nonlinear ARDL validated the EKC hypothesis for Tunisia and Morocco. Finally, the direction causality test documented unidirectional causality between renewable energy and ES, trade and ES, but the feedback hypothesis holds between EI and ES. We can advocate for specific sectoral environmental reforms in Tunisia and Morocco and suggest continuous environmentally friendly technologies by combining study findings. At the same time, subsidies on nonrenewable energy should be reduced, and green trade policies to help advance sustainable development should be implemented.