Commodities doi: 10.3390/commodities5020010

Authors: Dilshad Sarwar

Global supply chain disruptions, most acutely demonstrated during the COVID-19 pandemic, have exposed fundamental tensions between efficiency-oriented design and the adaptive capacity required for resilience. This paper addresses a critical gap in the existing literature: the absence of an integrative, operationalisable framework that treats sustainability and resilience as mutually reinforcing strategic objectives rather than competing trade-offs. Employing a systematic literature review guided by PRISMA protocols, complemented by comparative analysis of documented organisational responses across multiple sectors and commodity markets, the study identifies four primary pathways through which sustainability investments generate resilience: structural diversification, information and visibility, social capital and trust, and adaptive capabilities. The principal finding is that sustainability practices, particularly those enhancing supply network visibility, structural diversification, and workforce stability, create option value that becomes strategically decisive during periods of disruption. A decision intelligence framework is proposed that translates these insights into three managerial tools: a sustainability–resilience assessment matrix, a disruption scenario analysis tool, and a capability development roadmap. The framework challenges the prevailing trade-off assumption by demonstrating that efficiency, sustainability, and resilience can function as complementary dimensions of supply chain performance. Findings carry particular relevance for commodity-dependent supply chains, where price volatility, trade structure rigidity, and resource concentration constitute persistent sources of systemic disruption. Theoretical contributions include the integration of supply chain resilience theory, sustainable operations management, and decision science under deep uncertainty.

Commodities doi: 10.3390/commodities5020009

Authors: Shahidul Islam Subhadip Ghosh Wanhua Su

The transition from non-renewable to renewable energy sources has emerged as a pressing global issue, driven by concerns over climate change, resource depletion, and the need for sustainable development. This study compares Canada, an energy-rich nation, and Bangladesh, an energy-scarce country, to understand the structural, institutional, and market factors driving their respective renewable energy transitions. Using univariate time-series models (ARIMA, ETS, and Prophet) for energy demand forecasting and extensive literature-based policy evaluation, the paper examines trends in energy production, consumption, and trade from 1990 to 2024. Our analysis indicates that Canada’s vast reserves of both renewable and non-renewable energy sources, its diversified energy portfolio, and carbon-pricing framework support a stable decarbonization pathway, with renewables projected to account for more than 20% of total supply by 2030. However, regional disparities and political resistance from the established energy sector continue to delay transition outcomes. On the other hand, Bangladesh has limited renewable and non-renewable energy sources, with its primary energy resource being natural gas reserves. Consequently, its heavy reliance on imports (over 75% of primary energy) and institutional bottlenecks expose its energy system to commodity-price volatility, undermining energy security and slowing renewable investment. Despite these challenges, targeted solar programs and concessional financing have modestly increased the penetration of renewable energy. The analysis highlights that commodity market fluctuations, technological innovations (such as smart grids and energy storage), and market-based policy instruments critically shape each country’s transition trajectory. A coordinated policy linking market stabilization, innovation investment, and social inclusion is essential for achieving a just and secure low-carbon transition in both countries.

Commodities doi: 10.3390/commodities5020008

Authors: Ana Lorena Jiménez-Preciado Francisco Venegas-Martínez José Álvarez-García

This research examines the clustering structure and volatility spillover among steel-related products in monthly data from July 2004 to September 2025. Using various clustering methods, K-means, hierarchical techniques and market network analysis with correlations, four distinct marketing clusters have been identified: (1) US (United States) steel products, (2) global cyclical raw materials, (3) US iron ore market, and (4) global base metals. The overall volatility spillover index stands at 15.39%, exhibiting significant dynamics that vary over time, driven by major economic events, including the 2008 global financial crisis, the 2015 Chinese currency devaluation, the COVID-19 outbreak, the 2022 Ukrainian conflict, and the 2025 Trump trade tariffs. The primary driver of volatility in global trade is US carbon steel wire prices, while the largest net recipient of volatility shocks is the global copper price. These findings have key implications for understanding the global interconnectedness of steel markets in the current context.

Commodities doi: 10.3390/commodities5010007

Authors: Brenda Huerta-Rosas Eduardo Sánchez-Ramírez

This review examines the renewed strategic relevance of uranium within the evolving global energy system, emphasizing uranium market dynamics, emerging nuclear technologies, and geopolitical realignments. Moving beyond traditional perspectives that treat uranium primarily as a cyclical commodity or focus narrowly on reactor design, the article frames uranium as a critical strategic resource at the intersection of energy security, decarbonization, and industrial transformation. The analysis integrates market fundamentals with technological developments, particularly small modular reactors (SMRs) and advanced high-temperature reactor systems, and regional policy strategies to provide a holistic perspective largely absent from the existing literature. Quantitative evidence indicates a structurally tightening uranium market, with global reactor demand of approximately 67,500 tU per year and mine production historically meeting only 74–90% of annual requirements. Uranium prices have rebounded from below $20 lb−1 U3O8 in 2016 to above $80 lb−1 by late 2023, reflecting supply concentration, long development timelines for new mines, and renewed political commitments to nuclear energy. Demand projections suggest an increase of around 28% by 2030 and the potential for a doubling by mid-century under high-nuclear deployment scenarios. From a technological perspective, while SMRs and advanced reactors may increase uranium consumption per unit of electricity, they substantially expand nuclear energy deployment into new domains, including remote power systems, industrial heat applications, and large-scale low-carbon hydrogen production. Overall, the study highlights a qualitative shift in uranium’s role, positioning it as both a foundational component and a key enabler of integrated low-carbon energy systems spanning electricity, heat, and hydrogen production.

Commodities doi: 10.3390/commodities5010006

Authors: Nima Asgari Nan Zou Ying Zheng Joshua M. Pearce

Agricultural seeds are sold as commodities yet seed quality can be non-uniform. Despite the extensive literature showing that plasma treatments of seeds provides advantages for many crops, lettuce studies, particularly in indoor farming systems, are limited. This study provides a systematic investigation of the impacts of non-thermal plasma treatments with various feed gases (N2, O2, dry air, and wet air) on the germination and growth characteristics of four lettuce cultivars (Red Oakleaf (RO), Black Simpson (BS), Valley Heart Romaine (VHR), and Paris Romaine (PR)) under controlled cultivation conditions in an agrivoltaic agrotunnel. Although the germination time was not conclusively affected by the treatments, the results show a complex interaction between germination rate and yield across the different cultivars and plasma treatments. Except for PR seeds (77.8% vs. 65.8% control), wet air plasma treatments increased germination rates by 18.7–100% over controls for all other cultivars. In yield analysis, wet air treatment had the strongest effect, especially for VHR (51.7 vs. 42.5 g/pot). Treatments did not notably affect RO. For BS, N2 treatment gave the highest increase (54.2 vs. 48.1 g/pot), while PR responded best to O2 treatment (58.4 vs. 51.8 g/pot). The energy consumption of plasma treatments was negligible for all treatments, while labor costs for small batches of seeds accounted for the largest share of secondary operating costs (839, 622, and 659 h/year, respectively for BS, VHR, and PR). Despite additional expenses, including labor, O&M, and degradation costs, the reduced seed requirements from higher germination rates and higher yield increased net profit by 12.0% compared to untreated cultivation in the most impacted (Valley Heart Romaine) lettuce. There is an opportunity for further cost optimization of the non-thermal plasma treatment for each type of lettuce seed.

Commodities doi: 10.3390/commodities5010005

Authors: José A. Duarte Álvaro Hernández-Flores Francisco Iván Hernández-Cuevas

Mexican octopus fisheries play an important role in both domestic and international seafood markets, yet little is known about the determinants of retail price in the national frozen octopus sector. This study examines how trade flows and domestic demand interact to shape price dynamics, providing insights into sustainability challenges. Multiple linear regression was employed to test the influence of economic, production, and trade variables on retail prices, based on annual data from 2010 to 2024. The best-performing model identified average daily salary, apparent consumption and import value as significant determinants, explaining more than 90% of the observed variation. Results show that rising salaries and greater domestic consumption are exerting upward pressure on prices, while imports, although limited, contribute to price moderation. Export values have declined, signaling a weakening role of the international markets. These findings suggest that domestic demand is becoming increasingly important for sustaining value in the sector, but this shift could intensify fishing pressure on wild stocks. Strengthening compliance with management measures and aligning policies with domestic market realities are crucial to ensuring long-term sustainability of the Mexican octopus supply.

Commodities doi: 10.3390/commodities5010004

Authors: Belinda Tshiula Waldo Krugell Johann Jerling Christine Taljaard-Krugell

This paper investigates whether participation in Zambia’s social cash transfer programme (SCTP) improves household dietary diversity among ultra-poor rural households. While cash transfers are widely implemented across sub-Saharan Africa as social protection measures, empirical evidence regarding their impact on nutritional status remains mixed. This study focuses on dietary diversity, a proxy for nutrition quality, and uses data from the 2015 Rural Agricultural Livelihood Survey (RALS). The analysis employs propensity score matching to control for demographic differences between recipient and non-recipient households, followed by a regression analysis to examine the association between SCTP participation and dietary diversity scores. The findings reveal no statistically significant association between receiving social cash transfers and higher household dietary diversity. In contrast, positive predictors of dietary diversity included household remittances, own production of animal-source foods, and maize sales. Notably, households that relied on foraging exhibited significantly lower dietary diversity, suggesting foraging may be a coping strategy among food-insecure households. These results imply that while the SCTP may enhance household income stability, it does not necessarily translate into improved diet quality. This study contributes to the ongoing policy debate on the effectiveness of cash-based interventions in improving nutrition outcomes. It highlights the need to complement cash transfers with interventions that support food production and access, particularly in rural settings where market and infrastructure limitations persist.

Commodities doi: 10.3390/commodities5010003

Authors: Prosper E. Edoja Rosemary N. Okoh Emmanuella O. Udueni Goodness C. Aye

Poultry price instability remains a critical challenge for food security in Nigeria. This study examines the relationship between poultry price volatility (PPV), exchange rate (LEXR), and inflation (LCPI) from 1991 to 2024 using the Autoregressive Distributed Lag (ARDL) model. Descriptive results show that PPV had the highest variability (mean 0.65; standard deviation 1.07), while LEXR and LCPI were relatively more stable. Trend analysis indicates that poultry price volatility was high in the early 1990s but declined steadily after 2005, coinciding with persistent inflation and cycles of exchange rate depreciation and appreciation.Unit root and bounds tests confirm that the variables werecointegrated, with an F-statistic of 4.50 exceeding the upper bound at 5 percent significance. The long-run estimates reveal that inflation hada negative effect on poultry price volatility (−0.109), while the exchange rate exerteda positive effect (0.2702). The errorcorrection term (−0.336) indicates a 33.6 percent adjustment to equilibrium each period. In the short run, changes in inflation (0.942) and lagged exchange rate variations significantly influenced poultry price volatility. These findings underscore the importance of stabilizing exchange rates and controlling inflation to reduce price volatility in Nigeria’s poultry sector.

Commodities doi: 10.3390/commodities5010002

Authors: Ramsha Akhter Sisira Reddy Palli Mithilesh Walanjuwani Erick C. Jones

Global critical mineral production patterns differ markedly across the metals needed for advanced energy technologies. This study examines the extraction and processing landscape, in the year 2024, of six key commodities—lithium, cobalt, aluminum, nickel, manganese, and copper—to identify who the major players (countries and corporations) are in the critical mineral space and to understand what they are mining, where they are mining, and where are they sending their ore to be processed. This study aims to provide a snapshot of the critical mineral supply chain that serves as a useful resource for researchers and policymakers seeking to understand and improve the critical mineral supply chain. We analyze company financial filings, government datasets, and other public and proprietary sources for the year 2024. Then, we calculate production volumes and identify geographic and corporate concentration. The results show that copper and aluminum production and processing are relatively diverse, while lithium and cobalt extraction and processing are highly concentrated among a few countries and dominant firms. Nickel and manganese occupy an intermediate position, displaying moderate diversity with emerging signs of consolidation.

Commodities doi: 10.3390/commodities5010001

Authors: Renata G. Alcoforado Hudo L. S. G. Alcoforado Alfredo D. Egídio dos Reis Pedro A. d. L. Tenório

We study one of the world’s largest cattle markets by revisiting and extending previous work on the forecasting of Brazil’s Boi Gordo Index (BGI). Using an updated daily dataset (July 2006–September 2025, inflation-adjusted), we evaluate classical and machine learning (ML) approaches for price prediction. Methods include Exponential Smoothing (Simple, Holt, and Holt–Winters), ARMA/ARIMA/SARIMA, GARMA variants, GARCH, Theta, Prophet, and XGBoost; models are compared under a strictly chronological 90/10 holdout (~476 test days) using RMSE, MAE, and MSE, with the AIC guiding within-family selection. Results show that, for the full out-of-sample window, GARMA delivers the best overall accuracy, with ARMA and Holt–Winters close behind, while Prophet and XGBoost perform comparatively worse in this volatile setting. Performance is horizon-dependent: in the first 180 test days, prior to the late-2024 level shift, Holt attains the lowest RMSE/MSE, and XGBoost achieves the lowest MAE. No method anticipates the October–November 2024 exogenous jump and subsequent correction, highlighting the difficulty of structural breaks and the need for timely re-specification. We conclude that GARMA is a robust default for long, turbulent windows, whereas smoothing and ML methods can be competitive on shorter horizons. These findings inform risk measurement and risk mitigation strategies in Brazil’s cattle futures market.

