Exploring the impact of tourism and energy consumption on the load capacity factor in Turkey: a novel dynamic ARDL approach

Economic costs of non-native species in Türkiye: A first national synthesis

Biological invasions are increasingly recognised as a major global change that erodes ecosystems, societal well-being, and economies. However, comprehensive analyses of their economic ramifications are missing for most national economies, despite rapidly escalating costs globally. Türkiye is highly vulnerable to biological invasions owing to its extensive transport network and trade connections as well as its unique transcontinental position at the interface of Europe and Asia. This study presents the first analysis of the reported economic costs caused by biological invasions in Türkiye. The InvaCost database which compiles invasive non-native species' monetary costs was used, complemented with cost searches specific to Türkiye, to describe the spatial and taxonomic attributes of costly invasive non-native species, the types of costs, and their temporal trends. The total economic cost attributed to invasive non-native species in Türkiye (from 202 cost reporting documents) amounted to US$ 4.1 billion from 1960 to 2022. However, cost data were only available for 87 out of 872 (10%) non-native species known for Türkiye. Costs were biased towards a few hyper-costly non-native taxa, such as jellyfish, stink bugs, and locusts. Among impacted sectors, agriculture bore the highest total cost, reaching US$ 2.85 billion, followed by the fishery sector with a total cost of US$ 1.20 billion. Management (i.e., control and eradication) costs were, against expectations, substantially higher than reported damage costs (US$ 2.89 billion vs. US$ 28.4 million). Yearly costs incurred by non-native species rose exponentially over time, reaching US$ 504 million per year in 2020-2022 and are predicted to increase further in the next 10 years. A large deficit of cost records compared to other countries was also shown, suggesting a larger monetary underestimate than is typically observed. These findings underscore the need for improved cost recording as well as preventative management strategies to reduce future post-invasion management costs and help inform decisions to manage the economic burdens posed by invasive non-native species. These insights further emphasise the crucial role of standardised data in accurately estimating the costs associated with invasive non-native species for prioritisation and communication purposes.

Do renewable energy and human capital facilitate the improvement of environmental quality in the United States? A new perspective on environmental issues with the load capacity factor

Recently, countries have been making intensive efforts to alleviate the burden on the environment and to make environmental conditions sustainable. In this context, our study aims to investigate the long-term impact of renewable energy consumption (REC) and human capital (HC) by considering the load capacity factor (LCF). We also investigate the long-term impact of economic growth (Y) and non-renewable energy consumption (NREC) on the LCF. In this context, we analyze annual data for the U.S. for the period 1965-2018 using the newly developed augmented ARDL (AARDL) approach. The long-term empirical results show the following. i) Increases in Y negatively affect LCF and deteriorate environmental quality. ii) Increases in NREC negatively affect LCF and accelerate the deterioration of environmental quality. iii) REC has no significant impact on environmental quality. iv) Increases in HC support the improvement of environmental quality. The empirical results show that contrary to expectations, renewable energy consumption does not have a significant impact on environmental quality in the U.S., whereas human capital is an important factor in improving environmental quality. In this context, US policymakers should pave the way for more investment in eco-friendly renewable energy investments and human capital to establish sustainable environmental quality. Policymakers should also take steps to reduce the use of fossil fuels.

How do energy consumption, globalization, and income inequality affect environmental quality across growth regimes?

This paper investigates the impacts of renewable and nonrenewable energy consumption, income inequality, and globalization on the ecological footprints of 49 countries for the period of 1995-2018. Panel cointegration test reveals a long-run relationship between the variables. Long-run parameter estimates derived from AMG and CCEMG, increasing income and nonrenewable energy consumption, have a significant positive impact on the ecological footprint, while countries that consume more renewable energy have seen an improvement in the quality of the environment. Conversely, neither income inequality nor globalization has a significant effect on national EFs. Evidence from the estimation of the panel threshold error correction model, where GDP growth is used as the transition variable, indicates a significant threshold effect, which supports a nonlinear relationship among the variables by identifying two distinct growth regimes: lower and upper. For the estimation sample, the positive and significant parameter estimates for economic growth in both growth regimes do not support the EKC hypothesis. The results indicate that renewable and nonrenewable energy consumption has a larger impact on the EF in the upper than lower growth regime. The threshold estimates are in line with the linear long-run estimates that do not indicate that income inequality has a significant impact on ecological footprint. However, globalization appears to negatively affect environmental quality in the lower growth regime.

