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South Africa, one of the emerging markets and fast-developing economies in Sub-Saharan Africa recognised for varying world's natural assets on the international market, has recorded significant economic growth in the previous several years. However, aside from the ecological repercussions of energy generation, how economic uncertainties moderate the effects of energy intensity, renewable and non-renewable energy usage, and economic complexity on the environment has largely gone unnoticed. As a result, this paper addresses an important empirical vacuum by exploring the moderating influence of economic policy uncertainty in the environmental Kuznets curve for South Africa from 1960 to 2020. Results from the novel dynamic autoregressive distributed lag simulations framework reveal the following key findings: (i) economic policy uncertainty accelerates environmental degradation in both the short and long run; (ii) economic growth (as measured by the scale effect) increases environmental degradation, whereas the square of economic growth (as measured by the technique effect) slows it down, confirming the presence of the environmental Kuznets curve (EKC) hypothesis; (iii) environmental quality is deteriorated by energy intensity, economic complexity, non-renewable energy usage, and trade openness; (iv) the use of renewable energy and technological innovation increase environmental quality; (v) whereas the moderating effects of economic policy uncertainty on the environmental impacts of energy intensity, renewable and non-renewable energy consumption result in an increase in environmental destruction, its moderating effect on environmental implication of economic complexity plays an important role in improving environmental quality. These findings permit us to draw important policy recommendations for South Africa for improving environmental quality. [ABSTRACT FROM AUTHOR]

The energy environmental Kuznets curve is effectively an environmental Kuznets curve augmented by adding one or more energy-related variables. We suggest that the energy Kuznets curve (EKC) can be estimated separately from the conventional environmental Kuznets curve as a quadratic function of income. It is demonstrated that the environmental Kuznets curve implies and is implied by the EKC. The empirical results show consistently that both the environmental and EKC are valid for developed (high income) countries but not so for developing (low income) countries where the relations are positive and monotonic. The importance of considering energy consumption in conjunction with the environmental Kuznets curve is that economic growth on its own does not put an end to environmental degradation unless the underlying country is on the downward-sloping sections of both the environmental and EKC. [ABSTRACT FROM AUTHOR]

The Federal Reserve has played an arguably important role in financial crises in the United States since its creation in 1913 through monetary policy tools. Thus, this paper aims to analyze the impact of monetary policy on the United States' economic growth in the short and long run, measured by Gross Domestic Product (GDP). The Vector Autoregressive (VAR) method explores the relationship among the variables, and the Granger causality test assesses the predictability of the variables. Moreover, the Impulse Response Function (IRF) examines the behavior of one variable after a change in another, utilizing the time-series dataset from the first quarter of 1959 to the second quarter of 2022. This work demonstrates that expansionary monetary policy does have a positive impact on economic growth in the short term though it does not last long. However, in the long term, inflation, measured by the Consumer Price Index (CPI), is affected by expansionary monetary policy. Therefore, if the Federal Reserve wants to cease the expansionary monetary policy in the short run, this should be done appropriately, with the fiscal surplus, to preserve its credibility and trust in the US dollar as a global store of value asset. Also, the paper's findings suggest that continuous expansion of the Money Supply will lead to a long-term inflationary problem. The purpose of this research is to bring the spotlight to the side effects of expansionary monetary policy on the US economy, but also allow other researchers to test this model in different economies with different dynamics. [ABSTRACT FROM AUTHOR]

Although energy supply is not the only factor of the production function, it remains an important driver for any economy despite its negative environmental impacts. This paper examines the determinants of carbon dioxide emissions in a sample of 35 African countries from 1980 to 2016. It uses several econometric methods to ensure robust and reliable findings. Results from Mean group (MG) and Dynamic common correlated effects mean group (DCCEMG) models prove that the environmental degradation in the selected sample is caused mostly by economic growth and non-renewable energy consumption. Moreover, the results confirm that the Environmental Kuznets Curve hypothesis is not significant when consider cross sectional dependence. These finding are contradictive to those obtained from similar studies that used traditional panel estimators. This means that energy consumption and economic growth will continue to increase emissions in the future. Furthermore, the study provides evidence of bidirectional causal relationships between carbon dioxide emissions and economic growth, non-renewable energy consumption and economic growth and between non-renewable energy consumption and carbon dioxide emissions. These findings imply that a hard work must to be done by the African policymakers and a long corrective measure series have to be adopted to ensure more efficient and clean energy. [ABSTRACT FROM AUTHOR]

This paper is aimed at examining the short- and long-run relationships among consumption of renewable and non-renewable energies, economic growth, and CO2 emissions in Mexico during the period 1973–2018. Data were obtained from the World Bank and the British Oil Company BP. A cointegration model together with a fully modified ordinary least squares (FMOLS) is used to estimate possible associations among all variables. Subsequently, the Granger causality test is applied to empirically verify the environmental Kuznets curve (EKC) hypothesis. The main empirical results are that the variables under study explain CO2 emissions in the short and long run, with economic growth having the greatest influence on CO2 emissions, which provides empirical evidence of an EKC for Mexico. Moreover, consumption of renewable and non-renewable energies and economic growth causes in the Granger sense the current levels of CO2 emissions. Moreover, lagged GDP and lagged non-renewable energy consumption do influence (Granger cause) current CO2 emissions. Long-term policies should encourage the use of renewable energies in the electricity, transport, manufacture, and construction sectors. [ABSTRACT FROM AUTHOR]

This study investigates the rice price dynamics and their impacts on demand and supply over the time in agricultural markets of Pakistan. Time series data on production and prices for the period 1984-2018 were used to study the cobweb phenomenon in local rice markets. Linear demand and supply models were used to examine the unstable rice-market. Price dynamics were examined through identifying the time path of difference equation derived from demand and supply functions. The results inferred that market prices of rice have remained unstable in agricultural markets of Pakistan over the history. Furthermore, rice prices exhibited damped oscillations towards stable market equilibrium over last three decades in Pakistan. It is suggested that the government may respond promptly to the instability of rice markets by formulating the appropriate agricultural policies, developing state-of-the-art storage facilities and ensuring the steady transmission of market information across the national as well as international rice markets. The study provides deep insights into understanding the on-going and future trends of price fluctuations with respect to demand and supply shocks in rice market of Pakistan. It would greatly help the stakeholders and policy makers in forecasting and stabilizing the rice markets, and alleviating the food insecurity. [ABSTRACT FROM AUTHOR]

The motivation behind the study is continuous fluctuations in energy prices in Pakistan, so this study aims to investigate the role of a twin deficit, urbanization, climate change, energy production from oil and gas, and the exchange rate in energy inflation. This study utilized oil prices and electricity prices to capture energy inflation using time series data from 1972 to 2021, from World Development Indicators (WDI) and the Census of Electricity Establishment (CEE). This study utilized the vector auto-regressive (VAR) model to investigate the short-run and long-run estimates. This study found that the twin deficit and the exchange rate have a significant and positive association with energy inflation. However, the size impact of the twin deficit is greater on oil prices as compared to electricity prices. Furthermore, urbanization, climate change, and energy production from oil and gas have a positive and significant long-run association with electricity prices. Moreover, the results of the variance decomposition test indicate that the relative contribution of the budget deficit in electricity prices (Model 1) is greater than other modeled variables, while the relative contribution of the budget deficit and climate change is greater in oil prices (Model 2), as compared to other exogenous variables. This study helps policymakers to devise policies to control energy inflation, which affects the well-being of society. [ABSTRACT FROM AUTHOR]

