A speculative bubble in commodity futures prices? Cross‐sectional evidence

Recent accusations against speculators in general and long-only commodity index funds in particular include: increasing market volatility, distorting historical price relationships, and fueling a rapid increase and decrease in the level of commodity prices. Some researchers have argued that these market participants—through their impact on market prices—may have inadvertently prevented the efficient distribution of food aid to deserving groups. Certainly, this result—if substantiated—would counter the classical argument that speculators make prices more efficient and thus improve the economic efficiency of the food marketing system. Given the very important policy implications, it is crucial to develop a more thorough understanding of long-only index funds and their potential market impact. Here, we review the criticisms (and rebuttals) levied against (and for) commodity index funds in recent U.S. Congressional testimonies. Then, additional empirical evidence is added regarding cross-sectional market returns and the relative levels of long-only index fund participation in 12 commodity futures markets. The empirical results provide scant evidence that long-only index funds impact returns across commodity futures markets.     

Bubbles,Froth and Facts: Another Look at the Masters Hypothesis in Commodity Futures Markets

The Masters Hypothesis suggests that long‐only index funds were the main cause of a massive increase in commodity prices in 2007–2008 and 2011–2012. Central to the Masters Hypothesis are three basic tenets: (i) long‐only commodity index funds were directly responsible for driving futures prices higher; (ii) the deviations from fundamental value were economically very large; (iii) the impact was pervasive across commodity futures markets. There has been a great deal of empirical research on the Masters Hypothesis and commodity market bubbles. However, surprisingly few studies have found evidence that directly support the main tenets of the Masters Hypothesis. Some have attributed the lack of supporting evidence to the low‐power of time‐series tests, market efficiency issues and a lack of conditioning variables within models. In this paper, we address each of these issues using updated data and new empirical approaches. Still, price behaviour consistent with the Masters Hypothesis is surprisingly difficult to find in the data. This is an important finding given the on‐going policy debate and regulations proposed or being implemented to limit speculative positions in these markets.     

粮食金融化背景下投机行为与国际粮价波动——以大豆期货为例

利用CFTC公布的COT持仓报告数据检验了2006年6月至2013年7月大豆期货价格和投机性持仓两者间的关系,通过构造投机多头头寸变化率、投机多头头寸占比和投机净头寸3种度量投机力量的指标,发现3种指标均与大豆期货价格正相关,其中投机多头头寸变化率能更好地预测大豆价格的变动.由于投机行为有推高粮食价格的潜在危害,监管机构应当加强监管防止投机资金对粮食衍生品市场的过度投机.     

Agricultural price transmission across space and commodities during price bubbles

This article investigates agricultural price transmission during price bubbles. The empirical approach concerns the horizontal transmission of cereal prices both across different market places and across different commodities. The trade policy intervention put forward to mitigate the impact of price exuberance is considered. The analysis is performed using Italian and international weekly spot (cash) price data over years 2006–2010, a period of generalized turbulence of agricultural markets. Firstly, the properties of price time series are explored; then, interdependence across prices is specified and estimated by adopting appropriate cointegration techniques. Results suggest that the bubble had only a slight impact on the price spread and the temporary trade‐policy measure, when effective, has limited this impact.     

Agricultural Financial Risks Resulting from Extreme Events

Decision‐makers in the agricultural sector operate in a volatile and risky environment. The statistical assessment of agricultural commodity prices is necessary to deduce the stylised facts of agricultural markets and guide the action of market participants. This article examines the kurtosis values of 60 agricultural commodities and presents evidence that the distributions of their returns are fat‐tailed. We use power‐law distributions to model the tail returns and the possible time‐varying extreme event risks in commodity markets. Our results suggest that the usefulness of the value at risk and expected shortfall as risk management tools is questionable.     

Commodity index investment and food prices: does the “Masters Hypothesis” explain recent price spikes?

