This paper investigates the existence of pollution haven hypotheses (PHH) and the Environmental Kuznets Curve (EKC) for top five (China, Canada, Germany, Brazil, And France) carbon dioxide emitter countries during 1990-2018.The current study uses a panel autoregressive distributed lag (PARDL) technique to obtain empirical outcomes.The estimated results demonstrate the error-correction term's significant and adverse impact and the system's conversion to long-run equilibrium following a shock.The results of the short run and long term indicate that carbon dioxide emissions are positively associated with EC (energy consumption) and are statistically significant.For both the short run and long run the coefficients of GDP and the square of GDP are positive and significant respectively.This endorses the EKC relationship for the panel of these countries.The forest variable indicates that the short-run result predicts that forests are negative but insignificant relation with Carbon dioxide emission, while in the long run; it shows also a negative significant association.Domestic capital is positive and significant in the short-term analysis, while in the long run association between corban dioxide emission and domestic capital is also positive and significant.The foreign capital is negative and significantly linked to Carbon dioxide emission in the long-run analysis, which rejects the pollution heaven hypothesis in these countries.Furthermore, these nations should to switch to using cleaner, more environmentally friendly energy sources, like renewable energy sources.These nations must implement policies that do not hinder national economic expansion while achieving the goal of lower carbon dioxide emissions.
Cerebral ischemia is one of the leading causes of neurological disorders. The exact molecular mechanism related to chronic unilateral cerebral ischemia-induced neurodegeneration and memory deficit has not been precisely elucidated. In this study, we examined the effect of chronic ischemia on the induction of oxidative stress and c-Jun N-terminal kinase-associated detrimental effects and unveiled the inhibitory effect of specific JNK inhibitor (SP600125) on JNK-mediated brain degeneration in adult mice. Our behavioral, biochemical, and immunofluorescence studies revealed that chronic ischemic injuries sustained increased levels of oxidative stress-induced active JNK for a long time, whereas SP600125 significantly reduced the elevated level of active JNK and further regulated Nrf2/HO-1 and NF- κ B signaling, which have been confirmed in vivo. Neuroinflammatory mediators and loss of neuronal cells was significantly reduced with the administration of SP600125. Ischemic brain injury caused synaptic dysfunction and memory impairment in mice. However, these were significantly improved with SP600125. On the whole, these findings suggest that elevated ROS-mediated JNK is a key mediator in chronic ischemic conditions and has a crucial role in neuroinflammation, neurodegeneration, and memory dysfunction. Our findings suggest that chronic oxidative stress associated JNK would be a potential target in time-dependent studies of chronic ischemic conditions induced brain degeneration.
Here, we have unveiled the effects of cycloastragenol against Aβ (Amyloid-beta)-induced oxidative stress, neurogenic dysfunction, activated mitogen-activated protein (MAP) kinases, and mitochondrial apoptosis in an Aβ-induced mouse model of Alzheimer’s disease (AD). The Aβ-induced mouse model was developed by the stereotaxic injection of amyloid-beta (5 μg/mouse/intracerebroventricular), and cycloastragenol was given at a dose of 20 mg/kg/day/p.o for 6 weeks daily. For the biochemical analysis, we used immunofluorescence and Western blotting. Our findings showed that the injection of Aβ elevated oxidative stress and reduced the expression of neurogenic markers, as shown by the reduced expression of brain-derived neurotrophic factor (BDNF) and the phosphorylation of its specific receptor tropomyosin receptor kinase B (p-TrKB). In addition, there was a marked reduction in the expression of NeuN (neuronal nuclear protein) in the Aβ-injected mice brains (cortex and hippocampus). Interestingly, the expression of Nrf2 (nuclear factor erythroid 2–related factor 2), HO-1 (heme oxygenase-1), p-TrKB, BDNF, and NeuN was markedly enhanced in the Aβ + Cycloastragenol co-treated mice brains. We have also evaluated the expressions of MAP kinases such as phospho c-Jun-N-terminal kinase (p-JNK), p-38, and phospho-extracellular signal-related kinase (ERK1/2) in the experimental groups, which suggested that the expression of p-JNK, p-P-38, and p-Erk were significantly upregulated in the Aβ-injected mice brains; interestingly, these markers were downregulated in the Aβ + Cycloastragenol co-treated mice brains. We also checked the expression of activated microglia and inflammatory cytokines, which showed that cycloastragenol reduced the activated microglia and inflammatory cytokines. Moreover, we evaluated the effects of cycloastragenol against mitochondrial apoptosis and memory dysfunctions in the experimental groups. The findings showed significant regulatory effects against apoptosis and memory dysfunction as revealed by the Morris water maze (MWM) test. Collectively, the findings suggested that cycloastragenol regulates oxidative stress, neurotrophic processes, neuroinflammation, apoptotic cell death, and memory impairment in the mouse model of AD.
Tobacco is the country’s most valuable cash crop, contributing for a large portion of the country's agricultural output. This study intends to observe to evaluate the cost and benefit of the tobacco production in Swabi district, KP, Pakistan. During 2018-19 academic year, data was collected from three villages in Sikandari, Dagi, and Lahor using a random sampling technique. The total number of samples for analysis was 100. To estimate tobacco production, cost, and profitability, the Cobb-Douglas production function was employed. The total average Cost of per acre tobacco production was Rs. 151370while total revenue per acre was Rs. 457600. It was found that the average marketing costs were Rs. 82360 per acre, fertilizer costs were Rs. 12000 per acre, nursery costs were Rs. 4110 per acre, land rent was Rs. 37000 per acre, land preparation was Rs. 4000 per acre, irrigation costs were Rs. 3200 per acre and cultural costs were Rs. 6000 per acre. In the period of analysis, the average net income (net profit) from tobacco was Rs. 306230 per acre and the gross income was Rs. 343230 per acre. It is recommended that if the farmers use quality seeds, the latest technology, usage of chemical fertilizers, irrigation, insecticides, and weeding the tobacco profitability will be increased and a handsome contribution in our GDP. It is also be noted that in the research area, inputs such as marketing costs and land rent are quite expensive; therefore, the government may compensate farmers by lowering the prices of inputs such as fuel wood, rent, fertiliser, pesticides, and so on.
