Agricultural Price Volatility Research Articles

Climate change and political stability in African states: the role of agricultural food price volatility

Climate change and political stability in African states: the role of agricultural food price volatility

Forecasting the realized volatility of agricultural commodity prices: Does sentiment matter?

AbstractWe analyze the out‐of‐sample predictive power of sentiment for the realized volatility of agricultural commodity price returns. We use high‐frequency intra‐day data covering the period from 2009 to 2020 to estimate realized volatility. Our baseline forecasting model is a heterogeneous autoregressive (HAR) model, which we extend to include sentiment. We further enhance this model by incorporating various key realized moments such as leverage, realized skewness, realized kurtosis, realized upside (“good”) volatility, realized downside (“bad”) volatility, realized jumps, realized upside tail risk, and realized downside tail risk. In order to setup a forecasting model, we use (i) forward and backward stepwise predictor selection and (ii) a model‐based averaging algorithm. The forecasting models constructed through these algorithms outperform both the baseline HAR‐RV model and the HAR‐RV‐sentiment model. We conclude that, for the agricultural commodities studied in our research, realized moments play a more significant role in forecasting realized volatility compared to sentiment.

A Sustainable Risk Management Model and Instruments for Young Farmers in EU Agriculture

Young farmers are ready to embrace innovation, smart agriculture, and science-based research to ensure that their work has long-term viability, profitability, and productivity. To prevent the farming population from aging and to ensure farming success, financial support must be provided through instruments that are specifically aimed at young farmers. It is necessary that youth have access to agricultural land policy throughout the EU for the agricultural sector to remain sustainable. In the European Union, young farmers manage farms that are in the lowest-size group. The limited financial possibilities available to young people in the EU exacerbate this. The relationships between risk management instruments and other interventions (such as direct payment and ex-post instruments) and the integration of these tools into national and EU policy frameworks must be thoroughly examined in future policy. Evaluating the possible repercussions of risk management being widely implemented as well as measuring the anticipated variations in farm revenue and the volatility of agricultural commodity prices are equally crucial. Therefore, the present article utilized extant data to conduct a comparative analysis and ultimately present a set of multidisciplinary and quantitative indicators of supportive measures for young farmers in the EU, while also identifying the requisite areas for improvement.

Disparity And Volatility of Horticultural Prices In Indonesia Before and Pandemic Period (2019 and 2020)

Disparity, volatility, and asymmetry of horticultural agricultural commodity prices are important to study during the COVID-19 pandemic. The increase in horticultural prices can cause inflation and reduce the level of real welfare. The disparity in horticultural prices will encourage the flow of goods from low-priced to high-priced areas. The volatility of food prices during the COVID-19 pandemic will add economic pressure to the community. This study aims to analyze the disparity and volatility of horticultural prices and the transmission of food prices from upstream to downstream before and during the 2019-2020 pandemic. The analytical tools used are the average, price difference, coefficient of variation, and error correction model. The results show a disparity in food prices between provinces in Indonesia. Price disparities increase during the pandemic. Price volatility during the pandemic for horticultural commodities is higher than before the pandemic. Changes in horticulture prices at the upstream level significantly affect price changes at the downstream level

Forecasting agricultural price volatility of some export crops in Egypt using ARIMA/GARCH model

PurposeThis study focuses on forecasting the price of the most important export crops of vegetables and fruits in Egypt from 2016 to 2030.Design/methodology/approachThe study applied generalized autoregressive conditional heteroskedasticity (GARCH) model and autoregressive integrated moving average (ARIMA) model.FindingsThe results show that ARIMA (1,1,1), ARIMA (2.1,2), ARIMA (1,1,0), ARIMA (1,1,2), ARIMA (0,1,0) and ARIMA (1,1,1) are the most appropriate fitted models to evaluate the volatility of price of green beans, tomatoes, onions, oranges, grapes and strawberries, respectively. The results also revealed the presence of ARCH effect only in the case of Potatoes, hence it is suggested that the GARCH approach be used instead. The GARCH (1,1) is found to be a better model in forecasting price of potatoes.Originality/valueThe study of food price volatility in developing countries is essential, since a significant share of household budgets is spent on food in these economies, so forecasting agricultural prices is a substantial requirement for drawing up many economic plans in the fields of agricultural production, consumption, marketing and trade.

