Examining the behavior of renewable‐energy fund investors

Mutual fund investors could contribute to sustainable development by encouraging fund managers to channel their savings into the funding of sustainable energy projects adopted by firms. This study examines whether renewable‐energy investors take into account financial and/or nonfinancial factors when making the decision to invest in a specific fund, comparing their investment behavior with that of black‐energy and conventional investors. To this end, we have gathered information about 4,368 mutual funds (76 renewable‐energy funds, 109 black‐energy funds, and 4,183 conventional mutual funds) from January 2007 to December 2017. For this sample, we adopt a panel‐data approach with Petersen's standard errors clustered by fund and year. Our results indicate that renewable‐energy fund investors are less sensitive to past financial performance than are black‐energy and conventional fund investors, indicating that the former derive their utility from nonfinancial attributes whereas black‐energy investors derive their utility from a conditional multiattribute and conventional fund investors derive their utility from financial attributes.     

IPO performance of portfolio ventures funded by impact investors versus venture capital investors

With the global rise of impact investments to achieve societal goals, an increasing number of new ventures that aim to create societal impact now seek to go public. However, while many conceptual studies suggest that impact investors are less likely to pursue financially oriented exit plans in exchange for generating societal impact, there is little empirical evidence to back up this claim. Using a propensity score matching approach, we draw on data from Crunchbase and empirically compare the initial public offering (IPO) performance of a large sample of 3398 investments by impact investors with 3398 investments by matched venture capital (VC) investors. We find that impact investor investments are less likely to lead to an IPO than VC investments. Besides, our results indicate that syndication by impact investors increases the likelihood of an IPO. This suggests that companies funded by impact investors benefit more from syndication than their VC-funded counterparts. Our findings have practical implications for impact investors, portfolio ventures, and policymakers.     

Time-frequency causality and dependence structure between crude oil,EPU and Chinese industry stock: Evidence from multiscale quantile perspectives

This article investigates the time-frequency causality and dependence structure of Chinese industry stock returns on crude oil shocks and China's economic policy uncertainty (EPU) across quantiles over the period from January 2001 to June 2021. We use wavelet-based decomposition series to establish a multiscale causality-in-quantiles test and a quantile-on-quantile regression approach to reveal the complicated relationships involving crude oil, EPU and stock returns. Our empirical results are as follows: First, the predictability of crude oil and EPU on industry stock returns is significantly strong under extreme market conditions. Second, the explanatory ability of EPU on industry stock returns in the long term is stronger than EPU’s ability to explain short term returns. Third, the impacts of crude oil and EPU on industry stock returns remain remarkably asymmetric across quantile levels. Finally, nonenergy-intensive industries are also affected by crude oil shocks, but less than energy-intensive industries. Overall, these empirical findings can provide implications for policymakers to stabilize stock markets and investors to hedge the potential risks from crude oil and EPU.     

The path to renewable energy consumption in the European Union through drivers and barriers: A panel vector autoregressive approach

Renewable energy consumption brings sustainable economic growth and pollution reduction. Despite the worldwide increase in renewable energy consumption, global energy-related carbon dioxide emissions are rising and there are still considerable differences in the share of renewable energy consumption in national energy portfolios. These concerns require further effort at the policy level, especially by countries that make extensive use of energy imports. These countries could improve their lack of energy independence by using renewable energy sources and leveraging a few factors to facilitate their transition. This study aims to investigate renewable energy consumption drivers, focusing on the role of socio-technical (rather than economic) aspects such as policy stringency, lobbying, public awareness, and education. We employ a panel vector autoregressive model in first differences to test the complex dynamic relationships among renewable energy consumption, policy stringency, lobbying, public awareness, and education, controlling for variables such as per capita income and import levels, for 12 European Union net energy importing countries. Results show that the positive income effect prevails in the influence of the level of carbon dioxide emissions (negative) on renewable energy consumption, despite the latter being more significant in countries with higher levels of education. Increasing energy needs push traditional sources towards complementarity with renewable energy consumption, implying a positive lobbying effect. Public awareness is not enough to facilitate the transition to renewable energy consumption. By contrast, policy stringency has positive direct and indirect effects on renewable energy consumption, suggesting that the approach adopted by the European Commission in the recent Green Deal is a step in the right direction. Moreover, as shown, policymakers are able, through renewable energy consumption, to generate a decrease in carbon dioxide emissions and electricity production from oil, gas, coal, and nuclear sources in the first instance, but also in net energy imports, even if at a later stage.     

