Yazar "Bildirici, Melike E." seçeneğine göre listele

Listeleniyor 1 - 5 / 5
  • Küçük Resim
    Öğe
    Are cleaner energy and financial technologies needed? Contagion and causality evidence between global fintech markets, energy consumption, and environmental pollution
    (Springer Science and Business Media Deutschland GmbH, 2024) Ersin, Özgür Ömer; Bildirici, Melike E.
    Financial technology (FinTech) depends on high amounts of energy with an upward trend, possibly affecting emissions due to energy consumption (EC). The study investigates tail dependence, contagion, and nonlinear between FinTech, EC, and carbon dioxide emissions (CO2e) with MS-GARCH-copula and MS-GARCH-copula-causality with a daily sample covering 02 Jan 2012–28 December 2022. The method is a generalized version of single-regime GARCH-copula and causality tests to Markov-switching. Empirical results indicated that FinTech, EC, and CO2e series follow nonlinear processes in addition to unit roots as determined by BDS nonlinearity tests and a set of linear and nonlinear unit root tests. Further, for all series, heteroskedasticity and nonlinear forms of heteroskedasticity cannot be rejected by ARCH–LM and White heteroskedasticity tests, leading to the estimation of the series and their joint dynamics by MS-GARCH-copula and a new MS-GARCH-copula based nonlinear Granger-causality test, the RSGCC test, under two distinct regimes characterized with the low and high volatility for extreme tails of data. Positivity and significance of copula parameters under both regimes indicate a high degree of positive but asymmetric tail dependence and contagion between FinTech & EC, in addition to contagion between FinTech & CO2e and EC & CO2e. RSGCC results determine unidirectional causalities from EC to CO2e and from FinTech to CO2e, coupled with bidirectional causality between FinTech and EC, which enhance the dynamics due to feedback effects. The findings of this paper are of importance for two central Sustainable Development Goals. Results could also be used to bring the FinTech markets and EC to the attention of policymakers, researchers, and eco-friendliness-focused portfolio managers. Graphical Abstract: (Figure presented.)
  • Küçük Resim Yok
    Öğe
    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.
  • Küçük Resim
    Öğe
    Cement production and CO2 emission cycles in the USA: evidence from MS-ARDL and MS-VARDL causality methods with century-long data
    (Springer, 2024) Bildirici, Melike E.; Ersin, Özgür Ömer
    The cement industry is among the top three polluters among all industries and the examination of the nonlinear and cointegration dynamics between cement production and CO2 emissions has not been explored. Focusing on this research gap, the study employs a novel Markov-switching autoregressive distributed lag (MS-ARDL) model and its generalization to vector error correction, the MS-VARDL model, for regime-dependent causality testing. The new method allows the determination of nonlinear long-run and short-run relations, regime duration, and cement-induced-CO2 emission cycles in the USA for a historically long dataset covering 1900–2021. Empirical findings point to nonlinearity in all series and nonlinear cointegration between cement production and cement-induced CO2 emissions. The phases of regimes coincide closely with NBER’s official economic cycles for the USA. The second regime, characterized by expansions, lasts twice as long relative to the first, the contractionary regime, which contains severe economic recessions, as well as economic crises, the 1929 Great Depression, the 1973 Oil Crisis, the 2009 Great Recession, and the COVID-19 Shutdown and Wars, including WWI and II. In both regimes, the adverse effects of cement production on CO2 emissions cannot be rejected with varying degrees both in the long and the short run. Markov regime-switching vector autoregressive distributed lag (MS-VARDL) causality tests confirm unidirectional causality from cement production to CO2 emissions in both regimes. The traditional Granger causality test produces an over-acceptance of causality in a discussed set of cases. Industry-level policy recommendations include investments to help with the shift to green kiln technologies and energy efficiency. National-level policies on renewable energy and carbon capture are also vital considering the energy consumption of cement production.
  • Küçük Resim
    Öğe
    Long and short-run impacts of CEO narcissism on the nexus between financial performance and environmental and social governance: Evidence from new quantile-based panel cointegration and causality techniques
    (Elsevier, 2024) Bildirici, Melike E.; Ersin, Özgür Ömer; Fidan, Selahaddin Şamil
    This study investigates the crucial but understudied relationship between chief executive officer (CEO) narcissism, and environmental, social, and governance (ESG) performance in addition to the effects of financial performance. The study examines the nexus for their long-run and short-run associations and for quantile-specific effects including causality linkages that were governed by different levels of CEO narcissism for a sample of 55 energy companies from the United States for the 2003–2022 period. Novel Panel Autoregressive Distributed Lag and Panel Quantile Granger Causality methods are employed to encounter two modeling strategies. The model utilizes two newly proposed proxy variables for measuring CEO narcissism, namely, Policy Bribery and Corruption Scores (BC), and, Audit Fees (AF). Empirical findings with all CEO narcissism measures under different modeling strategies indicated positive and significant effects of CEO narcissism on ESG for all quantiles in the long run asymmetrically from the lowest levels towards higher levels of CEO narcissism with varying but positive magnitudes with an exception: at the highest quantile, the effect on ESG performances becomes reversed, indicating very high levels of CEO narcissism harming ESG performances. The short-run results also confirm these relations, confirming the effects of CEO narcissism at different levels with varying magnitudes. Quantile-specific causality tests determined causality from CEO narcissism to ESG performance in all quantiles without exception across different scenarios. Between financial performance and ESG there is a unidirectional causality from financial to ESG variables in 2nd, 4th and 5th, and, bidirectional causality at the 1st quantile. Further, CEO narcissism is the Granger-cause of financial performance in all quantiles. The new CEO narcissism variables are compared and tested statistically for robustness with traditional CEO narcissism measures of Chatterjee and Hambrick (2007, 2011). The findings of the proposed model and new CEO narcissism variables capture the dynamic changes in CEO narcissism in time and at different levels more effectively than the traditional CEO narcissism measure. The fresh finding led to a set of policy recommendations.
  • Küçük Resim
    Öğe
    Nonlinear contagion and causality nexus between oil, gold, vıx ınvestor sentiment, exchange rate and stock market returns: the ms-garch copula causality method
    (MDPI, 2022) Bildirici, Melike E.; Salman, Memet; Ersin, Özgür Ömer
    The fluctuations in oil have strong implications on many financial assets not to mention its relationship with gold prices, exchange rates, stock markets, and investor sentiment. Recent evidence suggests nonlinear contagion among the factors stated above with bivariate or trivariate settings and a throughout investigation of contagion and causality links by taking especially nonlinearity into consideration deserves special importance for the relevant literature. For this purpose, the paper explores the Markov switching generalized autoregressive conditional heteroskedasticity copula (MS-GARCH—copula) and MS-GARCH-copula-causality method and its statistical properties. The methods incorporate regime switching and causality analyses in addition to modeling nonlinearity in conditional volatility. For a sample covering daily observations for 4 January 2000–13 March 2020, the empirical findings revealed that: i. the incorporation of MS type nonlinearity to copula analysis provides important information, ii. the new method helps in the determination of regime-dependent tail dependence among oil, VIX, gold, exchange rates, and BIST stock market returns, in addition to determining the direction of causality in those regimes, iii. important policy implications are derived with the proposed methods given the distinction between high and low volatility regimes leads to different solutions on the direction of causality.