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    Bitcoin, Fintech, Energy Consumption, and Environmental Pollution Nexus: Chaotic Dynamics with Threshold Effects in Tail Dependence, Contagion, and Causality
    (Mdpi, 2024) Bildirici, Melike E.; Ersin, Ozgur Omer; Ucan, Yasemen
    The study investigates the nonlinear contagion, tail dependence, and Granger causality relations with TAR-TR-GARCH-copula causality methods for daily Bitcoin, Fintech, energy consumption, and CO2 emissions in addition to examining these series for entropy, long-range dependence, fractionality, complexity, chaos, and nonlinearity with a dataset spanning from 25 June 2012 to 22 June 2024. Empirical results from Shannon, R & eacute;nyi, and Tsallis entropy measures; Kolmogorov-Sinai complexity; Hurst-Mandelbrot and Lo's R/S tests; and Phillips' and Geweke and Porter-Hudak's fractionality tests confirm the presence of entropy, complexity, fractionality, and long-range dependence. Further, the largest Lyapunov exponents and Hurst exponents confirm chaos across all series. The BDS test confirms nonlinearity, and ARCH-type heteroskedasticity test results support the basis for the use of novel TAR-TR-GARCH-copula causality. The model estimation results indicate moderate to strong levels of positive and asymmetric tail dependence and contagion under distinct regimes. The novel method captures nonlinear causality dynamics from Bitcoin and Fintech to energy consumption and CO2 emissions as well as causality from energy consumption to CO2 emissions and bidirectional feedback between Bitcoin and Fintech. These findings underscore the need to take the chaotic and complex dynamics seriously in policy and decision formulation and the necessity of eco-friendly technologies for Bitcoin and Fintech.
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    Nexus between Industry 4.0 and environmental sustainability: A Fourier panel bootstrap cointegration and causality analysis
    (Elsevier Sci Ltd, 2023) Bildirici, Melike; Ersin, Ozgur Omer
    The paper aims at investigation of the nexus between Industry 4.0 (I4.0) and environmental sustainability in addition to exploring the long-run and short-run effects of Industry 4.0 on CO2 emissions. For this end, energy consumption, internet and communication technology (ICT) exports, research and development (R&D), artificial intelligence (AI), ICT technology patents and bitcoin are taken as control variables of Industry 4.0 for a panel of 9 countries that contribute to 62% of the total CO2 emissions in the world. For this purpose, the paper follows two approaches. First, the paper proposes utilization of AI and ICT technology patents, technology-related R&Ds and ICT exports as variables of I4.0 in addition to investigating the effects of economic growth, energy consumption and bitcoin. Second, to control structural changes and nonlinearity in the cointegrating relations and existence of degenerate cointegration, Fourier panel bootstrap autoregressive distributed lag model (FPBARDL) is utilized. Afterwards, FPBARDL based long, short and strong causality analyses are conducted. The empirical findings revealed positive impacts of all I4.0-related variables on emissions in the long-run. Though I4.0 related AI and ICT innovation has no direct effect in the short-run, its effects are determined through increased energy con-sumption towards emissions. The strong positive effects of energy consumption and positive effects of economic growth, ICT exports and R&D are observed both in the short and long-run. In addition to positive impacts of I4.0 on environment, the findings favor insufficiency of policies focusing on lowering emissions in I4.0 context.Policy recommendations include strong commitment to energy efficiency and renewable energies and trade policies with environmental concerns.
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    The role of environmental innovation on ecological footprint in nations with high technology exports concentrations in international trade
    (Elsevier Science Inc, 2024) Ersin, Ozgur Omer; Ustabas, Ayfer; Usman, Ojonugwa
    This study focuses on four major high-technology exporting countries--the USA, Germany, France, and China--to explore the long and short-run associations among ecological footprint, environmental technology patents, high-technology exports, and economic growth. The sample covering 1988-2019 is subject to a set of structural breaks, including 2009 Global Recession in addition to uncertainty in the order of integration captured by unit root tests, which provide basis for novel Fourier ARDL and Fourier Toda-Yamamoto causality methods. The Fourier ARDL findings reveal the importance of environmental technology innovations in dampening the level of ecological footprints and promoting a more sustainable environment in the USA, Germany, and France, whereas more high-technology exports in international trade worsen the ecological footprints in these countries in addition to the negative effects of economic growth in all countries including China. In contrast, hightechnology exports appear to mitigate ecological footprint in China, however, eco-friendly technologies fail to reduce ecological footprints as in other analysed nations. The causality tests indicate bidirectional and unidirectional causal relationships among variables with the exception of China where the neutrality hypothesis holds between economic growth and ecological patents and also high-technology exports and ecological patents. These findings provide important insights in achieving sustainable development.