Financial development, international trade, and environmental degradation: a nonlinear threshold model based on panel smooth transition regression

Khaskheli, Asadullah; Jiang, Yushi; Raza, Syed Ali; Khan, Komal Akram; Qureshi, Muhammad Asif

doi:10.1007/s11356-020-11912-8

Cited by 30 publications

(16 citation statements)

References 62 publications

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“…Trade of services exports is a strong predictor for CO 2 emission in China (R 2 = 0.82), South Korea (R 2 = 0.69), Singapore (R 2 = 0.75) and the United States (R 2 = 0.93), while it is a weak predictor in Latin American countries (R 2 = 0.22). Results of regression are similar to the study by (Wang et al, 2019) where a direct positive relationship A study by (Khaskheli et al, 2021) indicated a similar results pattern in low-income countries by using the panel smooth transition regression model. This study result confirmed that the nexus between the variables is nonlinear.…”

Section: Resultssupporting

confidence: 82%

The Nexus Between CO2 Emission, Economic Growth, Trade Openness: Evidences From Middle-Income Trap Countries

Galvan

Bhatti²,

Campo³

et al. 2022

Front. Environ. Sci.

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In recent years, the carbon dioxide emissions generated by the massive consumption of fossil energy have been increasing year by year, resulting in more and more obvious greenhouse effect, and the occurrence of climate disasters around the world has become more and more frequent. This study analyses the long-term effects of economic growth, trade, foreign direct investment (FDI) and gross domestic product (GDP) on carbon dioxide (CO2) emissions in Latin American countries that are in the middle-income trap (MIT). Using annual time-series data for the period 2000–2020, the results of middle-income countries of Latin America are compared with higher-income countries (Singapore, the United States, and South Korea) and an upper-middle-income country, China. Specifically, we examine the role of sector value addition to GDP on the CO2 emission nexus for middle-income economies, controlling for the effects on GDP, FDI, and trade. Using regression and path analysis (multiple regression) we find that for higher-income countries FDI, GDP and trade are the important variables that have a strong positive impact on CO2 emission, but that positive impact is weak in MIT countries, which makes this study significant as it highlights important variables needed for MIT countries to remain focused. Autoregressive distributed lag (ARDL) model results also explore that FDI, GDP growth and trade variables can significantly accelerate the environmental quality by CO2 emission, while tourism/travel services and education do not much impact the environment. Hence, our paper provides solid ground for developing a sustainable and pro-growth policy for MIT countries because they are plagued by the decline or stagnation of economic growth.

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Section: Resultssupporting

confidence: 82%

The Nexus Between CO2 Emission, Economic Growth, Trade Openness: Evidences From Middle-Income Trap Countries

Galvan

Bhatti²,

Campo³

et al. 2022

Front. Environ. Sci.

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“…Foreign direct investment has no effect on pollution (Wang et al, 2020 ; Nasir et al, 2019 ), a negative effect on pollution in HICs but a positive effect in developing countries (Khalil & Inam, 2006 ; Lau et al, 2018 ), a U-shaped effect in HICs (Christoforidis & Katrakilidis, 2021 ), a negative effect in both developed and developing countries (Essandoh et al, 2020 ), a negative effect only in developing countries (Pradhan, 2021 ), or a negative effect only in LMICs (Nguyen et al, 2020 ). Financial development reduces CO 2 emissions in HICs (Khaskheli et al, 2021 ) but increases emissions in LMICs and UMICs (Ehigiamusoe & Lean, 2019 ; Nasir et al, 2021 ; Thampanya et al, 2021 ), reduces CO 2 emissions in HICs, UMICs, and LMICs (Godil et al, 2020 ; Neog & Yadava, 2020 ), has no effect on pollution for HICs but has a negative effect on pollution in UMICs and LMICs (Di Vita, 2008 ), or has no effect on pollution for all cases (Katircioğlu, 2012; Öztürk & Acaravcı, 2013 ).…”

