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The study endeavors to explore whether the financialization of agricultural commodities, traditionally viewed as a catalyst for price volatility, has any repercussions on food security in BRICS economies.

The empirical analysis employs the examination of three agricultural commodities, namely wheat, maize and soybean. Utilizing data from the Chicago Board of Trade on futures trading for these commodities, we focus on parameters such as annual trading volume, annual open interest contracts and the ratio of annual trading volume to annual open interest contracts. The study spans the period 2000–2021, encompassing pre- and post-financial crisis analyses and specifically explores the BRICS countries namely the Brazil, Russia, India, China and South Africa. To scrutinize the connections between financialization indicators and food security measures, the analysis employs econometric techniques such as panel data regression analysis and a moderating effects model.

The results indicate that the financialization of agricultural products contributes to the heightened food price volatility and has adverse effects on food security in emerging economies. Furthermore, the study reveals that the impact of the financialization of agricultural commodities on food security was more pronounced in emerging nations after the global financial crisis of 2008 compared to the pre-crisis period.

This paper seeks to draw increased attention to the financialization of agricultural commodities by presenting empirical evidence of its potential impact on food security in BRICS economies. The findings serve as a valuable guide for policymakers, offering insights to help them safeguard the security and availability of the world’s food supply.

Very few studies have explored the effect of financialization of agricultural commodities on food security covering a sample of developing economies, with sample period from 2000 to 2021, especially at the individual agriculture commodity level. Understanding the evolving effects of financialization is further improved by comparing pre and post-financial crisis times.

The purpose of this paper is to discuss the pioneering work of the 19th-century French author Jean-Gustave Courcelle-Seneuil in developing a scientific perspective on management, whose origin is commonly associated with the contributions of Frederick Taylor and Henri Fayol.

Through a historical analytical approach and doing a parallel analysis with the origins of the economic theory, fragments of two works by Jean-Gustave Courcelle-Seneuil (1813–1892) are analyzed: The Theoretical and Practical Treatise on Industrial, Commercial and Agricultural Enterprises: A Business Manual (1855) and Ergonomics, the second part of the book Theoretical and Practical Treatise on Political Economy (1858), in which the author devotes a chapter to relevant aspects of management, such as entrepreneurship, production, human resources, finance and accounting.

In addition to noting the pioneering character of these contributions, particularly the emphasis on entrepreneurship, Courcelle-Seneuil’s argument favors in the 19th century a scientific approach to management, contradicting the belief of businesspeople of the time, according to whom management was something practical, impossible to be studied analytically.

This study indicates that looking to the past is essential to know what has already been produced in a particular field of knowledge. This return to the origins is fundamental to understanding how science evolves. Although management as a systematized field of expertise is usually dated to the beginning of the 20th century, there are reasons to expand on the influences that gave rise to this science, particularly regarding lesser-known but equally important contributions.

This study explores a lesser-known contribution to the origin of management theory and seeks to contribute to the study of the origin of the division of the fields of management science, its roots and its intersection with the economic science practiced in the half of the 19th century.

This study investigates the impacts of the Russia–Ukraine conflict on the cross-correlation between agricultural commodity prices and crude oil prices.

The authors used MultiFractal Detrended Fluctuation Cross-Correlation Analysis (MF-X-DFA) to explore the correlation behavior before and during conflict. The authors analyzed the price connections between future prices for crude oil and agricultural commodities. Data consists of daily futures price returns for agricultural commodities (Corn, Soybean and Wheat) and Crude Oil (Brent) traded on the Chicago Mercantile Exchange from Aug 3, 2020, to July 29, 2022.

The results suggest that cross-correlation behavior changed after the conflict. The multifractal behavior was observed in the cross correlations. The Russia–Ukraine conflict caused an increase in the series' fractal strength. The study findings showed that the correlations involving the wheat market were higher and anti-persistent behavior was observed.

The study was limited by the number of observations after the Russia–Ukraine conflict.

This study contributes to the literature that investigates the impact of the Russia–Ukraine conflict on the financial market. As this is a recent event, as far as we know, we did not find another study that investigated cross-correlation in agricultural commodities using multifractal analysis.

The aim of this study is to investigate for monotonicity, linearity and symmetry for the price volatility–trading volume relationship in the futures markets of agricultural commodities.

Empirical findings are produced with the use of a highly flexible, nonparametric approach. Data are daily prices and volumes from the commodities of corn, hard red wheat, oats, rice and soybeans.