In order to analyze the relationship between energy consumption and economic growth dynamics, the author proposes a dynamic analysis technology of energy consumption and economic growth based on the PVAR model. This technology uses the PVAR method to compare and quantitatively describe the relationship between economic growth and energy consumption in developed and developing countries from 1990 to 2009, using impulse response functions and variance decomposition analysis methods; study the similarities and differences between total energy consumption and various fossil energy consumption and the dynamic impact of economic development, and finally establish a PVAR model for analysis. Experimental results show that: in the forecast of variance analysis, the impact explanatory power of the total energy consumption of developing countries on the fluctuation of economic growth reaches 8.85070. However, the contribution of total energy consumption in developed countries to economic growth is insufficient. The explanatory power of economic growth in developed countries to total energy consumption is 15.58070, while that in developing country is 29.28070, both of which are greater than the explanatory power of their respective total energy consumption on economic growth. Conclusion. The technology based on the PVAR model can effectively meet the needs of analyzing the dynamic relationship between energy consumption and economic growth. [ABSTRACT FROM AUTHOR]

This study was conducted in an effort to better understand how decisions made by the government in Pakistan regarding taxation and spending have affected crime rates over the years 1980 to 2020. The Vector Error-Correction model suggests that the government's policies have a causal effect on crime rates in the long run. The study concludes that rising direct taxes and defence expenditures decreases the reported crime rate in Pakistan. Moreover, the empirics revealed that rising unemployment rate increase crimes. The income inequality has also portrayed positive relationship with reported crimes. The impulse responses affirm the persistent long run relationship trends in which both unemployment rate and income inequality increases crime rate and the direct taxes and defence expenditures decreases crime rate in the country. [ABSTRACT FROM AUTHOR]

We investigate the dynamic effect of external conflict risk on environmental transition by considering the impacts of eco-innovation, economic growth, and energy consumption in a panel comprising 26 European countries from 2011 to 2020. Using a non-parametric model represented by the panel QARDL, we find that in the short run, a 1% increase in external conflict risk statistically leads to a 0.25% and 0.13% increase in the likelihood of environmental transition for the median and extreme upper quantiles (50th and 95th percentiles), respectively. However, the same increase holds little importance when considering the lower quantile (5th percentile). The indicated effect substantially decreases in the long run, reaching zero across the different quantiles. We also note discrepancies in the impact of energy across various quantile levels. For instance, the effect of population is significant from the 5th to the 90th quintiles. Overall, our findings suggest that enhancing eco-innovation helps reduce environmental transition risk. The results are relevant to the development of environmental policies and provide valuable insights for energy officials, technology stakeholders, and policymakers in their attempts to strengthen resilience during an environmental transition. [ABSTRACT FROM AUTHOR]

In May 2019, the Climate Change Committee (CCC) recommended that the UK adopt a net-zero target, aiming to reduce its greenhouse gas emissions (GHG) by 100% from the 1990s baseline by 2050. The government accepted the recommendation, and the UK became the first major economy to establish a net-zero emissions law. To progress towards its climate objectives, the government took several initiatives, such as increasing its reliance on renewable energy sources and investing in climate mitigation technologies, which are commonly referred to as process eco-innovation. This study examines the impact of eco-innovation, process eco-innovation, renewable energy consumption, and economic growth on CO 2 emissions in the UK using data from 1988 to 2020. We used the ARDL bound test with an error correction model (ECM) to examine the long-run and short-run cointegration between the variables of concern. We found that eco-innovation, process eco-innovation, and renewable energy consumption have significant roles in mitigating CO 2 emissions, while economic growth contributes to environmental degradation in the UK. We also found that the effect of eco-innovation on CO 2 emissions abatement is stronger than that of process eco-innovation in the short and long-run. Our robustness tests have confirmed the accuracy of those findings. In addition, the results from the Toda-Yamamoto causality revealed a one-way causality from process eco-innovation to CO 2 , renewable energy to CO 2 , and eco-innovation to CO 2 emissions. Further, a bidirectional causality was found between GDP and CO 2 emissions. The evidence presented in this paper provides great insight for shaping the energy policy in the UK and for establishing the climate budget in line with the country's net-zero target. • Process eco-innovation, eco-innovation and renewable energy consumption contribute to CO 2 emissions reduction in the UK. • Eco-innovation has a stronger CO 2 mitigation effect compared to process eco-innovation. • The Environmental Kuznets Curve is not valid for the UK. • There is a one-way causality from process eco-innovation to CO 2 , eco-innovation to CO 2 and renewable energy to CO 2. • There is a bidirectional causality between GDP and CO 2. [ABSTRACT FROM AUTHOR]

The impact of political risk and financial development has been widely studied in the context of sustainable environmental practices. However, their effects on green finance and sustainable finance initiatives have not been thoroughly explored. This paper fills this gap by examining the influence of the political risk financial development index on green finance across 21 OECD economies from 1990 to 2020. Unit root and cointegration tests reveal that variables are stationary at first difference, and there is a long-run cointegration among them. For the primary analysis, we employed the novel MMQR approach, which demonstrates that the financial development index enhances green finance, while the political risk index diminishes it across all quantiles – upper, median, and lower. Robustness analysis using BSQR further confirms these findings. Policies aimed at fostering financial development and reducing political risk should acknowledge the growing significance of green finance in OECD economies. • We analyzed how political risk and financial development index impact green finance. • The data of 21 OECD economies have been sourced during 1990–2020. • Using the MMQR approach, we found that financial development boosts green finance, while political risk hinders it. • Policies on financial development and reduced political risk should acknowledge the growing importance of green finance. [ABSTRACT FROM AUTHOR]

Despite significant progress in the development of advanced technologies for detecting and monitoring unstable slopes, accurately predicting catastrophic landslides remains a challenge. To tackle this challenge, our research integrates advanced prediction models and granular systems theory to provide insights into regime shifts within slow-moving deep-seated landslide dynamics. Our approach is designed to discern exceptional departures from historical landslide dynamics. The approach leverages the “group dynamics,” crucial for identifying precursory failure indicators, according to the generic dynamics of the precursory failure regime in granular systems. We select three different monitored slow-moving landslides as test cases. We employ an error correction cointegration vector autoregression model together with an exogenous regressor to encode historical spatiotemporal landslide dynamics and predict displacement at multiple locations by considering the historical landslide motion and relationship with external triggers. Displacement residuals are obtained by computing the difference between predicted and measured displacement for a given historical calibration time window. Threshold values for the displacement residuals are determined by analyzing the historical distribution of these residuals. Lastly, persistence in time of the threshold exceedance and the number of monitoring points that exceed the threshold at the same time are considered to encode the group dynamics. This approach offers several advantages, including the effective identification of critical regime shifts, adaptability, and transferability, and it introduces regime shift information into local landslide early warning systems. This approach can enhance confidence in the resultant alert, particularly when integrated with conventional alert systems, thereby improving the reliability of landslide warning systems. [ABSTRACT FROM AUTHOR]