Commodities doi: 10.3390/commodities4040030

Authors: Tiroyaone Ambrose Sirang Waldo Krugell Lorainne Ferreira Riaan Rossouw

The Trump administration signalled a shift toward protectionism in U.S. trade policy, imposing tariffs on imports from both strategic partners and competitors, which generated renewed uncertainty in international trade relations and the future of existing frameworks such as the African Growth and Opportunity Act (AGOA) and the Generalised System of Preferences (GSP). Earlier analysis has shown that a Free Trade Agreement (FTA) between the Southern African Customs Union (SACU) and the United States can be trade-creating and lead to improved macroeconomic outcomes in SACU countries. However, these positive effects decline over time, with varying impacts across different industries, influenced by initial tariff levels and export orientation relative to the US. This paper examines whether there are economic and strategic incentives for SACU to negotiate a more beneficial agreement than a simple across-the-board elimination of ad valorem import tariffs. Using a dynamic computable general equilibrium (CGE) model, the paper examines the outcomes if cereals, poultry, dairy products, red meat, and sugar products—often classified as sensitive due to their labour intensity, food security implications, and exposure to import competition—were to retain some level of protection under a SACU–US Free Trade Agreement. The results suggest that while the FTA boosts key macroeconomic indicators in the short run, gains taper off over time. Crucially, real wages and employment remain stagnant, and terms of trade deteriorate, raising questions about the inclusivity and sustainability of such a deal. Shielding vulnerable sectors initially enhances SACU’s exports and supports some industry growth, particularly in agriculture. However, without broader reforms and export diversification, long-term competitiveness remains weak. A nuanced FTA design, combined with structural support policies, is essential to unlock lasting and inclusive trade benefits.

Commodities doi: 10.3390/commodities4040029

Authors: David Kalima Mariëtte Geyser Andrea Saayman

Price volatility in the South African fresh produce market poses significant risks to the entire value chain. This study examines the extent of price volatility and spillover effects in these markets to improve price risk management and enhance market stability. Using weekly price data for eight major vegetables (cabbages, carrots, garlic, onions, potatoes, sweet potatoes, spinach, and tomatoes) collected from 19 regional fresh produce markets, volatility patterns were initially assessed with descriptive statistics. Time-varying volatility persistence was modelled using ARCH and GARCH frameworks. The DCC-GARCH framework was used to evaluate spillover effects between markets, and cointegration analysis is employed to determine both short- and long-run interdependencies. The results confirm the existence of spillover effects and patterns of price volatility in the fresh produce markets. We found volatility spillovers between key regional markets. For example, Johannesburg and Tshwane fresh produce markets (large central markets) transmit to several smaller markets, as indicated by significant DCC-GARCH spillover coefficients. Cointegration results show the partial integration of fresh produce markets, suggesting that price movements and volatility are interconnected across regions. This empirical result underscores the importance of understanding price risk management strategies in fresh produce markets and helps value chain decision makers better understand, anticipate, or test the possible effects of price volatility in fresh produce markets at any given time. Policy makers and other stakeholders in the value chain are equipped with knowledge of how best to serve society.

Commodities doi: 10.3390/commodities4040028

Authors: Roland Amagbo Hélyette Geman Ilaria Peri

This study looks at the impact of geopolitical risk on the volatility of wheat futures returns over the period 2012–2023, while controlling for inventories, shipping rates, and speculative activity. Using the volatility of CBOT first nearby futures returns, we apply a quantile regression approach to assess the impact of the variables on different parts of the volatility distribution. More specifically, we adopt the Quantile Autoregressive Distributed Lag (QARDL) model, which allows for examining the dynamic short- and long-run effects. We find that geopolitical risk has a non-linear, large positive effect on the top quartile of the distribution of wheat futures returns. We also show that the response of the volatility of wheat futures to shocks in the control variables is mostly non-linear across the conditional quantiles, significant in the tails and not around the median.

Commodities doi: 10.3390/commodities4040027

Authors: Eder J. A. L. Pereira Thanmillys Nadhynne de Lima da Conceição Emanuel Cruz da Lima

The urgent need to mitigate climate change has elevated green hydrogen as a sustainable alternative to fossil fuels, while green cryptocurrencies have emerged to address the environmental concerns of traditional cryptocurrency mining. This study investigates the dynamic correlation between the green hydrogen market and selected green cryptocurrencies (Cardano, Stellar, Hedera, Algorand, and Chia) from July 2021 to April 2024, utilizing the Dynamic Conditional Correlation GARCH (DCC-GARCH) model with robustness checks using EGARCH and GJR-GARCH specifications. Our findings reveal significant correlations, with peaks reaching up to 50% in 2022, a period likely influenced by the Russia-Ukraine conflict. Subsequently, a decline in these correlations was observed in 2023. These results underscore the interconnectedness of sustainability-driven markets, suggesting potential contagion effects during periods of global instability. The high persistence of correlation shocks (α + β values approaching unity) indicates that correlation regimes tend to be long- lasting, with important implications for portfolio diversification and risk management strategies. Robustness checks using EGARCH and GJR-GARCH specifications confirmed qualitatively similar patterns, reinforcing the validity of our findings into the evolving landscape of green finance and energy.

Commodities doi: 10.3390/commodities4040026

Authors: Gabriel da Silva Medina Nicolau Brito da Cunha

Industrial bio-inputs can improve commodity farming by replacing the use of agrochemicals. To assess the potential of agricultural bio-inputs to contribute to Brazil’s agro-industrial growth, we analyzed the market share held by domestic companies and the local market created by farmers who adopt bio-inputs. The results revealed that Brazilian companies accounted for 82.8% of the 221 companies with agricultural bio-inputs registered in Brazil by 2024. These domestic companies used technologies available to local investors and developed in collaboration with public innovation centers. Adoption levels among interviewed farmers ranged from 41.7% for biosolubilizers to 88.9% for bionematicides, revealing a large domestic market potential for bio-inputs in Brazil. We conclude that industrial agricultural bio-inputs represent an area of opportunity for Brazilian neo-industrialization based on local competitive advantages, low entry barriers, and domestic and foreign investments that can benefit from the local market for bio-inputs.

Commodities doi: 10.3390/commodities4040025

Authors: Ingo Wolf Martin Užík

Technological advances in laboratory-grown diamonds (LGDs) have eroded the scarcity premium of natural diamonds, raising the question of whether diamonds still function as a safe haven. At the same time, crystalline osmium has become investable for the first time, as crystallization technology enables safe storage, certification, and global trading. Using monthly data from 2017–2025, we form diversified portfolios with and without diamonds and with and without osmium, as well as two-asset combinations with the MSCI World. The results show that diamonds no longer provide reliable stability, while osmium consistently contributes to reducing volatility. For portfolio investors, the key lesson is that traditional safe-haven roles can change; diamonds no longer offer robust protection, whereas crystalline osmium acts as a stabilizing component. These findings illustrate the contrasting effects of technological change: substitution and loss of value for diamonds, usability and stabilization for osmium.

Commodities doi: 10.3390/commodities4040024

Authors: Michael Bloss Dietmar Ernst Leander Geisinger

We analyze extreme gold price movements between 1975 and 2025 using Extreme Value Theory (EVT). Using both the Block-Maxima and Peaks-over-Threshold approaches on a daily return basis, we estimate Value-at-Risk (VaR) and Expected Shortfall (ES) for the entire distribution focusing on a long-term view. Our results demonstrate that models based on the standard normal distribution systematically underestimate extreme risks, whereas EVT provides more reliable measures. In particular, EVT captures not only rare losses, but also sudden positive rallies, highlighting gold’s dual function as a risk and opportunity asset. Asymmetries emerge in the analysis: at the 0.99 quantile, losses appear larger in absolute value than gains. At the 0.995 quantile, in some episodes, upside extremes dominate. Furthermore, we find that geopolitical and economic shocks, including the oil crises, the 2008 financial crisis, and the COVD-19 pandemic, leave distinct signatures in the extremes. By covering five decades, our study provides the most extensive EVT-based assessment of gold risks to date. Our findings contribute to debates on financial stability and provide practical guidance for investors seeking to manage tail risks while recognizing gold’s potential as both a safe haven and a speculative asset.

Commodities doi: 10.3390/commodities4040023

Authors: Marc Cortés Rufé Yihao Yu Jordi Martí Pidelaserra

The global push for electrification and decarbonization has sharply increased demand for critical raw materials—especially lithium and copper—heightening financial and strategic pressures on firms that lead these supply chains. Yet, the systemic financial risks arising from inter-firm interdependencies in this sector remain largely unexplored. This article presents a novel distance-based network framework to analyze systemic risk among the world’s top 15 lithium and copper producers (2020–2024). Firms are represented through standardized vectors of profitability and risk indicators (liquidity–solvency), from which we construct a two-layer similarity network using Euclidean distances. Graph-theoretic tools—including Minimum Spanning Tree, eigenvector centrality, modularity detection, and contagion simulations—reveal the structural properties and transmission pathways of financial shocks. The results show a robust-yet-fragile topology: while stable under minor perturbations, the network is highly vulnerable to failures of central firms. These findings highlight the utility of distance-based network models in uncovering hidden fragilities in critical commodity sectors, offering actionable insights for macroprudential regulators, investors, and corporate risk managers amid growing geopolitical and financial entanglement.

Commodities doi: 10.3390/commodities4040022

Authors: Jonathan Blackledge Anton Blackledge

Cryptocurrencies such as Bitcoin can be classified as commodities under the Commodity Exchange Act (CEA), giving the Commodity Futures Trading Commission (CFTC) jurisdiction over those cryptocurrencies deemed commodities, particularly in the context of futures trading. This paper presents a method for predicting both long- and short-term trends in selected cryptocurrencies based on the Fractal Market Hypothesis (FMH). The FMH applies the self-affine properties of fractal stochastic fields to model financial time series. After introducing the underlying theory and mathematical framework, a fundamental analysis of Bitcoin and Ethereum exchange rates against the U.S. dollar is conducted. The analysis focuses on changes in the polarity of the ‘Beta-to-Volatility’ and ‘Lyapunov-to-Volatility’ ratios as indicators of impending shifts in Bitcoin/Ethereum price trends. These signals are used to recommend long, short, or hold trading positions, with corresponding algorithms (implemented in Matlab R2023b) developed and back-tested. An optimisation of these algorithms identifies ideal parameter ranges that maximise both accuracy and profitability, thereby ensuring high confidence in the predictions. The resulting trading strategy provides actionable guidance for cryptocurrency investment and quantifies the likelihood of bull or bear market dominance. Under stable market conditions, machine learning (using the ‘TuringBot’ platform) is shown to produce reliable short-horizon estimates of future price movements and fluctuations. This reduces trading delays caused by data filtering and increases returns by identifying optimal positions within rapid ‘micro-trends’ that would otherwise remain undetected—yielding gains of up to approximately 10%. Empirical results confirm that Bitcoin and Ethereum exchanges behave as self-affine (fractal) stochastic fields with Lévy distributions, exhibiting a Hurst exponent of roughly 0.32, a fractal dimension of about 1.68, and a Lévy index near 1.22. These findings demonstrate that the Fractal Market Hypothesis and its associated indices provide a robust market model capable of generating investment returns that consistently outperform standard Buy-and-Hold strategies.

Commodities doi: 10.3390/commodities4040021

Authors: Erica Juvercina Sobrinho Rodrigo Fernandes Malaquias

The objective of this research is to understand the relationship between the tone of information released in government harvest reports, in extreme market conditions (rising and falling), and the behavior of agricultural commodity prices. In the period between January/2017 and February/2023, an autoregressive model of moving averages was used with a generalized autoregressive conditional heteroscedasticity approach. The evidence allows us to infer that investors can, on some occasions, use this information to direct their portfolios in order to balance risk and return. However, the full impact of the tone is not reflected immediately, possibly requiring time to be absorbed. Depending on the informational weight, the commodity, and the market context, there may or may not be an impact. This divergent empirical evidence indicates that there is a complex relationship between tone reading and asset pricing.

Commodities doi: 10.3390/commodities4030020

Authors: Nuno Soares Domingues

We study Portugal’s household electricity retail market after legal liberalisation, quantifying market concentration (Herfindahl–Hirschman Index (HHI) and the four-firm concentration ratio (CR4)), consumer switching, and asymmetric wholesale-to-retail price pass-through. Using monthly data for January 2014–December 2019 (primary sample) and robustness checks for 2008–2022, we compute concentration indices from ERSE supplier shares, analyse switching dynamics, and estimate nonlinear autoregressive distributed lag (NARDL) models that decompose wholesale price changes into positive and negative components. The retail market remains highly concentrated during the primary window (HHI ≈ 6300–6800 using shares expressed as percentages on a 10,000 scale); switching rose after deregulation but stabilised at moderate monthly rates; and long-run pass-through is estimated at β+ ≈ 0.55–0.61 for wholesale increases and β− ≈ 0.49 for decreases (Wald tests reject symmetry at conventional levels). Results are robust to alternative concentration metrics, exclusion of 2022, and varied lag orders. Policy implications emphasise tariff simplification, active consumer-activation measures, and regular monitoring of concentration and pass-through metrics.