Results reveal violations of monotonicity locally but not globally. Volume and price volatility have, in all markets, a nonlinear relationship to each other, indicating that the strength of the relationship does not remain constant over the entire joint distribution. Global symmetry is rejected for the markets of oats and hard red wheat but cannot be rejected for the remaining three markets. The latter suggests that large values of good volatility are likely to occur together with high trading volumes, as do large values of bad volatility in these markets.

To the best of the authors’ knowledge, this is the first empirical work to test simultaneously for monotonicity, linearity and symmetry between price volatility and trading volume in the futures markets of agricultural commodities.

The purpose of this paper is to test the overshooting effects of monetary expansion on prices of agricultural products at farm production, processing and circulation stages in China, and to investigate the heterogeneity of the overshooting mechanisms in these three links.

Empirical results are obtained through the vector error correction model and the overshooting framework proposed by Saghaian et al. (2002b). Specifically, we first apply the Dickey–Fuller generalized least squares (DF-GLS) method to test the stationarity of the key variables, and then use the Johansen’s (1991) method to conduct the cointegration test. Finally, the vector error correction model is employed to examine the overshooting hypotheses in the three stages of China’s agricultural sector.

Empirical results indicate that overshooting of prices relative to monetary expansion in China’s agricultural sector is a common phenomenon, but with significant heterogeneity. Firstly, at the stage of agricultural production, the overshooting degree and restoration rate of material price are greater than those of agricultural products price. Secondly, at the processing stage of agricultural products, both the purchase price of agricultural products and industrial producer price have an overshooting effect, but the overshooting effect of the former is more significant than the latter. Thirdly, at the circulation stage of agricultural products, the overshooting coefficient of the wholesale price index of agricultural products is the most significant, while that of the retail and purchase price of agricultural products is not significant.

The paper contributes to proposing a comprehensive framework on testing the overshooting effects for three main stages of agricultural sector in China and empirically investigating the heterogeneity of the overshooting mechanisms in different stages with time series methods.

The American agricultural economist Marion Clawson advised the Israeli government during 1953–1955. Clawson, a protégé of John D. Black and Mordecai Ezekiel, criticized the government for ignoring economic considerations, and stated that Israel’s national goals – defense, Negev Desert irrigation, immigrant absorption via new agricultural settlements, and economic independence – were mutually contradictory. His major recommendations were to improve the realism of Israel’s agricultural plan; end expensive Negev irrigation; enlarge irrigated farms eightfold; freeze new settlements until the number of semi-developed settlements falls from 300 to 100; and limit new Negev settlements to 10 over 5–7 years. Thus, Clawson ignored political feasibility and made value judgments. Minister of Finance Levi Eshkol and Minister of Agriculture Peretz Naphtali rejected Clawson’s recommendations because they ignored Israel’s national goals. By September 1954, Clawson shifted towards greater pragmatism: He acknowledged that foreign advisors should not question the national goals or make value judgments, and sought common ground with the Ministry of Agriculture. At his initiative, he wrote Israel Agriculture 1953/54 in collaboration with the Ministry of Agriculture. Israel Agriculture was a consensus document: Clawson eschewed recommendations and accepted that the government might prioritize non-economic goals. In proposing Israel Agriculture, Clawson made a pragmatic decision to relinquish some independence for (potentially) greater influence. Ultimately, Clawson was largely unsuccessful as an advisor. Clawson’s failure was part of a general pattern: Over 1950–1985, the Israeli government always rejected foreign advisors’ recommendations unless it was facing a severe crisis.

In a volatile agricultural postharvest market, producers require more personalized information about market dynamics for informed decisions on the marketed surplus. However, this adaptive strategy fails to benefit them if the selection of a computational price predictive model to disseminate information on the market outlook is not efficient, and the associated risk of perishability, and storage cost factor are not assumed against the seemingly favourable market behaviour. Consequently, the decision of whether to store or sell at the time of crop harvest is a perennial dilemma to solve. With the intent of addressing this challenge for agricultural producers, the study is focused on designing an agricultural decision support system (ADSS) to suggest a favourable marketing strategy to crop producers.

The present study is guided by an eclectic theoretical perspective from supply chain literature that included agency theory, transaction cost theory, organizational information processing theory and opportunity cost theory in revenue risk management. The paper models a structured iterative algorithmic framework that leverages the forecasting capacity of different time series and machine learning models, considering the effect of influencing factors on agricultural price movement for better forecasting predictability against market variability or dynamics. It also attempts to formulate an integrated risk management framework for effective sales planning decisions that factors in the associated costs of storage, rental and physical loss until the surplus is held for expected returns.

