Taiwan's Food Resiliency - or Not - in a Conflict with China

The US military, intelligence, and diplomatic communities have overlooked a key vulnerability in their assessment of a potential military conflict between China and Taiwan- Taiwan's growing reliance on agricultural imports and its food stocks (except for rice) that could endure trade disruptions for only six months. This article assesses Taiwan's agricultural sector and its ability to feed the country's population if food imports and production are disrupted;identifies the food products that should be prioritized in resupply operations, based on Taiwan's nutritional needs and domestic food production;and outlines the required logistical assets. These findings underscore the urgency for US military planners to develop long-term logistical solutions for this complex strategic issue.

Disentangling Short-Run COVID-19 Price Impact Pathways in the US Corn Market

Despite this focus on pandemic-related supply chain disruptions, fewer empirical studies have sought to isolate short-term price impacts in food and nonfood agricultural commodity markets.1 Understanding the drivers of short-term commodity price impacts is critical to understanding future susceptibility to major market shocks and to informing policies related to shock mitigation. Declines in ethanol production reached an estimated 2 billion gallons lost from March to November 2020, leading to a corresponding decline of 700 million bushels of corn usage and a loss of billions of dollars of ethanol producer surplus (Renewable Fuels Association, 2020b;Schmitz, Moss, and Schmitz, 2020). Increases in corn-based ethanol production that started in 2005 have linked agricultural commodity prices and energy markets as US ethanol production increased rapidly from 3.9 billion gallons in 2005 to 13.3 billion by 2010 and 15.8 billion by 2019 (Chakravorty, Hubert, and Nøstbakken, 2009;Wright, 2011;Roberts and Schlenker, 2013;Asgari, Saghaian, and Reed, 2020;US Department of Agriculture, 2021). Given that over 90% of US ethanol is used in mixtures of E10 gasoline and the US market reached a 10% "blend wall" in 2016, any reduction in gasoline use will cause proportional decreases in ethanol use (US Energy Information Administrationa, 2020;US Department of Agriculture, 2021).

How to reduce the extreme risk of losses in corn and soybean markets? Construction of a portfolio with European stock indices

Because of the COVID-19 pandemic and the war in Ukraine, agricultural commodities had significant price increases, which inevitably implies high risk. In this article, we try to mitigate the extreme risk of corn and soybeans by constructing multivariate portfolios with developed and emerging European stock indices. We measured extreme risk via conditional value at risk. To address different goals that investors might prefer, we produced portfolios with the lowest risk and highest return-to-risk ratio. According to the results, corn and soybeans had relatively high portfolio shares. However, they are the riskiest assets because they have a very low pairwise correlation with the stock indices. Portfolios with emerging European indices had better risk-reducing results, considering both agricultural commodities because these indices are less risky than developed indices. In particular, the risk reductions of corn were 38% and 50% in the portfolios with developed and emerging stock indices, respectively, whereas, for soybeans, the results were 28% and 41%, respectively. In optimal portfolios, emerging European stock indices had the upper hand in most cases. © The authors.

Risk Connectedness among International Stock Markets: Fresh Findings from a Network Approach

In this study, we analyze the upside and downside risk connectedness among international stock markets. We characterize the connectedness among international stock returns using the Diebold and Yilmaz spillover index approach and compute the upside and downside value-at-risk. We document that the connectedness level of the downside risk is higher than that of the upside risk and stock markets are more sensitive when the stock market declines. We also find that specific periods (e.g., the global financial crisis, the European debt crisis, and the COVID-19 turmoil) intensified the spillover effects across international stock markets. Our results demonstrate that DE, UK, EU, and US acted as net transmitters of dynamic connectedness;however, Japan, China, India, and Hong Kong acted as net receivers of dynamic connectedness during the sample period. These findings provide significant new information to policymakers and market participants.

Dynamics of Volatility Spillover and Connectedness Among Sectors of Indian Stock Market

This paper investigates the dynamic volatility spillover and connectedness among different sectors of the Indian stock market during the Covid-19 pandemic. The study considers 18 sectors listed on the National Stock Exchange. Diebold-Yilmaz Volatility spillover model and Baruník and Křehlík frequency connectedness methodology are used to investigate the time varying dynamics of the spillover during the turbulence period. Daily market prices of 18 sectors, from March 15, 2019, to February 28, 2022, are considered for the present study. The results reveal that the spillover from infra, commodities, services, MNC, oil and gas, financial services, private bank, energy, and PSE is more, and this clearly indicates that during the pandemic, these sectors mostly had a spillover effect on other sectors.