The digital economy has had an impact on the female employment rate over time. Currently, the researchers are more interested in investigating the impacts of the digital economy by focusing on its various aspects of female employment. The current study is motivated by this renewed interest to investigate the impact of the digital economy on female employment rates in Asian Developing Countries from 1990 to 2021. The digital economy is measured by several indicators such as fixed telephone subscriptions, fixed broadband subscriptions, mobile phone subscriptions, secure internet servers, and internet users. The Panel Autoregressive Distributed Lag (PARDL) model is used for analysis that reveals a positive relationship between female employment rates and the digital economy in both the short and long run. The control variables/factors, Education and GDP, also showed positive relationships with female employment. We suggest that governments prioritize funding for digital infrastructure and encourage fair access to technology, especially for women, based on our study. Furthermore, the positive effects of the digital economy on female employment can be strengthened through focused policy interventions, such as offering financial incentives to companies that hire and train women in digital skills. By utilizing these tactics, policymakers can guarantee that women are prepared to take advantage of the chances brought about by the quickly changing digital landscape, promoting gender equality and inclusive economic growth throughout Asian developing nations.
Purpose This study empirically examines the impact of some domestic as well as global factors such as trade openness (TO), money supply (MS), exchange rate, global oil prices (GOPs) and interest rate (IR) on inflation. Design/methodology/approach This study deploys a quantitative method considering 30 years of data (1991–2020) from four South Asian countries, namely, Sri Lanka, Pakistan, Bangladesh and India. To determine the potential impact of different factors on inflation, this study applies the panel analysis of the system generalized method of moments (SGMM). Findings This study empirically finds that TO, MS, exchange rate and GOPs have a positive impact on inflation, while IR and the structural adjustment program (SAP) have a negative impact on inflation. Out of the various determinants considered in this study, TO, exchange rate and the SAP are insignificant, while the rest of the variables are significant and consistent with previous studies. Practical implications This study informs policymakers about maintaining price stability and fostering economic growth in South Asian nations. It breaks new ground as the first empirical examination of the International Monetary Fund (IMF)’s SAP impact on inflation in the region. Originality/value This study tries to find out whether the SAP of the IMF is responsible for inflation in South Asian countries. It gives renewed attention to the causality of inflation from the perspective of countries receiving loans from donors, especially the IMF.
Maintaining a stable exchange rate is a challenging task for the world, especially for developing economies. This study examines the impact of asymmetric exchange rates on trade flows in selected Asian countries and finds that the effects of increased exchange rate volatility on exports and imports differ among Pakistan, Malaysia, Japan, and Korea. The quarterly data from the period 1980 to 2018 is collected from the International Financial Statistics (IFS) database maintained by the International Monetary Fund (IMF). We employ both linear and non-linear Autoregressive Distributed Lag (ARDL) models for estimation. The non-linear models yielded more significant findings, while the linear models did not indicate any significant effects of exchange rate volatility on trade flows. The results of the study suggest that in the case of Pakistan, both the linear and non-linear models indicate that increased exchange rate volatility adversely affects exports and imports, while decreased volatility enhances both. This implies that stabilizing the exchange rate would be beneficial for Pakistan's trade. In contrast, the linear model applied to Malaysia shows no long-run effects of exchange rate volatility on exports. However, the result suggests that decreased volatility stimulates Malaysia's exports. Therefore, in the case of Malaysia, stabilizing the exchange rate could contribute to boosting exports. We also found that increased exchange rate volatility boosts exports of Japan. On the other hand, decreased volatility hurts exports of Japan. As for the long-run effects of exchange rate volatility on imports, we found that increased volatility boosts imports of Korea. The study provides various policy implications regarding the impact of exchange rate volatility on trade flows in developing economies. The study highlights the importance of country-specific considerations in understanding the impact of exchange rate volatility on trade flows, and has important policy implications for promoting trade and economic growth in these nations. It emphasizes the need to model exchange rate volatility separately for developed and developing countries and to continue research and analysis to identify ways to mitigate its negative effects on the economy.
The main focus of this study is the asymmetric relationship between volatility in the exchange rate and demand for money in United State. Data was used from 1990 Q1 to 2020 Q1 to conduct this research. The study uses a nonlinear Autoregressive Distributed Lag technique to derive empirical estimates from selected sample data. Although the rate of exchange is regarded as a fundamental predictor of demand for money in the literature, there is insufficient empirical data to support this claim. We split the exchange rate into two strands in this analysis, positive (appreciation) and negative (depreciation) values, and we find that changes in the rate of exchange (EXR) affected asymmetrically the demand for money in United State. Furthermore, our findings show that when the US dollar appreciates, US citizens expect the dollar to appreciate even more, so they hold more US dollars. When the US dollar depreciates, the negative coefficients of exchange rate depreciation indicate that they continue to demand more US dollars. Rather than expecting additional deterioration, the impact of the wealth effect, and when the value of far-off assets held by US citizens’ increases in the US dollar, US citizens now want more US dollars to finance their rising consumption.
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