Agricultural Commodity Price Volatility Research Articles

Monetary policy and distributional effects of agricultural commodity price volatility in Sub-Saharan Africa

Monetary policy and distributional effects of agricultural commodity price volatility in Sub-Saharan Africa

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.

Asymmetric GARCH models on price volatility of agricultural commodities

Asymmetric GARCH models on price volatility of agricultural commodities

The COVID-19 effects on agricultural commodity markets

ABSTRACT This study examines the effect of the COVID-19 pandemic on major agricultural commodity prices (cattle, cocoa, coffee, corn, cotton, hog, rice, soya oil, soybeans, soybean meal, sugar and wheat) using daily data from 1 January 2016 to 25 February 2022. We measured COVID-19 effect using a news-based sentiment index. A robust nonparametric Granger causality-in-quantiles test is used to test the effect of the COVID-19 sentiment on agricultural commodity prices and price volatility. We find significant Granger causality from the news-based COVID-19 sentiment to mean of the agricultural commodity prices in the lower and upper ranges of the quantiles. Moreover, findings show that the COVID-19 sentiment is also causal for variance of agricultural commodity prices, but only above the quantile ranges above the first quarter. Thus, COVID-19 is causal for large volatility changes in agricultural commodity prices. Accordingly, the extremely negative sentiment associated with COVID-19 has not only caused a price crash in agricultural markets, but also significantly increased market risk. Policymakers should be wary of the risks and vulnerabilities of agricultural commodities to extreme events, as well as the ramifications for producers and consumers throughout the economy.

Short-Term Speculation Effects on Agricultural Commodity Returns and Volatility in the European Market Prior to and during the Pandemic

Motivated by increased agricultural commodity price volatility and surges during the past decade, we investigated whether financial speculation is to blame. The aim of this paper is to build on prior research about to what extent and in which ways financial speculation undermines agricultural commodity prices. In our analysis, we utilized the daily returns on milling wheat, corn, and soybean futures from the Euronext Commodities Paris market (MATIF) as well as the short-term speculation index. To quantify this impact, we apply Granger noncausality tests as well as the GARCH (generalized autoregressive conditional heteroskedasticity) technique. We also propose a model using seasonal dummy variables to examine whether financial speculation has a greater impact on price volatility during more volatile months. According to our results, financial speculation, as an external factor, in most cases has no effect or reduces the volatility of the underlying futures prices. The opposite is observed in the corn market, where volatility has risen in the post-2020 period and has been pushed up even more by speculation in April. However, since the influence on other commodities is limited or nonexistent, more emphasis should be focused on speculation in the European corn futures market or its interdependence with energy markets.

Price Volatility and Transmission: A case study of paddy and redgram markets in Karnataka

Price volatility of major agricultural commodities has attracted major attention in the last few years in India as well as in the world food markets. It is often observed that price changes of major staple food items have negative impact on the welfare of the producer farmers as well as consumers. This study tries to explore the nature and causes of the price changes of paddy and redgram in Karnataka. The secondary data of paddy and redgram prices from major markets were compiled and analysed using volatility index and co-integration techniques. Data from major markets by considering time series data for about two decades from2000-2018 were used to understand the trends, volatility and transmission. It was discovered that, prices were not particularly unpredictable, retail prices were more erratic than farm harvest prices, wholesale prices, and minimum support prices in Paddy whereas in redgram, farm harvest prices were comparatively erratic than other prices. The volatility may be related to agricultural production’s intrinsic instability as a result of unexpected and unpredictable exogenous shocks such as weather and poor price and income elasticities. And study on price transmission would help to know, how the prices have transmitted from one market to other market and reveals the relationship between prices over time between the markets considered.

Maize price volatility and deforestation

AbstractWe develop a model of deforestation using a real option on agricultural land conversion and establish an important link between agricultural commodity price volatility and forest loss. Higher price volatility of staple commodities increases incentives to delay land conversion and is associated with lower levels of deforestation. Using satellite‐derived estimates of local deforestation and high‐frequency local maize prices across a panel of market catchments across 26 countries in sub‐Saharan Africa, we find strong empirical evidence that maize price volatility is negatively associated with forest loss. Our findings are driven by catchments in biomes that are relatively well‐suited to maize production. Instrumenting for changes in price levels and price volatility with spatially explicit temperature and rainfall anomalies yields results consistent with our main approach. The findings highlight important tensions between agricultural price stabilization policies, conservation efforts, and environmental externalities.

