Bubbles in Grain Futures Markets: When are They Most Likely to Occur?

Abstract

Unprecedented changes in agricultural commodity markets since 2004 have had worldwide repercussions, often acting as a destabilizing economic and political influence. In this paper, we use a recently developed multiple bubble testing procedures to detect and date-stamp bubbles in corn, soybean, and wheat futures markets. To account for conditional heteroskedasticity and small sample bias, inferences are derived using a recursive wild bootstrap procedure. We find that the markets experienced price explosiveness about 2% of the time. Using a logit model which accounts for bias due to the rare occurrence of an event, we find that bubbles are more likely to occur in the presence of large aggregate global demand, low stocks to use ratios, and a weak US dollar. While commodity index traders had no effect on the probability of an explosive episode, speculative activity exceeding the minimum level required to absorb hedging activities as measured by the Working’s T reduces considerably the probability of a bubble. Agricultural commodity markets have experienced large price volatility since 2004. For instance, the deflated FAO food price index increased more than 60% from the beginning of 2004 to mid-2008 before subsequently plummeting by over 30% at the end of 2008. The extreme price fluctuations have had worldwide repercussions, often acting as a destabilizing economic and political influence in many countries (Arezki and Bruckner 2011, Bellemare 2011). Given the magnitude of these increases, the consequences can be especially devastating to consumers in less-developed countries. The World Bank (2008) estimates that the cost in 2008 associated with high food and fuel prices to consumers in developing countries was about $680 billion, pushing over 130 million people into extreme poverty and increasing by 44 percent the number of children suffering permanent cognitive and physical injury due to malnutrition. To date, much of the academic debate on recent agricultural price volatility has centered on whether speculative activities or fundamentals are to blame. The first stream of research directly tests the effect of index investment activities by financial traders on agricultural price movements, finding little 1 See http://www.fao.org/worldfoodsituation/foodpricesindex/en/. 2 evidence that index traders were a major driver of recent price spikes (e.g., Stoll and Whaley 2010, Sanders and Irwin 2011, Hamilton and Wu 2013). A related area of research examines the co-movements between commodity and financial prices over time, with some concluding that the financialization of commodity markets contributed to rising prices of non-energy commodity futures by more fully integrating commodity and financial markets (e.g., Tang and Xiong 2012). A second stream of research attempts to explain agricultural price movements through structural models, estimating the relative importance of various possible contributing factors in driving price volatility (e.g., Carter, Rausser, and Smith 2012, McPhail, Du, and Muhammad 2012, Baumeister and Kilian 2013). With the exception of McPhail, Du, and Muhammad (2012), these structural studies typically find that price behavior can be largely attributed to either global or market-specific supply/demand conditions. A third stream of research focuses on directly testing for a bubble component in agricultural prices. Research in this category attempts to identify periods when prices deviate away from a random walk and become mildly explosive using recursive testing procedures developed by Phillips, Wu, and Yu (2011), Phillips and Yu (2011), and Phillips, Shi, and Yu (2012). Several studies have recently applied these recursive testing procedures to various agricultural markets and find mixed results (Gilbert 2010b, Phillips and Yu 2011, Gutierrez 2013). In general, these studies indicate that bubbles, or mildly explosive prices, do exist in grain markets after 2004. However, as shown in the first essay of this dissertation, bubble episodes only represent a very small portion of the price behavior in agricultural commodity markets. In addition, most bubbles are short-lived, with 80 to 90% lasting fewer than 10 days. Previous studies, however, have mainly focused on detecting and date-stamping bubbles, without further investigation of the underlying causes of these explosive episodes. In this paper, we extend the research on bubble testing by examining the conditions in which bubbles are more likely to occur in U.S. grain futures markets. We first identify the exact episodes of explosive behavior, including origination and termination dates, in corn, soybeans, wheat, and KC wheat futures markets during the recent volatile period of 2004-2012. These explosive episodes are obtained by applying the multiple bubble testing procedure developed by Phillips, Shi, and Yu (2012) to series of