Evaluating the impact of technological innovation and energy efficiency on load capacity factor: empirical analysis of India

The determinants of environmental degradation have been investigated many times by utilizing carbon dioxide emissions and/or ecological footprint. However, these traditional environmental degradation indicators do not consider the supply side of environmental problems. Therefore, this study focuses on the dynamic influence of financial development, energy efficiency, economic growth, and technological innovation on environmental degradation in India through the load capacity factor, including both the supply and demand sides of environmental problems. For that purpose, the recently developed dynamically simulated autoregressive distributed lag (ARDL) method is employed using the annual time-series data extending from 1980-2020. The dynamically simulated ARDL results demonstrate that financial development, economic growth, and technological innovation have a dynamic adverse impact on the load capacity factor, whereas energy efficiency has a positive dynamic influence on environmental quality. In addition, the results support the validity of the environmental Kuznets curve hypothesis as the negative effect of economic growth on environmental quality decreases over time. Based on the study findings, policy recommendations are provided for India. Finally, this study utilizing load capacity factor as an indicator for environmental quality will provide new topics in exploring the determinants of environmental degradation.

Financial inclusion and environmental pollution in Türkiye: Fresh evidence from load capacity curve using AARDL method

Sustainability is an important concept for the whole world. Generally, in order to measure the sustainability of the environment, carbon dioxide emissions and ecological footprint indicators are used. However, these variables do not reflect the supply side of natural resources. Therefore, load capacity factor is an important environmental indicator for a sustainability. Environmental assessment based on the load capacity factor is more meaningful. Besides, improved access to financial services can contribute to environmental sustainability. The effect of financial inclusion on the load capacity factor in Türkiye has not been examined in the current literature. In this context, this study analyzes the impact of financial inclusion, hydropower energy consumption, and life expectancy at birth on environmental sustainability from a different perspective by focusing on load capacity factor. To this end, this study used the newly developed Augmented ARDL method to determine the cointegration relationship between the series and measure the values of the long-term coefficients. Based on the Augmented ARDL method, there is a cointegration relationship between the series. In the long run, hydropower energy consumption reduces pollution, while financial inclusion decreases load capacity factor. The effect of life expectancy at birth on pollution is not significant. Moreover, the results reveal that the load capacity curve hypothesis is valid in Türkiye. As a result, the Turkish government should promote renewable energy sources, especially hydropower energy consumption, align financial services with pollution reduction measures, and contribute to the creation of an environmentally conscious society.

Testing the income-finance-trade-environment nexus based on the ecological load capacity factor: Frequency-domain causality evidence from Nigeria

To ensure sustainable development, it is crucial that the consumption of ecological resources remains within their productive capacity. This study aims to support policy formulation by examining the nexus between income, financial development, trade openness, and the ecological load capacity factor in Nigeria from 1970 to 2021. The results of the Bayer-Hanck and autoregressive distributed lag (ARDL) bounds cointegration tests indicate a long-run equilibrium relationship among the variables. Parameter estimations were conducted using the dynamic ordinary least squares (DOLS) and ARDL model estimators. Both the long-run and short-run results indicate that the ecological load capacity factor has a U-shaped curve with income, thereby validating the load capacity curve hypothesis in Nigeria. The estimated threshold turning points of the curve fall within Nigeria's current range of per capita GDP, which indicates that further increases in income will enhance ecological sustainability. Additionally, the ecological load capacity factor exhibits a negative relationship with financial development and trade openness in the long run. The Breitung-Candelon spectral Granger causality tests reveal that, in the long run, unidirectional causality runs from income and trade openness to the ecological load capacity factor, and bidirectional causality exists in the case of financial development. Furthermore, the tests indicate that none of the causal paths are significant for wavelength periods below four years. Therefore, the study recommends implementing medium-to long-term policy strategies to strengthen the ecological resilience base of the economy.