Space activities are known for releasing different kinds of pollutants into the atmosphere. This study employs cointegration and error-correction techniques to explore the environmental impacts of U.S. space activity over both short and long terms. The findings reveal a long-run relationship between space activity and the environment. In the short run, except for biocapacity, space activity shows no significant impact on the environment according to the error-correction model analysis. In the long run, noteworthy relationships emerge, such as the launch of objects correlating with an increased ecological footprint and a decline in ozone concentration, and both objects and space debris contributing to reduced ozone concentration. Specifically, the estimates indicate that a one-percent increase in launches increases footprint by 0.07%, whereas a one-percent increase in object launches and space debris reduces the ozone concentration by 2.231% and 0.499%, respectively. The impulse response functions analysis affirms a predominantly permanent negative impact of space activity on the environment, jeopardizing environmental sustainability. Additionally, two crucial breakeven points are identified: space debris initially increases (i.e. deteriorates) the ecological footprint for the first 9 years before permanently improving footprint, while it initially enhances the ozone concentration for about 6 years before causing a lasting detrimental effect on the ozone layer. [Display omitted] • We investigate the impact of US space launches and debris on the environment. • Objects and space debris are each linked to the environment in the long-run. • Primarily, space objects and debris present a sustainability risk to the environment. • Space debris increases the ecological footprint for the first 9 years. • Space debris enhances the ozone concentration for about 6 years. [ABSTRACT FROM AUTHOR]

The most essential component of human capital is health capital; however, expenditures on health are gaining attention from practitioners, policymakers, and researchers. Accordingly, this study determined the dynamic association between health expenditures (HEP), economic growth (ECGW), carbon emissions (COEM), information and communication technology (ICT), institutional quality (IQ), and energy consumption (EC) in the context of Saudi Arabia. The autoregressive distributed lag and vector error correction model was employed to identify the dynamic linkages among under-considered variables by using data of 1995–2019. The empirical analysis indicated that COEM, ECGW, and EC have a positive influence on HEP, while ICT and IQ have a negative effect on HEP. There is bidirectional causality is identified between COEM, ICT, IQ, and EC, while one-way long-run causality is recognized from HEP and ECGW to these variables. Moreover, two-way short-run causality is identified between ICT and EC, whereas one-way causality is recognized from HEP and COEM to ICT. This study empirically established the essential role of IQ and ICT to enhance air quality and decrease the HEP. Consequently, policymakers should strengthen the institution and implement advanced ICTs to provide a healthy economy. [ABSTRACT FROM AUTHOR]

This study explores the relationship between economic growth and carbon dioxide and the moderating effect of institutional quality in Nigeria from 1990 to 2020, by employing long-run and short-run dynamic ARDL regression, quartile regression and Granger causality test for the estimation. Utilizing CO2 per capita emissions; GDP per capita, a proxy for economic growth; capital stock (CAPSTK), proxy for capital investment in Nigeria and control of corruption and regulatory quality (COC and RGQ) which represent the effective environmental regulations and laws put in place for the control and prevention of environmental degradation, the study found a significant cointegration between CO2 emissions and economic growth (lnGDP) in Nigeria. Furthermore, an N-shaped nexus exists between CO2 emissions and economic growth in the long-run and short-run instead of the inverted U-shape curve postulated by the EKC hypothesis. This was confirmed by both ARDL and quartile regression results. Similarly, InCAPSTK contributed significantly to the growth of CO2 emissions in Nigeria both in the long run and short run; although, the short run did so at 10% significant level. Contrary to expectations, control of corruption (COC) contributes significantly to CO2 emissions in the long run, but when it interacts with income (InGDP × COC), it significantly contributes to the reduction of CO2 emissions. More so, regulatory quality (RGQ) had no significant impact on CO2 emissions in Nigeria either in the long run or short run, even when it interacts with InGDP. This finding is further supported by the quartile regression outcomes and Granger causality. The study therefore concludes that CO2 emissions–economic growth nexus in Nigeria assumes an N-shape both in the long run and short run. Based on the results, the study recommends that Government should pursue industrialisation policy with sophisticated method of production that will bring about rapid economic progress and at the same time support environmental sustainability. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to reveal the mechanism and process of the dynamic evolution of the economy-energy-environment (EEE) system and study the variables that determine the speed of system evolution and development. The innovation is to overcome the defect of single index by constructing a system evaluation index and reveal the regional EEE system's evolution mechanism based on Haken's synergetic theory to supplement a systematic perspective's empirical evidence. It selects 30 provinces, municipalities, and autonomous regions in China to empirically analyse the evolution mechanism of the EEE system from 2005 to 2019. The empirical results show that economic development is the order parameter of the evolution and development of the EEE system. In the process of system evolution, the economic development subsystem is the decisive factor in EEE system evolution. In terms of the positive feedback mechanism of order parameter combination, the EEE system forms a positive feedback mechanism for increasing economic development in the stage of evolution and development. The negative feedback mechanism of decreasing environmental pollution emissions is formed in the EEE system. The increase in pollutant emissions has a certain inhibitory effect on economic growth. The improvement in the economic development level has no promoting effect on pollutants, and economic development, in turn, reduces environmental pollution. [ABSTRACT FROM AUTHOR]

The topic of climate change is so crucial that experts, world leaders, and international organizations are constantly working on how to solve this problem. One of the recommendations lies in using renewable energy to protect the global ecosystem and promote environmental sustainability. This study, therefore, examines the impact of renewable energy consumption (RNEW) on economic growth (RGDP) in Nigeria within the period of 1990Q1–2019Q4 using a non-linear autoregressive distributed lag (NARDL) model. This research contributes to existing literature by focusing on a single-country analysis using the NARDL methodology. Nigeria has the highest GDP in Africa and can drive continental growth. In addition, the NARDL approach examines the positive and negative shocks of the independent variables on the dependent variable. The bound test result confirms cointegration among the variables. Further results show that a positive shock of RNEW decreases RGDP, while a negative shock increases RGDP in the long run. This result differs from existing literature in which a majority of the studies found a positive relationship between RNEW and RGDP. In the short run, a positive shock of RNEW increases RGDP, while a negative shock decreases RGDP, although not significant. A positive shock in RNEW hurts RGDP because of the nature and source of renewable energy used in Nigeria, majorly wood biomass. Therefore, this study recommends that cleaner technologies be utilized to maximize the advantages of renewable energy sources, especially wood biomass, while minimizing their adverse effects. [ABSTRACT FROM AUTHOR]

