Showing papers on "Commodity published in 2021"

How does trade policy uncertainty affect agriculture commodity prices

Abstract: The present paper explores the impact of trade policy uncertainty (TPU) on agricultural commodity prices (ACP) by employing bootstrap full- and subsample rolling-window Granger causality tests We find that TPU has both positive and negative effects on ACP, suggesting that TPU may change the supply of and demand for agricultural commodities, leading to fluctuations in ACP These results support the hypotheses derived from the general equilibrium model, which highlights that TPU can significantly affect ACP In turn, we find a positive impact of ACP on TPU, indicating that the agricultural commodity market reflects trade conditions in advance In the context of Sino-U S trade frictions and the COVID-19 pandemic, the interaction between TPU and ACP can provide insights for governments to prevent large fluctuations in agricultural commodity markets and stabilize the national economy © 2021 Elsevier B V

Dynamic return and volatility connectedness for dominant agricultural commodity markets during the COVID-19 pandemic era

Abstract: This paper explores the dynamic return and volatility connectedness for the three most relevant agricultural and livestock commodity indexes (Softs, Grains and Livestock) and a media sentiment inde...

Do Commodity Price Shocks Cause Armed Conflict? A Meta-Analysis of Natural Experiments

Abstract: Scholars of the resource curse argue that reliance on primary commodities destabilizes governments: price fluctuations generate windfalls or periods of austerity that provoke or intensify civil conflict. Over 350 quantitative studies test this claim, but prominent results point in different directions, making it difficult to discern which results reliably hold across contexts. We conduct a meta-analysis of 46 natural experiments that use difference-in-difference designs to estimate the causal effect of commodity price changes on armed civil conflict. We show that commodity price changes, on average, do not change the likelihood of conflict. However, there are cross-cutting effects by commodity type. In line with theory, we find price increases for labor-intensive agricultural commodities reduce conflict, while increases in the price of oil, a capital-intensive commodity, provoke conflict. We also find that price increases for lootable artisanal minerals provoke conflict. Our meta-analysis consolidates existing evidence, but also highlights opportunities for future research.

COVID-19 induced lockdown effects on agricultural commodity prices and consumer behaviour in India – Implications for food loss and waste management

Abstract: Distortion in distribution and consumption of agricultural commodities is a result of disruptive shocks in prices and food value chains leading to a significant food loss as well as waste. We investigated the COVID-19 induced lockdown effects in India through an interrupted time series analysis coupled with a survey result of 729 consumers, 225 farmers and synthesis of the literature evidence on food loss as well as food waste. Our article complements the literature inventory on COVID-19 by estimating and tracking the effects on prices and consumer behaviour apart from discussing the implications for food loss and waste. Prices post-lockdown shot up immediately and significantly for chickpea (4.8%), mung bean (5.2%), and tomato (78.2%) corroborating the loss in highly perishable product – tomato – owing to its spiked price. We find no structural break in prices due to lockdown implying that lockdown-induced price change was not sufficient to alter the long-run price movement, and the prices of the major commodities reverted to the pre-lockdown levels. The pandemic induced lockdown did restrict the access to food markets and a majority of consumers (75.31%) experienced a price increase across COVID zones of different intensity of incidence leading to food loss along supply chain and wastage at consumers end. Consumers’ livelihood affected from moderate (59.53%) to severe (3.3%) with 92 per cent reporting a change in shopping behavior. The Kruskal-Wallis test on consumption behavior change indicated a significant shift among the consumers reporting altered income, mostly in the downside, post-lockdown. Despite the relaxation for agricultural related activities during the lockdown, farmers reported disruption in disposing their winter produce barring wheat, bolstered by a record state procurement in 2020. The paper affirms that the pandemic has caused a significant price change and unprecedented panic purchase that led to the food wastage but subsided soon exhibiting the resilience in Indian agriculture. We strongly recommend for promoting the capacity and collective resilience of small-scale production systems through institutions, policies and reforms. Contract farming, farmer producer organizations, creation and functioning of social safety nets to overcome income, production and price shocks, access to digital national markets and capacity building on food waste management practices will insulate vulnerable section as well as reduce the loss of food across supply chain.