Analyzing the validity of load capability curve: how economic complexity, renewable energy, R&D, and communication technologies take their part in G-20 countries

Intense anthropogenic contamination of the air, water, and soil inspires scholars to examine the causes of pollution and provide remedies to assure environmental sustainability. Therefore, researchers in this study are driven to investigate the causes of the severe air, water, and soil contamination that has resulted from human activity and to offer recommendations for achieving environmental sustainability. This research contributes to the ecological works by suggesting the load capability curve (LCH) hypothesis and using the load capacity factor (LC) to investigate components influencing climatic quality. The LC enables thorough climatic value examination when comparing ecological footprint and biocapacity. Information and communication technologies (INF), development and research (R&D), renewable energy (RE) usage, and disposable income are all examined, considering their effects on the load capacity factor. This analysis utilizes the cross-sectionally augmented autoregressive distributed lag estimator and the Westerlund cointegration on data for the G-20 countries from 1995 to 2018. Empirical evidence suggests that renewables, R&D spending, economic complexity, and INF all benefit environmental quality. This study cannot support the LCH hypothesis, which states that increasing income worsens ecological conditions up to a certain point but then aids in improving environmental quality afterward. Based on the findings, G-20 governments should prioritize environmental policies that boost economic growth, spread renewable energy, prioritize research and development spending, and assist the implementation of green INF infrastructure.

Evaluating the impact of digitalization, renewable energy use, and technological innovation on load capacity factor in G8 nations

Ecosystems are in danger due to human-caused air, water, and soil pollution, so it is important to find the underlying causes of this issue and develop practical solutions. This study adds to environmental research gap by suggesting the load capability factor (LCF) and using it to look at the factors affectting environmental health. The load capacity factor simplifies monitoring environmental health by illustrating the distinction between ecological footprint and biocapacity. We examine the interplay between mobile phone users (Digitalization DIG), technological advancements (TEC), renewable energy use, economic growth, and financial development. This study assesses G8 economies' data from 1990 to 2018, using a Cross-Section Improved Autoregressive Distributed Lag CS-ARDL estimator and a cointegration test. The data shows that green energy, TEC innovation, and DIG are all beneficial for natural health. Based on the results of this study, the G8 governments should focus on environmental policies that promote economic growth, increase the use of renewable energy sources, guide technological progress in key areas, and encourage the development of digital information and communications technologies that are better for the environment.

What is the role of remittance and education for environmental pollution? - Analyzing in the presence of financial inclusion and natural resource extraction

This study assessed the impact of gross domestic product (GDP), education, natural resources, remittances, and financial inclusion on carbon emissions in G-11 countries from 1990 to 2021. Based on the negative impact of pollution and the need for sustainable development, this study examined factors affecting CO₂ emissions in G-11 countries using non-linear panel ARDL model. The study found that a positive GDP shock increases CO₂ emissions in the short and long term, while a negative shock decreases emissions in the short term and increases emissions in the long term. Education was found to increase CO₂ emissions in the long term but decrease them in the short term, emphasizing the need for education on combating emissions. Natural resources were also found to increase emissions in the long term, highlighting the need for government-defined institutions to minimize extraction effects and enforce transparency and accountability. Positive changes in personal remittances and financial inclusion were found to increase emissions in both the short and long term, suggesting the need for policies that encourage renewable energy sources and energy efficiency improvement. The study concludes that policymakers should prioritize efficient resource allocation, promote renewable energy usage, and enhance environmental awareness to achieve sustainable development goals in G-11 countries. The possible applications of this study include the use of the models to investigate the asymmetric effects on CO₂ emissions. This model can be applied in future studies to examine the relationship between GDP, education, natural resources, personal remittances, financial inclusion, and CO₂ emissions in other countries.

Climate change, the by-product of tourism and energy consumption through a sustainable economic growth: a non-linear ARDL analysis for Turkey

Using a non-linear autoregressive distributed lag time-series analysis, this paper investigates the causal relationship between climate change, the tourism sector, and energy consumption in Turkey. The trade-off between a country's economic growth and the environmental degradation caused by tourism and the energy sector is critical in terms of scientifically addressing the issue and developing economic policies. As a result, climate change is used as the dependent variable and is represented by precipitation and temperature separately; the independent variables are tourist arrivals, energy consumption, and economic growth. Data is gathered by various institutions from 1995 to 2020. According to the test results, while positive and negative shocks contribute to the decrease in precipitation and temperature in renewable energy consumption (REC) in the long-run, they affect the increase in precipitation and temperature in non-renewable energy consumption (NREC). In the long-run relationship between tourism and temperature, a decrease in the number of tourist arrivals causes a decrease in temperature and precipitation. The findings reveal that a decrease in the number of tourist arrivals and an increase in REC may aid in decreasing temperature, while the increase in NREC may cause an increase in temperature. Through a case study of Turkey, decision-makers should consider these scientific findings that are in the frame of non-linear analysis as possible scenarios for mitigating climate change and fostering sustainable economic growth with efficient tourism policies for the world.