Continuing economic progress with less environmental damage and achieving a sustainable environment require switching from fossil fuels to green energy. However, alleviating environmental damage of growth has become a major challenge for BRICS where economic progress amidst rising urbanization pollutes the environment. In this context, the fight against climate change and actions towards environmental sustainability are greatly affected by rising economic policy uncertainty. Hence, this study assesses the role of green energy, urbanization, and economic growth in CO2 emissions in the presence of economic policy uncertainty in BRICS (excluding South Africa) from 1997 to 2020. The study used the cross-sectionally augmented auto-regressive distributive lag technique for revealing the short- and long-run effects of the analyzed variables on environmental quality. The empirical evidence suggested that the environmental Kuznets curve exists according to the recent framework of Narayan and Narayan Energy Policy 38:661–666, (2010) because even though economic growth increases CO2 emissions, its long-run effect is less than the short-run effect. Economic policy uncertainty boosts CO2 not only in the short-run but also in the long-run, evidencing that a sustainable environment requires decreasing the levels of policy uncertainty. For BRICS, switching towards green energy is a vital option to decrease environmental deterioration owing to the negative connection between green energy and CO2. The findings indicated that rapid urbanization is among the causes of high CO2. Furthermore, economic policy uncertainty influences both green energy and economic growth levels. Finally, policies are recommended to mitigate environmental deterioration. [ABSTRACT FROM AUTHOR]

The energy-growth nexus has been explored extensively by researchers and academia; however, the role of cleaner energy, especially in the context of emerging economies, i.e., Nex-11 countries, have been ignored. Therefore, to fill the gap in the literature, this paper considers a non-parametric panel method, to test directly for the importance of renewable energy in economic performance for Next eleven (N-11) countries. The econometric estimations—which focused on a panel of N-11 countries—determined that: (i) renewable energy consumption boosts economic growth in short run only; and (ii) industry value added, human development, and consumption expenditures accelerate economic, whereas globalization decrease it. Hence, all countries need to reduce the risk associated with renewable energy so that to make them effective for economic growth. Moreover, there is a need to provide different types of invested capital for ongoing activities of renewable energy production. In general, this study provides relevant policy implications in the context of renewable energy, globalisation and economic growth for the Nex-11 economies. • Renewable Energy led Economic Growth Hypothesis is tested in the Next-11 countries. • The novel Method of Moments Panel Quantile Regression is employed. • Renewable energy led economic growth is valid in the selected panel economies. • Consumption expenditures, Human Development, Industry Value Added enhances growth. • Globalisation is found to limit economic growth in case of Next-11 countries. [ABSTRACT FROM AUTHOR]

The global financial markets are greatly affected by crude oil price movements, indicating the necessity of forecasting their fluctuation and volatility. Crude oil prices, however, are a complex and fundamental macroeconomic variable to estimate due to their nonlinearity, nonstationary, and volatility. The state-of-the-art research in this field demonstrates that conventional methods are incapable of addressing the nonlinear trend of price changes. Additionally, many parameters are involved in this problem, which adds to the complexity of such a prediction. To overcome these obstacles, a Mutual Information-Based Network Autoregressive (MINAR) model is developed to forecast the West Texas Intermediate (WTI) close crude oil price. To this end, open, high, low, and close (OHLC) prices of crude oil are collected from 1 January 2020 to 20 July 2022. Afterwards, the Mutual Information-based distance is utilized to establish the network of OHLC prices. The MINAR model provides a basis to consider the joint effects of the OHLC network interactions, the autoregressive impact, and the independent noise and establishes an intelligent tool to estimate the future fluctuations in a complex, multivariate, and noisy environment. To measure the accuracy and performance of the model, three validation measures, namely, RMSE, MAPE, and UMBRAE, are applied. The results demonstrate that the proposed MINAR model outperforms the benchmark ARIMA model. [ABSTRACT FROM AUTHOR]

The current work estimated the relative importance of joke and audience characteristics for the occurrence of amusement. Much psychological research has focused on stimulus characteristics when searching for sources of funniness. Some researchers have instead highlighted the importance of perceiver characteristics, such as dispositional cheerfulness. Across five preregistered studies (N s = 118–54,905) with varied stimuli and perceiver samples (website visitors, students, Mechanical Turk and Prolific users), variance-decomposition analyses found that perceiver characteristics account for more variance in funniness ratings than stimulus characteristics. Thus, psychological theories focusing on between-persons differences have a relatively high potential for explaining and predicting humor appreciation (here, funniness ratings). Crucially, perceiver-by-stimulus interactions explained the largest amount of variance, highlighting the importance of fit between joke and audience characteristics when predicting amusement. Implications for humor-appreciation theories and applications are discussed. [ABSTRACT FROM AUTHOR]

The COVID‐19 pandemic has had a significantly negative impact on all transportation modules, especially air passengers. The authors aimed to forecast the air passenger load factor using time series modelling for the affecting variables. After providing general information about this pandemic, the forecasting results regarding getting back into the recovery period were presented by time series modelling. The last five years (2016–2020) and the first eight months of 2021 were examined with the following variables: available seat kilometre, revenue passenger kilometre, passenger load factor, gross domestic product, and domestic and international passenger numbers. The forecast results reveal that the recovery period started in June of 2021 and continues with a robust growth trend until September 2021 due to the vaccination process and the starting of the summer season. This trend changed between September to November 2021 slightly negative, from November 2021 to January 2022 slightly positive, and from January 2022 to March 2022 mildly negative. Correspondingly, passenger load factor (PLF) is affected by itself and domestic transportation in the short‐term period. This effect seems short‐term in domestic and international transport. This research reveals that minimising the economic damage by benefiting from the increasing trend of air passenger numbers increases the recovery period. [ABSTRACT FROM AUTHOR]

Transport demand and supply are deemed to determine each other in a cyclic manner. The major idea has been that the demand is usually the preceding one. However, in urban cases, usually the land use variables in place of supply interfere this process. Cleansing the land use variables, the regional/national level variable pairs of demand and supply are employed to analyze the cause-effect mechanism. For objectivity, the Granger-causality test (GCT) is used to understand the relationship between transportation demand and supply. The Analyses were made at four dimensions; (a)whether the nexus is one-directional or bidirectional, (b)its significance level, (c)whether demand or supply is the preceding, (d)whether the effects are short-term or long-term. Using the Turkish statistics, the GCT results showed that, in the short/medium run, overwhelmingly the supply variables preceded (mostly in railway mode), mostly unidirectional (one-way causality) manner, however, in the long-run almost no relationship was found. In other transportation modes, no significant relationship is observed. Finally, bi-directional relations were usually observed in suburban rail. The investments then should be made according to known demand. Usually, the effects of supply (especially of railways and roadways) could rather fade away in the long-run. Still, no general statement can be made for the demand/supply causality especially in terms of which one is preceding and of the direction of causality. The chaotic nature of the process reigns over with the changing conditions. [ABSTRACT FROM AUTHOR]