Commodities doi: 10.3390/commodities4030019

Authors: Md Shahed Almi Sajid Kentaka Aruga

This study investigates the impact of the COVID-19 pandemic on the Tokyo mango market by combining transaction data from the Ota Fruit Market with Google Mobility indices. In Japan, mangoes are regarded as a luxury fruit, largely dependent on imports and associated with high domestic production costs, which positions them as premium commodities. To assess the influence of price dynamics and human mobility on mango trading volumes during the pandemic, this study employs an autoregressive distributed lag (ARDL) model. The long-run results indicate that mango demand was positively associated with increased residential activity: a 1% rise in time spent at home during the COVID era corresponded to an increase of 786 kg in trade volume. Similarly, a 1% increase in time spent in retail and recreation areas was associated with a 364 kg rise in trade volume. In contrast, time spent in grocery and pharmacy locations showed no statistically significant effect. In the short run, fluctuations in mobility patterns and price levels contributed to variations in demand, with sales volumes adjusting toward their long-run equilibrium. The mobility indices exhibited mixed short-term effects on trade volumes. Notably, the analysis revealed that mango trading volumes rebounded in 2022, coinciding with the easing of pandemic-related disruptions.

Commodities doi: 10.3390/commodities4030018

Authors: César Ramírez-Márquez

As global economies accelerate their energy transitions, the photovoltaic sector faces critical challenges linked to material supply, security, and sustainability. Solar-grade silicon, enabling over 90 percent of photovoltaic technologies, has become a strategic commodity underpinning the expansion of renewable energy infrastructures. This short communication examines the evolving role of solar-grade silicon within the global energy transition, moving beyond its traditional classification as a technical material to frame it as a commodity of geopolitical and economic significance. We analyze recent price trends, regional production asymmetries, and trade dependencies, identifying key vulnerabilities in current supply chains. Although alternative photovoltaic materials such as perovskites and organics attract research interest, their commercial immaturity reinforces the centrality of silicon. The novelty of this contribution lies in treating solar-grade silicon through a commodity lens, integrating techno-economic metrics with policy and investment considerations. We highlight opportunities for reinforcing supply resilience through domestic production, circular economy strategies such as silicon recovery and reuse, and diversification of technological pathways. Our findings advocate for the inclusion of solar-grade silicon in strategic resource planning and industrial policy frameworks. Recognizing its unique position at the intersection of energy, technology, and trade is essential to achieving secure, scalable, and sustainable photovoltaic deployment worldwide.

Commodities doi: 10.3390/commodities4030017

Authors: Matilde Elvira Muneilowe Tyaima Hanamulamba Suellen Mariano da Silva Leonardo Castilho-Barros Pinto Leonidio Hanamulamba Marcelo Barbosa Henriques

Artisanal fishing is a central pillar of the Angolan economy, particularly in the southern province of Namibe, where it serves as the primary economic activity for numerous coastal communities. However, these communities face significant challenges, including competition from expanding industrial fisheries and inadequate infrastructure at fishing centers, which hampers the storage, preservation, and transportation of catches. These limitations contribute to post-harvest losses and the reduced market value of products, despite the region’s rich diversity of pelagic and demersal resources. This study evaluated the economic viability of artisanal fishing in Namibe under three production scenarios, varying in catch levels and the inclusion of fish processing activities such as dried fish and fishmeal production. Scenario A (pessimistic) assumed a 10% reduction in production compared to the best estimates; Scenario B (intermediate) was based on average reported catches; and Scenario C (optimistic) considered a 10% increase in catches, accounting for seasonal and environmental variability. Results indicated that artisanal fishing was economically viable under all scenarios, with the Internal Rate of Return (IRR) consistently exceeding the Minimum Attractive Rate of Return (MARR) of 7.5%. IRR values ranged from 34.30% (Scenario A, without by-product commercialization) to 106.28% (Scenario C, with dried fish and fishmeal production and sales), representing a more than threefold increase in profitability. This substantial gain underscores the transformative potential of processing by-products into higher-value commodities, enabling integration into larger-scale and more liquid markets. Such value addition supports the concept of a proximity economy by promoting short production cycles, reducing intermediaries, and strengthening local value chains. Beyond financial returns, the findings suggest broader socioeconomic benefits, including local economic growth, job creation, and the preservation of traditional production knowledge. The payback period was less than four years in all cases, decreasing to 1.94 years in the most favorable scenario. By-products such as dried fish and fishmeal exhibit commodity-like characteristics due to their higher commercial value, increasing demand, and potential integration into regional and animal feed markets. In conclusion, diversifying marketing strategies and maximizing the use of fish resources can significantly enhance the economic sustainability of artisanal fishing, foster socioeconomic inclusion, and support the development of artisanal fishing communities in Namibe.

Commodities doi: 10.3390/commodities4030016

Authors: Moammar Dayoub

Gum arabic production is a key source of income for communities in several African countries. Despite this, producing nations capture only a small share of the market value due to weak domestic markets, low price incentives, and limited value-added. Meanwhile, global demand is expected to grow from USD 1.1 billion in 2025 to USD 2.2 billion by 2035, driven by rising consumption in food, pharmaceuticals, cosmetics, and textiles. Importing countries, such as France and the US, benefit from significantly higher export prices—French export prices rose from USD 1.58/kg to USD 4.63/kg—highlighting the value added from outside producer regions. This study uses a qualitative analytical approach to examine trends and challenges in enhancing value capture within producer countries. Key strategies include local value-added, collective action, compliance with international standards, market transparency, and direct trade linkages. Findings suggest that implementing these measures could raise farmgate prices by 30–50%, retain more value within African economies, and improve access to premium export markets. In conclusion, targeted interventions are crucial for strengthening the gum arabic supply chain and promoting sustainable and equitable collection practices in producer countries.

Commodities doi: 10.3390/commodities4030015

Authors: Mert Demir Terrence F. Martell Lene Skou

Futures and forward contracts together offer farmers of all sizes important tools for shifting and managing production risk. This risk shifting is particularly apparent in the U.S. grain complex, where the United States also has a significant export position. Because of this international reach, we argue that the futures and forward markets play a critical role in reducing world food insecurity and thus contribute to satisfying Sustainable Development Goal #2: Zero Hunger. We further argue that the presence of investors willing to take the opposite side of the farmers’ natural short hedge helps futures markets perform their key functions of price discovery and risk management. In addition to these roles, futures markets also enable farmers to finance their crops more efficiently over the production cycle, supporting operational stability. Finally, we highlight that agricultural markets in the United States are supported by significant regulation at the county, state, and federal levels. These farming regulations, coupled with federal oversight of agricultural futures markets, provide sufficient confidence that the goal of Zero Hunger is being pursued in an appropriate and effective manner, reinforcing the case for agricultural futures as a meaningful component of a broader sustainable investment strategy.

Commodities doi: 10.3390/commodities4030014

Authors: Stephan Mabica Erasmus Narteh Tetteh Ingrid Fromm Caleb Melenya Ocansey

The enforcement of the European Union Deforestation Regulation (EUDR) may reduce the supply of natural rubber to the European Union (EU), potentially leading to price increases due to the inelastic nature of rubber demand. This study assesses the potential financial implications for smallholder producers in Ghana, considering both the opportunities and risks associated with the evolving regulatory environment under EUDR and local market access conditions. A cost–benefit analysis (CBA) was conducted to evaluate the impact of different EUDR-related export decline scenarios on the net present value (NPV) of a standard 4-hectare plantation. The results suggest that even a minor 2.5% decline in global exports to the EU could increase the NPV by 17% for an independent compliant producer. However, a simulated COVID-19-like crisis in the fifth year of production leads to a 20% decline in NPV, reflecting vulnerability to external shocks. Based on these findings, the study identifies two priorities. This first is improving the coordination and harmonization of compliance efforts across the value chain to enable more producers to benefit from potential EUDR-related price increases. The recent creation of the Association of Natural Rubber Actors of Ghana (ANRAG) presents an opportunity to support such collective mechanisms. Second, minimizing losses during demand shocks requires the Tree Crops Development Authority (TCDA) to establish clear rules and transparent reporting for authorizing unprocessed rubber exports when factories reduce purchases due to low international prices—thus preserving market access for vulnerable producers. Together, these approaches would ensure that the potential benefits of the EUDR are realized inclusively, remain stable despite market downturns, and do not undermine value addition in domestic processing factories.

Commodities doi: 10.3390/commodities4030013

Authors: Roza Galeeva

The phenomenon of rising forward price volatility, both historical and implied, as maturity approaches is referred to as the Samuelson effect or maturity effect. Disregarding this effect leads to significant mispricing of early-exercise options, extendible options, or other path-dependent options. The primary objective of the research is to identify a practical way to incorporate the Samuelson effect into the evaluation of commodity derivatives. We choose to model the instantaneous variance employing the exponential decay parameterizations of the Samuelson effect. We develop efficient calibration techniques utilizing historical futures data and conduct an analysis of statistical errors to provide a benchmark for model performance. The study employs 15 years of data for WTI, Brent, and NG, producing excellent results, with the fitting error consistently inside the statistical error, except for the 2020 crisis period. We assess the stability of the fitted parameters via cross-validation techniques and examine the model’s out-of-sample efficacy. The approach is generalized to encompass seasonal commodities, such as natural gas and electricity. We illustrate the application of the calibrated model of instantaneous variance for the evaluation of commodity derivatives, including swaptions, as well as in the evaluation of power purchase agreements (PPAs). We demonstrate a compelling application of the Samuelson effect to a widely utilized auto-callable equity derivative known as the snowball.

Commodities doi: 10.3390/commodities4030012

Authors: Hiroki Wakamatsu Kentaka Aruga

The COVID-19 pandemic had significant global impacts. In Japan, consumers refrained from going out, and dining out decreased significantly, which strongly affected the restaurant industry and resulted in a shift in food demand from eating out to home consumption. The seafood industry is no exception to this trend. This study surveyed 300 individuals with experience in seafood transactions across wholesalers, restaurants, and retailers to examine how the pandemic influenced supply and demand patterns from a distribution perspective. Results indicated that while the volume of luxury seafood handled by restaurants and wholesalers decreased, the volume handled by retailers increased. Conversely, the volume of inexpensive popular seafood declined across all three sectors. The findings suggest that some of the luxury seafood previously sold to restaurants was redirected to retailers as consumer demand shifted from dining out to home consumption during the pandemic.

Commodities doi: 10.3390/commodities4020011

Authors: Tuoyuan Cheng Saikiran Reddy Poreddy Kan Chen

Weather derivative markets, particularly Chicago Mercantile Exchange (CME) Heating Degree Day (HDD) and Cooling Degree Day (CDD) futures, face challenges from complex temperature dynamics and spatially heterogeneous co-extremes that standard Gaussian models overlook. Using daily data from 13 major U.S. cities (2014–2024), we first construct a two-stage baseline model to extract standardized residuals isolating stochastic temperature deviations. We then estimate the Extreme Value Index (EVI) of HDD/CDD residuals, finding that the nonlinear degree-day transformation amplifies univariate tail risk, notably for warm-winter HDD events in northern cities. To assess multivariate extremes, we compute Tail Dependence Coefficient (TDC), revealing pronounced, geographically clustered tail dependence among HDD residuals and weaker dependence for CDD. Finally, we compare Gaussian, Student’s t, and Regular Vine Copula (R-Vine) copulas via joint VaR–ES backtesting. The R-Vine copula reproduces HDD portfolio tail risk, whereas elliptical copulas misestimate portfolio losses. These findings highlight the necessity of flexible dependence models, particularly R-Vine, to set margins, allocate capital, and hedge effectively in weather derivative markets.

Commodities doi: 10.3390/commodities4020010

Authors: Philipp Galkin Jennifer Considine Abdullah Al Dayel Emre Hatipoglu

Oil inventories are essential in alleviating realized and anticipated supply shocks and represent a key market indicator. This study examines the responses of global and country oil inventories to supply shocks under tight and loose market conditions. We utilize an expanded version of the GVAR model, adding the OECD oil inventories variable, incorporating major oil-producing countries: Iran, Russia, and Venezuela, and extending the coverage period. Our simulations indicate that a negative global supply shock significantly affects oil inventories under “tight” market conditions. The model correctly predicts the trajectory of changes to oil inventories in South Korea following a supply shock to Russian production in tight markets and Iranian output in loose markets. This case also shows that commercial players, using their inventories as a buffer, can negate government attempts to maintain constant levels of reserves. Overall, the response to the oil inventory tends to vary across producing and importing countries and market conditions. Such dynamics highlight potential problems with specific policies, such as using inventories as a buffer to alleviate price fluctuations or disrupting the oil production of individual countries through sanctions, as these measures oftentimes result in unintended consequences due to complex interconnections of the global oil market.