Assessing the role of the insurance market and renewable energy in the load capacity factor of OECD countries

In the empirical literature, few studies assessed the influence of the insurance market on carbon emissions. However, the effects of insurance markets on the load capacity factor (LCF) have been ignored. In this regard, the objective of the current work is to assess the potential impact of the insurance market on environmental sustainability in 27 OECD countries from 1990 to 2018 based on the LCF, which implies the strength of a state to enhance the population based on the current lifestyle. The present work employed the novel Method of Moments Quantile Regression (MMQR). This model is the prime and correct technique to better understand the association between the insurance market and the LCF across heterogeneous quantiles and to yield more robust empirical outcomes. The MMQR findings indicate a negative interaction between the insurance market and the LCF. In other words, the insurance sector has a powerful influence on economic activities and investments, such that insurance activities lead to an increase in the level of energy utilization, and thus have a negative influence on ecological sustainability. In contrast, the findings illustrate a positive and considerable association between renewable energy consumption and LCF. Based on the overall outcomes, it is suggested that OECD countries should focus on policies that encourage the use of renewable energy rather than incentivizing the insurance market. OECD country governments should also support green insurance activities to minimize the environmental damage of the insurance market.

Evaluation of renewable energy policies in Turkey with sectoral electricity demand forecasting

Energy is an essential requirement for sustainable development, society, and the world. Turkey has been trying to increase the use of renewable sources in electricity energy production with the incentive policies it has implemented in recent years. Accordingly, in the 2019-2023 Strategic Plan of the Ministry of Energy and Natural Resources, targets to increase the installed capacity of renewable energy sources have been determined. In this context, this article examines fort the first time, the effect of installed capacity of renewable energy sources on sectoral electricity demand. Thus, the study aims to evaluate the renewable energy policies implemented in Turkey. For this purpose, firstly, sectoral electricity demands were estimated for the period 1988-2017 using the autoregressive distributed lag bound testing approach. Then, forecasts were made for the period 2019-2023 with the econometric simulation method. The findings show that the Installed Capacity variable significantly and negatively affects electricity demand in all sectors in the long run. According to the forecast results made in the second stage of the study, it was observed that the higher the increase rate in the installed capacity of renewable energy sources, the faster the electricity demand would decrease. According to these results, Turkey needs to increase the share of renewable energy sources in electricity production in terms of economic and environmental sustainability.

Can financial globalization and good governance help turning emerging economies carbon neutral? Evidence from members of the BRICS-T

Since turning carbon neutral is regarded as a major macroeconomic agenda worldwide, this study examines whether financial globalization and good governance can help Brazil, Russia, India, China, South Africa, and Turkey in achieving carbon neutrality. Considering the period of analysis from 2000 to 2020 and utilizing robust econometric methods, it is observed that the environmental consequences vary across different components of financial globalization. In particular, the results validate the pollution haven hypothesis by confirming the carbon emission-boosting effect of de facto financial globalization indicators. In contrast, the pollution halo effect hypothesis is verified by the finding of the carbon emission-abating effect of de jure financial globalization indicators. Besides, promoting good governance is evidenced to impose carbon emission-mitigating impact in the long-run. The findings also authenticate the existence of the Environmental Kuznets Curve (EKC) hypothesis for the emerging countries of concern. Finally, for both the short and long runs, it is found that the non-renewable to renewable energy transition contributes to lower discharges of carbon dioxide, while urbanization results in the amplification of the carbon emission figures. Considering these critically important findings, it is necessary for these countries to impose restrictions on the influx of unclean foreign direct investment, facilitate and ease the investment process for foreign investors for investing in environment-friendly projects, promote good governance, and adopt green economic growth and sustainable urbanization policies by developing their respective renewable energy sectors.