The COVID-19 Effects on Agricultural Commodity Markets

This study examines the effect of the COVID-19 pandemic on major agricultural commodity prices (cattle, cocoa, coffee, corn, cotton, hog, rice, soya oil, soybeans, soybean meal, sugar and wheat) using daily data from February 28, 2020 to November 20, 2020. We measured COVID-19 effect using a news-based sentiment index. A novel nonparametric causality-in-quantiles test was used to test the effect of the COVID-19 sentiment on agricultural commodity prices and price volatility. We found significant causality from the news-based COVID-19 sentiment to mean of the agricultural commodity prices in the lower and upper ranges of the quantiles, but not in the quantiles around the median, implying that the COVID-19 sentiment largely causes extreme changes in the agricultural commodity prices. Moreover, findings show that the COVID-19 sentiment is also causal for variance of agricultural commodity prices, but only above the quantile ranges above the first quarter. Thus, COVID-19 is causal for large volatility changes in agricultural commodity prices. Accordingly, the extremely negative sentiment associated with COVID-19 has not only caused a price crash in agricultural markets, but also significantly increased market risk.

Statistical Analysis of Price Volatility of Agricultural Commodities Traded at the Ethiopian Commodity Exchange (ECX) Using Multiplicative GARCH-MIDAS Two-component Model

We applied multiplicative GARCH-MIDAS two component models for price return volatility of selected commodities traded at the Ethiopian commodity exchange (ECX). Unlike the ‘traditional’ generalized autoregressive conditional heteroscedasticity (GARCH) family models, GARCH-MIDAS component model can capture the time-varying conditional as well as unconditional volatilities, and accommodates macroeconomic variables observed at different frequencies through mixed interval data sampling (MIDAS) specification. The results of our specification tests revealed the existence of both time-varying conditional and unconditional variance. The fitted GARCH-MIDAS component models showed that realized volatility, inflation rate and fuel oil price have had an increasing effect on the price volatility of the commodities under consideration, while real effective exchange rate (REER) had the opposite effect. Furthermore, mean square error (MSE), mean absolute error (MAE) and Diebold and Mariano (DM) test were used for evaluating and comparing the forecasting ability of GARCH-MIDAS component models against standard GARCH models. The results revealed that GARCH-MIDAS component models outperformed the standard GARCH model for high-frequency data.

Macroeconomic Impact of Agricultural Commodity Price Volatility in Nigeria

Introduction: The Nigerian economy has remained consistently heavily dependent on earnings from commodity exports which constitute over 95% external earning and 85% of budgetary and fiscal financing. Agricultural commodity exports have witnessed a significant price swings in the international market in the past few decades resulting in food price hike and macroeconomic distortions in economies heavily dependent on food imports. Methods and Materials: The study assesses the macreoconomic impact of agricultural commodity price volatility in Nigeria from 1970-2017 using Autoregressive Distributive Lag (ARDL) cointegration and Impulse-Response Function (IRF) analysis. The study adopted an atheoretical statistics to ascertain the evidence of swings in macroeconomic aggregates. Results: There was evidence of persistent fluctuations in the macroeconomic variables observed, implying that external price shocks exert a significant impact on the macroeconomic management, since bulk of national budgetary and fiscal financing is from commodity exports. Conclusion: The study found that volatile agricultural prices were responsible for a meager 2% of macroeconomic fluctuations. The empirical evidence corroborates the statistics showing that the share of agriculture in primary commodity exports has consistently remained less than 3% since the advent of crude oil. Furthermore, the study found that the swings in agricultural prices impacts foreign reserves and inflation more significantly and earlier in the time horizons than other macroeconomic aggregates.

Price volatility of Polish agricultural commodities in the view of the Common Agricultural Policy

In the paper, the price volatility was examined. The authors used 650 weekly observations from 2003 to 2015. Such a long period of analysis helped to reveal periods with high volatility. The objective of the paper was to recognize price volatility of agricultural commodities in Poland. The authors chose beef, pork and wheat markets to show the differentiation of price volatility. It revealed periods of large and small volatility. The global market situation impacted Polish agricultural markets with the opening markets and a greater access to the new markets. The periods having the strongest impact on Polish agricultural markets were the integration with the EU, the global crisis in 2008, and problems in the EU zone. The prices of analysed agricultural commodities differed in various EU countries. The prices of wheat increased most in France, Hungary and Lithuania. The prices of store cattle increased most in the years 2004–2015 in Estonia, Sweden and Luxemburg. The prices of pigs increased most in Malta, Sweden and Cyprus.