Network analysis of corn cash price comovements

Abstract: Commodity price comovements are an important issue in economics given their significant implications for food and resource sectors that directly influence social well-being. This study approaches this issue by focusing on daily cash prices of 182 corn markets from the seven largest harvest states in the United States for 2006–2011 by using correlation based hierarchical analysis and synchronization analysis, through which we can determine interactions and interdependence among these prices, heterogeneities in price synchronization, and their changing patterns over time. As the first study of the issue concentrating on prices of hundreds of spatially dispersed markets for a commodity of indubitable economic significance, empirical findings show that the degree of comovements is generally higher after November 2006 but no persistent increase is observed. Different groups of markets are identified, each of which has its members exhibit similar price dynamics. Certain markets show potential of serving as price leaders. Results here benefit food and resource policy analysis and design for economic welfare. The empirical framework has potential of being adapted to network analysis of prices of different commodities.

A Review of the Applications of Genetic Algorithms to Forecasting Prices of Commodities

Abstract: This paper is focused on the concise review of the specific applications of genetic algorithms in forecasting commodity prices. Genetic algorithms seem relevant in this field for many reasons. For instance, they lack the necessity to assume a certain statistical distribution, and they are efficient in dealing with non-stationary data. Indeed, the latter case is very frequent while forecasting the commodity prices of, for example, crude oil. Moreover, growing interest in their application has been observed recently. In parallel, researchers are also interested in constructing hybrid genetic algorithms (i.e., joining them with other econometric methods). Such an approach helps to reduce each of the individual method flaws and yields promising results. In this article, three groups of commodities are discussed: energy commodities, metals, and agricultural products. The advantages and disadvantages of genetic algorithms and their hybrids are presented, and further conclusions concerning their possible improvements and other future applications are discussed. This article fills a significant literature gap, focusing on particular financial and economic applications. In particular, it combines three important—yet not often jointly discussed—topics: genetic algorithms, their hybrids with other tools, and commodity price forecasting issues.

Assessing the Impact of COVID-19 Pandemic on the Stock and Commodity Markets Performance and Sustainability: A Comparative Analysis of South Asian Countries

Abstract: COVID-19 is certainly the first sustainability crisis of the 21st century. The paper examines the impact of COVID-19 on the Indian stock and commodity markets during the different phases of lockdown. In addition, the effect of COVID-19 on the Indian stock and commodity markets during the first and second waves of the COVID-19 spread was compared. A comparative analysis of the stock market performances and sustainability of selected South Asian countries is also included in the study, which covers the lockdown period as well as the time frame of the first and second waves of COVID-19 spread. To examine the above relationship, the conventional Welch test, heteroskedastic independent t-test, and the GMM multivariate analysis is employed, on the stock return, gold prices, and oil prices. The findings conclude that during the different phases of lockdown in India, COVID-19 has a negative and significant impact on oil prices and stock market performance. However, in terms of gold prices, the effect is positive and significant. The results of the first wave of COVID-19 infection also corroborate with the above findings. However, the results are contradictory during the second wave of coronavirus infection. Furthermore, the study also substantiates that COVID-19 has significantly affected the stock market performances of selected South Asian countries. However, the impact on the stock market performances was only for a short period and it diminished in the second wave of COVID-19 spread in all the selected South Asian countries. The findings contribute to the research on the stock and commodity market impact of a pandemic by providing empirical evidence that COVID-19 has spill-over effects on stock markets and commodity market performances. This result also helps investors in assessing the trends of the stock and commodity markets during the pandemic outbreak.

Combined innovations in public policy, the private sector and culture can drive sustainability transitions in food systems

Abstract: Global food system analyses call for an urgent transition to sustainable human diets but how this might be achieved within the current global food regime is poorly explored. Here we examine the factors that have fostered major dietary shifts across eight countries in the past 70 years. Guided by transition and food-regime theories, we draw on data from diverse disciplines, reviewing post-World War 2 shifts in consumption of three food commodities: farmed tilapia, milk and chicken. We show that large-scale shifts in commodity systems and diets have taken place when public-funded technological innovation is scaled-up by the private sector under supportive state and international policy regimes, highlighting pathways between commodity systems transformation and food-system transitions. Our analysis suggests that the desired sustainability transition will require public policy leadership and private-sector technological innovation alongside consumers who culturally value and can afford healthy, sustainable diets. Transition theory and the political economy of food regimes provide insights for transforming food systems. Recent historic case studies of scientific, technological, political and cultural innovations, including advances in tilapia farming and ultra-heat treatment of milk, provide lessons for future food system shifts.