Commodities doi: 10.3390/commodities4020009

Authors: Mulue Gebreslasie Indranil SenGupta

In this study, Gaussian process (GP) regression is used to normalize observed commodity data and produce predictions at densely interpolated time intervals. The methodology is applied to an empirical oil price dataset. A Gaussian kernel with data-dependent initialization is used to calculate prediction means and confidence intervals. This approach generates synthetic data points from the denoised dataset to improve prediction accuracy. From this augmented larger dataset, a procedure is developed for estimating an upcoming crash-like behavior of the commodity price. Finally, multiple data-science-driven algorithms are used to demonstrate how data densification using GP regression improves the detection of forthcoming large fluctuations in a particular commodity dataset.

Commodities doi: 10.3390/commodities4020008

Authors: Richard Luan Silva Machado Rosangela Rodrigues Dias Mariany Costa Deprá Adriane Terezinha Schneider Darissa Alves Dutra Cristiano R. de Menezes Leila Q. Zepka Eduardo Jacob-Lopes

The exploitation of the Amazon biome in search of net profit, specifically in the production of cocoa (Theobroma cacao) and açaí (Euterpe oleracea), has caused deforestation, degradation of natural resources, and high greenhouse gas (GHG) emissions, highlighting the urgency of improving the environmental, economic and social sustainability of these crops. These species were selected for their rapid expansion in the Amazon, driven by global demand, their local economic relevance, and their potential to either promote conservation or drive deforestation, depending on the production system. This study analyzes the pillars of environmental, social, and economic sustainability of cocoa and açaí production systems in the Amazon, comparing monoculture, agroforestry, and extractivism to support forest conservation strategies in the biome. Analysis of the environmental life cycle, social life cycle, and economic performance were used to determine the carbon footprint, the final point of workers, and the net profit of the activities. According to the results found in this study, cocoa monoculture had the largest carbon footprint (1.35 tCO2eq/ha), followed by agroforestry (1.20 tCO2eq/ha), açaí monoculture (0.84 tCO2eq/ha) and extractivism (0.25 tCO2eq/ha). In the carbon balance, only the areas outside indigenous lands presented positive carbon. Regarding the economic aspect, the net profit of açaí monoculture was USD 6783.44/ha, extractivism USD 6059.42/ha, agroforestry USD 4505.55/ha, and cocoa monoculture USD 3937.32/ha. In the social sphere, in cocoa and açaí production, the most relevant negative impacts are the subcategories of child labor and gender discrimination, and the positive impacts are related to the sub-category of forced labor. These results suggest that açaí and cocoa extractivism, under responsible management plans, offer a promising balance between profitability and environmental conservation. Furthermore, agroforestry systems have also demonstrated favorable outcomes, providing additional benefits such as biodiversity conservation and system resilience, which make them a promising sustainable alternative.

Commodities doi: 10.3390/commodities4020007

Authors: Lauren Olsen Frederic de Mariz

Debt-for-nature instruments are financial transactions that allow countries to restructure and reduce foreign debt in exchange for investments in environmental conservation measures. Can debt-for-nature instruments attract more capital for biodiversity finance? Debt-for-nature instruments first appeared in the market in the 1980s; however, they have seen a recent surge in popularity, with transactions predominantly focused on marine conservation. These transactions have gained attention for their size, innovative nature, and conservation focus. However, they have also faced criticism surrounding sovereignty, effectiveness, and transaction costs. The descriptive qualitative analysis of a comprehensive and global sample of the eight tripartite type debt-for-nature instruments brought to market since 2015, with a detailed case study of the Belize transaction, indicates that such deals may be costly to negotiate, the use of blue bond labeling can be misleading, conservation benefits are limited, and they have limited replicability. On the positive side, these deals have introduced innovative structures to unlock additional funds for conservation. The best examples are structured with a larger financial commitment to nature and strong enforcement mechanisms. In some cases, the transaction laid the groundwork for future marine conservation funding and commitments. Debt-for-nature instruments are not a silver bullet for either environmental impact or debt refinancing; however, the benefits of recent transactions indicate a role for such innovative instruments in conservation finance.

Commodities doi: 10.3390/commodities4020006

Authors: Kentaka Aruga Md. Monirul Islam Arifa Jannat

The COVID-19 pandemic and the Russia–Ukraine war have struck the world’s energy markets. This study analyzed how the recent unstable fossil fuel markets impacted the Japanese electricity contracts, classified as extra-high-, high-, and low-voltage contracts. Multiple structural break tests were conducted to endogenously determine breaks affecting electricity prices during January 2019 to November 2022. By incorporating the effects of these breaks in the autoregressive distributed lag (ARDL) model, the study analyzed the effects of natural gas, coal, and crude oil prices on the types of electricity contract prices. The results of the analyses indicated a surge in electricity prices for low- and high-voltage contracts driven by an increase in natural gas. The results imply the importance of providing proper financial support to mitigate the effects of soaring electricity prices and implementing policies to diversify the electricity generation mix in Japan.

Commodities doi: 10.3390/commodities4020005

Authors: Narayana Maharana Ashok Kumar Panigrahi Suman Kalyan Chaudhury

This study examines the volatility and hedging effectiveness of commodities, specifically gold and oil, on the Indian stock market, focusing on both aggregate and sectoral indices. Data have been collected from 1 January 2021 to 31 December 2024 to cover the post-COVID-19 period. Utilizing the Asymmetric Dynamic Conditional Correlation Generalized Autoregressive Conditional Heteroskedasticity (ADCC-GARCH) model, we analyze the volatility spillovers and time-varying correlations between commodity and stock market returns. The analysis of spillover connectedness reveals that both commodities exhibit limited and inconsistent hedging potential. Gold demonstrates low and stable spillovers in most sectors, indicating its diminished role as a reliable safe-haven asset in Indian markets. Oil shows relatively higher but volatile spillover effects, particularly with sectors closely tied to energy and industrial activities, reflecting its dependence on external economic and geopolitical factors. This study contributes to the literature by providing a sector-specific perspective on commodity–stock market interactions, challenging conventional assumptions of hedging efficiency of gold and oil. It also emphasizes the need to explore alternative hedging mechanisms for risk management in the post-crisis phase.

Commodities doi: 10.3390/commodities4020004

Authors: Salim Lahmiri

This study analyzes the market efficiency of crude oil markets, namely Brent and West Texas Intermediate (WTI), during three different periods: pre-COVID-19, during the COVID-19 pandemic, and during the ongoing Russia–Ukraine military conflict. To evaluate the efficiency of crude oil markets, wavelet entropy is computed from price, return, and volatility series. Our empirical results show that WTI prices are predictable during the Russia–Ukraine military conflict, but Brent prices are difficult to predict during the same period. The prices of Brent and WTI were difficult to predict during the COVID-19 pandemic. Returns in Brent and WTI are more difficult to predict during the military conflict than they were during the pandemic. Finally, volatility in Brent and WTI carried more information during the pandemic compared to the military conflict. Also, volatility series for Brent and WTI are difficult to predict during the military conflict. These findings offer insightful information for investors, traders, and policy makers in relation to crude oil energy under various extreme market conditions.

Commodities doi: 10.3390/commodities4010003

Authors: Debanjan Das

Secondhand clothing has undergone a significant transformation from a vital household asset in the pre-industrial era to a dynamic segment of global trade in the 21st century. However, the advent of fast fashion has led to overproduction and mass consumption of inexpensive garments, fueling a surge in the secondhand clothing trade. Between 2002 and 2022, the market value of this industry quadrupled, with exports accounting for 1.17% of total global clothing exports in 2022. This study examines global secondhand clothing exports using export competitiveness tools such as revealed comparative advantage (RCA), the index of export market penetration (IEMP), the trade intensity index (TII), unit values, market shares, and the compound annual growth rate (CAGR). The top eleven secondhand clothing exporting countries are analyzed for a ten year period (2013 to 2022) using the United Nations Commodity Trade Statistics Database. The analysis reveals notable trends: the United States and China dominate the market, while Pakistan and the UAE exhibit the highest growth rates. The study also reaffirmed that trade patterns for secondhand clothing continue to flow from the Global North—including China—to the Global South, a trend observed since the early 2000s. This research provides a comprehensive, current analysis of the ever growing secondhand clothing export market within the sustainable management of the secondhand clothing context.

Commodities doi: 10.3390/commodities4010002

Authors: Salim Lahmiri

The article analyzes the Granger-based causal relationship between two major crude oil markets, namely Brent and West Texas Intermediate (WTI), by using the standard vector autoregression (VAR) framework. In this regard, the effects of the COVID-19 pandemic and the Russia–Ukraine war on causality between Brent and WTI are examined. The empirical results from Granger-causality tests show (a) strong causality from Brent to WTI during the period prior to the COVID-19 pandemic and Russia–Ukraine war, (b) no causality from WTI to Brent during the period prior to the COVID-19 pandemic and Russia–Ukraine war, (c) no causality from Brent to WTI during the COVID-19 pandemic, (d) evidence of causality from WTI to Brent during the COVID-19 pandemic, and (e) no evidence of causality from both markets during the period of Russia–Ukraine war. In addition, causality tests in quantiles support results from the linear Granger causality tests in general. However, contrary to the standard linear causality test, the quantile-in-regression causality test shows that Brent returns cause WTI returns during the pandemic period and WTI returns cause Brent returns before the pandemic. Furthermore, the results from the time-varying Granger causality tests support all conclusions from the standard linear (and static) Granger causality test, except the hypothesis that Brent causes WTI during the pandemic. Moreover, the time-varying Granger tests show evidence that causality between Brent and WTI clearly varies across the pandemic and war periods. Revealing the causalities between Brent and WTI across periods of economic and political stability, pandemic, and war would help policymakers develop appropriate energy policy and help investors determine appropriate risk management actions.

Commodities doi: 10.3390/commodities4010001

Authors: Julien Chevallier

The year 2024 was marked by significant unpredictability and volatility in global commodity markets, characterized by notable price fluctuations, evolving policy frameworks, and unexpected disruptions [...]

Commodities doi: 10.3390/commodities3040028

Authors: Prosper E. Edoja Goodness C. Aye Rangan Gupta

The focus of this investigation was to examine the effects of energy consumption, agricultural commerce, and productivity on CO2 emissions in Nigeria using quantile regression. Time series data from 1960 to 2021 were used. The findings revealed that the impact of agricultural raw materials imports (AGRIMs) and exports on carbon footprints is positive. There is a prevalence of a set of notable percentile differences in the conditional distribution of the variables on CO2 emissions. Initially, the coefficient of energy consumption (EnCons) was high, but constantly nosedived from the 25th quantile until it reached the 90th quantile when it picked up again, and the same was true in the case of AGRIM. Thus, a 1% increase in agricultural imports will bring about 0.0047—a significant unit increase in CO2 emissions in Nigeria from the 0.382946 coefficient in the 10th quantile to the 0.264392 coefficient in the 50th quantile, and thereafter, the effects become insignificant. Profound significant variance across disparate percentiles in the conditional spread of AGRIM, food production index (FPI), CPI, and FDI was found. It further showed that the effects of the regressors on carbon emissions differ over the quantiles. Overall, AGRIM and EnCons have positive and significant effects on carbon emission. However, the agricultural raw material export has significant negative effects on CO2 emissions as the movement (transportation) of goods within a country prior to export involves a huge level of carbon release. This study provides recommendations and policy implications.

Commodities doi: 10.3390/commodities3040027

Authors: E. M. Ekanayake

Brazil is a resource-rich economy that relies heavily on the exports of several important commodities. The variability of commodity prices affects both the economy and the stock market. This study investigates the relationship between commodity price shocks and stock returns in Brazil using a structural vector autoregressive (SVAR) model. This study uses monthly data on prices of five major export commodities, stock returns, and several control variables, covering the period from January 2010 to December 2022. To account for the Brazilian economic crisis between 2014 and 2016, we have analyzed the effects of commodity prices on stock prices in three different time periods, namely, before the economic crisis (January 2010–March 2014), during the economic crisis (April 2014–December 2016), and after the economic crisis (January 2017–December 2022). The empirical results of this study provide evidence to conclude that stock returns increase following a positive global commodity price shock or a positive exchange rate shock. The effects are more noticeable during the economic crisis in Brazil. The results also show that the volatility of Brazilian stock returns is mostly explained by global oil prices and exchange rate movements in the long run.

Commodities doi: 10.3390/commodities3040026

Authors: Stavros Karamperidis Konstantinos D. Melas Nektarios A. Michail

We examine how LNG carrier port congestion in European ports, measured via detailed vessel-level AIS data, affects euro area energy inflation. As energy inflation significantly affects headline inflation, this study provides an additional factor that can contribute to inflationary pressures. Overall, the results show that higher port congestion increases natural gas prices with the latter having an impact on energy inflation. The reaction stands at 0.1% per 1% shock in port congestion. These findings underline the relationship between the shipping industry and the real economy and support the view that shipping developments can potentially be used as leading indicators.

Commodities doi: 10.3390/commodities3040025

Authors: Jungho Baek

Since I was appointed Editor-in-Chief of the international, peer-reviewed, open access journal Commodities ISSN 2813-243 [...]

