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• TVP-VAR extended joint connectedness approach employed. • Range-based volatility measures calculated over 2005–2022. • Connectedness between the agribusiness firms and agricultural commodities increases during turmoil periods. • Among the agricultural futures, coffee, cocoa, corn, and live cattle are the largest receivers of volatility. • MOS, FMC, BUN, and SMG stand as the largest volatility transmitters. This paper investigates the volatility connectedness between ten major agribusiness common stock prices and various agricultural commodity prices between August 11, 2005, and November 4, 2022. We employ the time-varying parameter vector autoregressions (TVP-VAR) extended joint connectedness framework. The results show that agribusiness stocks are net volatility transmitters, whereas agricultural commodities are net volatility receivers. The results provide significant implications for investors and policymakers concerned with commodity prices. [ABSTRACT FROM AUTHOR]

The literature has mainly relied on an annual and short span of data to analyze the relationship between energy, environmental and financial indicators. This study analyzes the relationship between energy efficiency, energy research, pollution mitigation, and FinTech by applying two novel methods-the causality test in the frequency domain [11] and the causality test in the time domain (Shi et al., 2018; 2020)- on the daily data from June 17, 2016 to November 16, 2021. Empirical results from the frequency domain test report that pollution mitigation temporarily causes energy efficiency only in the short run while energy efficiency Granger causes it in the short, medium, and long run. Furthermore, energy efficiency can predict FinTech in the short, medium, and long-run; on the other way, FinTech Granger causes energy efficiency in the long and medium run, suggesting a permanent causality relationship. Empirical results from the time-varying test show a bidirectional relationship between energy efficiency, and environmental and financial variables, especially with very high significant episodes around the recent pandemic collapse. Policymakers should promote the launch of financial technologies that will provide finance through green bonds for energy efficiency improvements as well as energy efficiency improvements for pollution mitigation. Further policy implications are discussed in the study. • The study analyzes the nexus between energy efficiency, pollution and FinTech. • The novel time-varying Granger causality test is employed. • The results show bidirectional causality among the variables during most periods. • The pandemic period is worth to focus in terms of causality checking. [ABSTRACT FROM AUTHOR]

• We analyze the impact of financial development on sustainable economic development. • We use fixed effects, the feasible generalized least squares and bootstrap panel quantile regression to capture the results. • We consider two aspects of financial development – broad money and domestic credit to private sector. • We find that financial development positively affects sustainable economic development. This paper investigates the impact of financial development on sustainable economic development (SED) in low-middle-income countries. It adopts an unbalanced panel data approach on 50 low-and middle-income countries over the period of 1991–2020. We apply Fixed Effects (FE), the Feasible Generalized Least Squares (FGLS) and Bootstrap Panel Quantile Regression to analyze the results. We find that sustainable economic development is positively affected by financial development, natural resource abundance, international tourism, trade openness and foreign direct investment. Additionally, financial development plays a positive moderating role through natural resource abundance. Foreign direct investment (FDI) also enjoys a positive moderating role through international tourism. The Bootstrap Quantile outcomes point out the diversified effects of the addressed variables at different quantiles. Accordingly, it is crucial to consider financial development alongside socioeconomic variables such as trade openness, aging population and FDI to identify and address sustainable economic development issues. [ABSTRACT FROM AUTHOR]

Although a few studies have analyzed the nexus of renewable energy and green finance, the literature lacks the use of renewable energy by sources. The other major failure is that it uses only annual and small data. Therefore, this study investigates the connectedness and spillovers relationship between green finance and five types of renewable energy (biofuels, fuel cell, geothermal, solar, and wind) by applying the novel TVP-VAR method of Balcilar et al. [1] to the daily indexes from July 31, 2014, to Feb 4, 2022. The results show that dynamic connectedness, both total and pairwise, is heterogeneous over time and influenced by economic events. Furthermore, wind is found to be the largest transmitter of shocks to green finance, followed by biofuels, while both fuel cell and geothermal receive the least shocks. The findings suggest that green finance is mostly a net receiver of shocks from renewable energy sources and that wind has been a net receiver of shocks during the COVID-19 pandemic. A high interconnectedness between the indexes highlights the safe-haven property for diversification purposes of green finance. Our results are important for energy policymakers, those responsible for the implementation of environmental policies, individual investors, and portfolio managers, while also shedding light on the achievement of COP26 goals. • The study aims to analyze the spillovers and connectedness relationship between green and renewable energy sources. • Five types of renewable energy (biofuels, fuel cell, geothermal, solar and wind) are considered. • The novel method TVP-VAR is applied on a daily data. • Dynamic connectedness is heterogenous over time. • Green finance is mostly a net receiver of shocks from renewable energy sources. [ABSTRACT FROM AUTHOR]