Are the impacts of renewable energy use on load capacity factors homogeneous for developed and developing nations? Evidence from the G7 and E7 nations

Both developed and underdeveloped economies worldwide are now more concerned than ever in respect of achieving environmental sustainability. Accordingly, the majority of the global economies have ratified several environment-related pacts to facilitate the tackling of global environment-related problems. Although these problems are assumed to be addressed using diverse mechanisms, limiting the use of fossil fuels has often been recognized as the ultimate enabler of environmental sustainability. Against this backdrop, this study aims to assess the environmental impacts associated with higher renewable energy use, controlling for economic growth and population size, in the context of the G7 and E7 countries using data from 1997 to 2018. Moreover, instead of using the traditional environmental quality proxies, this study tries to proxy environmental degradation with the load capacity factor levels of the countries of concern. The long-run associations among the study's variables are confirmed by outcomes generated from the cointegration analysis. Besides, regression analysis highlighted that integrating renewable energy into the energy systems while withdrawing from the use of fossil fuels can help to improve environmental quality by increasing the load capacity factor levels. In contrast, economic growth and population size expansion are evidenced to impose environmental quality-dampening impacts by reducing the load capacity factor levels. However, the findings, in the majority of the cases, are seen to differ across the groups of the G7 and E7 countries, especially in terms of the variations in the magnitudes of marginal environmental effects over the short and long run. Lastly, the causality analysis confirms the directions of the causal relationships among the variables of concern. Based on these results, a couple of policy interventions are recommended for improving environmental quality in the G7 and E7 countries.

How effective are renewable energy, tourism, trade openness, and foreign direct investment on CO2 emissions? An EKC analysis for ASEAN countries

The effects of renewable energy, tourism, foreign direct investment, and income on environmental degradation have attracted the attention of many researchers, but to date, no researcher has examined the concurrent effects of these variables on CO₂ emissions for the Association of Southeast Asian Nations (ASEAN) countries. Motivated by this gap in the literature, this study aims to analyze the determinants of carbon dioxide (CO₂) emissions under the environmental Kuznets curve (EKC) hypothesis for six ASEAN countries. To this end, the study utilizes the panel ARDL estimator and the Dumitrescu-Hurlin panel causality test from 1995 to 2018. The results show that (i) tourism and foreign direct investment increase CO₂ emissions. (ii) Real income and trade openness reduce environmental degradation. (iii) Since the long-run income elasticity is lower than the short-run, the EKC hypothesis is valid. (iv) Renewable energy reduces carbon emissions only in the short term and has no effect on environmental quality in the long term. There is also no causal relationship between renewable energy and environmental degradation. This could be due to the ineffective deployment of renewable energy in ASEAN countries. Based on these results, this study suggests that ASEAN countries should effectively use renewable energy, reduce the amount of fossil energy in the tourism sector, and support economic development to achieve a sustainable environment.

Role of energy consumption and trade openness towards environmental sustainability in Turkey

The growth of financial services has been critical in Turkey's pursuit of economic growth objectives throughout the last two decades. Nevertheless, it cannot be denied that it has a negative impact on environmental quality. Based on this, in the current paper, the effect of energy use, trade openness, and financial development on the load capacity factor (LCF) is explored for Turkey between 1965 and 2018. In doing so, a series of quantile approaches such as quantile cointegration (QC), quantile-on-quantile regression (QQR), nonparametric causality-in-quantiles (NCQ), and quantile regression (QR) are used. The results generated from the QQR and also validated by the QR reveal that in the majority of the quantiles, primary energy use, trade openness, and financial development impact the LCF negatively. These results suggest that primary energy use, trade openness, and financial development damage environmental quality. Furthermore, the findings gathered from the quantile causality disclose that all primary energy use, trade openness, and financial development can forecast LCF in the majority of the quantiles. Based on the research outcomes, policies, which may aid to solve the damaging environmental effects of the primary energy use, trade openness, and financial sector development in Turkey are recommended.

The effect of financial globalization and natural resource rent on load capacity factor in India: an analysis using the dual adjustment approach

Currently, the most crucial economic and ecological issues are related to environmental degradation and sustainability. On this backdrop, this paper examines the impact of financial globalization and natural resource rent on load capacity factor, using the novel dual adjustment approach and time-frequency domain causality approaches, in the case of India. This study contributes to the extant body of knowledge in the area of environmental economics. First, it is the first attempt to analyze the factors responsible for load capacity factor, specifically for India. As such, studies on environmental concerns on both the supply and demand sides are put into consideration. Empirical results show that only renewable energy consumption lessens the load capacity factor, while economic growth and financial globalization are positively correlated with the load capacity factor, and natural resource rent is insignificant in the short run. In the long run, only economic growth is negatively correlated with load capacity factor, while the other series positively influence load capacity factor. To reap greater ecological merits, policymakers should focus on transitioning from conventional non-renewable energy sources that contribute to rising carbon emissions to more cost-effective and dependable renewable sources of energy that support sustainable growth and a healthy environment.