Commodities doi: 10.3390/commodities3040024

Authors: Papa Ousseynou Diop

The cryptocurrency market is characterized by extreme volatility, with events such as the Terra-LUNA crash of 2022 raising significant questions about the resilience of algorithmic stablecoins. This paper investigates the collapse of LUNA Classic during the USTC depeg, focusing on the role of trading volumes and collateral assets like Bitcoin in amplifying the price crash. Using a Vector Logistic Smooth Transition AutoRegressive (VLSTAR) model, we analyze daily data from October 2020 to November 2022 to uncover how exogenous volumes influenced LUNA’s price trajectory during the crisis. Our findings reveal that high trading volumes, particularly during regime two (the post-depeg period), significantly exacerbated the price decline, validating the impact of large-scale liquidations on LUNA’s price path. Additionally, Bitcoin volumes played a critical role in destabilizing the system, confirming that the liquidity of underlying collateral assets is pivotal in maintaining price stability. These insights contribute to understanding the systemic vulnerabilities in algorithmic stablecoins and offer implications for future stablecoin design and risk management strategies. They are relevant for investors, policymakers, and researchers seeking to be aware of market volatility and prevent future crises in stablecoin ecosystems.

Commodities doi: 10.3390/commodities3040023

Authors: K. Thomas Liaw

Property Assessed Clean Energy (PACE) programs finance energy efficiency and renewable energy improvements to residential and commercial properties with a special tax assessment added to property taxes. This paper surveys the literature and documents the quantitative estimates of the environmental and economic benefits. This paper extends to discuss the securitization of PACE loans. The issuance of PACE green bonds frees up capacity for more PACE improvements. In addition, we summarize the concerns raised after the programs have been implemented. Those concerns include consumer protection, audit after program implementation, and lien-related risks for lenders. We discuss those concerns and suggest measures to continue to grow PACE financing. The success of PACE programs will contribute to reducing carbon emissions, mitigating climate change and to achieving six of the seventeen United Nations Sustainable Development Goals (SDGs).

Commodities doi: 10.3390/commodities3040022

Authors: Bernhard Koelmel Tim Haug Leonie Klein Lukas Schwab Rebecca Bulander Henning Hinderer Matthias Weyer Tanja Brugger Ansgar Kuehn Tanja Brysch

This research paper examines the risks posed by the MIH EV Open platform to German automotive suppliers, in particular, the risk of commoditization and falling into a commodity trap. The term commodity trap describes a situation in which companies dealing with standardized products or services face intense price and margin pressure and struggle to differentiate themselves from competitors. The MIH EV Open platform, established by Foxconn, also known as Hon Hai Precision Industry Co. Ltd., headquartered in Tucheng, Taipei, Taiwan, aims to create a collaborative platform for the comprehensive development of key software, hardware components, and services in the electric vehicle (EV) industry. It unites over 2700 companies from more than 70 countries and fosters collaboration to accelerate the development and market entry of new EV products. This paper analyzes the MIH EV Open business ecosystem model and assesses the strengths and weaknesses of German suppliers in addressing these challenges. This study highlights strategic approaches, including innovation, portfolio adaptation, customer relationships, and sustainability practices, that can enable German suppliers to mitigate commodity trap risks. The findings underscore the importance of proactive, segment-specific strategies amidst the transformation of the automotive industry. Key insights are provided on the potential impact of open platform ecosystems and recommendations for German automotive suppliers to maintain competitiveness. This research fills a gap in the literature by examining the commoditization risks posed by the MIH EV Open platform for German automotive suppliers. Unlike previous studies that focus on traditional market structures, this study explores the novel dynamics introduced by platform ecosystems and provides strategic insights to mitigate these risks.

Commodities doi: 10.3390/commodities3030021

Authors: Ramesh Adhikari

This paper analyzes the return performance of various commodity futures-based dynamic portfolios over the period from 31 January 1986 to 31 July 2023. By constructing 30 distinct portfolios categorized by style and performance, we assess their potential for enhancing the performance of traditional portfolios consisting of equity and bonds. We find that most commodity portfolios do not offer statistically significant returns, either in terms of average or risk-adjusted returns. Only the portfolios in the basis category and portfolios in the term structure category exhibit significantly positive risk-adjusted returns, indicating their potential value for portfolio enhancement. The performance of these portfolios is not different in pre-financialization and financialization periods.

Commodities doi: 10.3390/commodities3030020

Authors: Yigang Wei Yan Li Julien Chevallier Michal Wojewodzki

This study evaluates the efficiency of China’s seven emission trading schemes (ETS) piloted in 2013. We evaluate seven pilots’ overall technical and scale efficiencies and temporal dynamics during 2014–2023. We use a bootstrap correction data envelopment analysis (bootstrap-DEA), which guarantees a more accurate efficiency estimation than the traditional DEA model. The results show that the average overall (pure technical) efficiency of the seven pilot markets increased from 0.612 (0.844) in 2014 to 0.898 (0.990) in 2023. Furthermore, we document that seven ETS pilots differ remarkably in efficiency and transaction price, whilst all have shortages. Specifically, the small-scale market transaction is the main constraint effect on the average scale efficiency of the ETS. This study provides concrete recommendations for policy makers to consummate institutional designs to improve ETS efficiency.

Commodities doi: 10.3390/commodities3030019

Authors: Marco Haase Jacqueline Henn

This study introduces a robust model that captures wheat futures’ volatility dynamics, influenced by seasonality, time to maturity, and storage dynamics, with minimal calibratable parameters. Our approach reduces error-proneness and enhances plausibility checks, offering a reliable alternative to models that are difficult to calibrate. Transferring estimated parameters from liquid to illiquid markets is feasible, which is challenging for models with numerous parameters. This is of practical importance as it improves the modeling of volatility in illiquid markets, where price discovery is less efficient. In liquid markets, on the other hand, where speculative activity is high, we find that implied volatility is usually the best measure. Additionally, the introduced volatility model is suitable for pricing options on wheat futures as a risk-neutral measure.

Commodities doi: 10.3390/commodities3030018

Authors: Bernhard Koelmel Leon Fischer Emilia Juraschek Levi Peuker Noah Stemmler Anton Vielsack Rebecca Bulander Henning Hinderer Katharina Kilian-Yasin Tanja Brugger Ansgar Kühn Tanja Brysch

The transition to battery electric vehicles (BEVs) poses significant challenges for automotive suppliers, particularly in the Northern Black Forest Region, Germany’s largest industrial area. This study examines the risk of falling into the commodity trap and the impact of platform economics on these suppliers. A VUCA (volatility, uncertainty, complexity, ambiguity) analysis is used to assess the consequences of the open platform approach promoted by the Mobility in Harmony (MIH) Consortium. The methodology is based on a comprehensive literature review on commodity traps and platform economies, as well as an analysis of the MIH Consortium’s strategies for standardizing BEV components. The results show that while the MIH Consortium’s modularization and standardization efforts can reduce costs and facilitate mass production, they also intensify competition and limit differentiation, threatening the profit margins of smaller suppliers. The study highlights the importance of strategic positioning and innovation to counter these risks. It concludes with recommendations on how automotive suppliers can adapt to the evolving environment and be agile in responding to new technological standards and market dynamics.

Commodities doi: 10.3390/commodities3030017

Authors: Roza Galeeva Zi Wang

The goal of this paper is to derive closed-form approximation formulas for the spread option value and Greeks by using double integration and investigating the exercise boundary. We have found that the straight-line approximation suggested in previous research does not perform well for curved exercise boundaries. We propose a novel approach: to integrate in a sector and find a closed-form formula expressed in terms of the bivariate normal CDF. We call it the sector formula. Numerical tests show the good accuracy of our sector formula. We demonstrate applications of the formula to the market data of calendar spread options for three major commodities, WTI, Natural Gas, and Corn, listed on the CME site as of May, April, and June 2024.

Commodities doi: 10.3390/commodities3030016

Authors: Bilgi Yilmaz Christian Laudagé Ralf Korn Sascha Desmettre

The dynamic structure of electricity markets, where uncertainties abound due to, e.g., demand variations and renewable energy intermittency, poses challenges for market participants. We propose generative adversarial networks (GANs) to generate synthetic electricity price data. This approach aims to provide comprehensive data that accurately reflect the complexities of the actual electricity market by capturing its distribution. Consequently, we would like to equip market participants with a versatile tool for successfully dealing with strategy testing, risk model validation, and decision-making enhancement. Access to high-quality synthetic electricity price data is instrumental in cultivating a resilient and adaptive marketplace, ultimately contributing to a more knowledgeable and prepared electricity market community. In order to assess the performance of various types of GANs, we performed a numerical study on Turkey’s intraday electricity market weighted average price (IDM-WAP). As a key finding, we show that GANs can effectively generate realistic synthetic electricity prices. Furthermore, we reveal that the use of complex variants of GAN algorithms does not lead to a significant improvement in synthetic data quality. However, it requires a notable increase in computational costs.

Commodities doi: 10.3390/commodities3030015

Authors: Julien Chevallier

Election cycles have been called for in many countries for 2024, including [...]

Commodities doi: 10.3390/commodities3020014

Authors: Gurdip Bakshi Xiaohui Gao Zhaowei Zhang

In this study, we investigate the ability of three higher-order risk-neutral return cumulants to predict short maturity (weekly) returns of oil futures. Our data includes weekly West Texas Crude Oil futures options that expire in 7 days (7DTE). Using a model-free approach, we estimate these risk-neutral return cumulants at the beginning of each options expiration cycle. Our results suggest that the third risk-neutral return cumulant consistently predicts the returns of various oil futures (including WTI, Brent, Dubai, Heating Oil, and RBOB Gasoline). We compare our findings with 14 other predictors and offer a theoretical explanation for the negative coefficient observed for the 7DTE third risk-neutral return cumulant. Our theory connects higher-order risk-neutral return cumulants with the risk premiums of oil futures. Furthermore, our quantitative investment strategy favors the predictability of oil futures returns.

Commodities doi: 10.3390/commodities3020013

Authors: Bahattin Büyükşahin Michel A. Robe

We revisit, and document new facts regarding, the financialization of U.S. energy markets in 2000–2010. We show that, after controlling for macroeconomic factors and physical energy market fundamentals, the strength of energy markets’ co-movements with the U.S. stock market is positively related to the energy paper market activity of hedge funds that trade both asset classes. This relation weakens when credit risk is elevated. We find, in contrast, no link with the aggregate positions of commodity index traders in energy futures markets. Our findings have implications for the ongoing debate regarding the financialization of commodities.

Commodities doi: 10.3390/commodities3020012

Authors: Kentaka Aruga Hiroki Wakamatsu

The COVID-19 pandemic, with increased home cooking and decreased restaurant dining, significantly altered seafood consumption patterns. By applying an ordered logit model to identify factors affecting seafood consumption during the pandemic, this study found that the shift in seafood consumption was driven by factors such as changes in meal preparation methods, more time spent at home, and shifts in financial situations. While take-out consumption boosted overall seafood intake, popular varieties saw a rise in home consumption, while high-end seafood suffered from decreased demand as consumers focused more on home dining. This study underscores the importance of supporting suppliers, restaurants, and retailers dealing with high-end seafood, as they face economic challenges due to reduced consumption. In summary, pandemic-induced restrictions on mobility led to a notable transition from restaurant-prepared seafood to home-cooked options, highlighting the need for targeted policies to aid affected sectors.

Commodities doi: 10.3390/commodities3020011

Authors: Houssem Eddine Hamdaoui Maite Cancelo

This study aims to investigate the impact of the banking sector on economic growth and commodity prices. Through panel data analysis, the research explores the relationship between the banking sector and economic growth in Spain, France, and Romania from 2000 to 2020. The findings reveal a positive correlation between the strength of the banking sector and economic growth across these nations, underscoring its pivotal role in fostering economic expansion and subsequently improving commodity prices. Additionally, this study evaluates various regulatory measures crucial ensuring the banking sector’s sustainability and preventing financial crises, including credit risk management, lending policies, liquidity constraints, and international financing and investment strategies. By analyzing the interplay between regulatory measures and banking sector performance, incorporating variables such as non-performing loans, household debt, liquid liabilities, government consumption expenditure, foreign investments, and trade openness, this research provides policymakers with valuable insights to formulate effective strategies for promoting economic stability and ensuring the sustainability and growth of the banking sector.

Commodities doi: 10.3390/commodities3020010

Authors: Antaya March Tegan Evans Stuart Laing Jeremy Raguain

The Seychelles blue bond is an innovative finance mechanism that has played a pivotal role in shaping the global landscape of blue bonds. Seychelles leadership in the blue economy sets a significant precedent. However, this precedent has also raised concerns among various stakeholders. This study evaluates of Seychelles’ sovereign blue bond, which was co-developed by the government of Seychelles and the World Bank. Three themes are explored, how the blue bond relates to other actors and donors in the blue economy space of Seychelles; how the blue bond contributes to advancing the national agenda and blue economy of Seychelles; and the key strengths, enablers and weaknesses of the blue bond. A series of considerations for future blue financing and blue bond mechanisms are presented, based on the findings of this study, to ensure that financing extends beyond blue washing and contributes meaningfully to the holistic transition to a sustainable blue economy. Our findings imply significant considerations for stakeholders in sustainable finance, suggesting ways to enhance the efficacy of blue bonds and emphasising the need for further research on their long-term impact and integration with other financial instruments.