MODELING THE NEXUS BETWEEN SUSTAINABLE DEVELOPMENT AND RENEWABLE ENERGY: THE AFRICAN PERSPECTIVES

Motivated by the gained momentum of the sustainable development goals (SDGs) under the umbrella of the United Nations organization, in the light of the SDG‐7, which stipulates the access to affordable, sustainable, and modern energy, this paper explores the dynamic relationship between renewable energy and the pillars of sustainable development. Its insights are driven using a simultaneous equation model based on a panel of 25 African economies covering the period 1990–2014. The results show that renewable energy is important for sustainable development and that higher levels of renewable energy can increase sustainability. The findings also confirm the positive influence of renewable energy on the economic, environmental, social, and institutional dimensions. These positive effects stem from investment in clean energy in the whole of Africa, combined with structural changes promoting the use of clean energy and the achievement of the millennium development goals. The findings should be useful for policymakers in Africa. Aggressive renewable energy policies will be crucial for achieving energy‐policy goals and the “multiple benefits” of renewable energy, such as reducing climate change and air pollution, improving energy security, and increasing access to energy.     

Explanatory analysis of the key factors in an energy sustainability index

The need to reduce the emissions of greenhouse gases in energy generation has led to international and national bodies recommending and encouraging a series of policies and measures to boost so-called green energy generation and achieve sustainability in the energy sector. In order to assess the energy sustainability path of countries worldwide, we first propose a dynamic analysis of an energy sustainability index (ESI) based on the methodology of composite indicators built on a large dataset of 136 heterogeneous countries and 38 variables observed in 3 years (2000, 2005 and 2011). Second, to isolate the influence of socio-demographic and economic characteristics on the energy sustainability of countries, we perform quantile regression with clustered data. Our findings demonstrate that major changes are required in developing countries, where development is pursued mainly through the use of energy sources based on fossil fuels. To ensure access to sustainable energy, policy makers need to consider and improve the key factors according to the ESI’s quantiles. In particular, human development variables (i.e., life expectancy and the percentage of completed secondary schooling attained in the population) and the variables related to civil rights and institutions (e.g., percentage of women in national parliaments) are crucial in promoting energy sustainability. By contrast, high unemployment rates, high congestion costs and the continued use of highly polluting energy sources have the effect of reducing energy sustainability.     

Spillover analysis across FinTech,ESG, and renewable energy indices before and during the Russia–Ukraine war: International evidence

This study is epicentral to analyze the impact of the Russia–Ukraine war on the financial markets, specifically focusing on the connectedness and spillover dynamics of FinTech, Environmental, Social, and Governance (ESG), renewable energy, gold, and Morgan Stanley Capital International (MSCI) indices in developed and emerging countries. Data are collected from Thomson Reuters, ranging from May 8, 2020, to May 11, 2022, and a time-varying parameter vector autoregression (TVP-VAR) and the dynamic conditional correlation (DCC) generalized autoregressive conditional heteroskedasticity (GARCH) t-Copula (DCC-GARCH t-Copula) are used to analyze the data. The results show that FinTech, ESG, and MSCI are net transmitters in developed countries, whereas gold and renewable energy are net receivers pre- and during war periods. ESG and MSCI are net transmitters in emerging countries, while FinTech, renewable energy, and gold become net receivers in both periods. The hedging ratio sheds light on the costs and weights of efficient pair investments that might change in the context of each region and under the combined scenario. The study has important implications for merchant bankers, policymakers, investors, hedgers, and risk managers.     

Venture Capital Investments in Europe and Portfolio Firms' Economic Performance: Independent Versus Corporate Investors

Using a new European Commission‐sponsored longitudinal dataset—the VICO dataset—we assess the impact of independent (IVC) and corporate venture capital (CVC) investments on the economic performance of European high‐tech entrepreneurial firms during the period 1992–2010. After controlling for potential sources of endogeneity and selection bias, our results indicate that both IVC and CVC investments boost portfolio firms' economic performance. These effects are mostly due to an increase in real sales value. Moreover, the dynamics of the impact of VC investments on firms’ overall economic performance and its components—real sales value, real fixed assets, and real labor costs—differs depending on the type of investor. Finally, we do not detect any impact related to the syndication of investments by both IVC and CVC investors.     

The role of mutual funds in the sustainable energy sector

The integration of renewable energy criteria in mutual fund investment decisions could channel private resources into the funding of environmentally related projects implemented by firms contributing to sustainable development. This paper examines the performance of European renewable energy funds that invest globally by comparing their risk‐adjusted returns with those achieved by black energy and conventional mutual funds. It uses Carhart's model on a sample of 81 renewable energy funds, 125 black energy funds, and 4,337 conventional mutual funds. The results indicate that 32.1% of renewable mutual funds—most of which adopt energy producers, renewable energy technology, and energy efficiency‐focused criteria—perform significantly better than the S&P Clean Energy market benchmark, this percentage being affected by the different states of the economy. However, none of them are able to beat the fossil fuel energy (S&P Global 1200 Energy Index) or conventional market benchmarks (S&P Global 1200 Index). Furthermore, 37.04% of renewable energy funds significantly underperform the S&P Global 1200 benchmark. Therefore, the investment in renewable energy funds has a financial cost for investors in relation to conventional fund investors.     