Section: Explaining the Macroeconomic Governance–pollution Nexusmentioning

confidence: 99%

“…For low- and lower-middle-income countries, population diversity is a small driver of CO2 emissions 44 Dong et al (2020) 130 countries (1997–2015) -CO 2 emissions from fuel combustion, GDP Decomposition (identity) analysis UMI countries are the main contributors to recent CO 2 emission growth For the last two decades, while income increase had positively affected global CO 2 growth, declining energy intensity had a mitigating effect 45 Abban et al ( 2020 ) 44 Countries, 16 low- and lower middle-income countries (1995–2015) CO2 emission, GDP per capita, GDP squared, EI (kilograms of oil equivalent), FDI inflows Westerlund–Edgerton cointegration, AMG estimation EKC is only confirmed in HICs. Bidirectional causal effect between CO 2 and FDI Except LMICs, there is a bidirectional relation among EI and CO2 emissions For LMICs, there is a one-way causal effect from CO 2 to EI, and bidirectional relation among GDP and CO2 emissions Unidirectional causal effect from GDP to CO 2 emissions in HICs and LICs 46 Khaskheli et al ( 2021 ) 19 Low-income countries (1990–2016) Environmental degradation is estimated by CO 2 emissions, Private credit by banks as a percentage of GDP, GDP per capita, International trade percentage of GDP, population Panel smooth transition regression model (PSTR) The environmental measures of low-income countries are nonexistent. However, the implementation of measures mitigates environmental quality by decreasing CO 2 emissions FD has a positive relation with CO 2 in low regimes; however, on higher regimes effect turns in to negative GDP, international trade, and population has a positive effect on CO 2 ; however, in higher regimes, it has a diminishing effect 47 Alola and Joshua ( 2020 ) 217 countries with low, lower middle, upper middle and high income (1970–2014) Renewable energy, fossil fuel, globalization, CO 2 emission Panel pooled mean group and Granger causality Fossil fuel energy usage is the leading cause for increased carbon emissions in each of the included income groups ...…”

Section: Appendixmentioning

confidence: 99%

Why are some countries cleaner than others? New evidence from macroeconomic governance

Akan

Gündüz

Vanlı

et al. 2022

Environ Dev Sustain

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This study aims to investigate why some countries are cleaner than the others with reference to macroeconomic governance (MEG) in order to explain how major macroeconomic aggregates should be governed to mitigate environmental pollution at the level of economic systems. Using per capita carbon dioxide emissions (CPC) as the proxy for air pollution, and macro-non-financial governance (MNFG) and macro-financial governance (MFG) as the proxies for MEG, the study introduces the systemic and fragmented governance of green complementarities (GCMs) and dirty complementarities (DCMs) as analytic concepts to compare the MEG models for managing pollution in 13 high-income countries (HICs), 10 upper-middle-income countries (UMICs), and nine lower-middle-income countries (LMICs) for the period 1994–2014. The paper concludes that (i) HICs reduced their CPC levels thanks to adopting green systemic governance by creating GCMs between both MNFG and MFG variables in the long run; (ii) UMICs experienced a remarkable increase in their CPC levels due to adopting dirty systemic governance by creating DCMs between the MNFG variables, but prevented pollution from being higher through creating GCMs between the MFG variables; and (iii) LMICs experienced the highest comparative increase in CPC due to adopting a fragmented governance in managing both MNFG–pollution and MFG–pollution nexus.

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“…ere is an objective risk in the exchange rate transactions of international trade goods. erefore, to reduce the loss caused by the objective risk, it is necessary to consider the degree of risk exposure in the exchange rate transactions of international trade goods [25,26]. e risks involved in the exchange rate transactions of goods in international trade are difficult to control and will increase.…”

Section: Calculation Of Exchange Rate Transaction Risk Of Goods In International Tradementioning

confidence: 99%

Exchange Rate Transaction of International Trade Goods Based on Fuzzy Granulation and Deep Learning

Jin¹,

Han

2021

Scientific Programming

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The change of international trade goods exchange rate transaction has an impact on economic operations and economic stability. Therefore, an international trade goods exchange rate transaction based on fuzzy granulation and in-depth learning is proposed. Based on fuzzy information granulation and BP neural network, this paper analyzes the interest rate evaluation theory. For the future expectation of currency exchange rate, portfolio equilibrium determines the proportional relationship of each component in the portfolio and analyzes the impact of asset price and exchange rate change according to this relationship. Then, it points out the risk evaluation index system, calculates the risk degree of exchange rate transaction of international trade goods, and then evaluates the risk of exchange rate transaction of international trade goods. It completes the research on exchange rate transactions of international trade goods based on fuzzy granulation and in-depth learning. The experimental results show that excessive exchange rate fluctuation will bring the same proportion fluctuation to the asset price in the financial market, and the coordination between exchange rates and the coordination of exchange rate and asset price can promote the steady growth of national economy.

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Financial development, international trade, and environmental degradation: a nonlinear threshold model based on panel smooth transition regression

Cited by 30 publications

References 62 publications

The Nexus Between CO2 Emission, Economic Growth, Trade Openness: Evidences From Middle-Income Trap Countries

The Nexus Between CO2 Emission, Economic Growth, Trade Openness: Evidences From Middle-Income Trap Countries

Why are some countries cleaner than others? New evidence from macroeconomic governance

Exchange Rate Transaction of International Trade Goods Based on Fuzzy Granulation and Deep Learning

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