Search

The primary objective of this study is to investigate the impact of financial markets development and financial institutions development on the ecological footprint in Saudi Arabia during the period from 1981 to 2018. To this end, the nonlinear autoregressive distributed lag model is implemented to estimate the asymmetric effects The findings suggest that the ecological footprint is only affected by negative changes in the financial development index (fall in financial development) in the long-run. The disaggregate analysis suggests some divergence regarding the contribution of financial markets and financial institutions to environmental degradation. The analysis suggests that more (less) financial institutions development improves (deteriorates) the ecological footprint in the long-run. In contrast, the presence of more developed financial markets can have a negative impact on the ecological footprint in the long-run. These aforementioned findings are robust to additional control variables and structural breaks in the nonlinear ARDL specification. The results of the present study may assist policymakers when designing financial and monetary policies to accelerate the energy transition and effectively address the challenges posed by climate change. [ABSTRACT FROM AUTHOR]

This study investigates whether international crude oil prices predicted the exchange rate in Algeria between January 1988 and June 2022. This paper does so by employing a variety of causality tests. More specifically, the causal linkages are checked using various time domain causality tests, the frequency domain causality test proposed by Breitung-Candelon (J Econom 132(2):363–378, 2006) and the time-varying causality test recently developed by Shi et al. (2018, 2020). The different causality tests suggest that fluctuations in Brent crude oil prices do not cause the real effective exchange rate. These findings are robust to introducing alternative exchange rates and crude oil price proxies. The analysis is further extended by considering the asymmetric and volatile behaviors of crude oil prices. The time-varying causality test indicates that the real effective exchange rate exhibits a significant response solely to decreases in oil prices. Finally, oil price volatility obtained from the EGARCH (2,2) model has predictive power on the exchange rate following each decline in crude oil prices. The discussion and policy recommendations are subsequently provided. [ABSTRACT FROM AUTHOR]

The present research reexamines the validity of the EKC hypothesis in the top three polluted nations in Africa, Algeria, Egypt, and South Africa, over the period 1970–2020. The central idea of the research is to reexamine the EKC hypothesis by incorporating the ARMEY curve linking government spending and GDP into the Kuznets curve, as suggested by Işık et al. Environ Sci Pollut Res 29(11):16472-16483, (2022) and Ongan et al. Environ Sci Pollut Res 29(31):46587-46599, (2022). To this end, the ARDL equation with a Fourier function is implemented to estimate the long-run drivers of environmental deterioration. The Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model results revealed that the composite model is only valid in Algeria, and the optimal government spending that maximizes CO2 emissions is 16.88% of gross domestic product. On the contrary, the results showed that the composite model is not valid for South Africa and Egypt due to the failure of the desired shapes for the three curves. The outcomes also confirm the role of energy consumption and population as key drivers of environmental degradation in the three countries. [ABSTRACT FROM AUTHOR]

Although a plethora of literature has shed light on the export-growth nexus over the past few decades, most studies have maintained the assumption of linear symmetric causal linkages. The current research contributes to the existing literature by investigating the export-growth linear and nonlinear causal relationships in Next Eleven emerging economies during the period 1960–2020. The empirical analysis is based on the Toda-Yamamoto linear causality test and the Kyrtsou-Labys nonlinear symmetric and asymmetric causality tests. The Toda-Yamamoto linear causality test suggests little evidence of significant causal relationships between exports and growth. According to the symmetric version of the Kyrtsou-Labys nonlinear causality test, the export-led growth hypothesis holds for only four countries, while the growth-led exports hypothesis is valid for five countries. When using the asymmetric version of the Kyrtsou-Labys nonlinear causality test, the obtained findings, albeit mixed, provide fresh insights into the relationship between exports and growth. The analysis particularly reveals that exports and growth are more sensitive to negative than positive shocks. [ABSTRACT FROM AUTHOR]

The present study examines the symmetric and asymmetric effects of natural resource exploitation on the ecological footprint in Saudi Arabia during the period 1981–2018. The analysis is performed for total natural resources and different types of natural resources, including oil, natural gas, and minerals. This research employs the dynamic Autoregressive Distributed Lag (DYNARDL) simulation approach. In addition to its statistical and computational superiority, the DYNARDL allows assessing the environmental repercussions of shocks that occurred on natural resources in both the short- and long-run. The findings suggest that total, oil, and natural gas rents have a positive symmetric association with the ecological footprint in the long run, while no significant impact is identified for mineral resources. When conducting the asymmetric analysis, the findings reveal that only increases in total, oil, and natural gas rents deteriorate the ecological footprint in the long run, while no effects are confirmed for decreases in natural resource rents. The shock analysis reveals that a 10% increase in total and oil rents leads to environmental degradation by 3% in the long run, while a similar upsurge in natural gas rents induces a 4% deterioration in environmental quality. These findings may help design effective resource-use policies to achieve environmental sustainability in Saudi Arabia. [ABSTRACT FROM AUTHOR]

The accuracy of short-term electricity load forecasting is of great interest since it allows avoiding unexpected blackouts and lowering operating costs. In this paper, we aim to implement the artificial neural networks to model and forecast the half-hourly electric load demand in Tunisia over the period 2000–2008. To improve the quality of forecasts, the proposed artificial neural network model uses not only past electric load values as inputs, but also climatic and calendar variables. To determine the optimal structure of the neural network model, this paper employs the pattern search algorithm. Moreover, the neural network model is equipped with the Levenberg–Marquardt learning algorithm. Our findings confirm the performance of this algorithm to the view of evaluation indicators since the mean absolute percentage error values range between 1.1 and 3.4%. The analysis also shows the superiority of the Levenberg–Marquardt algorithm compared to the resilient back propagation algorithm and the conjugate gradient algorithm. In the light of the current research, we stress the aptness of the proposed artificial neural network model in forecasting short-term electricity demand. [ABSTRACT FROM AUTHOR]

Based on a micro-level dataset composed of 548 firms operating in Tunisian manufacturing industries, we examine the effects of exchange rates on employment over the period 1997-2002. The estimation of a dynamic employment equation using the system GMM technique suggests that employment positively responds to the depreciation of effective exchange rates and bilateral exchange rates vis-à-vis the Euro and the US dollar. Moreover, the different elasticities of employment to exchange rates vary according to specific characteristics of firms such as the ownership structure, the international exposure, the size and the industries to which they belong. Finally, using different measures of volatility, we confirm that the exchange rate volatility significantly lowers the employment level in all categories of firms. [ABSTRACT FROM AUTHOR]

The international community is more than ever before worrying about the unremitting global warming and climate change and the responsibility of extensive energy use for that situation. This article contributes to the existing literature by examining whether energy consumption predicts CO2 emissions during the past 50 years in the five most polluting nations in the world. To do this, we have been using the recently developed predictability test of Westerlund and Narayan (Journal of Banking and Finance, 36, 2632–2640, 2012, Journal of Financial Econometrics, 13, 342–375, 2015). We take thereby into account the problem of endogeneity and persistence in the explanatory variable. Likewise, this test has the advantage of treating the problem of heteroscedasticity. Using several predictive evaluation measures and assuming the historical average as a benchmark, we find that the basic model of the predictability test of Westerlund and Narayan (2012, 2015) surpasses the benchmark model. These findings reveal that primary energy consumption predicts CO2 emissions in the world and all countries, for different forecast horizons. Further, the in-sample evidence of predictability has been supported by the out-of-sample analysis. [ABSTRACT FROM AUTHOR]