Measuring the macroeconomic determinants of agricultural price volatility: Implications for natural resource commodity prices for green recovery.

With rapid growth, green economic recovery has been a key agenda for the globe. However, the price volatility for natural resources plays a significant role in reshaping the green recovery. Therefore, the current study investigates the impact of green recovery, hum, a capital index, GDP growth, foreign direct investment and inflation on natural resource volatility in China from 1995 to 2020. In order to investigate the long-term association among selected variables, this study employs the Autoregressive Distributive Lag (ARDL) model. In addition, the current research uses the Aikaik information (AIC) criteria for the model selections. Obtained outcomes show the significant contribution of green recovery, human capital, GDP growth, FDI and inflation increase the natural resource price volatility level. However, to validate the results of ARDL, this study also used the ECM approach and validated the prior findings. On behalf of outcomes, the current study implies some imperative policies to attain the desired objective for green growth.

Financial Speculation Impact on Agricultural and Other Commodity Return Volatility: Implications for Sustainable Development and Food Security

Global commodity markets, due to major health crises, political tension, sanctions, growing demand, and other global supply and demand factors, are currently particularly unstable. In addition to the macro-environmental factors that drive the prices, agricultural and other commodity markets are becoming more susceptible to the continuously-growing speculation on major commodity exchanges. Therefore, the purpose of this study is to analyze the influence of financial speculation on agricultural and other commodity prices and return volatility. In our study, we use daily returns on wheat, soybean, corn, and oats futures from the Chicago Mercantile Exchange as well as two additional commodities (crude oil and gold) to compare the extent of this effect. To measure this impact, we, besides traditional tools for time-series analysis, apply the threshold autoregressive conditional heteroskedasticity (TGARCH) technique. We also provide a model using dummy variables for the season to determine whether or not financial speculation’s impact on return volatility differs among seasons, as seasonality plays an important role in return dynamics for agriculture. Our study’s findings show that financial speculation, except for the oats market, either has no impact or makes the underlying futures returns less volatile. Therefore, we draw the conclusion that either there is no relationship between the rise in short-run speculation and the volatility of agricultural commodity prices, or the link is at best questionable. Research results provide important implications for the sustainable development of commodity markets, as passive legislation measurers can be seen as more effective ones compared to more strict active ones in order to maintain these markets liquid and capable of distributing price risks for agricultural producers and manufacturers in a challenging economic and geopolitical environment.

농산물 시장개방과 재정투융자의 파급영향 분석

In order to analyze the effect of market openness and fiscal investment & loan on economic performance indicators (real production value, real agricultural income, price volatility, and factor productivity) in the agricultural sector, we construct a panel dataset that includes the calculated index of openness for each product group (rice, fruits, vegetables, livestock) and the newly classified agricultural budget (fiscal investment & loan) by purpose and product-group during 1995~2019. This study estimates the system of equations established for each of the four performance indicators using the Seemingly Unrelated Regression (SUR) method and then compares the marginal effects of market openness and fiscal investment & loan on each performance indicator. Separate aggregation of these two key variables by product group gives sufficient observations to measure the causal relationship between economic performance and them, and the SUR method was selected to obtain efficient estimates if the error terms of each equation are correlated. Our empirical analysis shows that market openness acts in the direction of worsening all performance indicators, whereas fiscal investment & loan has a positive effect overall. In the face of further opening via RCEP and CPTPP, agricultural investment & loan in the future should be reorganized focusing on food security, rural maintenance, climate change and environment, and shared growth with related industries.