Commodities doi: 10.3390/commodities3020009

Authors: Ionuț Nica Nora Chiriță

This study presents a comprehensive bibliometric analysis conducted in R Studio of the scientific landscape regarding commodity markets, trading strategies, sustainable production, integration of technologies such as machine learning, and their economic impacts, covering publications from 1974 to 2023. Employing a sophisticated query in Scopus, we meticulously compiled and analyzed data, revealing an annual growth rate of 10.46% in related scientific publications, with an average citation rate of 6.60 per document. The results indicate sustained interest in commodity research over time, with a significant increase observed in scientific production, particularly since the early 2008s. International collaboration is prominent, reflecting the global nature of research in commodity markets. Key themes such as “futures markets”, “commodity prices”, and “energy commodities” emerge from the analysis of keywords and bigrams, highlighting areas of interest within the field. Additionally, thematic mapping highlights emerging and niche themes in commodity research, providing insight into evolving trends and areas of specialization. Factorial analysis of keywords reveals the underlying structures of association between key concepts, shedding light on the intricate dynamics of research in the field of commodities. This research delineates the complex interplay between commodity markets and global economic dynamics, offering invaluable insights for academics, policymakers, and market participants aiming to navigate the intricate world of commodities in the digital age.

Commodities doi: 10.3390/commodities3010008

Authors: Amit K. Sinha

Gold prices have been of major interest for a lot of investors, analysts, and economists. Accordingly, a number of different modeling approaches have been used to forecast gold prices. In this manuscript, the geometric Brownian motion approach, used in the pricing of numerous types of assets, is used to forecast the prices of gold at yearly, monthly, and quarterly frequencies. This approach allows for simulating one-period-ahead prices and the associated probabilities. The expected prices obtained from the simulated prices and probabilities are found to provide reliable forecasts when compared with the observed yearly, monthly, and quarterly prices.

Commodities doi: 10.3390/commodities3010007

Authors: Ezio Lauro Amélie Têtu Hélyette Geman

Real assets in the energy market are subject to ecological uncertainty due to the penetration of renewables. We illustrate this point by analyzing electrolyzers, a class of assets that recently became the subject of large interest, as they lead to the production of the desirable green hydrogen and green ammonia. The latter has the advantage of being easily stored and has huge potential in decarbonizing both the fertilizer and shipping industries. We consider the optimization of green ammonia production with different types of electricity procurement in the context of stochastic power and ammonia markets, a necessary assumption to translate the features of renewable, hence intermittent, electricity. We emphasize the importance of using stochastic prices to model the volatile nature of the price dynamics effectively, illustrating the project risks that hedging activities can mitigate. This study shows the pivotal role of flexibility when dealing with fluctuating renewable production and volatile electricity prices to maximize profits and better manage risks.

Commodities doi: 10.3390/commodities3010006

Authors: Celso Brunetti Jeffrey H. Harris Bahattin Büyükşahin

We analyze the role of hedge fund, swap dealer, and arbitrageur activity in the crude oil market. The contribution of our work is to examine the role of institutional traders in switching between high-volatility and low-volatility regimes. Using confidential position data on institutional investors, we first analyze the linkages between trader positions and fundamentals. We find that these institutional position changes reflect fundamental economic factors. Subsequently, we adopt a Markov regime-switching model with time-varying probabilities and find that institutional position changes contribute incrementally to the probability of regime changes.

Commodities doi: 10.3390/commodities3010005

Authors: Jungho Baek

The paper conducts extensive research on how Alaska’s oil production is affected by shocks in oil supply, aggregate demand, and oil-specific demand under both symmetric and asymmetric scenarios. We demonstrate that employing an empirical model with the inclusion of an asymmetric assumption provides a more suitable approach for comprehensively understanding the short and long-term impacts of various oil shocks on Alaska’s oil production. We also find that Alaska’s oil production is significantly affected by oil supply and aggregate demand shocks over both short and long periods, whereas oil-specific demand shocks have a minimal impact. Finally, our research identifies asymmetric effects in the long term, particularly concerning the influence of aggregate demand and oil-specific demand shocks on Alaska’s oil production. However, no asymmetric effects are observed for the three oil shocks in the short term.

Commodities doi: 10.3390/commodities3010004

Authors: Ramesh Adhikari Kyle J. Putnam

This paper examines the relationship between commodity index returns and the Office of Financial Research Financial Stress Index (OFR FSI). Utilizing the S&P GSCI and its five sub-indices (agriculture, livestock, energy, industrial metals, and precious metals), we find that the causal relationship between financial market stress and commodity index returns is conditional on the sample period examined and the methodology employed. We also note that stress in financial markets has a negative relationship with commodity index returns during low commodity return states; however, during high commodity return states, financial market stress exhibits a positive relationship with commodity index returns. Our findings highlight the importance of considering a time-varying framework for analyzing commodity return dynamics.

Commodities doi: 10.3390/commodities3010003

Authors: Jungho Baek

As we delve into the realm of economic research concerning commodities, it becomes increasingly evident that the contemporary world is marked by constant change and evolving dynamics [...]

Commodities doi: 10.3390/commodities3010002

Authors: Roman Kopych Viktor Shevchuk

Using quarterly data for the 2002–2022 period, we estimate the output and inflation effects of several commodity prices (agricultural raw materials, crude oil, and metals) for 8 Eastern European countries with different exchange rate regimes. The Kalman filter is used for estimating the time-varying parameters. Our main findings can be summarized in the following way: (i) higher crude oil prices are inflationary in most of the countries (except Slovakia), with a stronger price effect since 2020; (ii) crude oil prices are neutral with respect to output growth in 4 out of 8 countries, with an expansionary effect in Croatia, Slovenia, and Romania, as well as a contractionary effect in Slovakia, but the crude oil shock of 2021–2022 seems to be expansionary in almost all countries (except Slovakia), regardless of the exchange rate regime practiced; (iii) inflation and output effects of metals prices are quite heterogeneous across countries; (iv) agricultural raw material prices play a role in both inflation and output growth only in Bulgaria and Poland. Since 2021, a growing inflationary impact of crude oil prices suggests a stronger monetary policy reaction to the oil shock, especially in the presence of its favorable output effect.

Commodities doi: 10.3390/commodities3010001

Authors: Sèna Kimm Gnangnon

The effect of trade-related government expenditure on backward and forward participation in global value chains (GVCs) is at the heart of the present analysis. The latter builds on an unbalanced panel dataset of 74 developing countries over the annual period from 2005 to 2018. It has used several estimators, the primary one being the Quantile via Moments approach. The outcomes suggest that trade-related government expenditure exerts no significant effect on countries’ forward participation in GVCs. At the same time, countries located in the 20th to 90th quantiles experience a positive and significant effect of trade-related government expenditure on backward participation in GVCs, with the magnitude of this positive effect being larger for countries in the upper quantiles than for countries in the lower quantiles. The least integrated countries into the backward participation in GVCs (i.e., those in the 10th quantile) experience no significant effect of trade-related government expenditure on backward participation in GVCs. Interestingly, expenditure in favour of developing economic infrastructure, and expenditure for enhancing productive capacities reinforce each other in positively affecting backward GVC participation by countries located in the upper quantiles (i.e., the 50th to 90th quantiles). However, the interaction between these two types of trade-related government expenditure does not influence countries’ forward participation in GVCs. These findings shed light on the importance of trade-related expenditure for enhancing developing countries’ participation in backward GVCs.

Commodities doi: 10.3390/commodities2040024

Authors: Shabbir Ahmad

Innovation and technology are important tools for delivering efficiency and productivity improvement in the minerals sector. The uptake of technologies has proven to be an important lever for increasing the productivity of the mining sector. This paper provides a comprehensive analysis of mine-level productivity using global data of copper, gold, and platinum from 1991 to 2020. Various drivers of productivity have been analysed to draw policy insights. Empirical findings reveal significant disparities in terms of technical efficiency and productivity across mines and regions. The further decomposition of total factor productivity (TFP) into its different components suggests that the adoption of innovative practices and investment in technology adoption could improve the overall productivity of these commodities sectors. Our findings also suggest that an appropriate input mix and optimal scale of production could boost platinum mining productivity. Regional disparities in the productivity of different commodities sectors (e.g., South Africa vs. Zimbabwe) give policymakers insights into how to support production scale and productivity through appropriate input mixes.

Commodities doi: 10.3390/commodities2040023

Authors: Renata G. Alcoforado Alfredo D. Egídio dos Reis Wilton Bernardino José António C. Santos

This study analyses a series of live cattle spot and futures prices from the Boi Gordo Index (BGI) in Brazil. The objective is to develop a model that best portrays this commodity’s behaviour to estimate futures prices more accurately. The database created contains 2010 daily entries in which trade in futures contracts occurs, as well as BGI spot sales in the market, from 1 December 2006 to 30 April 2015. One of the most important reasons why this type of risk needs to be measured is to set loss limits. To identify patterns in price behaviour in order to improve future transaction results, investors must analyse fluctuations in asset values for longer periods. Bibliographic research reveals that no other study has conducted a comprehensive analysis of this commodity using this approach. Cattle ranching is big business in Brazil given that in 2021, this sector moved BRL 913.14 billion (USD 169.29 billion). In that year, agribusiness contributed 26.6% of Brazil’s total gross domestic product. Using the proposed risk modelling technique, economic agents can make the best decision about which options within these investors’ reach produce more effective risk management. The methodology is based on Holt–Winters exponential smoothing algorithm, autoregressive integrated moving-average (ARIMA), ARIMA with exogenous inputs, generalised autoregressive conditionally heteroskedastic and generalised autoregressive moving-average (GARMA) models. More specifically, five different methods are applied that allow a comparison of 12 different models as ways to portray and predict the BGI commodity behaviours. The results show that GARMA with order c(2,1) and without intercept is the best model. Investors equipped with such precise modelling insights stand at an advantageous position in the market, promoting informed investment decisions and optimising returns.

Commodities doi: 10.3390/commodities2040022

Authors: Tarjei Kristiansen

This paper conducts an empirical analysis of risk premiums in the Brazilian electricity market, a critical but understudied field. Employing two distinct methodologies—Average Forward Prices and Last Observed Forward Prices—the study calculates risk premiums between spot and forward electricity prices. Our analysis consistently identifies negative risk premiums, which serve as indicators that the market may be underestimating certain types of risk. These underestimations are potentially influenced by inherent market uncertainties, including volatile demand, unpredictable supply, and frequent regulatory shifts. Additionally, we observe a high volatility in risk premiums, signifying a dynamic and ever-changing market where expectations are continuously recalibrated. Such conditions present possible arbitrage opportunities for market actors and underline the need for policymakers to introduce measures mitigating market unpredictability. By focusing on these nuances, this paper enriches the broader discourse on risk premiums in electricity markets and underscores the necessity for further research aimed at devising effective risk management strategies.

Commodities doi: 10.3390/commodities2040021

Authors: Leokadia N. P. Ndjuluwa John A. Adebisi Moammar Dayoub

Climate change, soil erosion, and degradation among others affect the growth and production of crops. Soil is suffering from intensive farming and unsustainable soil disturbance, leading to severe soil degradation. The Internet of Things (IoT) allows the monitoring of crucial environmental parameters such as soil nutrients, moisture, humidity, and temperature. A pre-understanding of these parameters allows agriculturists to use the optimum quantity of water and fertilizer for different types of soil. Soil fertility can be detected by using NPK sensors. The Internet of Things (IoT) brought a new face to the crop farming approach where conventional methods are automated and/or remotely controlled to improve crop farming. In this paper, a survey on IoT technologies for crop farming including sensors, communication, and network protocols in crop farming activities is considered. Additionally, applications of IoT technologies in soil management and monitoring, growth and yield estimation, and quality control mechanisms are presented.

Commodities doi: 10.3390/commodities2040020

Authors: Casey Watters

This paper offers an in-depth exploration into the intricate world of decentralized digital assets (DDAs), shedding light on their categorization as currencies, commodities, or securities. Building on foundational cases such as SEC v. Howey, the analysis delves into the current controversies surrounding assets like XRP and LBC, exploring the nuances in their classification. By highlighting the challenges of defining categories of DDAs within traditional legal frameworks, this study emphasizes the need for a simple taxonomy that encapsulates the dynamism of digital currencies while permitting flexibility. A proposed framework aims to simplify the categorization process while respecting recent jurisprudence, ensuring regulatory clarity for developers and users of DDAs.

Commodities doi: 10.3390/commodities2040019

Authors: Pauline Braun Andrew Knight

Conventional seafood production contributes to some of the most alarming global problems we face at present, such as the destabilization of aquatic ecosystems, human health risks, and serious concerns for the welfare of trillions of aquatic animals each year. The increasing global appetite for seafood necessitates the development of alternative production methods that meet consumer demand, while circumventing the aforementioned problems. Among such alternatives, cell-based seafood is a promising approach. For its production, cells are taken from live aquatic animals and are cultivated in growth media, thus making the rearing, catching, and slaughtering of a great number of animals redundant. In recent years, this alternative production method has transitioned from aspiration to reality, and several cell-based seafood start-ups are preparing to launch their products. Market success, however, has been reckoned to largely depend on consumer attitudes. So far, there has been little research exploring this within Asia, and none in Japan, which has one of the highest seafood consumption footprints per capita globally. The present study explores cell-based seafood-related knowledge, attitudes and behavioral intentions of Japanese consumers (n = 110) via a questionnaire-based, quantitative analysis. Although findings suggest low awareness of the concept of cell-based seafood, attitudes and intentions were positive overall, with about 70% of participants expressing an interest in tasting, and 60% expressing a general willingness to buy cell-based seafood. Younger age was significantly associated with more positive attitudes, while prior knowledge of cell-based seafood was strongly linked to willingness to pay a premium for cell-based products. While highlighting the need for information campaigns to educate Japanese consumers about cell-based seafood, this study’s findings suggest the Japanese market to be moderately ready for the launch of such products.

