Annals of Financial Economics

This paper computes the welfare gains from optimal hedging with futures contracts for an oil-exporting country. Unlike previous studies, this paper derives the welfare gains under a more realistic futures hedging model. This is accomplished by considering basis risk and by relaxing the full-hedging assumption. Furthermore, this is the first paper to derive the welfare gains under optimal hedging strategies. We also incorporate the empirical relationship between spot and futures prices within our models, rather than the theoretical relationship which most studies employ. The models were developed under a dynamic stochastic optimization framework and the optimal consumption and value functions were found using the method of Endogenous Gridpoints. The results showed that the choice of the optimal hedging strategy employed led to a slight improvement in the country’s welfare gains relative to full hedging. We also found that the strategies with the highest welfare gains were the most effective at volatility reduction. Finally, this paper provides compelling evidence for the use of optimal macro futures hedging as an effective risk management tool for oil-exporting developing countries.

Emerging nations focus more on new and innovative business activities across national borders for economic advancement. Further, trade openness has recently emerged in BRICS countries. Thus, global entrepreneurship development can be a great opportunity for the traded open countries. In line with this, the study aims to examine the impact of trade openness on global entrepreneurship development in BRICS countries. The study collected balanced-panel data from BRICS countries for 2001–2020 and applied random-effects estimation to analyze the data. The study drives a cross-sectional dependence test, unit root test, and model specification test before applying the estimated model. The study further checked the robustness of the findings by alternative estimation methods like FMOLS and DOLS and found similar results. The results revealed that trade openness positively influences global entrepreneurship development, but average tariffs can discourage entrepreneurs. Specifically, trade openness through trade spread, trade freedom, and average tariffs increase the total early-stage entrepreneurial activities and entrepreneurial intentions rate in BRICS countries. Through cross-country analysis, the study found that trade openness significantly enhances global entrepreneurship development in Brazil, India, China, and South Africa rather than in Russia. The study found similar results after checking the robustness of the findings by alternative estimation methods like FMOLS and DOLS. Thus, the findings could be a great insight for the policymakers of BRICS countries. Governments, academics, international entrepreneurs, etc., can use the findings in future decisions as a policy dialogue.

This study reinforces the minimal empirical work on the nonlinear relationship between innovative activities, economic growth, and income distribution. Meanwhile, this study assesses panel data of 40 developing economies from 1996 to 2020, wielding the newly developed threshold model by Seo and Shin (2016). Firstly, the empirical findings hold that there exists a nonlinear relationship between the variables. So, by regressing Innovation on economic growth, this study acquires a threshold value of 0.36% of R&D. Hence, indicating above the threshold value of 0.36, the economic growth will revamp. Secondly, regressing R&D on GINI, this study obtains a threshold value of 0.27% of R&D. So, above the threshold value of 0.25, the income inequality will topple down. In contrast, below the threshold level of Innovation will cause both economic growth and income inequality to exacerbate. All in all, the empirical findings of this study suggest that it is plausible to argue that governments and policymakers in developing economies should lavish more on Innovation because higher innovation activities result in inclusive growth.

The purpose of this study is to investigate the dynamic relationship between financial assets and agricultural commodities market in Turkey. For this purpose, first, this study investigates financialization of agricultural commodities with a newly established agricultural commodities market of Turkey. Second, this paper analyzes hedging and portfolio diversification performances of agricultural commodities. By employing the DCC-GARCH approach of Engle (2002) and spillover index approach of Diebold and Yilmaz (2014), we analyze the financialization of agricultural commodities and calculate optimal hedge ratios and portfolio weights between two classes of assets. The results show the financialization of agricultural commodities at a very early age in Turkey. There exists a low degree of comovements and volatility spillovers between financial assets and agricultural commodities. Second, we show that agricultural commodities do not hedge financial investments sufficiently but they perform very well in terms of diversification and boost portfolio performances. Considering the previous limited literature on the topic, this study contributes to the literature by displaying the dynamics of a newly established agricultural commodities market in an emerging market. The findings of this study have many important implications for farmers and producers of agricultural commodities, and financial market actors such as individual investors, hedge funds and investment banks in terms of risk management and hedging.

The firm’s market capitalization is an ideal proxy of the size of listed firms. Hence, this paper uses the firm’s market capitalization to capture the firm size instead of using other prior proxies to investigate the relationship between the market capitalized scale and corporate capital structure by employing the Generalized Method of Moments (GMM) method to conduct analysis based on a sample of the 300 largest listed firms in China from 2010 to 2017. The CSI300 list consists of two subsample (CSI100 and CSI200), divided upon the firm’s market capitalized scales to represent both large-cap and small-cap firms. Our paper contributes to the literature on corporate finance by obtaining some new empirical results to assess the effect of market capitalized scale on corporate capital structure. We find that the market capitalized size has a significantly negative association with corporate leverage. We also find that both the Trade-Off Theory (TOT) and Pecking-Order Theory (POT) can partially explain the capital structure of the listed firms of the CSI300 Index such that the negative relationship between the market capitalized scales and corporate leverage is firmly identified in small-cap firms. Third, we observe that the greater validity of the POT’s predictions is enhanced in small-cap firms such that the greater inverse impact of profitability and the more significant positive effect of growth opportunities on corporate leverage are clearly shown in small-cap firms. Inversely, the more significant adverse effects of non-debt tax shields on corporate leverage are found in large-cap firms and there is no difference in the impact of tangible assets on debt ratios between CSI100’s listed companies and CSI200’s listed enterprises. Academics and practitioners could use our findings to draw better implications while policymakers could use our results to obtain better policies to improve the banking system with small listed companies.

Amidst the tumultuous COVID-19 pandemic and the Russia–Ukraine conflict, India has defied the odds and exhibited remarkable consistency in its macroeconomic performance, surpassing other top 10 global economies. This laudable progress was made even in the aftermath of significant prior disruptions. Therefore, the objective of this research paper is to meticulously scrutinize the macroeconomic determinants that impacted India’s economic growth from 1990 to 2020. The data utilized was sourced from the Reserve Bank of India, and a time series econometric technique was employed to identify stationary and its co-integration using an auto-regressive distributed lag (ARDL) model. This study exhaustively investigates the impact of five macroeconomic indicators, exports, imports, gross capital formation, gross savings, and gross inflow, which propel economic growth. Our findings unequivocally demonstrate that exports, gross capital formation, gross savings, and gross inflows have an indisputably positive and significant effect on India’s economic growth in the short and long run. However, imports negatively impact both the short and long runs. Other macroeconomic variables could not be comprehensively covered due to the absence of relevant data. Nevertheless, this study confers novel insights to policymakers and researchers alike by examining both the short-run and long-run dynamics and employing the Wald test to provide a profound understanding of the macroeconomic determinants indispensable for realizing sustainable economic growth. To the best of the author’s knowledge, this study constitutes a pioneering and original endeavor that undertakes a comprehensive and nuanced examination of economic growth by analyzing multiple macroeconomic indicators simultaneously, thereby providing a holistic and multifaceted understanding of the complex phenomenon of economic growth.