Effects of the agricultural commodity and the food price volatility on economic integration: an empirical assessment

This paper empirically examines the effects of the global agricultural commodity price volatility and the food price volatility on the level of economic integration over the period 1970–2012. The benchmark regressions are based on the data from 133 countries. The results indicate that the level of economic integration is negatively related to both the agricultural commodity price volatility and the food price volatility. In addition to this, the negative impacts of the agricultural commodity price volatility and the food price volatility on the level of economic integration are statistically significant in the middle- and the high-income countries. These findings remain robust when it considers different estimation techniques and different measures of price volatility, and deals with extreme cases.

Modeling regime‐dependent agricultural commodity price volatilities

AbstractIn stark contrast to financial markets, relatively little attention has been given to modeling agricultural commodity price volatility. In recent years, numerous methodologies with various strengths have been proposed for modeling price volatility in financial markets. We propose using a mixture of normals with unique GARCH processes in each component for modeling agricultural commodity prices. While a normal mixture model is quite flexible and allows for time varying skewness and kurtosis, its biggest strength is that each component can be viewed as a different market regime and thus estimated parameters are more readily interpreted. We apply the proposed model to ten different agricultural commodity weekly cash prices. Both in‐sample fit and out‐of‐sample forecasting tests confirm that the two‐state NM‐GARCH approach performs better than the traditional normal GARCH model. A significant and state‐dependent inverse leverage effect is detected only for pork in the regime where the price is expected to drop, indicating the volatility in this regime tends to increase more following a realized price rise than a realized price drop.

Spekulation am Terminmarkt und die Preisentwicklung von Agrarrohstoffen am Kassamarkt: Eine Zeitreihenanalyse der CFTC Berichte für Weizen, Mais und Sojabohnen / Speculation in Futures Markets and the Impact on Agricultural Commodity Prices: A Time Series Analysis of the CFTC Reports for Wheat, Corn and Soybeans

Summary Over the last few years, rising prices and increasing price volatility of major agricultural food commodities were observed. This caused a debate among various organizations about who is responsible for this development. While many Non-Governmental Organizations proclaim that speculations in future markets cause the rise in food prices, academic research provides ambiguous results on this topic. This controversy is the motivation for this study. In order to offer additional insights, the relationship between the price changes of corn, wheat, and soybeans and the corresponding changes in open interests are analyzed. Commitments of Traders as well as Disaggregated Commitments of Traders reports are investigated to determine whether the activities of speculators adversely affect food prices. First, Johansen cointegration tests are employed to analyze the relationship between price and position data. Second, VAR and VECM are used to analyze short- and long-term dynamics. The results of the empirical analysis demonstrate that in the short-run price changes precede changes in open interest. Additionally, soybeans show a long-run equilibrium relationship between both series, indicating that speculators influenced past prices to some extent. However, the percentage price change is rather low. Therefore, sharp rises in soybean prices cannot be explained by it.

The Impact of Price Volatility of Agricultural Commodities in Polandon Alternative Incomes of Conventional, Ecological and AgritourismFarms

The objective of this paper is to recognize price volatility of main commodities and to measure the impact of price level on agricultural incomes of farms and the number of farms having alternative income sources. First we focused on price volatility changes in the European Union and Poland. Economic and econometric analysis tools were used to measure the impact of the price volatility. We collected observations from the Ministry of Agriculture and Rural Development in Poland. The analysis found big differences in price volatility for Polish commodities. The price volatility was connected with the global crisis. The Polish agricultural sector faced global problems, but could not fully overcome them. The rise of agricultural commodity prices created market problems such as increased bread and food prices. Polish consumers adjusted their purchases and their expenditures on food. This situation is common for many EU states and the price volatility can be reduced only through the Common Agricultural Policy. Poland’s markets are global and stabilization is achievable only by active EU rural policy.