The evolution of the environmental Kuznets curve hypothesis assessment: A literature review under a critical analysis perspective

Environmental changes based on factors like urbanization, population, economic growth, increase in energy consumption, and agricultural intensification are never far from the top of any agenda. The topics of environmental degradation and climate change cannot be confined to a single country or region but need to be addressed on a global scale. If the focus is on the relationship between environmental degradation and economic growth, then one hypothesis that is comprehensively used as an empirically model is the widely known Environmental Kuznets Curve. A substantial amount of research has been published about the Environmental Kuznets Curve, and this present study provides a detailed and extensive literature review of more than 200 articles from 1998 to 2022 to explain and assess its evolution. This literature review provides in detail the Environmental Kuznets Curve relationship under analysis, the additional variables included, the type of analysis and methods performed, the relationships obtained, and if the turning point is calculated. Furthermore, this comprehensive literature points out critical issues and gaps in the Environmental Kuznets Curve analysis. It is important to note that there are components that are not considered in the Environmental Kuznets Curve analysis. The Environmental Kuznets Curve only focuses on production and overlooks the impact of the consumption of imported goods on the environment. Consequently, environmental improvements from technological progress will be offset, and economic growth will result in more environmental degradation. This goes against the change in consumer behaviour which occurs with a rise in income, which is one basic assumption of the Environmental Kuznets Curve. The relocation of pollutant industries and consequent relocation of emissions could distort the emissions trajectory over the economic growth path and is also not considered in the Environmental Kuznets Curve analysis. On the other hand, the growth path traced by the inverted U-shaped is not efficient, and the environmental damage provoked in the first phases of the EKC might not be repairable. Therefore, technological progress, climate finance, and energy transition could improve the Environmental Kuznets Curve assessment.

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A EKC literature survey of more than 200 articles from 1998 to 2022.

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Comprehensive description of the EKC evolution and its functional specification.

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Three dilemmas of the EKC are explained by the Green Solow Model.

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EKC estimation is sensitive to functional specification.

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Climate finance and technological progress could influence EKC assessment.

Assessing the influence of urbanization and energy on carbon emissions of Turkey: evidence using the new RALS analysis

This research aimed at examining the nexus among urbanization, energy use, foreign direct investment (FDI), economic growth, and environmental sustainability in Turkey. Time-series data from 1970 to 2017 were used in the analysis, and ecological footprint was used as an indicator for environmental sustainability. The aim was to investigate the long-run nexus among the indicators and contribute to the literature in several ways. One of these contributions is to empirically investigate this relationship with the residual augmented least squares (RALS) augmented Dickey-Fuller ADF for stationarity test and RALS-EG (residual augmented least squares-Engle and Granger) for the long-run steady-state relationship of investigated variables. Together with, fully modified OLS (ordinary least squares) model has been employed to observe the long-run effect and the significance of the investigated variables on environmental sustainability. The results revealed that the long-run relationship exists and the long-run coefficients show statistically significant effects on environmental sustainability. In the long run, urbanization and energy usage degrade the environment and reduce environmental quality, although FDI inflow and gross domestic product (GDP) growth contribute 0.22% and 8.03% to environmental sustainability in Turkey, respectively. The environmental Kuznets curve (EKC) hypothesis is not valid in this model and U-shaped relationship was found between increasing economic performance and the ecological footprint. The causality results reflect that urbanization has feedback causality with energy use. The study suggests that to achieve sustainable urbanization, policymakers in Turkey should execute well-planned urbanization programs, create an energy conservation policy, and encourage green industries to ensure a sustainable increase in environmental quality for Turkey.