This study examines the causal relationship between road transportation and economic growth in 31 provinces and municipalities in China by using province-level panel data covering the period from 1980 to 2015. This study adopts the Granger causality analysis based on meta-analysis in heterogeneous mixed panels. The empirical model also considers the heterogeneity of the coefficients and the cross-sectional correlations of the panel data. The empirical results confirm that the bi-directional causal relation between road transportation and economic development is the dominant type in various provinces and municipalities in China. Moreover, the results reveal a unidirectional causality running from road transportation to economic growth in Beijing, Shanghai, Heilongjiang; a unidirectional causality running from economic growth to road transportation in Tianjin, Fujian and Hunan; and no causal relation in Tibet. The results imply that road transportation and economic growth in most parts of China are mutually coordinated. [ABSTRACT FROM AUTHOR]

Carbon emissions and economic growth are two contradictions in urban development, and their decoupling is related to the sustainable development of cities. This paper took urban agglomeration in the middle reaches of the Yangtze River (UAMRYR), China, as the study area. The Kaya model, the Tapio decoupling model, and the Logarithmic Mean Divisia Index (LMDI) model were adopted to analyze the spatiotemporal differentiation of carbon emissions, the decoupling of economic activities, and driving factors. The results indicate that (1) carbon emissions increased by 66% in the study period, but the growth momentum was curbed after 2015. Low level and medium level areas continue to decrease, and relatively high level area gradually become dominant. (2) Spatially, carbon emissions are in a pattern of middle-hot and east-cold. Jiangxi is in the sub-cold and coldspot area, while the hotspot area is driven by the transformation from Wuhan's single-core to Wuhan and Changsha's dual-core. (3) Since 2010, most cities have been in a good decoupling state, and weak decoupling cities have risen from 35.5% in the initial period to 87.1% in 2010–2011, but the decoupling situation of industrial cities with more high-energy-consuming industries still rebounded slightly. (4) The economic level and energy intensity effect had the most significant impact on the economic decoupling of carbon emissions, whose absolute contribution rates were greater than 35%. Urbanization and economic level both play a positive role in promoting carbon emissions, and the energy intensity plays a negative role in retarding carbon emissions. The population effect was mainly manifested in carbon increase from 2006 to 2011, and 45.2% of the cities from 2011 to 2017 turned into carbon suppression. Finally, we suggest that decoupling carbon emissions from economic growth requires developing green urbanization and a decarbonized economy, optimizing the structure of energy consumption and guiding rational population flow. [ABSTRACT FROM AUTHOR]

Purpose: The paper aims to examine the effects of floods on economic growth in India from 1980 to 2019, taking into account the role of foreign direct investment (FDI) inflows and foreign aid. Design/methodology/approach: The study uses augmented Dickey–Fuller (ADF) and Phillip–Perron (PP) tests to determine the stationarity of the variables. Several models, including autoregressive distributed lag (ARDL), fully modified ordinary least square (FMOLS), dynamic ordinary least square (DOLS) and canonical cointegration regression (CCR), are used to examine the impact of floods on economic growth. Findings: The bounds test determines the long-term relationship between floods, FDI inflows, economic growth and foreign aid. According to the ARDL and FMOLS models, floods have a negative long-term and short-term impact on India's economic growth. Furthermore, FDI inflows and foreign aid are beneficial to economic growth. The findings of the ARDL and FMOLS models are confirmed by the DOLS and CCR models. Granger causality establishes a unidirectional causality that extends from floods to economic growth. Further diagnostic tests show that the estimates are free of heteroskedasticity, serial correlation and parameter instability. Practical implications: Indian government needs to invest more in research and development on flood management techniques. Institutional strengthening is also required to implement pre- and post-flood prevention measures properly. Sound disaster financing strategy and proper water bodies management should be prioritised. Foreign investment opportunities should be encouraged by strengthening international relations. Originality/value: This is the first time-series study that analysed the effects of floods on economic growth in India. Moreover, the paper contributes to floods literature by applying several econometric models for robustness check. [ABSTRACT FROM AUTHOR]

This research investigates the relationships among renewable energy consumption, economic growth, and financial development in five sub-Saharan African nations utilizing panel data from 2000 to 2020. Econometric methods are used to ascertain the existence or absence of cross-sectional dependence and the short-run and long-run connections between the following factors: Pesaran cross-sectional dependence (CD) and cross-sectionally augmented IPS (CIPS) unit root tests, pooled mean group (PMG), and dynamic ordinary least squares (DOLS) estimations. The presence of cross-sectional dependence is found and represented with the CIPS unit root test. No significant short-run relationship is found between the variables of the study, yet a significant long-run relationship is present among them. A positive relationship exists between CO2 emissions and financial development, while financial development and renewable energy consumption are found to have negative relationships with CO2 emissions. The study also supports the scale effect of the environmental Kuznets curve hypothesis. Additionally, no causality is found among the variables, and impulse response and variance decomposition estimation are carried out to recommend future effects. Policy implications of findings are discussed, with accompanying suggestions. [ABSTRACT FROM AUTHOR]

We model a mixture of asymmetric and nonlinear bidirectional and unidirectional causality between four macroeconomic variables (exchange rate, GDP, global economic policy uncertainty, and relative CPI) and stock returns of BRICS economies in the frequency-domain using the information flow theory. The Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN)-based Rényi effective transfer entropy approach is used to establish dynamic flow of information between macroeconomic variables and stock returns of BRICS. The original return series suggested insignificant information flow between most macroeconomic variables and stock returns. However, we reveal both asymmetric and tail dependent analyses at diverse scales between macroeconomic variables and stock returns of BRICS economies. Moreover, we find negative significant flow of information between the variables, in that knowing the history of one variable (either stock or macroeconomic variable), in this case, indicates considerably more uncertainty than knowing the history of only the other variable (either stock or macroeconomic variable). We also observe that global economic policy uncertainty has the most significant adverse causal relationship with stock returns of BRICS, especially in the long term. These results have important implications that investors and policymakers should take into account. Regulators should consider instituting sound policy actions geared towards minimising long-term effects of external shocks and uncertainties. [ABSTRACT FROM AUTHOR]

This article seeks to examine the impacts of renewable and non-renewable energy on carbon dioxide emissions for 14 Middle East and North Africa economies using fully modified least-squares and vector error correction model techniques. Different sectoral outputs (agricultural, industry, and services) are considered in the analysis to find the influence of each sector on carbon emissions and to validate the environmental Kuznets curve model at both aggregate and disaggregate levels. The fully modified least-squares estimates show that renewable energy enhances environmental quality, whereas non-renewable energy deteriorates it. We also find that the industry sector has the highest contribution to environmental degradation. The results of the vector error correction model technique show a two-way linkage between CO2 emissions and renewable energy and between CO2 emissions and non-renewable energy in both short and long runs. At the sectoral level, we also find a two-way linkage between agricultural value added and CO2 emissions, a unidirectional relationship running from emissions to industry value added, and a unidirectional linkage running from services value added to CO2 emissions in both short and long runs. Therefore, governments must focus their actions on environmental policies of a green and inclusive economy that combine tools of environmental economics with those of the ecological economy. This can be considered a call for policymakers to take relevant and quick policies and actions towards low-carbon energy to reach these dual objectives. [ABSTRACT FROM AUTHOR]

