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Market efficiency in non-renewable resource markets: evidence from stationarity tests with structural changes

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Abstract

The dynamics of metal prices are highly significant for worldwide economic activity due to metals being key intermediate inputs to industrial production and construction and treated as investment assets. In that sense, this study investigates the efficient market hypothesis, i.e., predictability of price patterns, for several non-renewable resources, namely copper, lead, tin, nickel, zinc, aluminum, gold, platinum, and silver. Our period covers 1980Q1–2019Q4, during which metal markets witnessed many extraordinary times due to market-specific and global factors. Accounting for the importance of the potential breaks in the analysis of stochastic properties of non-renewable resource prices, we utilize two different stationarity tests; one is designed to capture smooth breaks, and the other one is designed to detect abrupt changes in the prices. Our empirical results reveal that none of the prices, except silver, can be characterized by the efficient market hypothesis. They follow stationary and predictable patterns with structural changes related to market-specific and global economic events, though concerns on economic uncertainties appeared to be more effective on precious metals.

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Data availability

The data used in this study are available from the corresponding author upon request.

Code availability

The GAUSS code used for the analysis is available from the corresponding author upon request.

Notes

  1. The Malthusian approach states that natural resources are fixed in supply, and their demand grows with population, which puts upward pressure on resource prices. However, due to technological advances, which enable the exploration of new reserves, the supply is not considered entirely fixed. Technological progress further leads to cost reductions, increases in labor productivity, efficiency gains, and improvements in workers’ safety through automated, remote-controlled, and autonomous types of equipment. Hence, innovation plays an essential role in the mining industry by loosening the supply constraint and leading to price declines even in the face of volatile commodity markets.

  2. The reason behind selecting this set of non-renewable resources is that although different groups of resources are analyzed in the literature, copper, lead, tin, nickel, zinc, and aluminum are the ones investigated in almost all studies. For precious metals, gold, silver, and platinum are selected, while palladium, one of the metals commonly used in the literature, is excluded due to data constraints.

  3. Regarding cyclicality, it is worth mentioning that a common characteristic of metal prices is that periods of rising prices (expansions) are generally followed by falling prices (contractions). There are many studies, including Davutyan and Roberts (1994),  Cashin and McDermott (2002), Roberts (2009), and Rossen (2015), examining whether these fluctuations are sufficiently regular to be characterized as cycles or they occur randomly. Despite some differences, those studies agree on the finding that some of the fluctuations are not purely random and show some degree of cyclicality. Rather than being confined to a single filtering procedure, a comprehensive analysis covering various different filters designed for specific data characteristics is required to analyze the cyclicality in the metal price. In our study, in line with all existing empirical studies in the literature, we limit our scope to propose a reliable testing procedure for the market efficiency hypothesis without accounting for metal price cycles. We agree that the cyclicality of the metal prices is an issue that requires great attention and leave it for future research. We are grateful to an anonymous referee for bringing this valuable extension to our attention.

  4. In their papers, Carrion-i Silvestre and Sanso (2007) have proposed seven different specificants for the deterministic terms that are represented by \(f\left( {t,T_{b1} ,T_{b2} } \right)\). Among them, we select the most general form that allows for two structural changes in the intercept and trend terms. For other deterministic specifications, see Carrion-i Silvestre and Sanso (2007).

  5. When we extend the grid search procedure for each integer value of \(k \in \left[ {1,5} \right]\), we observe no substantial change in the reported results.

  6. Russia was the second largest primary aluminum producer after the USA in years 1992 and 1993 (Bureau of Mines 1993:107).

  7. The first exchange-traded fund backed by gold is established in 2003.

  8. Given the historical correlation between gold and silver, the nonstationarity finding for silver prices can sound surprising while gold prices follow a stationary path. To clarify this point, we can recall that there are numerous studies on the co-movements of gold and silver (e.g., Ciner (2001); Escribano and Granger (1998); Lucey and Tully (2006); Soytas et al. (2009), Rossen (2015)). Overall, results indicate that the connection between gold and silver prices depends on the time period under consideration, and they have become more separated over time. The reason behind such a divergence, which is more apparent in the short run, is that these precious metals do not belong to one great pool due to their characteristics and economic uses. Although both gold and silver are used in the jewelry industry and treated as investment assets, the industrial use of silver is quite remarkable so that almost half of the silver consumption is for industrial applications (electronic and electrical industries (mobile phones, computer hardware) and photography to a smaller extent).

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Authors and Affiliations

  1. Banking and Financial Institutions Department, Central Bank of the Republic of Turkey, 06100, Ankara, Turkey

    Alper Kara

  2. Department of Economics, Middle East Technical University, 06531, Ankara, Turkey

    Dilem Yildirim & G. Ipek Tunc

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  1. Alper Kara
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Kara, A., Yildirim, D. & Tunc, G.I. Market efficiency in non-renewable resource markets: evidence from stationarity tests with structural changes. Miner Econ 36, 279–290 (2023). https://doi.org/10.1007/s13563-022-00312-8

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