Commodities doi: 10.3390/commodities2030018

Authors: Mst Shanaz Akter Md Taj Uddin Aurup Ratan Dhar

This study examined the rearing and management methods, financial profitability, and consumer perceptions towards safe broiler production in Bangladesh. Employing stratified random sampling, 60 participants (30 farmers and 30 consumers) from two sub-districts in Mymensingh district were interviewed. A mix of descriptive, mathematical, and statistical approaches was used for data analysis and representation. This study identified key components of safe broiler management, including brooding, housing, feed and water management, lighting, litter maintenance, medication and vaccination, and biosecurity and hygiene control. A benefit–cost of 1.40 obtained from profitability analysis indicated the profitability of safe broiler farming. Consumer awareness of safe broiler meat was assessed using the Likert scale, highlighting the significance of nutrition, packaging, freshness, taste, and natural ingredients in purchasing decisions. The Logit model revealed that factors such as meat size, freshness, taste, and family income significantly impacted consumer purchasing choices. The main challenges faced by safe broiler producers included high prices and limited availability of feed, day-old chicks, medicine and vaccines, and lack of knowledge. To ensure efficient safe broiler production in Bangladesh, this study recommends the implementation of stable input supplies, accessible credit, skill development, and infrastructure enhancement.

Commodities doi: 10.3390/commodities2030017

Authors: Eyden Samunderu

This paper applies a two-tier model based on fuel hedging (model 1) and the testing of the impact of commodity risk on airline capacity forecasting, which is based on a system dynamics framework (model 2). Model 1 provides a comprehensive examination of the worldwide airline industry, including an analysis of the statistical impact of oil price fluctuations on the sector and the corresponding hedging strategies employed by airlines. This study examines a sample of North American and European airlines over a 10-year timeframe to assess the degree to which these airlines have engaged in kerosene hedging for future periods and the potential impact of such hedging on their corporate value and performance. In model 2, the author integrates a capacity-forecasting model within the system dynamics framework, drawing upon the theory of capacity forecasting. The study examines the impact of commodity risk by analysing the influence of fluctuations in the jet fuel spot price on the average airfare and its subsequent effects on other interdependent capacity variables. The hypotheses presented in this study were formulated based on a comprehensive review of the relevant literature and a causal feedback loop diagram. The diagram effectively depicts the dynamic interrelationships between capacity forecasting and risk variables. Furthermore, the diagram capturing causal feedback loops was transformed into a stock-flow diagram. This diagram was then utilised to evaluate the hypotheses that were derived using a dataset that pertains to the domestic airline market in the United States. The verification of the qualitative and quantitative models demonstrates the proven impact of commodity risk on capacity forecasting.

Commodities doi: 10.3390/commodities2030016

Authors: Amel Melki Ahmed Ghorbel

This study aims at examining whether hedging emerging Eastern Europe stock markets with commodities sectors can help in reducing market risks and whether it has the same effectiveness among different sectors. As an attempt to achieve this goal, we opt for three types of MGARCH model. These are DCC, ADCC and GO-GARCH, which are used with each bivariate series to model dynamic conditional correlations, optimal hedge ratios and hedging effectiveness. Rolling window analysis is used for out-of-sample one-step-ahead forecasts from December 1994 to June 2022. The results have shown that the commodities sectors of industrial metals and energy represent the optimal hedging instruments for emerging Eastern Europe stock markets as they have the highest hedging effectiveness. Additionally, our empirical results have proved that hedge ratios estimated by the DCC and ADCC models are very similar, which is not the case for GO-GARCH, and that hedging effectiveness is preferably estimated by the ADCC model.

Commodities doi: 10.3390/commodities2030015

Authors: J. Ignacio Del Rio Paulina Fernandez Emilio Castillo Luis Felipe Orellana

The challenges climate change poses require careful consideration and addressing within specific industries. In the mining context, climate change introduces potential limitations to the sustainable sourcing of minerals, thereby amplifying the criticality of several metals. However, most studies examining mineral criticality fail to assess the localized impacts of climate change, despite significant variations occurring at a relatively small scale. In this study, we propose a methodological approach for conducting a climate risk assessment in the mining industry, encompassing the identification of relevant hazards, vulnerabilities, and exposure specific to the sector. To illustrate the application of this approach, we utilize micro-level data for the Antofagasta region in Chile, a prominent mining cluster situated in a country projected to be profoundly affected by climate change. The findings of this study underscore the necessity for coordinated efforts in adaptation and climate resilience while offering a valuable tool for allocating resources to more vulnerable locations, thus strengthening the mineral supply chain.

Commodities doi: 10.3390/commodities2030014

Authors: Barbara Sawicka Piotr Barbaś Dominika Skiba Barbara Krochmal-Marczak Piotr Pszczółkowski

(Background) Raspberry (R. idaeus L.) is very popular with consumers around the world for its intense flavor, attractive appearance, and health benefits. In recent years, interest in healthy eating and natural products has increased, and raspberry fits perfectly into these trends, which translates into its greater importance on the consumer market. (Aim) The aim of this study was the commodity evaluation of raspberry fruits bearing fruit on 2-year-old shoots, cultivated under conditions of varied nitrogen fertilization against the background of constant phosphorus-potassium fertilization. (Methodology) The first-order factors were cultivars (‘Laszka’ and ‘Glen Ample’), and the second-order factor was nitrogen fertilization (0, 50, 100, and 150 kg N ha−1), against the background of constant phosphorus-potassium fertilization (100 kg P2O5 and 120 kg K2O ha−1). The experiment was set up in a dependent split-plot design with three repetitions. (Results) The importance of raspberry on the consumer market was shaped by taste and quality of fruit, health benefits, naturalness and freshness, universality of use, availability, and nutritional trends. (Conclusions) The tested cultivars were characterized by similar production and quality capabilities. Fertilization of the tested cultivars with a dose of 135 kg N·ha−1 turned out to be justified in terms of yield. Increasing nitrogen doses resulted in a significant increase in fresh fruit yield and fruit weight. Different doses of nitrogen increased fruit resistance to mechanical damage, firmness, and quality indices.

Commodities doi: 10.3390/commodities2030013

Authors: Kamesh Anand K Aswini Kumar Mishra

Evaluation of market connectedness and asymmetric volatility spillover has recently seen a surge in financial risk analytics and portfolio diversification. We carried out a meta-literature review on connectedness and spillovers, providing solid insight into the research field and robust guidelines for future investigation. The review consists of a quantitative bibliometric analysis of 594 papers and a qualitative content analysis of 77 papers covering 1991 to 2021. The results of the meta-citation analysis show that Diebold’s Spillover index (2007) is the predominant method in most works as far as market connectedness and spillover are concerned. With an extensive review, we achieved the following objectives: (1) Analyze the most influential authors, journals, and publications. (2) Understand the research streams and most studied streams. (3) Understand the theme’s structure, thematic evolution, and keyword trends. (4) Examine the pattern of collaboration and most productive affiliations. (5) Explore future research directions and untapped areas. The content analysis revealed the following important research streams in the current literature: (1) Asymmetries in market connectedness. (2) Influence of macro factors in market connectedness and spillover. (3) The role of oil in market spillovers and hedging portfolios. (4) Dynamic cross-market connectedness and spillovers. Our study is the first to employ a meta-review to assess the domain of market connectedness; thus, our work will significantly contribute to macroeconomic policymakers, researchers and hedging investors.

Commodities doi: 10.3390/commodities2030012

Authors: Jungho Baek

This article studies the asymmetric effects that the price of crude oil has on Korean exports to and imports from its largest partners—China, the U.S., and Japan—controlling for world trade policy uncertainty. The results support the evidence of the long-run asymmetry of oil prices for Korea’s exports to Japan, and imports from China and Japan. However, there is no evidence of the short-run asymmetry of oil prices. Finally, world trade policy uncertainty appears to be more important for determining Korea’s bilateral trade in the short run than in the long run.

Commodities doi: 10.3390/commodities2020011

Authors: Subhadip Ghosh Shahidul Islam

The import demand for energy resources, including liquefied natural gas (LNG), has been steadily increasing in the Asia-Pacific region. Australia, the Middle East (Qatar), the Russian Federation, and the U.S. are the major players who compete strategically to capture this ever-growing market for LNG. The objective of this paper is to examine the potential for Canada’s entry into this market as another LNG exporter and what impact that can have on the existing suppliers. Using a game-theoretic LNG export competition model, we explore the conditions under which Canada can make a profitable entry. We also investigate the effect of Canada’s entry on the profitability of the four incumbent exporters. Employing a multi-leader Stackelberg model, we found that Canada’s entry could be a Pareto superior outcome under certain conditions because it benefits all competing firms and consumers. Further, Canada’s entry into the LNG export market always helps the low-cost incumbent firms by increasing their output and profit. However, the high-cost incumbent firms’ output falls, while their profit may increase or decrease depending on the unit cost and market size parameters. With differential export costs between Canada and the U.S., the latter has an incentive to act strategically to affect the entrance of the former.

Commodities doi: 10.3390/commodities2020010

Authors: Julien Chevallier

Asset markets have long contained a section devoted to commodities, breaking them into «soft», «grains», «metals», «energy», etc [...]

Commodities doi: 10.3390/commodities2020009

Authors: Ibrahim Niftiyev Gubad Ibadoghlu

Understanding long-term agricultural productivity is essential for designing agricultural policies, planning and targeting other economic policies (e.g., industrial policy), and managing agricultural business models. In a developing and oil-rich country such as Azerbaijan, agriculture is among the limited opportunities to diversify oil-based value added and address broad welfare issues, as farmers and agricultural workers account for a large share of total employment and the labor force. However, previous studies have not focused on an empirical assessment of the long-term and subsectoral productivity of crop commodities. Rather, they have used a highly aggregated and short-run perspective, focusing mainly on the impact of the oil sector on agricultural sectors. Here, we applied principal component analysis and hierarchical cluster analysis to identify similarities and differences in the productivity of specific crop commodities (e.g., cotton, tea, grains, tobacco, hay, fruits, and vegetables) between 1950 and 2021. We show that some crops are similar in terms of their variation, growth rates, and transition from the Soviet era to the post-Soviet period. Although the dynamics of change are different for food and non-food crops and for high- and low-productive commodities, it is still possible to narrow down specific subsectors that could reach the same productivity levels. This helps map out the productivity levels of crop commodities over time and across different subsectors, allowing for better policy decisions and resource allocation in the agricultural sector. In addition, we argue about some outlier commodities and their backward status despite extensive government support. Our results provide a common basis for policymakers and businesses to focus specifically on productivity and profitability from an economic standpoint.

Commodities doi: 10.3390/commodities2020008

Authors: Pick-Schen Yip Wee-Yeap Lau Robert Brooks

This paper investigates the liquidity effect of the U.S. QE on the sovereign yield spreads of commodity-exporting countries by employing the two-stage least squares approach. The key contributions of the paper are in terms of our empirical findings. First, our results show that the U.S. QE has an economically and statistically significant liquidity effect in terms of both the HPW illiquidity measure and the TIPS liquidity premium. This is of policy importance because adjusting for the liquidity premium is a key stage in modeling inflationary expectations. Second, our results show that the U.S. QE reduced the liquidity premium with improved market liquidity and hence reduce sovereign yield spreads of most commodity-exporting countries. This finding is of macroeconomic importance as reduced sovereign yield spreads have been shown to lead to higher real activity and higher credit activity.

Commodities doi: 10.3390/commodities2020007

Authors: Khalil Alnabulsi Emira Kozarević Abdelaziz Hakimi

The main purpose of this paper is to present a systematic literature review of studies on the determinants of non-performing loans (NPLs) published over the period 1987–2022. This paper reviewed 76 studies in 58 peer-reviewed journals. The provocation for this analysis is that the issue of NPLs is attributed to close attention from policymakers and is currently addressed with various measures. The authors synthesize the literature according to the following main boards: macroeconomic factors, bank-specific factors, and industry factors. This study tries to construct the main findings from the numerous studies that are performed concerning NPLs and their determinants. The authors’ motivation is to provide a detailed perspective on NPLs. Hence, this study provides a complete and coherent framework for the researchers to examine the varied NPL literature.