On the optimal accumulation of renewable energy generation capacity

As fossil fuels are finite and responsible for environmental problems, renewables have been promoted in recent decades. To study the optimal accumulation of a generation capacity for renewable energy (backstop) and the trade-off between capital investments, backstop capacity investments and consumption, we develop a capital-energy economy with exhaustible fossil fuels. It turns out that optimal economic evolution and, therefore, the steady-state levels of capital, backstop capacity, and consumption depend on the capital endowment and the time preference rate. If the latter is low and the former is high, an intertemporal consumption trade-off renders the accumulation of an excess capacity optimal. In contrast, given a low capital endowment and a high time preference rate, the trade-off is not beneficial, so that capacity investments are nil for all points of time.     

Measuring systemic risk of the Chinese banking industry: A wavelet-based quantile regression approach

In systemic risk measure, a large amount of literature has emerged, but few of them take into account the multi-scale natures of financial data. Considering these natures, we develop a novel W-QR-CoVaR method to measure systemic risk. To be specific, the W-QR-CoVaR method combines the wavelet multiresolution analysis (MRA) with the conditional value-at-risk (CoVaR) method based on the quantile regression (QR) framework. We then apply it to measure the systemic risk in the Chinese banking industry covering the period from September 2007 to September 2018. Our experiment results show that the hybrid W-QR-CoVaR method performs better than the traditional CoVaR method in terms of predictive accuracy. Furthermore, we also explore the relation between the systemic risk contribution of each individual bank and the bank-specific characteristics. Size and leverage appear to be the most robustness determinants. The findings suggest that regulators should pay more attention to the banks with smaller size and higher leverage.     

Leadership change and shareholder value: How markets react to the appointments of women

This study examines whether the appointment of women into senior leadership positions has a more positive effect on share price than the appointment of men into equivalent positions. Our dependent variable is the degree of change in share price following the announcement of men and women into senior leadership positions. Although market reactions to corporate events represent a complex process, we argue that changes in stock price represent a barometer for how investors assess the decision's potential effect on a corporation's short‐ and long‐term economic viability. We find a significant spike in stock price following the announcement of women into top leadership positions. The size and direction of change in stock price, however, is moderated by the gender composition of the industry. © 2011 Wiley Periodicals, Inc.     

人力资本与产业结构转化对经济增长的效应分析

本文根据两部门经济增长模型,以1995~2009年中国29个省际数据为对象,运用分位数回归的方法考察了人力资本、产业结构对中国经济增长的影响。理论分析和实证研究均表明：人力资本对经济增长有显著的促进作用,且在条件分布的不同位置,这种作用存在明显差异;产业结构从传统产业向现代产业的转化也是经济增长的重要推动力;人力资本的经济增长效应受产业结构的影响,与人力资本相适应的产业结构转化可以优化人力资本的配置,提高人力资本的产出效率,有助于经济持续、快速地增长。     

中国能源结构低碳化转型的政策分析

本文构建了中国能源-经济社会核算矩阵,使用SAM账户乘数分析方法探讨可再生能源电力产业在经济结构中的特征,部门扩张对其他经济部门的影响.同时利用SAM价格乘数研究不同的能源价格政策对经济系统的影响,结果表明政府采用对煤炭收取碳税的同时,对可再生能源电力产业进行补贴的价格政策是有效的.可再生能源电力产业的发展对经济结构的优化和能源结构低碳化转型有着积极作用,并能够降低成本推动型通货膨胀的发生风险.     

A multi-criteria expert decision system for investment decisions: The case of commercial real estate investments in China

Consistent with the rapid growth of the Chinese economy and its commercial real estate (CRE) market, evaluating CRE investments in China is becoming an important application area where a multi-criteria expert decision system can make a significant contribution. We used a multi-criteria expert decision system to evaluate ten actual CRE investments in China. Based on thirty-one industry experts, we identified key decision factors to consider when evaluating different CRE investment projects and determined their importance weights. We then evaluated whether or not the ten CRE investment projects were considered to be successful, taking into account the unique characteristics of each CRE investment project. We finally compared the evaluations for the ten cases with their actual performance using four different performance indicators. The results showed that the evaluations had at least 87.5% accuracy across four different performance indicators. As probably one of the first systematic and in-depth scholarly studies to evaluate CRE investment projects in China, this study contributes to a better understanding of such evaluations and helps CRE investors evaluate CRE investment projects in a more informed fashion.     