With the EU Green Deal initiatives, European members seek to launch the first climate neutral continent by 2050. This paper assesses the stochastic convergence of per capita energy consumption series for an illustrative sample of 15 EU countries with memberships prior to the 2004 enlargement, using data spanning the 1970–2018 period. Results from the confidence interval subsampling (asymmetric and equal-tailed) highlight that 11 out of the 15 EU series exhibit a long-run memory behaviour, while a diverging pattern was observed for the UK, Germany, Portugal, and Italy. Finally, per capita energy use series persist but fail to reveal one of the above dynamics for Ireland and Spain. Also, findings from the non-parametric Bayesian application (ANOVA/linear Dependent Dirichlet Process (DDP) mixture model) show how economic growth operates as a converging energy consumption-enabler over the long-run, from which the EU membership cannot be excluded. In particular, we highlight how the nature of energy-GDP hypotheses vary with the stochastic properties of energy use (converging behaviour with temporary shocks, converging pattern with permanent shocks, and diverging dynamic). Finally, our conclusions overcome the well-established development stage argument as we claim that countries with similar energy convergence patterns may need to adopt similar energy policies. [ABSTRACT FROM AUTHOR]

This research analyzed the relationship between openness to agricultural exchange, foreign direct investment, capital, consumer price index, and GDP in Pakistan utilizing time series data for the 1971-2019 period. We used autoregressive distributed lag ARDL-bound testing method to analyze the long-run and short-run correlation between projected variables. The study's findings also confirmed a positive and important long-term correlation between openness to agricultural trade, foreign direct investment and Pakistan's economic development. There is no long-run relationship between consumer price and economic growth. [ABSTRACT FROM AUTHOR]

The studies exploring inter-relations between non-renewable energy consumption, renewable energy consumption, GDP, and CO2 emission are quite limited in Vietnam due to the limitation of data. Different major players in this market, such as investors, regulators, and other financial actors have different time horizons. By applying innovative multivariate wavelet analysis tools, including partial wavelet coherency and partial wavelet gain, this paper investigates these relations in the time and frequency dimensions in Vietnam during the 1985–2019 period. The multiple coherencies between the non-renewable energy consumption and GDP and CO2 growth suggest that these regions were located at medium frequencies (5–12 years) and concentrated on the 1985–2000 period and the 2003–2019 period. Regarding the relation between renewable consumption and GDP and CO2 growth that the region only concentrated in the high-frequency band (from 2 to 12-year frequency-band) running from 1985 to 2001 and low-frequency band (from 22 to 25-year frequency-band) running from 2011 to 2019. The partial coherency between non-renewable energy consumption and GDP reveals two phases. In the first phase (the beginning of sample to 2000), changes in the non-renewable energy consumption led to changes in GDP, and the relation is negative, while GDP is in-phase with non-renewable energy consumption leading in the second phase (from 2000 to 2015). The partial phase-difference between non-renewable energy consumption and CO2 emission suggests that changes in CO2 emission led to changes in non-renewable energy consumption, and the relation was negative. Regarding the partial coherency between renewable consumption and GDP, most regions were located in the 2–12-year frequency band running from 1985 to 2001, from 2001 to 2003, and from 2005 to 2012. During the 1985–2991 period, the results indicate the anti-phase relation with the GDP growth leading, while changes in renewable energy consumption led to changes in GDP growth, and the association is negative from 2001 to 2003. Since 2003, there was an anti-phase relation with the GDP growth leading. Lastly, the partial wavelet coherency of renewable energy consumption and CO2 emission indicates that regions were found to be statistically significant in the 3-4- and 7-15-year frequency band and there was the anti-phase relation with the CO2 emission leading. [ABSTRACT FROM AUTHOR]

Background: Worldwide environmental pollution has called for overwhelming concern of researchers and stakeholders in the last twenty years because of the menace it unlashes on man's life. The aim of this research work is to ascertain the causation among economic advancement, Carbon emission, energy consumption and taxation. The study focused on the Nigerian economic and the period under review is thirty-three (33) years. Methods: Test was performed to explain the accurate transmission among the dependent and the independent variables. This study employed Granger estimation to ascertain the direction of the connection amongst the variables. Result: Results revealed that tax has unidirectional connection with economic advancement. The result also showed that Carbon emission has unidirectional relationship with economic growth. The result further revealed that energy consumption has a unidirectional association with taxation. This study suggests that economic growth does not affect energy consumption, taxation and carbon emission. This study recommended that for future study, intending researchers should use fuel consumption to proxy energy consumption. The study also recommended that the Nigerian government should increase tax paid by oil companies in order to curtail their excesses and generate more revenue. [ABSTRACT FROM AUTHOR]

In this study, causalities of COVID-19 across a group of seventy countries are analyzed with effective transfer entropy. To reveal the causalities, a weighted directed network is constructed. In this network, the weights of the links reveal the strength of the causality which is obtained by calculating effective transfer entropies. Transfer entropy has some advantages over other causality evaluation methods. Firstly, transfer entropy can quantify the strength of the causality and secondly it can detect nonlinear causal relationships. After the construction of the causality network, it is analyzed with well-known network analysis methods such as eigenvector centrality, PageRank, and community detection. Eigenvector centrality and PageRank metrics reveal the importance and the centrality of each node country in the network. In community detection, node countries in the network are divided into groups such that countries in each group are much more densely connected. [ABSTRACT FROM AUTHOR]

This paper explores the impact of tariffs, imports substitution and investment efficiency on economic growth in Pakistan. For this purpose, secondary data was collected from world development indicators from 1981 to 2017. The study found that all variables have integrated at different orders by employing the augmented dickey-fuller test. Econometrically, the study employed Johansen and Juselius (1990) Cointegration Test, vector error correction model and autoregressive distribution lag model to build up the relationship among the variables. The results found that the tariff rate had a positive effect on economic growth. The coefficients of all variables' like consumer price index, private investment, public investment and exchange rate are positively related to economic growth. While tariffs rate was negatively related to public investment. Moreover, Foreign assistance, consumer price index and Government revenue was positively related to public investment. Employment in Agriculture sector was positively related to economic growth, while Employment in the industrial sector is negatively related to economic growth. There is a positive relationship between employment in the service sector and economic growth. The foreign exchange reserves had a positive effect on economic growth, while Tariffs on all manufactured products had a positive effect on economic growth, while the Tariff on all products are negatively related to economic growth. Finally, the relationship between subsidies and economic growth is directly related. The results of the short-run and long-run relationship amongst the measurable indicators of import substitution had a positive and negative effect on economic growth in Pakistan. This study suggested that the government should re-consider a tariff and import substitution policy to promote economic growth. Due to imposition of high tariff rate and import substitution it will create an opportunity to domestic producer to produce import substitution goods in domestically. It will lead to increase in economic growth. [ABSTRACT FROM AUTHOR]