The “Masters Hypothesis” is the claim that unprecedented buying pressure in recent years from commodity index investors created massive bubbles in food and energy prices. The purpose of this article is to review the evidence from recent studies that investigate the empirical relationship between index investment and price movements in agricultural futures markets. One line of research uses time‐series regression tests, such as Granger causality tests, to investigate the relationship between price movements and index positions. This research provides little evidence in support of the Masters Hypothesis in agricultural futures markets. A second line of research uses cross‐sectional regression tests and studies in this area provide very limited evidence in favor of the Masters Hypothesis for agricultural futures markets. A third line of research investigates whether there is a significant relationship between commodity index trading and the difference, or spread, between futures prices of different contract maturities on the same date. These studies report a range of results depending on the type of test. However, the bulk of the evidence indicates either no relationship or a negative relationship, which is once again inconsistent with the Masters Hypothesis. Overall, this growing body of literature fails to find compelling evidence that buying pressure from commodity index investment in recent years caused a massive bubble in agricultural futures prices. The Masters Hypothesis is simply not a valid characterization of reality.     

Measuring the functional efficiency of agricultural futures markets

This article presents a method for measuring the functional efficiency of agricultural futures markets in terms of social welfare using a standard futures market structural model. Employing the concept of social surplus, it can be shown that, when futures prices are used to estimate future spot prices, the errors in prediction produce to some degree resource misallocation, which in turn results in welfare losses. Therefore, the social welfare associated with the presence of futures markets can be measured using a Social Loss index. The indicator was calculated for the period 1975–2015 and for several subperiods, which allow us to analyse functional efficiency before and after the 2007–2008 spikes in the prices of agricultural commodities. Futures contracts for 12 products are evaluated. The products are grouped in three different categories: ‘soft products’, ‘livestock’ and ‘grains and oilseeds’. The results indicate that livestock contracts tended to be more efficient than the rest of the contracts during the whole period, but in 2008–2015 their efficiency decreased vis‐á‐vis the rest of the products. Nevertheless, 2008–2015 proved to be the most efficient subperiod, confirming the remarkable development of agricultural futures markets over time.     

Financial activity in agricultural futures markets: evidence from quantile regressions

This study analyses the relationship between financial activity and price returns in 12 US agricultural futures markets. It contributes to the existing research by exploring the forecasting power of trading activity for returns from the perspective of conditional quantiles. Quantile regressions detect Granger‐causal effects from positions of speculators and index traders to price returns in a wide range of commodity markets such as cocoa, coffee, corn, sugar and SRW wheat.     

The political economy of quality measurement: a case study of the USA slaughter cattle market

As agricultural products move from being economic commodities to quality–differentiated goods, price dispersion within specific markets increases and implicit subsidies from high quality producers to low quality producers are removed. The present paper examines how these distributional effects can influence patterns of support and opposition to changes in marketing arrangements. The simple model developed is calibrated using data from the USA slaughter cattle market. Estimates of the impact on prices of measuring quality more accurately are found to be similar in size to previous estimates of market power price suppression in the market.     

Price relationships between qualitatively differentiated agricultural products: organic and conventional wheat in Germany

Organic agriculture, which produces commodities that can be qualitatively differentiated from conventional food products, has grown into an important market in many countries. The dynamics of commodity prices in both sectors are partly interdependent, but are also shaped by independent determinants and have rarely been studied. We analyze organic food markets and their interdependencies with conventional markets in the context of wheat markets in Germany, which have been subject to a number of fundamental changes during the last two decades. Based on institutional market characteristics, we suggest a flexible Markov‐switching asymmetric time series model. We find a pronounced temporal sequence of market phases that differ in their asymmetric dynamics and the extent to which the organic price is influenced by the conventional price. Organic wheat prices tend to be increasingly connected to prices of conventional wheat.     

Economic development, institutional change, and the political economy of agricultural protection An econometric study of Belgium since the 19th century

This empirical study uses 100 years of annual data on 11 agricultural commodities from Belgium to measure the impact of structural changes coinciding with economic development and changes in political institutions on agricultural protection. The analysis shows that changes in agricultural protection are caused by a combination of factors. Governments have increased protection and support to farmers when world market prices for their commodities fell, and vice versa, offsetting market effects on producer incomes. Other economic determinants were the share of the commodities in total consumer expenditures (negative effect) and in total output of the economy (positive effect). With Belgium a small economy, there was no impact of the trade position. Changes in political institutions have affected agricultural protection. Democratic reforms which induced a significant shift in the political balance towards agricultural interests, such as the introduction of the one‐man‐one‐vote system, led to an increase in agricultural protection. The integration of Belgian agricultural policies in the Common Agricultural Policy in 1968 coincided with an increase in protection, ceteris paribus. Both institutional factors, related to changes in access to and information about the decision‐making at the EU level, and structural changes in the agricultural and food economy may explain this effect.     