Book Reviews

Finn Tarp of UNU-WIDER and University of Copenhagen reviews “The Economics of Food Price Volatility”, by Jean-Paul Chavas, David Hummels, and Brian D. Wright. The Econlit abstract of this book begins: “Nine papers, plus nine comments, present and assess recent research on central issues related to recent food price volatility. Papers discuss influences of agricultural technology on the size and importance of food price variability; corn production shocks in 2012 and beyond─implications for harvest volatility; biofuels, binding constraints, and agricultural commodity price volatility; the evolving relationships between agricultural and energy commodity prices─a shifting-mean vector autoregressive analysis; the question of bubble troubles─rational storage, mean reversion, and runs in commodity prices; bubbles, food prices, and speculation─evidence from the Commodity Futures Trading Commission's daily large trader data files; food price volatility and domestic stabilization policies in developing countries; food price spikes, price insulation, and poverty; and trade insulation as social protection.” Chavas is Anderson-Bascom Professor of Agricultural and Applied Economics at the University of Wisconsin-Madison. Hummels is Professor of Economics in the Krannert School of Management at Purdue University. Wright is Professor of Agricultural and Resource Economics at the University of California at Berkeley.

Food Security Component of Sustainable Development – Prospects and Challenges in the Next Decade

Abstract In this article we will presents a series of interesting aspects regarding food security as component of sustainable development and also possible factors that influence the national and global food security. All this elements putted together will analyze the next possible steps prospects and challenges in the next decade for global food security. Today, there is a series of rising risk phenomena near Romania and we notice that, a series of global problems affects more and more our sustainable development and obvious our food security. Thus, it is highly important to approach food security as a phenomenon that may generate social convulsions. Sustainable development is a new type of human strategy that meets current needs, without compromising the ability of future generations to meet their own needs. This process incorporates immediate and long-term purposes, economic and environment problems, agro food potential and all these elements being in tight connection. There are many factors that can influence the sustainable development and the connection between agriculture potential and the possibility of creating food security in our region. One of the great challenge of next decade at the global and regional level is and will remain the “price volatility” of commodity is a serious problem especially for countries of the world which are dependent producers of raw materials. Agricultural commodity price volatility it is and will remain as generate factor of national food insecurity and the future solid sustainable development.

Impacts of energy shocks on US agricultural productivity growth and commodity prices—A structural VAR analysis

We examine the impacts of energy price shocks on U.S. agricultural productivity growth and commodity prices' volatility by developing a structural VAR model. We use historical annual data of real U.S. gasoline prices, agricultural total factor productivity (TFP), real GDP, real agricultural exports, and real agricultural commodity price from 1948 to 2011 to estimate the model. Our results indicate that an energy price shock has a negative impact on productivity growth in the short run (1year). An energy price shock and an agricultural productivity shock each account for about 10% of U.S. agricultural commodity price volatility with the productivity shock's contribution slightly higher. However, the impact from energy prices outweighs the contribution of agricultural productivity in the medium term (3years). With more persistent impacts, energy shocks contribute to most (about 15%) of commodity price's variation in the long run.

Analysis of woody biomass commodity price volatility in Austria

Several energy and agricultural commodities have experienced higher price volatility in recent years. Management of price risks usually leads to additional costs that are often shared and transmitted along the supply chain to the final consumers. Only little information is currently available on how price volatility of woody biomass commodities has developed compared to energy and agricultural commodities in recent years. We compute the historic price volatility of woody biomass commodities using the standard deviation of log returns as well as univariate GARCH models. The results show that the price volatility of several woody biomass commodities has increased in recent years. However, the price volatility of woody biomass is still lower compared to the price volatility of agricultural commodities and fossil fuels. The analysis of factors and linkages provides insights of the current biomass market developments.

L'obbligo dei contratti di cessione dei prodotti agricoli e alimentari: una valutazione degli effetti dell'articolo 62 della legge n. 27/2012

In recent years, European farmers have been facing two new phenomena: agricultural commodity price volatility and a decrease in agricultural added value. These issues led the High Level Forum to censure low transparency in relationships between firms and frequently unfair commercial practices, after the European Commission had recognized that the agri-food supply chains were functioning imperfectly. Economic theory considers contracts as a means of coordinating entrepreneurs’ decisions (e.g. in terms of time, quantity, prices and product quality). Nevertheless, in the presence of oligopsony, buyers use contracts to improve and exercise their market power, for example by imposing vertical restraints. This situation is typical of European food supply chains, where highly concentrated sectors (food industry and retail) use their bargaining power against agriculture. In this context, antitrust authorities and eu Member States have sought to resolve the situation by stipulating appropriate competition policy measures. In Italy, Law 27/2012 has recently introduced new mandatory rules regarding sales contracts for agriculture and food products, in order to increase trading transparency and reduce payment times. Using an embedded multiple-case study, carried out through interviews and direct observations, this article analyses the initial effects of the application of the law on the Italian agri-food system.