Commodity price bubbles and macroeconomics: evidence from the Chinese agricultural markets

Abstract

This paper investigates the linkages between commodity price bubbles and macroeconomic factors, with an application to agricultural commodity markets in China from 2006 to 2014. Price bubbles are identified using a newly-developed recursive righttailed unit root test. A Zero-inflated Poisson Model is used to analyze the factors contributing to bubbles. Results show that a) there were speculative bubbles in most of the Chinese agricultural commodities during the sample period, though their presences are rather infrequent; b) economic growth, money supply and inflation have positive effects on bubble occurrences, while interest rate has a negative effect; c) among all macroeconomic factors considered, economic growth and money supply have the greatest effects on bubble occurrences. Our findings shed new light on the nature and formation of bubble behavior in the Chinese agricultural commodity markets.

Price bubbles in agricultural commodity markets and contributing factors: evidence for corn and soybeans in China

“…Currently, the GASDF test has been widely accepted and used to detect bubbles in many markets, such as stock markets (Caspi and Graham, 2018; Hu and Oxley, 2018), real estate markets(Anundsen et al , 2016; Engsted et al , 2016; Pavlidis et al , 2016) and energy markets (Caspi et al , 2018; Tsvetanov et al , 2016). Recently, many studies also try to apply this method into the agricultural commodity markets (Etienne et al , 2015; Gutierrez, 2013; Li et al , 2017a, b). Detailed introduction of the GSADF test is described as following.…”

“…Phillips and Yu (2011) even point out that varying interest rates could induce temporary explosive behaviors in asset prices. Li et al (2017a, b) find that price bubbles are more likely to happen under certain macroeconomic conditions. In addition, some other studies concerning commodity price volatility prove that macroeconomic factors significantly affect the low-frequency component of price volatility (Engle and Rangel, 2008; Karali and Power, 2013).…”

“…Importantly, our study is different from the other studies in the way of estimating the contributing factors of price bubbles. Due to the rare occurrences of bubbles, the existing empirical studies would pool different commodities together, when estimating the common potential influencing factors of price bubbles (Etienne et al , 2015; Li et al , 2017a, b). This is no longer appropriate if considering the specific features of different commodity markets and may even result in misleading conclusions.…”

A quantile autoregression analysis of price volatility in agricultural markets

“…There is evidence that low stocks have contributed to high price volatility (e.g., Bobenrieth, Wright, & Zeng, ; Wright, ; von Braun & Torero, ), stimulating a debate about strategic public food stock policy (Gouel, ,b; Headey, ; von Braun & Torero, ). However, previous research also argues that by smoothing price fluctuations through the accumulation of large amount of public stocks, a government is depriving the private agents of the much‐needed speculative opportunities (Gouel, ; Li, Chavas, Etienne, & Li, ). The low level of private stocks all through the 1980s‐early 1990s can be seen as an illustration of the possible crowding‐out effect of public stocks on private ones.…”

An Agent-Based Modeling and Simulation Approach to Commodity Markets

“…As witnessed by the 2007–2008 world food crisis, the high increase in price observed in these years heavily reduced the access to food by poor countries and lowered the possibility for them to receive help from aid agencies (Wiggins & Levy, 2008). Second is the role of commodities as an input for real production activities (Li, Chavas, Etienne, & Li, 2017). This heavily impacts on the macroeconomic performance, which is perhaps a less urgent issue than that of survival, but nevertheless affects the standard of living of the whole population.…”