Does disease outbreak news impact equity, commodity and foreign exchange market? Investors' fear of the pandemic COVID-19

Abstract: Purpose: Market volatility is subject to good or bad news and even responses to fake news and policy changes. In this piece of work, the authors consider the effects of the recent COVID-19 pandemic event on the global equity market, commodities and FX market, measured in terms of the investors' fear index. Design/methodology/approach: In this empirical work, the authors employ time series-based regression models followed by augmented dummy regressions and growth of the COVID-19. Findings: COVID-19-induced investors' fear appears to be higher in the equity segment for the first time since the market crash of 1987 and the global financial crisis of 2008–2009. Furthermore, this disease outbreak shock has been more pronounced in terms of crude oil prices. Besides, a market participant in the commodity and FX market has paid a disproportionate premium to protect such pandemic development. Findings show that Options act as the best hedge against an uncertainty like COVID-19 and that option-based implied volatility is the best measure of investors' fear and market volatility. Practical implications: This study has practical implications for the financial markets, e.g. (1) Contagious disease outbreak news matters for the equity, commodity, and foreign exchange markets – empirical outcome validates the theory of market efficiency valid for the Options. (2) Option's implied volatility is the best indicator of investor fear measured for the unprecedented economic news. Further implication holds for the policymakers and society, e.g. (1) The unavailability of short-selling could be one plausible reason for increased uncertainty and volatility;hence, policymakers should look upon this issue at the exchange level. (2) Any market needs multiple lines of risk management, effective price discovery and attractive liquidity. Originality/value: The study is novel in terms of presenting market behavior amid COVID-19 across global equity markets and commodities and FX markets. © 2021, Emerald Publishing Limited.

Can Global Economic Policy Uncertainty Drive the Interdependence of Agricultural Commodity Prices? Evidence from Partial Wavelet Coherence Analysis

Abstract: This paper employed wavelet coherence and partial wavelet coherence to investigate the time-frequency effect of global economic policy uncertainty on the comovement of five agricultural commodities such as maize, oat, rice, soybean, and wheat using monthly data from January 1997 to December 2019. In general, we observed heterogeneity in comovement structures of the agricultural commodities market at different time-frequency scales which are profound at high frequencies from the bivariate wavelet coherence. The partial wavelet coherence analysis shows that global economic policy uncertainty is a driver of agricultural commodity market connectedness. This implies that extreme changes in economic policy uncertainty have the tendency to influence commodity price comovement. This poses risk to the stability of the agricultural commodities market, which requires the policymaker’s intervention to protect against the spillover risk contagion effect in uncertain times.

Forecasting spot prices of agricultural commodities in India: Application of deep-learning models

Abstract: Food price fluctuations can impact both producers and consumers. Forecasting the prices of the agricultural commodities is of prime concern not only to the government but also to farmers and agribusiness firms. In developing countries like India, management of food security needs competent and efficient forecasting of food prices. With the availability of data, recent innovation in deep‐learning models provides a feasible solution to accurately forecast the prices. In this study, we examine the superiority of these models using the daily spot prices of five major commodities traded on the National Commodity and Derivatives Exchange: cotton seed, castor seed, rape mustard seed, soybean seed, and guar seed. The results were obtained from the application of the traditional univariate autoregressive integrated moving average model and deep‐learning techniques like the time‐delay neural network (TDNN) and long short‐term memory (LSTM) network. The empirical results indicate that the LSTM model is indeed suitable for the financial domain and captures the directional movement of the spot price changes with high accuracy compared with the TDNN and other linear models. Accuracy of the performance of these models has been compared using out‐of‐sample performance measure. The overall objective of this paper is to demonstrate the utility of spot price forecasting for farmers and traders in offering them the best predictions of the price movements. Our results provide a possibility of developing pricing models that can help in fairly regulating agricultural commodity prices.

The Connections between COVID-19 and the Energy Commodities Prices: Evidence through the Dynamic Time Warping Method

Abstract: The main objective of the study is to assess the similarity between the time series of energy commodity prices and the time series of daily COVID-19 cases. The COVID-19 pandemic affects all aspects of the global economy. Although this impact is multifaceted, we assess the connections between the number of COVID-19 cases and the energy commodities sector. We analyse these connections by using the Dynamic Time Warping (DTW) method. On this basis, we calculate the similarity measure—the DTW distance between the time series—and use it to group the energy commodities according to their price change. Our analysis also includes finding the time shifts between daily COVID-19 cases and commodity prices in subperiods according to the chronology of the COVID-19 pandemic. Our findings are that commodities such as ULSD, heating oil, crude oil, and gasoline are weakly associated with COVID-19. On the other hand, natural gas, palm oil, CO2 allowances, and ethanol are strongly associated with the development of the pandemic.