Recently, policymakers have been developing some policies to improve environmental quality. Environmental taxes are the most important of these policies. This study examines the effects of transport taxes, economic growth, and fossil fuel energy consumption on air pollution within the Environmental Kuznets Curve (EKC) hypothesis framework. The study used data from 1994 to 2019 for the ten countries with the highest transport tax revenues. According to the results, while the EKC hypothesis is valid for Portugal and Switzerland, it is not valid for all other countries. Moreover, fossil fuel energy consumption seems to increase air pollution in all countries except the Netherlands and Switzerland. However, transport taxes increase air pollution in Brazil. Therefore, transport taxes are not effective in reducing air pollution. In this context, it was concluded that the structure of transport taxes should be improved or reformed. In addition, it has been underlined that those national decisions alone will not be sufficient to improve transport taxes or environmental taxes. Therefore, regulations to be made with international coordination will be more successful in combating environmental problems by preventing tax competition and increasing tax harmonization. [ABSTRACT FROM AUTHOR]

The study aims to compare CO2 emissions, renewable energy, trade openness, gross domestic product (GDP), financial development (FD), and remittance in selected G-20 countries. The study carried out fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) models for estimation covering annual data from the year 1990–2019. LM tests detected the cross-section dependency while stationarity of the variables was checked through Levin-Lin-Chu and Im-Pesaran-Shin tests along with Hansen's Covariate-Augmented Dickey Fuller (CADF) test in the presence of cross-section dependency. The panel unit root tests reported that all variables became stationary after converting them into the first difference. The Panel Cointegration and Wester-Lund test examined the existence of long-run equilibrium nexus among selected variables in the context of G-20 countries. The study's findings show that there is a significant and negative relationship between renewable energy and CO2 emissions. It was proven in two models that the economic growth of selected G-20 countries has a positive relationship with CO2 emissions. Furthermore, findings indicate that the coefficient of financial development is positive and significantly impacts CO2 emissions. The remittances have a significant positive effect on CO2 emissions, while trade openness has an insignificant impact on CO2 emissions in both models. This research will enlighten policymakers, researchers, governments, and environmentalists toward attaining a sustainable environment by wisely consuming remittances and renewable energy resources. [ABSTRACT FROM AUTHOR]

This paper investigates the short-term dynamics as well as the long-term relationship between natural gas consumption and economic growth in Nigeria, taking breaks into account. The techniques employed include Shahbaz-Omay-Roubaud unit root test with sharp and smooth breaks and autoregressive distributed lag (ARDL) model with breaks. The results revealed that natural gas consumption is positively related to growth both in the short-term and long-term but only significant in the latter. However, there is evidence of bidirectional causality in the long-term and unidirectional causality in the short-term, from growth to natural gas consumption. The implication of the findings is that natural gas is a contributing factor to the growth of the Nigerian economy, and any energy policy aimed at increasing the consumption of natural gas could lead to the increase in economic growth and that Nigerian authorities could adopt energy conservation policies in the short-term so as to take the issue of global warming into consideration. Therefore, the paper recommends stepping up efforts to increase natural gas consumption by building more gas storage facilities, pipeline installations, exploring alternative energy sources, raising awareness/enlightenment about the uses of natural gas, suitability in its use, economic and environmental benefits of its use, ensuring its affordable availability, and beeping up security against pipelines vandalization. Moreover, in the short-term, the country could enact energy conservation policies to combat global warming. [ABSTRACT FROM AUTHOR]

Bangladesh has significant natural gas reserves, and total demand has climbed substantially in recent years. The study uses the autoregressive distributed lag (ARDL) model for cointegration and the vector autoregressive(VAR) Granger causality model to analyze a long-run link between natural gas (NG) consumption, economic development, urbanization, and CO2 emissions. The objective is to investigate the relationship between the environmental Kuznets curve (EKC) and Bangladesh's NG consumption using data from the years 1990 to 2018. According to the ARDL model, economic growth, urbanization, and NG consumption, all have a positive and significant influence on CO2 emissions. Despite having a negative coefficient, the square of economic development has a significant impact on CO2 emissions. In the long run, it verifies the EKC hypothesis in Bangladesh. Both linear and nonlinear economic development determinants display statistically significant positive and negative signals in the short run. From Bangladesh's perspective, this also demonstrates the presence of an EKC. The impact of NG consumption in the short run is insignificant; nevertheless, urbanization has a significant effect. The VAR Granger causality demonstrates that economic development and urbanization have a bidirectional response; however, NG consumption and CO2 emissions have just one-way causality. The key policy implication of the study is that NG use is expected to raise emissions. Increasing the share of clean energy in the energy utilization system, such as nuclear power and renewable energy, is a plausible policy choice. [ABSTRACT FROM AUTHOR]

China is facing increasing pressure to reduce CO2 emissions from energy consumption. Given this issue, understanding the characteristics, influencing factors, and trends can provide adequate information for decision-makers to solve the CO2 emission problem. This study analyzes the characteristics of CO2 emissions from energy consumption in 30 regions of China from 2005 to 2018 and applies the STIRPAT model to identify the impact of the influencing factors. Combined with the CO2 emission trend in 2030 as predicted by the ARIMA model, the key mitigation regions and strategies reduction have been determined. Results indicate that CO2 emissions have been increasing from 2005 to 2018 in China, thus showing the characteristic of the east being larger than the west spatially. Under the baseline scenario, these emissions will continue to rise in 2030. Carbon emissions intensity is declining, and the gap between provinces with the highest and lowest per capita CO2 emissions is widening. Although per capita GDP is significantly positively correlated with provinces, population is the key factor influencing more provinces, followed by the proportion of the secondary industry and urbanization rate. To achieve low-carbon sustainable development, Shandong, Shanxi, Inner Mongolia, Guangdong, Shaanxi, Xinjiang, and Ningxia are considered the key regions of concern for emission reduction. The heterogeneity of CO2 emission characteristics and influencing factors among regions provides a direction for the development of targeted and differentiated regional emission reduction strategies. [ABSTRACT FROM AUTHOR]

Oman has traditionally relied upon natural gas and oil for meeting its domestic energy demand. As a result, despite growing economically, the level of carbon dioxide emissions in Oman has persistently surged; consequently, the nation has failed to ensure environmentally sustainable economic growth. Against this background, this current study aims to explore the impacts of energy consumption, energy efficiency, and financial development on Oman's prospects of attaining environmentally sustainable growth over the 1972–2019 period. The estimation strategy is designed to take into account the structural break issues in the data. Using the carbon productivity level as an indicator of environmentally sustainable economic growth, we find long-run associations amid the study variables. Besides, higher energy consumption and greater financial development are found to impede carbon productivity while improving energy efficiency is observed to boost carbon productivity in Oman. Therefore, it is pertinent for Oman to consume low-carbon and energy-efficient fossil fuels, improve energy efficiency levels, and green its financial sector to achieve environmentally sustainable growth. [ABSTRACT FROM AUTHOR]