Post–Uruguay Round price linkages between developed and developing countries: the case of rice and wheat markets

The Uruguay Round Agreement on agriculture attempted to lower distortions in global agricultural markets. However, the significant fall in commodity prices in the late 1990s may have reduced the incentives for both developed and developing countries to better integrate into world markets. This study analyzes price linkages and adjustment between developed and developing countries during the post–Uruguay Round period. Prices of two key commodities, long‐grain rice and medium‐hard wheat, are assembled for major exporters and producers. Results of multivariate cointegration analysis suggest partial market integration between developed and developing countries in the post–Uruguay Round period. Developed countries are found to be price leaders in these two markets, and in most cases, changes in their prices have relatively large impacts on those of the developing countries. Developing countries (e.g., Vietnam and Argentina) have faced considerable price adjustment due to changes in the developed countries' prices.     

An Analysis of Removal of Agricultural Trade Barriers between the United States and Canada with Emphasis on the Southeast

A four-region, 23-commodity small world agricultural trade liberalization model within the SWOPSIM framework is used to measure the impact of tariff removal between the United States and Canada. The tariffs are simply defined as negative import subsidy equivalents in the model and are then removed from the trade prices. The model recalculates domestic supply and demand levels in all regions, rebalancing world trade, production, consumption and prices. In summary, the impacts of the Canada-U.S. Trade Agreement on selected commodity groups are significant. Canadian imports of beef and veal, poultry meat, soybean oil and fresh strawberries increase. Furthermore, the results indicate larger trade flows for selected products and declines in producer and consumer prices in Canada, U.S. and Southeast regions. Since the U.S. share of Canadian agricultural imports averaged 60% in the 1980s, the impact of trade liberalization will be greater in Canada in selected commodities than in the U. S. or the southeastern region, and Canadian dependence on the U.S. market will be increasing in the future. The tariff phaseout, together with a reduction in nontariff barriers and harmonizing of domestic agricultural policies, will create more export opportunities in selected commodities for both the United States and Canada, and will create the world's largest free trade market.     

Mobile Phones and Radios: Effects on Transactions Costs and Market Participation for Households in Northern Ghana

The literature on agricultural markets suggests that transactions costs are the main obstacles preventing households from participating in agricultural markets. We examine the impact of the recent massive penetration of information communication technologies (ICTs), particularly mobile phones and radios, in developing countries to investigate the role of information in economic transactions and participation in food crop markets. To fully capture market participation behaviours, the current theoretical framework on market participation and transactions costs is extended to include those households that sell and buy in the same time period. We correct for endogeneity and selectivity throughout our models. We used a novel dataset of 393 households in northern Ghana with detailed information on market transactions and ICTs usage. Results show that receiving market information via mobile phones has a positive and significant impact on market participation, with a greater impact for households with a surplus of food crops. We find that radios have a larger impact on the quantity traded. This may reflect the nature of mobile phones in reducing searching costs, whereas radios provide an updated and regular flow of information which affects the pattern of crops consumed and sold. We also emphasise that the most significant factor is how ICTs are used, rather than their ownership.     

Do farmers benefit from participating in specialty markets and cooperatives? The case of coffee marketing in Costa Rica1

Historically low prices in the conventional coffee market have caused financial and social hardship among coffee farmers. In the face of this crisis, specialty markets have attracted the attention of the international donor community. These market segments have shown consistent growth over the last decade and exhibit price premiums in international markets. Therefore, if higher prices are passed on to farmers, access to specialty markets could help to alleviate the crisis brought on by low prices in the conventional sector. The present study attempts to identify the factors that determine farmers' participation in specialized markets and whether participation in these markets leads to higher prices for farmers. A two-stage model is used to analyze farmers' marketing decisions and their effect on the prices received. This procedure allows us to control for the endogeneity bias introduced by the marketing choice. Our results indicate that farmers participating in the specialty coffee segment do in fact receive higher prices than those participating in conventional channels. Additionally, we find that participation in cooperatives has a positive impact on the probability that a farmer chooses to grow specialty coffee and analogously on the prices that they receive. Based on these results, it seems that efforts to increase participation in the specialty coffee segment and in cooperatives would help to lessen some of the hardships brought on by low prices in the conventional coffee sector.     