UNIFORM INFERENCE IN A GENERALIZED INTERVAL ARITHMETIC CENTER AND RANGE LINEAR MODEL

Via generalized interval arithmetic, we propose a Generalized Interval Arithmetic Center and Range (GIA-CR) model for random intervals, where parameters in the model satisfy linear inequality constraints. We construct a constrained estimator of the parameter vector and develop asymptotically uniformly valid tests for linear equality constraints on the parameters in the model. We conduct a simulation study to examine the finite sample performance of our estimator and tests. Furthermore, we propose a coefficient of determination for the GIA-CR model. As a separate contribution, we establish the asymptotic distribution of the constrained estimator in Blanco-Fernández (2015, Multiple Set Arithmetic-Based Linear Regression Models for Interval-Valued Variables) in which the parameters satisfy an increasing number of random inequality constraints.

Continuous Wavelet Transform of Time-Frequency Analysis Technique to Capture the Dynamic Hedging Ability of Precious Metals

Exploring the hedging ability of precious metals through a novel perspective is crucial for better investment. This investigation applies the wavelet technique to study the complicated correlation between global economic policy uncertainty (GEPU) and the prices of precious metals. The empirical outcomes suggest that GEPU exerts positive influences on the prices of precious metals, indicating that precious metals could hedge against global economic policy uncertainty, which is supported by the inter-temporal capital asset pricing model (ICAPM). Among them, gold is better for long-term investment than silver, which is more suitable for the short run in recent years, while platinum's hedging ability is virtually non-existent after the global trade wars. Conversely, the positive influences from gold price on GEPU underline that the gold market plays a prospective role in the situation of economic policies worldwide, which does not exist in the silver market. Besides, the effects of platinum price on GEPU change from positive to negative, suggesting that the underlying cause of its forward-looking effect on GEPU alters from the investment value to the industrial one. In the context of the increasing instability of global economic policies, the above conclusions could offer significant lessons to both investors and governments.

The US-China trade war and the volatility linkages between energy and agricultural commodities

Any disruptive changes in the competitive environment, such as the U.S.-China trade war, may influence the price volatility of crude oil and agricultural commodities. This study examines the volatility linkage between crude oil and agricultural commodity markets in the context of the U.S.-China trade war and compares the impact of the trade war with that of other exogenous shocks. The results show that the volatility of soybeans exhibits the highest level of responsiveness to the U.S.-China trade war - which is not surprising given that the U.S. agribusiness trade to China is dominated by soybeans - followed by coffee and cotton. The sizes and dynamics of the impacts of shocks are largely commodity-specific. Notably, the trade war impacts most agricultural commodities more extensively than other exogenous shocks, including the global financial crisis and the COVID-19 pandemic and associated recession. These findings matter not only for the decision-making of investors and portfolio managers but also for commodity-exporting and importing countries because changes in the volatility dynamics of crude oil and agricultural commodities often impact export revenues and import expenditures and consequently feed through exports to the global supply chain under exogenous shocks such as the U.S.-China trade war. © 2023 The Authors

Trends in rice research: 2030 and beyond

Rice production and research have met unprecedented challenges in recent years. Yield and total production have plateaued for many years in some major producing rice-producing countries while the demand from populations in poverty is ever increasing. For example, more than 100 million additional people became extremely poor, mostly from Asia and sub-Saharan Africa in 2020 alone. Rice is not only the calorie source for half of the global population but also the key staple food for the world's poorest and undernourished people living in Asia and Africa. In this review, we have analysed the trends in rice research in the past three decades, particularly on the mega-projects that attempted to revolutionize rice yield, sustainability and quality of both Asian (Oryza sativa) and African (O. glaberrima) rice, with their impact on rice cultivation. We have also analysed the trends in population growth, rice cultivation, production, price and consumption along with their projections for 2030 and beyond. Furthermore, we have analysed recent trends in variety release using Bangladesh as an example. Finally, we have identified the future challenges and priorities of rice research.

High frequency volatility spillover between oil and non-energy commodities during crisis and tranquil periods.

In this article, we scrutinize volatility spillover between oil and individual non-energy commodities during crisis and non-crisis periods. We use high-frequency data to capture the effects of both the global financial crisis (2008) and the COVID-19 pandemic between 2008 and 2022. To this end, we utilize wavelet coherence analysis to diagnose the magnitudes of dynamic co-movements and lead-lag effects between commodities. Our results provide evidence of strong coherence between oil and the majority of individual non-energy commodities during both crises. Precious metals were generally found to exhibit heightened levels of co-movement with oil as opposed to other non-energy commodities. On the other hand, weak co-movements were found between oil and a few commodities, namely soy, wheat, zinc, and tin. The lead-lag effects of oil on agricultural commodities, base metals, and precious metals were evident, especially during crisis periods. However, aluminium and precious metals, especially gold, silver, and palladium, also had a lead-lag effect on oil at different points in time, including during the pandemic. We further utilize dynamic frequency-domain connectedness for capturing pairwise volatility spillover indices, with the results providing evidence of heightened volatility spillovers during turbulent times. Our findings have significant implications for retail investors, portfolio managers, and policymakers.

