How financial development scale and R&D influence regional innovation efficiency: empirical evidence from the financial industry

Financial elements and R&D elements are significant drivers for enhancing regional innovation efficiency. This paper measures financial elements by financial development scale and the marketization level of the financial industry and R&D elements by the inputs and flow of R&D personnel and R&D capital and specifically considers R&D element flow to quantify the consequential spatial spillover effects. Based on provincial panel data from 2008 to 2018, the paper firstly estimates the regional innovation efficiency of China's 30 provincial-level administrative regions using super-efficiency DEA and then conducts an empirical analysis of the influence of financial elements and R&D elements on regional innovation efficiency by the use of the Tobit model and three spatial econometric models. It is found that, by and large, the financial development scale, the marketization level of the financial industry, the inputs of R&D personnel and R&D capital, and R&D capital flow all have significant effects on regional innovation efficiency. Nonetheless, by region, R&D personnel flow in central China can significantly boost regional innovation efficiency while fails in eastern and western China. From the spatial perspective, both financial elements and R&D elements have significant positive spatial spillover effects. Therefore, in order to bolster regional innovation efficiency, it is crucial to improve the allocation of financial elements and R&D elements and build a tight regional collaborative innovation network.

How COVID-19 induced panic on stock price and green finance markets: global economic recovery nexus from volatility dynamics

This paper investigates the effect of different categories of essential COVID-19 data from 2020 to 2021 towards stock price dynamics and options markets. It applied the hypothetical method in which investors develop depression based on the understanding suggested by various green finance divisions. Furthermore, additional elements like panic, sentiment, and social networking sites may impact the attitude, size, and direction of green finance, subsequently impacting the security prices. We created new emotion proxies based on five groups of information, namely COVID-19, marketplace, lockdown, banking sector, and government relief using Google search data. The results show that (1) if the proportional number of traders' conduct exceeds the stock market, the effect of sentimentality indexes on jump volatility is expected to change; (2) the volatility index component jump radically increases with the COVID-19 index, city and market lockdown index, and banking index; and (3) expanding the COVID-19 index gives rise to the stock market index. Moreover, all indexes decreased in jump volatility but only after 5 days. These findings comply with the hypotheses proposed by our model.

Globalization, renewable energy consumption, and agricultural production impacts on ecological footprint in emerging countries: using quantile regression approach

Nowadays, paying attention to globalization and the consumption of renewable energy on the ecological footprint is one of the most important issues in the world. In the age of globalization, all countries are trying to prevent the spread of ecological degradation by enacting laws and regulations at the national level and regulating international agreements. This study investigates the effect of explanatory variables of globalization, renewable energy consumption, and agricultural production on the ecological footprint in emerging countries using fixed-effect panel quantile regression of 10th, 25th, 50th, 75th, and 90th in the period 2002 to 2016. The results showed that the consumption of renewable energy at all levels except the 25th quantile has a positive and significant effect on the ecological footprint; this effect is more in higher quantiles. Globalization in all quantiles has a negative and significant impact on the ecological footprint and has had the most excellent effect among other explanatory variables. Agricultural production variable at the 25th and 50th quantile levels had the most significant and positive effect on the ecological footprint. Therefore, it can be concluded that the increase in agricultural production, income, renewable energy consumption, population, and trade openness can lead to increased environmental degradation. However, the effects of globalization have had the most negligible negative impact on the ecological footprint.

Exploring the role of finance, natural resources, and governance on the environment and economic growth in South Asian countries

We studied the influence of finance, natural resources, and governance on environmental degradation and economic growth for seven countries of the South Asian Association for Regional Cooperation (SAARC) using the latest panel data over 1996-2018. Panel cointegration tests and the long-run algorithms capable of addressing endogeneity and cross-sectional dependence have been applied to analyze the variables' linkages. To explore the short-run causalities, we further utilized a panel heterogeneous causality test. Empirical estimates concluded that there is a mediating role of finance and governance on improving environmental quality and have a significant positive impression on the economic growth of the SAARC countries. The results supported the natural resources curse theory and substantially contributed to environmental emissions in the study area. The causal results concluded the unilateral causality from the environment to governance and bidirectional causality between finance and environmental degradation. Similarly, there were unilateral causal linkages between economic growth and natural resources, where links are bidirectional between natural resources and environmental degradation for SAARC countries. Based on the outcomes of the study, some policy implications are provided for theory and practice.