Searching hedging instruments against diverse global risks and uncertainties

We evaluate the influence of five major risk and uncertainty factors on four asset classes. Our time-varying findings suggest that each asset hedges only a particular uncertainty factor, whereas gold does more than one factor, especially during COVID-19. Our frequency-based quantile regression (QR) results show that in the raw frequency, gold and Islamic stock can better hedge various uncertainty factors than Bitcoin and crude oil, depending on the market conditions. Additionally, using the frequency bands (e.g., short, medium, and long term) data, we further notice that, depending on the market circumstances and investment horizons, gold and Islamic stock returns are still better hedges for the various risks and uncertainties than Bitcoin and crude oil returns. Our findings have crucial risk and portfolio management implications for investors, portfolio managers, and policymakers.     

Happiness sentiments and the prediction of cross-border country exchange-traded fund returns

This research examines whether social media (Twitter) happiness sentiment and country-level happiness sentiment indices predict cross-border ETF returns. To account for complicated associations between happiness sentiment and ETF returns, we use a quantile regression approach and find that Twitter and trading market (U.S.) happiness sentiments are strong predictors of future ETF returns, for which both have far greater predictive power than those of their home countries. Home country happiness indices exhibit asymmetric impacts across quantiles, suggesting the importance of trading country (U.S.) and Twitter happiness sentiments. Higher U.S. and home countries’ freedom to make life choices, absence of corruption perception, and confidence in national government precede higher ETF returns, while U.S. GDP, social support, health life expectancy, positive affect, and negative affect precede lower (abnormal) returns. We find that higher return quantile country ETFs provide a safe haven for U.S. investors during a U.S. bear market.     

Twitter’s daily happiness sentiment,economic policy uncertainty,and stock index fluctuations

This research applies quantile Granger causality and impulse-response analyses to evaluate the causal linkages among Twitter’s daily happiness sentiment, economic policy uncertainty (EPU), and S&P 500 indices across the U.S. stock market cycles. We present notable evidence of bi-directional causality among cyclical components of Twitter’s daily happiness sentiment, economic policy uncertainty, and S&P 500 indices for most quantiles. The causal linkage of Twitter’s daily happiness sentiment and S&P 500 indices identified in this study reconciles the so-called Easterlin Paradox and Easterlin Illusion arguments from previous studies on income-happiness relationship. Moreover, given a high (low) EPU level, the positive (negative) impulse-response effects between the Twitter’s daily happiness sentiment and the S&P 500 indices are justified during a stock market bust cycle, but the signs of these correlations change to negative (positive) during a stock market boom cycle. These findings imply that investors’ hedging strategies can be linked to the surveillance of the Twitter’s daily happiness sentiment index.     

Dependent relationships between Chinese commodity markets and the international financial market: Evidence from quantile time-frequency analysis

In this article, the quantile time–frequency method is utilized to study the dependence of Chinese commodities on the international financial market. The impacts of risk management and diversification benefits of different portfolios are examined by calculating the reduction in downside risk. Moreover, we estimate and compare Sharpe Ratios (SRs) and Generalized Sharpe Ratios (GSRs) based on the frequencies of the investigated portfolios. Our empirical results reveal a strong asymmetric response from Chinese commodity markets. Specifically, we find that gold is a safe-haven asset, and due to negative correlations found at lower quantiles in medium and long term, an increase in the USD index damages bull commodity markets but boosts bear conditions under long-term investments, and negative (positive) tail correlations with interest rates (IRs) in bull (bear) markets are observed. It is proven that WTI can decrease short-run risks while USD and GOLD are more efficient in the diversification of downside risk. Adding international commodities may not improve the returns of Chinese commodities at given risk levels in the short and medium term through SRs and GSRs. In brief, investors should consider these dependence structures and modes of risk management in terms of time and frequency.     

An analysis of renewable mini-grid projects for rural electrification

Almost 900 million people are living with no access to electricity, mostly in remote regions where extending the central grid is infeasible. These remote communities often heavily depend on expensive and polluting diesel generators that create significant financial and operational challenges. Following the recent advances and cost reductions in renewable technologies, governments, private sector, and non-profit organizations started investing in rural electrification projects through renewable mini-grids, some of which were reported to have been unsuccessful. The findings and the lessons learned from these projects remain highly compartmentalized across different studies, making it significantly challenging to derive evidence-based insights on clean rural electrification for investors and practitioners. This study aids in closing this gap by collecting project-level data on 104 renewable energy mini-grids installed across the globe. We first conduct a systematic review of these projects to derive qualitative insights on drivers of project success and the benefits to communities. Next, we empirically validate some of our qualitative findings and identify the factors contributing to mini-grid project success and cost.