The impact of COVID-19 on agricultural market integration in Eastern Canada

Since the outbreak of the coronavirus pandemic in early 2020 and the resulting economic fallout, reports and official statistics have pointed to an unequivocal effect of the disease on almost all global economic activities, including the agricultural and agri-food sectors. The aim of this article is to use a price transmission approach in order to study the price relationships of agricultural commodities, including potatoes, corn, hogs, eggs, and chicken between regional Canadian markets and to verify their economic integration. The method of panel cointegration is applied to investigate the potential impact of the pandemic on the spatial integration of the provincial agricultural markets in Eastern Canada. It is found that these markets were fully integrated and efficient prior to COVID-19 restrictions. However, the statistical results show that travel restrictions and labor shortages represented trade barriers between the provinces, and they are likely the factors that impacted the price transmission mechanism, and consequently the markets became much less integrated. It is suggested that government policies should include actions that would manage future shocks to the agricultural commodity prices by accelerating the necessary transformations in the agri-food sector to make it more resilient and less vulnerable to future pandemics and other potential natural challenges.

FROM THE DESK OF CHIEF EDITOR: A QUARTERLY PEER REVIEWED MULTI-DISCIPLINARY INTERNATIONAL JOURNAL

Energy market instability and price increases are specifically being caused by the conflict in Ukraine, with headwinds in most other economies more than offsetting growth in energy exporters. In many emerging market and developing countries, the invasion of Ukraine has also contributed to a sharp rise in the price of agricultural commodities, causing food insecurity and extreme poverty (EMDEs). In order to enhance development, strengthen macroeconomic frameworks, lessen financial vulnerabilities, help disadvantaged population groups, and lessen the long-term effects of recent global shocks, EMDE authorities and the international community must take decisive and comprehensive policy action.

Investigating Technology Transfer Gaps Through Farmers Field School

Technology transfer is one of the core elements in a rapidly changing agricultural sector. However, the booming of agricultural innovation is not followed by the generation of methodological tools able to diffuse innovation in farmers and other stakeholders. For the last decades, Farmers Field School (FFS) approach is offering technology transfer and co-generation, infused by agricultural extension. Traditional FFS form is a learning by doing method and farmers are learning from other experienced farmers. Even though FFS has various forms which are trying to cover gaps between science and practice, there are still different methodological challenges in each FFS form. In this research, we propose a Hybrid FFS strategy, assembled by the strengths of various FFS forms and trying to close these gaps. We review and implement a metaanalysis of FFS forms, investigating these gaps. Afterwards, a comprehensive, holistic and dynamic conceptual and methodological model, derived from meta-analysis is proposed to cover the technology transfer methodological gaps. Our Hybrid FFS strategy highlight strategic questions which offer the appropriate background for establishing a strong educational strategy and overcome possible challenges. "Learning by doing" is supported from farmers to farmers as well as from experts to experts. Various stakeholders from value chain are promoted to use and be familiarized with new technologies, practical tools and the internet, as well as develop their managerial skills in value chain products. Modules cover the gaps ofrecent FFS approaches, by incorporating issues of sustainability and certification of value chain products, with business and entrepreneurship. Flexibility of a hybrid (virtual and physical) environment resolve complex situations (i.e. COVID-19). This methodology can be useful to policy makers managers or agricultural extension researchers, in order to construct, implement and evaluate an FFS agricultural program. Hybrid FFS strategy describes how agricultural education approaches of the past can create educational environments of the future and lead learning accelerators in agricultural sector.

Spatial market integration for food price stabilization during the Covid 19 pandemic in West Nusa Tenggara, Indonesia: A case study of the cayenne pepper

The Covid-19 pandemic can affect the movement and prices of agricultural commodities, including red chili peppers as a result of restrictions on community activities or lock-down. This study aims to empirically examine the spatial integration of the four main markets for cayenne pepper in West Nusa Tenggara, namely Mandalika (Mataram City), Aikmel (East Lombok), Seketeng (Sumbawa), and Amahami (Bima City).The analysis was carried out using the Johansen Cointegration Model and the Vector Error Correction Model (VECM) using weekly time series data. The results of the study concluded that the four markets studied are spatially integrated. The role of the Aikmel market is very dominant for the occurrence of price volatility compared to the other three markets.