Empirical demonstration of the model was simulated on the dynamic markets of tomatoes, onions and potatoes in a north Indian region. The study results endorse that farmer-centric post-harvest information intelligence assists crop producers in the strategic sales planning of their produce, and also vigorously promotes that the effectiveness of decision making is contingent upon the selection of the best predictive model for every future market event.

As a policy implication, the proposed ADSS addresses the pressing need for a robust marketing support system for the socio-economic welfare of farming communities grappling with distress sales, and low remunerative returns.

Based on the extant literature studied, there is no such study that pays personalized attention to agricultural producers, enabling them to make a profitable sales decision against the volatile post-harvest market scenario. The present research is an attempt to fill that gap with the scope of addressing crop producer's ubiquitous dilemma of whether to sell or store at the time of harvesting. Besides, an eclectic and iterative style of predictive modelling has also a limited implication in the agricultural supply chain based on the literature; however, it is found to be a more efficient practice to function in a dynamic market outlook.

This paper aims to explore the relationship between prudence in risk attitudes and patience of time preference of Chinese apple growers regarding off-farm cold storage of production and marketing in non-harvest seasons. The authors also consider the effect of farmer participation in cooperative-like organizations known as Farm Bases (FBs).

The authors use multiple list methods and elicitation strategies to measure Chinese apple farmers' risk attitudes and time preferences. Because these farmers can either sell their apples immediately to supermarkets or intermediaries or place them in storage, the authors assess correlations between their storage decisions and their preferences regarding risk and time. The authors also differentiate risks involving gains and losses and empirically examine individual risk attitudes in different scenarios.

Marketing decisions are moderately associated with risk attitudes but not time preference. Farmers with memberships in local farmer cooperatives are likely to speculate more in cold storage. Thus, risk aversion behavioral and psychological motives affect farmers' decision-making of cold storage and intertemporal marketing activities. However, membership in cooperatives does not always result in improved income and welfare for farmers.

The research confirms that behavioral factors may strongly drive vulnerable smallholder farmers to speculate into storage even under seasonal and uncertain marketing volatility. There is the need to think deeper about the rationale of promoting cooperatives and other agricultural forms, because imposing these without careful consideration can have negative impacts.

Do risk and time preferences affect the decision of farmers to utilize storage facilities? This question is important because it is not clear if and how risk preferences affect the tradeoff between consuming today and saving for tomorrow, especially for farmers in developing countries.

Considering the importance of Russia and Ukraine in agriculture, the authors quantify the potential impact of the Russia–Ukraine conflict on food output, trade, prices and food security for the world.

The authors mainly use the quantitative and structural multi-country and multi-sector general equilibrium trade model to analyze the potential impacts of the conflict on the global food trade pattern and security.

First, the authors found that the conflict would lead to soaring agricultural prices, decreasing trade volume and severe food insecurity especially for countries that rely heavily on grain imports from Ukraine and Russia, such as Egypt and Turkey. Second, major production countries such as the United States and Canada may even benefit from the conflict. Third, restrictions on upstream energy and fertilizer will amplify the negative effects of food insecurity.

This study analyzed the effect of Russia–Ukraine conflict on global food security based on sector linkages and the quantitative general equilibrium trade framework. With a clearer demonstration of the influence about the inherent mechanism based on fewer parameters compared with traditional Global Trade Analysis Project (GTAP) models, the authors showed integrated impacts of the conflict on food output, trade, prices and welfare across sectors and countries.

Considering the frequency of extreme events, enhancing the global financial system's stability has become crucial. This study aims to investigate the contagion effects of extreme risk events in the international commodity market on China's financial industry. It highlights the significance of comprehending the origins, severity and potential impacts of extreme risks within China's financial market.

This study uses the tail-event driven network risk (TENET) model to construct a tail risk spillover network between China's financial market and the international commodity market. Combining with the characteristics of the network, this study employs an autoregressive distributed lag (ARDL) model to examine the factors influencing systemic risks in China's financial market and to explore the early identification of indicators for systemic risks in China's financial market.

The research reveals a strong tail risk contagion effect between China's financial market and the international commodity market, with a more pronounced impact from the latter to the former. Industrial raw materials, food, metals, oils, livestock and textiles notably influence China's currency market. The systemic risk in China's financial market is driven by systemic risks in the international commodity market and network centrality and can be accurately predicted with the ARDL-error correction model (ECM) model. Based on these, Chinese regulatory authorities can establish a monitoring and early warning mechanism to promptly identify contagion signs, issue timely warnings and adjust regulatory measures.

This study provides new insights into predicting systemic risk in China's financial market by revealing the tail risk spillover network structure between China's financial and international commodity markets.