Finding the right price: supply chain contracts as a tool to guarantee sustainable economic viability of organic farms

The aim of this study is to analyse the volatility of agricultural commodity prices and assess the effectiveness of supply chain contracts as possible tools to prevent it. The study refers to the cereal sector, which is of vital importance for the agri-food system of the Mediterranean area. Since Italy is the world’s largest producer of durum wheat semolina, the proper functioning of the Italian durum wheat supply chain is central to this investigation. The study was conducted following two different paths of analysis: (1) the calculation of volatility indices using annual and monthly data of durum wheat prices, both organic and industrial, observed in the Bologna Commodity Exchange (AGER); (2) the analysis of two organic durum wheat supply chain contracts, defined by a cooperative involving hundreds of Italian farms mainly from the Marche region and by an agricultural consortium operating in the Adriatic regions. Despite the limited number of cases examined, the present study shows how supply chain contracts can be valid tools for building stable relationships between the various players, from production to processing and distribution, guaranteeing farms fairer and more remunerative raw material purchase prices and higher quality standards.

The Impacts of Trade Restrictions on World Agricultural Price Volatility during the COVID‐19 Pandemic

During the COVID‐19 pandemic, countries applied trade restrictions to insulate their domestic markets from the world market. However, these trade policies could have amplified international market price fluctuations. This paper explores the effects of trade restrictions on international agricultural price volatility. A theoretical model is developed to quantify how trade policies amplify the initial shock. Using panel data covering 71 countries from January 2020 to July 2021, we examine empirically the effects of trade policies on world agricultural price volatility. The results show that trade distortions further induced volatility of world agricultural prices by around 22 percent during the COVID‐19 pandemic. The multiplier effects are much more substantial in agricultural exporting countries than in importing countries. Large countries like China and the US could make significant contributions to stabilizing world prices by limiting the extent of unilateral trade policy interventions.

Oil Price Volatility is Effective in Predicting Food Price Volatility. Or is it?

Volatility spillovers between food commodities and oil prices have been identified in the literature, yet, there has been no empirical evidence to suggest that oil price volatility improves real out-of-sample forecasts of food price volatility. In this study we provide new evidence showing that oil price volatility does not improve forecasts of agricultural price volatility. This finding is based on extensive and rigorous testing of five internationally traded agricultural commodities (soybeans, corn, sugar, rough rice and wheat) and two oil benchmarks (Brent and WTI). We employ monthly and daily oil and food price volatility data and two forecasting frameworks, namely, the HAR and MIDAS-HAR, for the period 2nd January 1990 until 31st March 2017. Results indicate that oil volatility-enhanced HAR or MI-DAS-HAR models cannot systematically outperform the standard HAR model. Thus, contrary to what has been suggested by the existing literature based on in-sample analysis, we are unable to find any systematic evidence that oil price volatility improves out-of-sample forecasts of food price volatility. The results remain robust to the choice of different out-of-sample forecasting periods and three different volatility measures

Effects of variable EU import levies on corn price volatility

The variable import levy for corn imports in the European Union aims to support European producers by insulating domestic prices from low international prices. Such price-insulating policies have been associated with an increase in global market volatility. Eliminating these distortions has been one of the key issues in international negotiations on agricultural trade liberalization, e.g., the commitment of WTO member states to follow the principle of tariffication as part of the Uruguay Round Agreement on Agriculture. Nevertheless, the Blair House Agreement effectively allowed the EU to maintain a variable import levy regime for grain imports, although the magnitude of this levy is substantially smaller than in the past. Notwithstanding that this policy has been a cornerstone of the EU’s Common Agricultural Policy, empirical evidence on the magnitude of its effects on price volatility is largely missing. This paper employs a multivariate asymmetric volatility model to assess these effects on domestic and foreign corn markets, using Argentina – a large exporter of corn – as an example. In line with the relevant theoretical literature, we find empirical evidence for the 2002–2017 period that the variable import levy reduced corn price volatility in the EU market, while significantly increasing volatility to the same extent in Argentina. In a distorted sense, the import levy of the EU has thus been a success, as its variable application rate has stabilized prices in the EU domestic market. However, our results show that this policy has merely shifted price volatility abroad since it has led to increases in price volatility in Argentina. A less distortionary policy to target the problems of agricultural price volatility should shift its focus away from direct price interventions. For instance, domestic policies that improve farmers’ ability to cope with price-related risks would avoid the negative effects of domestic price stabilization in foreign countries.