Market interdependence and volatility transmission among major crops

This article provides a comprehensive analysis of the dynamics of volatility across major agricultural commodities in the United States. Volatility interactions across markets may lower the effectiveness of diversification strategies to mitigate price risks and should be taken into account when analyzing the pricing behavior of different agricultural commodities. We follow a multivariate GARCH approach to evaluate the time evolution of conditional correlations and volatility transmission across corn, wheat, and soybeans price returns on a daily, weekly, and monthly basis. The period of analysis is from 1998 to 2012. The estimation results indicate a lack of lead‐lag relationships between corn, wheat, and soybeans price returns at the mean level. We find, however, important volatility spillovers across commodities, particularly at the weekly and monthly level. Wheat and corn seem to play a major role in terms of volatility transmission. Despite the supposed higher financial market integration of agricultural commodities, we do not observe that agricultural markets have become more interdependent in recent years.     

Residential housing bubbles in Hong Kong: identification and explanation based on GSADF test and dynamic probit model

We aim to investigate whether the current high housing price in Hong Kong contains a bubble and to identify the causes of such housing bubble if it exists by combining the generalised sup augmented Dickey–Fuller (GSADF) test and dynamic probit models. Empirical results indicate that the current Hong Kong housing market contains a bubble, and it’s the investors’ speculative demand and the increase of monetary supply that lead to the housing bubbles in Hong Kong. Moreover, speculative investors would prefer the mass markets to the luxury ones considering the outstanding performance of the former. Such preference would contribute to more bubbles in the mass markets than in the luxury ones. In view of these, Hong Kong Government should retrospect the linked exchange rate system and be alert to the impacts of the US monetary policies on Hong Kong residential market. To offset the housing bubble, a targeted and effective approach to the Hong Kong Government is to constrict the speculative demand from investors particularly in the mass markets.     

Alpaca Lies? Speculative Bubbles in Agriculture: Why They Happen and How to Recognize Them

The speculative bubble phenomenon has been studied extensively by economists and psychologists in recent years. The recent literature is surveyed and extended to enhance the understanding of speculative bubbles in agricultural industries. The analysis is applied to the U.S. alpaca industry, where prices for breeding stock are many times higher than in Peru, home of the world's largest alpaca herd. We present a framework to assess whether current prices for U.S. alpaca stock are supported by market fundamentals or are likely to represent a speculative bubble. Finally, we identify "warning signs" common to agricultural bubbles.     

Pricing to market behaviour of India's high value agri‐food exporters: an empirical analysis of major destination markets

The pricing behaviour of India's high value agricultural and food exporters in their major destination markets is examined using a pricing‐to‐market (PTM) model for noncompetitive and exchange rate related pricing behaviour. The analysis was undertaken in a context where India is showing high commodity concentration in agricultural trade. The econometric analysis employed is panel corrected standard errors (PCSE) estimation technique. The results indicated evidence of a greater degree of imperfect competition either through price discrimination across destinations or through imperfect exchange rate pass‐through. The analysis of exchange rate effects showed that the local currency price stabilization by the Indian exporters were more prominent than the amplification of exchange rates. The analysis of the asymmetric effects of exchange rates on export prices showed that in most cases the depreciation of Indian rupee had a greater impact than the appreciation. Moreover the results showed that the exchange rate pass‐through is sensitive to the kind of exchange rate index utilised. In our analysis we found that the commodity specific exchange rate better predicts the pricing to market behaviour in most cases.     

Monetary policy shocks and the dynamics of agricultural commodity prices: evidence from structural and factor‐augmented VAR analyses

Fluctuation in commodity prices is a significant and timely issue to be studied. This study is to examine the impact of monetary policy and other macroeconomic shocks on the dynamics of agricultural commodity prices. The major contributions of this study are twofold. First, unlike other studies that use indexes, this study analyzes the commodities individually, affording the inclusion of commodity‐specific fundamentals such as the level of inventory—an important determinant of commodity price—in a structural VAR framework. Second, it exploits a rich data set of agricultural commodity prices which includes commodities that are usually overlooked in the literature, and extracts a common factor using the dynamic factor model to understand the extent of comovement of the prices and to gauge the extent to which macroeconomic shocks drive the “comovement” in a factor‐augmented VAR (FAVAR) framework. The findings show that monetary policy, global economic conditions, and the U.S. dollar exchange rates play an important role in the dynamics of agricultural commodity prices.