FARMERS' PERSPECTIVE OF COVID-19 EFFECTS ON DEMAND AND SUPPLY OF AGRICULTURAL COMMODITIES IN NYAMASHEKE DISTRICT, RWANDA

COVID-19 is an infectious disease caused by a new strain of coronavirus. This disease disrupted the functionality of the global economy, and the agriculture sector was not spared. It is in this context that this paper aims at assessing farmers' perceptions about the perceived shocks of COVID-19 on the side of demand and supply of agricultural commodities. The study was guided by three objectives viz to investigate the perceptions of farmers on the effects of COVID-19 pandemic on the demand for agricultural commodities, to explore the perceptions of farmers on the effects of COVID-19 pandemic on the supply of agricultural commodities and to analyze the factors affecting farmers' perceptions of COVID-19 pandemic on demand and supply of agricultural commodities in Nyamasheke district. The target population size was 6237 composed of farmers of three irrigated lands in Nyamasheke District. Yamane's formula for the sample size determination was used to find the sample size of the respondents which was 376 and then stratified and systematic sampling procedures were employed to get 174 farmers in Kirimbi, 114 farmers in Mugonero and 88 farmers in Kamiranzovu irrigated lands, respectively. This study employed both descriptive and inferential statistical tools to analyze data. Descriptive statistics were used to analyze data on the perceptions of farmers towards COVID-19 pandemic effects on the demand and the supply for agricultural commodities while the inferential statistics were used to estimate the logit of farmers' perceptions on COVID-19 pandemic effects of demand and supply of agricultural commodities in the area under study. Results from the descriptive statistics revealed that 326 (86.7%) farmers agreed that COVID-19 pandemic has affected the demand of agricultural commodities while 244 (64.9%) farmers confirmed that COVID-19 pandemic has affected the supply of agricultural commodities in the area under study. The output of the model revealed that the independent variables that significantly contribute to the logit of the dependent variable were farming experience and labor. During the COVID-19 pandemic, farmers encountered several challenges that disrupted their livelihoods including changes in household consumption patterns, changes in market functionalities, discontinuity of the planned training and field visits, and low number of farmers in the farms. Researchers recommend that farmers' purchasing power should be reinforced by providing financial support to them through lowering interest rates on loans. [ FROM AUTHOR]

Do biofuel production and financial speculation in agricultural commodities influence African food prices? New evidence from a TVP-VAR extended joint connectedness approach

Many African countries experienced social disorder and subsequent political instability as a result of global commodity price inflation in 2007–2008, which reaffirmed the importance of overseas factors such as biofuel production, international food and energy prices, and financial speculation. Biofuel, in particular, is often placed at the center of the debate around identifying potential determinants of food price hikes. We apply a time-varying parameter vector autoregressive (TVP-VAR) extended joint connectedness approach to uncover the dynamic connectivity of African food prices, US biofuel production, global energy and food prices, and financial speculation. The key findings are;1) the results of averaged connectedness suggest that US biofuel production and financial speculation in agricultural commodities significantly influence African food prices;2) the hefty surges in the dynamic connectedness between African food prices and four cross-border factors are triggered by global events like the 2000 dot-com bubble, the 2008 global commodity boom, and the 2020 COVID-19 pandemic;3) arbitrage transactions transmitted intense shocks to African food prices between 2001 and 2012, while biofuel production constantly affected African food prices between 2001 and 2021. We draw pragmatic policy implications to prevent or mitigate market shock transmissions to African food markets.

The Relationship between Agricultural Commodities and Stock Market in Case of Thailand: Safe-haven, Hedge, or Diversifier? – Cross Quantilogram Analysis

This paper proposes to identify Agricultural futures’ roles (Safe haven, Hedge, and Diversifier) in the Thai stock market during 2000-2020 by applying a bivariate Cross-Quantilogram (CQ) approach. The CQ approach can examine the cross-quantile correlation between assets, while the traditional approaches (such as GARCH, DCC, and MSV) examine only mean-to-mean dependency structures. The CQ methodology can estimate the tail dependencies and directional predictability between financial assets more accurately than traditional methods since financial assets typically have a skewed and asymmetric distribution. The correlation between assets during the extreme market condition (tail dependencies) is important to classify a financial asset as a Safe-haven role. The agricultural commodities considered in this study are the most active asset categories in the markets (cereals, oilseeds, other soft commodities, and miscellaneous commodities). The results show that the agricultural assets are more explicitly correlated with the Thai stock market in crisis periods, such as a negative result in canola during COVID-19. Agricultural commodities, including wheat, oats, and canola, can play a strong safe-haven role in the Thai stock market, according to the lowest cross-quantiles (bearish market) data. According to the results of overall quantiles (normal situations), wheat, corn, canola, soybean, and sugar can all be used as hedges. The rolling windows for directional predictability, which show the time-varying CQ, confirm that these agricultural commodities can be served as Safe-havens throughout the study periods. Therefore, including these specific agricultural commodities (Safe-haven or Hedge) in a portfolio of Thai stocks will help lower risk and boost performance under normal and extreme downturn situations.