Impact of Weather on Agriculture Commodity Market and the Price Discovery: An Empirical Analysis

This paper focused on studying the agricultural commodity prices in India and it's extreme volatility due to many reasons such as government interference, growth, market forces factors, regular floods and droughts, transport and warehousing problems, etc. These are contributing factors to demand fluctuations. In this case, the future market plays an important role in the economy. The demand for commodity futures has three particular economic functions: price discovery, price risk management, and price volatility. The future market plays a key role in the process of price discovery. The main aim of this system is to regulate prices to minimize uncertainty, to provide price signals to market traders for futures spot prices through the price discovery phase. So, this study emphasized the role of the derivative market in reducing the volatility of agricultural commodity prices in the Indian market. Keywords: volatility, future market, derivatives

Systemic Risk in Global Agricultural Markets and Trade Liberalization under Climate Change: Synchronized Crop-Yield Change and Agricultural Price Volatility

Climate change will increase simultaneous crop failures or too abundant harvests, creating global synchronized yield change (SYC), and may decrease stability in the portfolio of food supply sources in agricultural trade. This study evaluated the influence of SYC on the global agricultural market and trade liberalization. The analysis employed a global computable general equilibrium model combined with crop models of four major grains (i.e., rice, wheat, maize, and soybeans), based on predictions of five global climate models. Simulation results show that (1) the SYC structure was statistically robust among countries and four crops, and will be enhanced by climate change, (2) such synchronicity increased the agricultural price volatility and lowered social welfare levels more than expected in the random disturbance (non-SYC) case, and (3) trade liberalization benefited both food-importing and exporting regions, but such effects were degraded by SYC. These outcomes were due to synchronicity in crop-yield change and its ranges enhanced by future climate change. Thus, SYC is a cause of systemic risk to food security and must be considered in designing agricultural trade policies and insurance systems.

An approach to measuring food losses in the potato chain in Ecuador and Peru

Potato production and the related commercial and technological characteristics in the potato value chain, is one of the most important sources of income and food security of thousands of small-scale farmers in the Andes, who are increasingly challenged by trends of urbanization, volatility of agricultural prices, water and land scarcity, environmental stress, and weather shocks. Understanding food losses along the potato value chain and what role these losses play in food security has recently caught the interest of researchers and policy makers as reducing food losses can improve food availability without increasing agricultural inputs, use of land, or technological improvements on the production side. However, estimating food losses has proven to be a daunting task and efforts have yielded estimates that vary considerably. The methodology presented in this study distinguishes losses that are due to physical quantities from those due to quality and value. The results show that the most important losses occur in the production link and that the most important losses faced by small-scale potato producers occur due to crop management practices (before harvest), pests and diseases, frost and drought. Losses in production amount to an average of 95% of total losses in the value chain. This paper reports on the study conducted by the International Potato Center (CIP) through the CGIAR Program on Policy, Institution and Markets (PIM) lead by IFPRI, to evaluate the extent and sources of food losses taking as case study key potato value chains in Ecuador and Peru.

A quantile autoregression analysis of price volatility in agricultural markets

AbstractThis paper investigates the dynamics of agricultural price volatility based on a quantile autoregression (QAR) model. The QAR model provides a flexible representation of the distribution of price and its dynamics. The approach is applied to U.S. wheat and corn markets over the period of 1980–2017. This period is of significant interest as it covers important changes in agricultural policy and increased reliance on markets. The price analysis is conducted conditional on stocks held in the previous period. We show how increasing previous stocks shift the price distribution to the left and decreases the odds of facing price spikes (by shifting down the upper tail of the price distribution). Our analysis also examines the effects of changing public stocks on prices. For both wheat and corn, this reflects changing agricultural policy, contrasting the 1980s (when public stocks were relatively high) with the post‐2005 period (when public stocks became zero). We document how higher public stock ratio during the previous period did not lower the odds of facing price spikes. Applied to the wheat and corn markets, we also uncover evidence of local dynamic instability in the upper tail of the price distribution, suggesting that price instability becomes more pronounced when previous stocks are low.

