Narrow Results

This study presents a novel fractional order grey model FGM ($\alpha$,1) obtained by extending the grey model (GM (1,1)). For this, we generalize the whitenization first-order differential equation to fractional order by using the Caputo fractional derivative of order $\alpha$. A real-world case study, scrutinize the economic growth influence on environmental degradation in Turkey, is performed to evaluate the significance of the projected model FGM ($\alpha$,1) in contrast to the current classical GM. We apply autoregressive distributed lags bounds testing co-integration approach to empirically examine the long-run and short-run relation among economic growth, agriculture, forestry and fishing (AFF), electricity utilization and CO₂ emissions. Using the new fractional order model, all the variables are forecasted in the forthcoming years until 2030. Findings disclose that electricity utilization and economic growth (GDP) accelerate emission of CO₂ though in the long run agriculture, forestry, and fishing reduce the environmental pollution in Turkey.

The paper investigates the impact of financial integration and energy consumption on economic growth in Vietnam during the period 1986–2017. By applying the Autoregressive Distributed Lag ARDL) approach proposed by Pesaran et al. [Pesaran, MH, Y Shin and RJ Smith (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289–326.] and the bounds cointegration test, the empirical results show the existence of long-term cointegration among all the variables, and that an increase in financial integration leads to an increase in economic growth in the long run. There is a positive impact of energy consumption on growth in both the short run and long run. The causality test of Toda and Yamamoto [Toda, HY and T Yamamoto (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1–2), 225–250.] confirm that there is bi-directional causality between the pairs, financial integration and economic growth, and energy consumption and growth, which support the feedback hypothesis. However, there is only uni-directional causality from energy consumption to financial integration. The empirical results should be of major empirical importance for public policy decision-makers to plan sustainable development goals for Vietnam.

Understanding currency fluctuations carries a high level of risk. A currency can slide or spike as a response of an economic indicators revelation or an unexpected political event, both of which are unforeseeable. As foreign investors become more optimistic about the country’s future, a healthier economy usually requires a strong currency. Therefore, it is necessary to assess the exchange rate volatility risk in the context of direct investment in order to develop preventive policy routes that would encourage foreign investors into the country. To this purpose, the autoregressive distributive least square (ARDL) technique has been employed to investigate the symmetric effect of exchange rate volatility on foreign direct investment (FDI) during global financial crises and political regimes from January 2000 to December 2018. In order to eliminate arbitrariness, the study uses the most accredited estimate of volatility, GARCH (1 1), as part of the re-estimation process. Besides this, the interaction has been studied under various regimes to see how the political environment affects foreign market participants’ expectations for future gains. The findings suggest that exchange rate volatility is adversely related to FDI and is a source of decreased net foreign investment in Pakistan. It also illustrates that during times of crises and apolitical regimes, Pakistan’s average FDI falls dramatically. The findings are extended to the context of Pakistan that has seen significant rupee volatility for the past few years. Our study recommends that policymakers should pursue exchange rate measures that promote exchange rate stability, which might assist to minimize risk of exchange rate volatility and so attract higher FDI. It is also crucial to formulate more sustainable investment methods that allow for efficient capital allocation during times of economic uncertainty.

Increasing environmental degradation and its impact on long-term economic prosperity have become major global concerns, particularly in developing economies like Nigeria. Environmental quality is crucial for Sustainable Development (SD), affecting economic growth, resource availability, and societal well-being. However, balancing economic growth and environmental preservation remains a challenge for policymakers. Therefore, this study uses an Autoregressive Distributed Lag (ARDL) estimation approach to examine the relationship between environmental quality and SD in Nigeria using quarterly data from 2000 to 2021. The research examines the impacts of CO₂ emissions, forest area, Natural Resource Depletion (NRD), capital, and labor on SD from both short- and long-term perspectives. The findings demonstrate that CO₂ emissions negatively affect SD, emphasizing the importance of strong environmental legislation. In contrast, forest areas have a beneficial impact on SD, emphasizing the necessity of environmental preservation. Lagged and contemporary NRDs show trade-offs between resource use and long-term prosperity. Capital emerges as a key engine of SD. However, this study finds that factors like labor lack statistical significance in explaining variations in SD. These insights provide valuable guidance for policymakers aiming to balance economic growth with environmental sustainability. The study recommends the implementation of stringent environmental policies to curb CO₂ emissions and emphasizes the need for responsible resource management practices to mitigate the adverse effects of NRD.