Commodities doi: 10.3390/commodities2020006

Authors: Elie Kapengut Bruce Mizrach

On 15 September 2022, the Ethereum network adopted a proof-of-stake (PoS) consensus mechanism. We study the impact on the network and competing platforms in a two month event window around the Beacon chain merge. We find that the transition to PoS has reduced energy consumption by 99.98%. Miners have not transformed into validators, and total block reward income (in USD) has fallen by 97%, though transaction fees (in ETH) for Ether have increased nearly 10%. The Herfindahl index for the top 10 is 1009; the network is 19% less concentrated after the merge. Ethereum supply growth has been deflationary since the merge. The time between consecutive blocks is now steady at 12 s and transactions per day are up 7.0%. On Polygon, Matic fees rose but token fees fell. Polygon also slows, processing 3.3% fewer transactions per day. Solana’s fees fall by $0.0003, and transactions per day are down 48%. Stablecoin transfer volumes fall on Ethereum and Polygon, but rise on Solana.

Commodities doi: 10.3390/commodities2010005

Authors: Jungho Baek

Studying the exchange rate effect of oil price shocks is one focus of a rapidly growing area of empirical research [...]

Commodities doi: 10.3390/commodities2010004

Authors: Rachel Rose Dimitrios Paparas

The UK milk market has faced major economic difficulties over the last 20 years, seeing the smallest milk producers exit the industry. The key objective of this study is to examine price transmission within the UK milk market to understand the market’s efficiency and influences. An Augmented Dickey–Fuller unit root test identified all the examined series were stationary at the first difference. A modified Dickey–Fuller test allows for levels and trends that differ across a single break date and Bai–Perron test identified multiple structural breaks, including January 2012, July 2015, and November 2017. The Johansen cointegration test identified one cointegrating factor. The Error Correction Model results identified that prices would regain equilibrium at 14%, roughly 7 months after a price shock. Granger Causality identified the producer to granger cause retailer prices. The Threshold Autoregressive model suggests the dataset is symmetric. Econometric research into the UK’s liquid milk market is limited. As such, this study will provide an understanding as to whether current econometric policies are working, alongside the potential to aid the improvement or development of new policies while the UK exits the EU. Additionally, this study includes structural breaks as previous studies have failed to do so, which has led to a mixture of results.

Commodities doi: 10.3390/commodities2010003

Authors: Ramadas Sendhil Kashish Arora Sunny Kumar Priyanka Lal Arnab Roy Ramalingam Jayakumara Varadan Sivasankar Vedi Anandan Pouchepparadjou

Uncertain price movement in staple food commodities puts agrarian economies at risk if not monitored and managed consistently. Hence, an attempt has been made to analyze the price behavior and integration across major wholesale and retail markets for rice and wheat in India. Monthly data (July 2000 to June 2022) on prices viz. wholesale and retail were sourced from the Food and Agriculture Organization and analyzed using growth rate, instability index, seasonal price index, Bai-Perron’s test for structural breaks, Johansen’s test on cointegration, Granger causality test, and impulse response function. Findings indicated strong evidence of price dynamics in the selected markets in terms of spatial and temporal variation, clear-cut seasonality linking to production, and price divergence between wholesale and retail markets. Johansen’s test indicated a strong cointegration between wholesale and retail prices after accounting for structural breaks, exhibiting unidirectional-, bidirectional- and no causality. Impulse response analysis revealed that the selected wheat and rice markets are efficient in terms of ‘price discovery’ which takes place initially in the wholesale market, and is then transmitted to the retail market. The study advocates decision-making information to the producers, traders, and consumers who are interested in taking advantage of the price movement. It is concluded that strengthening the market intelligence and reducing the distortion in markets will improve the existing overall performance.

Commodities doi: 10.3390/commodities2010002

Authors: Julien Chevallier

The pandemic crisis of COVID-19 hit the financial markets like a shockwave on 16 March 2020. This paper attempts to capture which ‘safe assets’ asset managers could have fled during the first wave of the pandemic. From an investment manager’s perspective, candidate assets are stocks, bonds, exchange rates, commodities, gold, and (gold-backed) cryptocurrencies. Empirical tests of the ‘Safe-Haven’ hypothesis are conducted, upon which the selection of assets is performed. The methodological framework hinges on the Global Minimum Variance Portfolio with Monte Carlo simulations, and the routine is performed under Python. Other optimization techniques, such as risk parity and equal weighting, are added for robustness checks. The benchmark portfolio hits a yearly profitability of 7.2% during such a stressful event (with 3.6% downside risk). The profitability can be enhanced to 8.4% (even 14.4% during sub-periods) with a careful selection of ‘Safe assets’. Besides short- to long-term U.S. bonds, we document that investors’ exposure to Chinese, Argentinian, and Mexican stocks during COVID-19 could have been complemented with Swiss and Japanese currencies, grains, physical gold mine ETFs, or gold-backed tokens for defensive purposes.

Commodities doi: 10.3390/commodities2010001

Authors: Marie Steen Olvar Bergland Ole Gjølberg

It is widely recognized that climate change makes the weather more erratic. As the combination of temperature and precipitation is a major driver of grain crop productivity, more frequent extreme rainfalls and heat waves, flooding and drought tend to make grain production and hence grain prices more volatile. We analyze daily prices during the growing season for corn and wheat over the period 1971–2019 using an EGARCH model. There have been occasional spikes in price volatility throughout this period. We do not, however, find that grain prices have become more volatile since the 1970s, with an exception for a small but statistically significant upward trend in wheat price volatility. To the extent that climate change has caused more frequent weather extremes affecting crop yields, it appears that the price effects have been softened, most likely through farmers’ adaption to climate changes, introduction of more stress-tolerant hybrids, storage, regional and international trade and risk management instruments.

Commodities doi: 10.3390/commodities1020012

Authors: Jungho Baek

Many empirical studies have examined the role of oil price fluctuations on macroeconomic activities [...]

Commodities doi: 10.3390/commodities1020011

Authors: Fjona Zeneli

Energy and grain markets are historically connected since oil, natural gas, and/or coal are used as inputs for fertilizers’ production or transportation costs. The recent rising prices in the energy market following important events such as the COVID-19 pandemic and the Russia-Ukraine conflict have again brought attention to researchers. The focus of this paper is to assess any changes in the relationships between crude oil, natural gas, and grain prices contributing to the review of the fuel-food relationship using time series models. Several techniques that account for structural breaks and regime shifts (Zivot-Andrews and Clemente, Montañés, Reyes unit root tests, Johansen’s cointegration test, and Toda-Yamamoto time domain causality test with time dummy variables for structural breaks, and Hatemi-J asymmetric causality test) are applied for monthly data covering the period from January 1982 to September 2022. The main result is that the neutrality hypothesis is still valid in light of recent developments in the respective markets (no significant linear causality and asymmetric causality were detected among the series).

Commodities doi: 10.3390/commodities1020010

Authors: Maria Cristina Sterie Ionut Laurentiu Petre Iulia Bianca Bogos

The objective of the present research was to determine the external influence of the grain trade, i.e., the influence of Ukraine’s grain trade through Romania on price levels recorded at Romania’s borders. The research methods to achieve this objective consisted of quantitative and qualitative analyses of wheat and maize imports and export data from the beginning of 2022 to the present, as well as using the t-stat test to determine the existence of significant price differences, and the linear regression model. The research results confirm that there were differences between the two pre- and post-military conflict periods regarding the volume of imports from Ukraine and the increase in the supply of wheat and maize from Romania, through this trade activity, led to changes in prices.

Commodities doi: 10.3390/commodities1020009

Authors: Tayyba Rashad Khalid Zaman Haroon ur Rashid Khan Awais Rashid

The natural resource commodity price paradox is a phenomenon that has been observed in the past. The price of a commodity constantly and unpredictably fluctuates. This phenomenon makes it difficult for businesses to plan for future needs and investments. This study examined the relationship between natural resource commodity prices, renewable energy demand, economic growth, high-technology exports, inbound FDI, and greenhouse gas (GHG) emissions in Pakistan, using the 1975 to 2020 time period. The robust least squares (RLS) regression results showed that natural resource commodity prices and economic growth increased GHG emissions. In contrast, there was a negative relationship between renewable energy demand (and high-tech exports) and GHG emissions in Pakistan. The results verified the resource price curse hypothesis and growth-associated emissions in a country. The Granger causality estimates showed the unidirectional relationship of renewable energy consumption with GHG emissions, natural resource pricing, and inbound FDI. Further, high-technology exports Granger caused GHG emissions and GDP per capita. The results verified the country’s growth-led green energy sources and inbound FDI, resource pricing-led inbound FDI, and GHG emissions-led resource pricing. The impulse response function suggested that resource commodity pricing and the country’s economic growth will likely increase GHG emissions in the next ten years. At the same time, green energy demand, technological advancements, and sustainable investment in cleaner production would help decrease GHG emissions over time. The variance decomposition analysis suggested that technology advancements would likely have greater variance shock on GHG emissions, followed by commodity resource pricing and green energy demand. The resource price paradox hampers economic and environmental outcomes, which need to be resolved through advancement in cleaner production technologies, adoption of green energy demand, and stabilization of resource commodity pricing that helps to move forward toward the sustainable development of the country.

Commodities doi: 10.3390/commodities1020008

Authors: Mohammad Zohaib Saeed Shankar Ghimire

Increasing levels of carbon emissions have been a growing concern worldwide because of their adverse environmental effects. In that context, this paper examines the association between different categories of trade and carbon dioxide emissions. In particular, we analyze whether total trade, commodity trade, and service trade affect the environment differently. The analysis is based on panel data for 147 developing countries for the period from 1960 to 2020. Methodologically, the fixed-effects model, as suggested by the Hausman test, is used to examine the relationships. We present two main conclusions: (1) overall trade increases CO2 emissions, and (2) commodity trade contributes to higher levels of CO2 emissions than service trade. These results have important policy implications—climate change policies should target commodity trade sectors to help reduce environmental carbon emissions.

Commodities doi: 10.3390/commodities1020007

Authors: Nuno Domingues

Lithium has emerged as a key commodity in the clean energy transition, with demand for the mineral set to soar as low-carbon technologies grow more advanced and widely deployed. Under the motto of the energy transition and a decarbonization of the economy, governments and mining industries seek agreements for the granting of prospecting licenses around the World, defining then the ones that will extend to exploration. New investments in photovoltaic solar exploitations, research in the fields of secondary batteries, thermonuclear power generation, and the fever of the electric car are some of the main uses and exerts pressure regarding the availability, in sufficient quantities, of lithium. Consequently, concern over environmental impacts and undefined local social benefits are alarming residents in rural areas and non-governmental organizations. Therefore, the concern for the environmental impacts and the undefined local social benefits are alarming residents in rural areas and non-governmental organizations. This article reflects on the situation in Portugal, making an economic, energic, environmental and social balance. The article uses the international experience to strengthen the study. In the absence of case studies in Portugal, an analogy with quarry exploitation will be used, whose impacts are similar. The present paper explains why Portugal is currently the key country for lithium exploration in the world, despite it being 7th in the world with regard to lithium reserves. Taking into consideration all parts and the best practices in the world, and if environmental and social concerns are resolved, mining is a good opportunity for Portugal as a Country and for the local population at risk of desertification areas, in the author’s opinion.

Commodities doi: 10.3390/commodities1020006

Authors: Zar Shah Khalid Zaman Haroon ur Rashid Khan Awais Rashid

Natural resources and ecological services provide the foundation for manufactured capital, increasing public financing and decreasing inequality by diversifying the economy. The exploitation of natural resources is frequently the backbone of economic stability in developing and middle-income nations. As a result of their importance, natural resources need vigilant and long-term management. Recent research has tested two hypotheses, the natural resource blessing hypothesis and the natural resource curse hypothesis, on the impact of a country’s natural resources on its economy. This research is an essential contribution to the growing body of work that attempts to quantify natural resource endowments’ role in national economic growth. Investigations focus on Pakistan and span the years 1975 through 2020. Robust Least Square (RLS) estimations show that coal rents, energy use, inbound FDI, and oil rents contribute to a country’s economic growth. While consumption of renewable energy sources and industrial value-added have a detrimental effect. Natural resources, foreign direct investment, energy consumption, and industrial ecology are predicted to significantly impact economic growth during the next decade, according to the Impulse Response Function (IRF) and the Variance Decomposition Analysis (VDA). The findings may provide helpful information for academic and governmental institutions to develop natural resource management policies for sustainable development.

Commodities doi: 10.3390/commodities1010005

Authors: Jaime Marquez

This paper examines the relevancy of price measurement for characterizing the relation between real oil prices and real exchange rates. The current empirical literature shows a consensus on using the U.S. CPI to deflate the nominal oil price simply because of its numerous advantages. However, reliance on the U.S. CPI assumes that the worldwide alternative to a barrel of oil is the U.S. consumption basket. There are, however, alternative baskets, and I consider two: the price of gold and the IMF Global Commodity Price Index. Inspection of the results reveals that the relation between real oil prices and real exchange rates is sensitive to the choice of deflator for the price of oil and to the use of effective or bilateral exchange rates. Specifically, using the IMF’s Global Commodity Price Index as a deflator reveals that real oil prices and real exchange rates (effective or bilateral) are clustered along a long-run relation with unitary elasticity. Further, this choice of deflator has the lowest forecast errors. To be sure, much work remains to be completed along the lines of measurement and estimation methods. However, extending the results of this paper will emphasize its main point—namely, that measurement matters.