Dairy Policy in Senegal: The Need to Overcome a Technical Mindset

Since the 1970s, the import of tax-free powdered milk has presented an easy solution to the growing demand for dairy products in West Africa. Recent increases in agricultural price volatility have since contributed to a renewed interest in local milk. However, while the present situation raises issues of food security, rural development and trade policy, public policy remains overly focused on the technical dimensions of dairy development. This article presents the dairy landscape of Senegal, a major regional importer of powdered milk, by considering development dynamics in light of the interactions between technical and organizational models and livestock systems, in terms of relationships with resources and environment, knowledge and social organization. Two implications are discussed: the need for effective sectoral policy to tip the balance in favor of local milk, and the need to base public action on a better understanding of, and improved support for, livestock systems in all their diversity.

Agricultural price volatility and speculation by commodity index funds: a theoretical analysis

PurposeThe role that speculation in futures markets plays during food price spikes is a subject of lively dispute. This issue is often addressed with empirical analyses. They suffer from data limitations and focus on the short-term impacts. The paper aims to discuss these issues.Design/methodology/approachThe authors develop a theoretical model to explain the behaviour of speculators and producers in futures and cash markets. Compared to the only two theoretical analyses by Vercammen and Doroudian where informational externalities are excluded and by Fishe et al. where production responses are excluded, the authors introduce both informational externalities and lagged production responses.FindingsThe authors find that the expanded net long positions of commodity index funds (CIF) are inconsistent with lower stock levels that typically prevail before the price spikes. These positions stimulate production, hence stocks, before the price spikes. Thus they contribute to soften the price volatility.Practical implicationsThe simulation results indicate that before imposing new regulations on financial markets, such as position limits on index funds, their beneficial medium-term effect as a hedging instrument for commercial participants should not be omitted or underestimated.Originality/valueBecause the authors develop a second-best theoretical framework, the authors find that CIF are not a systematic cause of medium-term market swings.

Climate variability and the volatility of global maize and soybean prices

Volatility in the price of agricultural commodities is one of the main factors affecting food security. Many studies have analyzed agricultural market instability from different points of view, but the effect of climate oscillations on agricultural price volatility has been little studied. Climate anomalies, and in particular extreme events, can alter agricultural yields and stocks with related effects on prices. This paper presents a Volatility Impulse Response Function (VIRF) from a multivariate GARCH model to investigate the effects of variability in climatic shocks (El Nino/Southern Oscillation - ENSO) on international maize and soybean price volatility from 1960 to 2014. For both commodities, VIRF analysis was conducted splitting the effect of El Nino and La Nina events according to Spring-Summer and Autumn-Winter meteorological seasons. Both events increase expected price volatility of maize, showing the strongest impact during the El Nino phase in Spring-Summer. Soybean price volatility tends to slightly decrease during Autumn-Winter meteorological seasons and to increase during the Spring-Summer period. To minimize the impact of ENSO events on commodity price volatility, various measures can be taken, both political and technical. Financial aspects should also be considered. It is possible that financial agents can use the ENSO index as information for trading activity, creating a new link between this index and volatility in commodity prices.

Measuring productivity change accounting for adjustment costs: evidence from the food industry in the European Union

This paper extends the measurement of dynamic productivity change over time to provide its full decomposition into economically meaningful components in the Data Envelopment Analysis framework. The dynamic approach accounts for dynamics of production decisions via adjustment costs and is visualized as a dynamic Luenberger productivity change indicator. The paper also estimates the dynamic productivity change and its components for a large dataset of European food companies from 2004 till 2012, grouped into Eastern, Southern, and Western regions. The study reveals three main results. First, the overall trend of dynamic technical regress and positive dynamic technical inefficiency change across almost all regions and sectors was found. Second, some differences for this general pattern were found for the bakery industry and for Eastern European firms. Thirdly, there are also some remarkable changes in indicators observed during the periods related to the financial crisis and the volatility of agricultural commodity prices.