The impact of the US interest rate and oil prices on renewable energy in Turkey: a bootstrap ARDL approach

This research investigates the spillover effect of the US interest rate and oil prices on renewable energy utilization in Turkey. By employing a novel bootstrap autoregressive distributed lag approach on annual data from 1985 to 2016, the empirical findings and discussions represent the first contribution to the energy economics literature. The findings of this research confirm that the US interest rate has a significant spillover effect on the use of renewable energy in Turkey through the channels of income and local interest rate. Due to limited foreign exchange reserves, high foreign debt, low international reserves, and devaluation of the local currency, the Turkish economy is highly intertwined with the US economy through international investment and trade. All these factors reinforce the spillover influence of the US interest rate on energy consumption in Turkey. Moreover, this study affirms that the price of oil has a negative impact on renewable energy use through the real income channel. In order for Turkey to realize its investments in renewable energy resources more reliably and sustainably, the study suggests that policymakers should revise the current economic growth model by making it more resilient to external shocks such as the US interest rate, exchange rate, and oil prices.

Towards a clean production by exploring the nexus between agricultural ecosystem and environmental degradation using novel dynamic ARDL simulations approach

Agriculture, which serves as a lifeline for us, is unequivocally vital for an agriculture-dependent economy like Bangladesh, not only for its food supply but also because of its significant contribution towards achieving Sustainable Development Goals (SDGs) 1 and 2. However, in a third-world nation like Bangladesh, where farming practices largely circumvent the environmental consequences, raised our concern. In this milieu, this study is a novel attempt to explore the association between agricultural ecosystem and environmental degradation in Bangladesh using a long time spanning from 1972 to 2018. We observed a long-run association between the agroecosystem and CO₂ emission. Further, findings from the dynamic autoregressive distributed lag (DARDL) simulation model revealed that the environmental quality of Bangladesh is heavily distorted by total cereal production, total livestock head, enteric methane emissions, N₂O emissions from manure application, and CO₂ equivalent N₂O emissions from synthetic fertilizers in the short and long run, whereas agricultural technology, pesticide use in agriculture, and burned biomass crop residue deteriorated the environmental quality only in the long run. The counterfactual diagram entailed from the DARDL model projected the trend of CO₂ emission in response to positive and negative changes in the analyzed variables. Lastly, this study established a causal relationship between the agroecosystem and environmental degradation using frequency domain causality. Indeed, our study will aid in reshaping agricultural practices in an eco-friendly manner to mitigate environmental degradation and help formulate pragmatic policy actions so that agro-lead nations can thrive in the race of achieving SDGs 1, 2, and 13.

Analyzing the Nexus Between Geopolitical Risk, Policy Uncertainty, and Tourist Arrivals: Evidence From the United States

This study attempts to explore the causal linkage of the COVID-19 pandemic, economic policy uncertainty, geopolitical risk, and tourism arrivals in the United States taking data from January to November 2020. In order to analyze the above relationship, this study uses a novel time-varying granger causality test developed by Shi et al. (2018), which incorporates its three causality algorithms such as forward recursive causality, rolling causality, and recursive evolving causality. The findings from forward recursive causality could not confirm any significant causal relationship between COVID-19 and tourism, geopolitical risk (GPR) and tourism, economic policy uncertainty and tourism, and geopolitical risk and COVID-19 but found causality between economic policy uncertainty and COVID-19. The rolling window causality reported bidirectional causality between COVID-19 and tourism and unidirectional causality running from tourism to geopolitical risk. However, the recursive evolving causality identified a significant bidirectional causal relationship between all the variables. Based on the findings, policy implications for the tourism sector are provided.

The criticality of tourism development, economic complexity, and country security on ecological footprint

What kinds of countries are likely to be prosperous and have a sustainable environment at the same time? How might countries reorient their policy setting to be more capable of suppressing environmental degradation? To explore these questions, this research examines data from 99 countries for 2006-2017, takes the six major forms of ecological footprint (EF) as indicators of environmental quality, and probes the environmental Kuznets curve (EKC) hypothesis via quantile regression approach. We find that tourism development leads to greater environmental degradation, with tourism development particularly corresponding to more usage of carbon absorption land and cropland. The lower the country security is, the better is the environmental quality. Economic complexity also worsens environmental quality. However, country security weakens the negative influence of tourism development and economic complexity on environmental quality, specifying that better country security stalls the negative impact of tourism and economic complexity on environmental quality. Results mostly support the tourism- and country security-induced EKC hypotheses in fishing footprint, whereas economic complexity-induced EKC is generally validated in cropland footprint. Finally, we present that tourism arrivals, economic complexity, and country security have varying impacts across diverse ecological footprint quantiles.