The Trilogy of the Chinese Apple Futures Market: Price Discovery, Risk-Hedging and Cointegration

The agricultural futures market plays an extremely important role in price discovery, hedging risks, integrating agricultural markets and promoting agricultural economic growth. China is the largest apple producer and consumer in the world. In 2017, Chinese apple futures were listed on the Zhengzhou Commodity Exchange (CZCE) as the first fruit futures contract globally. This paper aims to study the efficiency of the apple futures market by using the Wild Bootstrapping Variance Ratio model to estimate the price discovery function, the ARIMA-GARCH model to estimate the risk-hedging function, and the ARDL-ECM model to estimate the cointegration relationship of the futures and spot market. Experimental results firstly demonstrate that the apple futures market conforms to the weak-form efficiency, which indicates that it is efficient in price discovery. Secondly, the apple futures market is not of semi-strong efficiency because it generated abnormal profit margins amid China–US trade friction, climate disaster, and COVID-19;in terms of the degree of impact, the COVID-19 pandemic had the greatest impact, followed by the rainstorm disaster and trade friction. Thirdly, the results of this study indicate that the cointegration relationships exist between the futures market and the spot markets of the main producing areas. This paper is not only conducive to sustainable development of the global fresh or fruit futures market, but also has potential and practical importance for China in developing the agricultural futures market, strengthening market risk management and promoting market circulation.

A Causal Nexus Of Indian Agricultural Futures Market In Pre- And Post-COVID19 Outburst: A Case Of India's First Tradable Agri-Futures Index

The research article examined the causal nexus in between two listed (NCDEX) benchmark agricultural futures indices in India, say, NKRISHI (Weighted Index) and AGRIDEX (Return based Index). Daily closing futures prices has been retrieved from official platform of NCDEX dated from April 1, 2018 to January 29, 2020 as first period (Pre-COVID19) and from January 30, 2020 to October 11, 2021 as second period (During COVID19). The causal nexus has been examined by using of Unit Root test (ADF), pairwise Granger Causality and Johansen Co-integration tests. The empirical investigation help to comprehend that there is no significant relationship (long-run as well as short-run) in between AGRIDEX and NKRISHI indices in both Pre-COVID19 and During-COVID19 periods. The results concluded that there is not a big impact on both the indices after the COVID19 outbreak. The Results highlight the efficiency of both the markets, say, NKRISHI and AGRIDEX futures indices, and also establish relevant information for investors, policymakers, researchers and hedgers for future investments and further analysis. It contributes to the market efficiency literature for agricultural futures market.

Time-frequency analysis of the comovement between wheat and equity markets

Purpose>This study aims to investigate the time-frequency comovement between wheat futures traded on three US markets (Chicago Board of Trade (CBOT), Kansas City Board of Trade (KCBOT) and Minneapolis Grain Exchange (MGE)) at different maturities and a global equity index.Design/methodology/approach>As they allow to trace transitional shifts over time and across different frequency bands, this paper relies on continuous wavelet tools to investigate the time-frequency comovement among wheat and global stock markets.Findings>The results show an increase in wheat futures prices at all maturities and a weak integration level within each wheat market during the subprime crisis. Moreover, the wavelet power spectra maps show high wheat and equity price volatility at different time scales and for various subperiods. Furthermore, the continuous wavelet coherence highlights time-frequency-varying comovements between the markets considered, which become particularly high during times of crisis.Practical implications>The results provide market participants with a better understanding of the nature as well as the magnitude of the relationship between the global financial market and different wheat markets at different maturities and during tranquil and crisis periods. Indeed, from investors' perspective it is important to understand how markets are segmented or integrated during tranquil and crisis periods in order to better assess risks, diversify portfolios and implement more effective hedging strategies. As for regulators, a better understanding of the level of integration of different markets would further help refine macroprudential policies, and thus strengthen financial stability and resilience.Originality/value>This paper enriches the existing literature by investigating the time-frequency comovement between wheat and a global equity market. Indeed, the dynamics between stock and wheat markets across different nearest to maturities have not been widely explored by previous studies.