This study aims to analyze the asymmetric long-run relationship between economic growth (EG), foreign direct investment (FDI), and carbon emissions (CO2) within the context of the environmental Kuznets curve (EKC) and the pollution haven hypothesis (PHH) in China. Employing the quarterly data from 1982Q1 to 2018Q4, we have used novel techniques to meet the stated objectives of our study, named quantile ARDL and quantile Granger causality. The study provides novel outcomes using the advanced quantile ARDL and quantile Granger causality tests. The significant implication of this method is that it provides locational asymmetry. We find strong evidence of the EKC and PHH for China based on the empirical results of linear and nonlinear ARDL models. Similarly, findings of quantile Granger causality validate the bidirectional relationship among all variables in upper and lower quantiles. Moreover, the results of the Wald test confirm the asymmetric long-run relationship between FDI and carbon emissions (CO2). Thus, legal measures must be enhanced, accepted, rigorously imposed, and monitored in all provinces to assure a further reduction in carbon emissions. This study will be conducive for the policymakers to combat environmental contamination concerning economic growth and FDI inflow in China. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to investigate the links between renewable energy (RE), non-renewable energy (NRE), capital, labour and economic growth, using the nonlinear autoregressive distributive lag (NARDL) model in Malaysia for the period of 1980–2018. The results of NARDL confirm the asymmetric effect of RE and NRE consumption on the economic growth in the long run as well as the short run in Malaysia. The findings also show that in the long and short run, positive shocks of NRE are greater than the positive shocks of RE. It indicates that Malaysia's economic growth is highly dependent on NRE which is not a good indication as NRE consumption increases carbon dioxide (CO2) emission in the country. Moreover, the empirical results of this study demonstrated that RE consumption reduction accelerates economic growth, whereas NRE consumption reduction decreases economic growth. It can have claimed that in Malaysia, RE is still more expensive than NRE. In conclusion, this study offered a variety of measures to develop RE to reduce the dependency on NRE consumption. [ABSTRACT FROM AUTHOR]

Most developing economies have recently experienced significant economic growth without corresponding substantial poverty reduction and improved population wellbeing. This paper uses a nonlinear autoregressive distributed lag model to explore the growth-poverty relationship in Tanzania using annual time series data on per capita consumption expenditure, real GDP, GINI index, and unemployment from 1991–2020. To explore the causality among the variables and long-run asymmetry between per capita consumption expenditure and economic growth, the study employs Granger causality and Wild test respectively. The results confirm the presence of long and short-run asymmetric behavior of economic growth. Besides, in the short-run, the Granger causality test supported the feedback hypothesis between economic growth and consumption expenditure, and the unidirectional hypothesis from income inequality and unemployment to consumption expenditure. In the long-run, unidirectional causality was observed from consumption expenditure to both economic growth and unemployment. The study submits that while economic growth exhibits poverty reduction features, growth alone is not sufficient to alleviate poverty because the interaction of income inequality with economic growth dampens the poverty-reducing effects of economic growth. Therefore, economic growth has a significant explanation for poverty but not all about the evolution of poverty. The study opens policy perspectives with wide international relevancy as outlined in the policy implication section. [ABSTRACT FROM AUTHOR]

Sustainable development goal 17 emphasizes the importance of international trade in achieving inclusive growth. Likewise, countries with high level of corruption will experience limited growth. In order to examine the causality, this study considers the impact of international trade and corruption on the economic growth of selected sub-Saharan African countries (Angola, Ghana, Kenya, Nigeria, and South Africa) from the period 2000-2019. The granger causality test and fixed effect method of estimation were adopted. The result of the granger causality tests shows that there is no causality between import and economic growth, there is unidirectional causality between export and economic growth and there is no causality between control of corruption and economic growth. Furthermore, it was discovered that export, import, and control of corruption have a positive impact, 25.4%, 32%, 45.5% respectively, on the economic growth of selected sub-Saharan African countries. Hence from these findings, policies towards export promotion should be encouraged as export is crucial for the economic growth of these countries and policies to curb corruption should be implemented in order to promote economic growth in the selected sub-Saharan African countries. [ABSTRACT FROM AUTHOR]

Over the past several decades, weather radar has become an indispensable tool in flood forecasting studies, especially in ungauged regions. However, the rainfall extremes with radar data may contain biases, and this can be removed by using the information provided by rain gauges. For this purpose, a procedure that covers additive and multiplicative error correction methods with three vector norms, taxicab norm (L1), Euclidean norm (L2), and maximum norm (L∞), is proposed for adjusting radar data. The top 26 flood events with 20 stations in a 5-year database of radar data are used to quantify the overall agreement between radar and gauge datasets. After finding the best model and norm for adjusting the error in radar data, the correction factor in the model is analyzed with the aspects of the season, station height, rainfall amount, and distance between radar location and rain gauge station. Results show that the multiplicative error model with L1 norm minimization is the best choice given all criteria. It is noted that as the systematic error in the radar data is nonlinear, the additive factors are inconclusive in rainfall variability. Moreover, it is found out that the values in multiplicative constant evaluation are more apparent with grouping done for the season, rainfall amount, and distance, but a consistent result is not found for the grouping done for the station height. [ABSTRACT FROM AUTHOR]

The current study explores the impact of financial technology (FinTech) on the economic growth in Jordan using annual time series data from (1990 – to 2021). The autoregressive distributed lag approach has been performed to test Cointegration, while the vector error correction model is applied to examine long-term and short-term causality. However, the results show that FinTech products (number of individuals using the internet, number of broadband subscriptions, number of Mobile cellular subscriptions, number of automated transfer machines, and number of branches) contribute to further growth in financial inclusion, which in turn increases economic growth in Jordan. These findings recommend that policymakers in Jordan pay more attention to increasing the ability to access financial services. [ABSTRACT FROM AUTHOR]

The relationship between economic growth (in terms of GDP) and renewable energy (RE) and nonrenewable energy (NRE) consumption was investigated in 20 countries featured on the Renewable Energy Country Attractiveness Index list, also known as the Paris Club. The effect of both RE and NRE consumption on economic growth is discussed in the growth model based on the neoclassical production function. Labor and capital, which are important dynamics of growth, are also considered in the model. Granger causality and panel vector autoregression analysis are performed for the period 1991–2016. The results show that neither RE nor NRE consumption has a positive effect on economic growth. In reality, a 1% increase in RE consumption will reduce the GDP growth by 0.14%. For the effect of GDP growth on energy types, if growth increases by 1%, NRE consumption increases by 5.54%. If economic growth increases by 1%, a reduction of 1.73% occurs in RE consumption. In contrast, a causal link between both types of energy to growth has not been determined. There is no statistically significant coefficient of NRE and capital factors on GDP. A mutually positive and statistically significant relationship was determined between labor and growth. According to the results of variance decomposition, the basic dynamic of growth is itself: over a ten-year period, growth was affected by itself by 98%. [ABSTRACT FROM AUTHOR]