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Relationship between price and consumption of metals
Abstract
The relationship between the average price P and the annual consumption C of some 14 metals has been assessed for the nine year period from 1975 to 1983. A relationship has been obtained of the form: log P=log α +β log C. The value of the term β has been found to be about −2/3 in agreement with a previous study. The value of the term a has been found to depend upon the level of inflation expressed through the Consumer Price Index (CPI) and the level of industrial activity expressed through the world Index of Industrial Production (INDPRO). The results obtained are compared with other studies on the subject.MST/830
... Several studies in the academic field of resources policy, have attempted to answer these questions. Examples are Nutting (1977), Georgentalis, Nutting and Phillips (1990), Pei and Tilton (1999), Tcha and Takashina (2002), Lewis (2002, 2005), Chen and Clements (2013), Crompton (2015), and Stuermer (2017). In general, these studies have concluded that per capita consumption is more elastic with respect to income than own price, and that income elasticity may considerably vary across metals and countries. ...
... Specifically, a low (high) β would reflect easy (more difficult) substitution. This type of function has been widely used for analyzing the demand for agricultural commodities (see, for instance, Georgentalis, Nutting and Phillips, 1990, for additional references). For a critical discussion of this statistical approach, see Lewis (2002, 2005). ...
... Resources Policy xxx (xxxx) xxx-xxx the formulation log(P it ) = α i + βlog(C it ) + η it , where P it , C it , and η it are price, consumption, and an error term, respectively, the intercept, α i , is assumed random and usually modeled, at a later stage, as a function of world inflation and world industrial production (e.g., Georgentalis et al., 1990). According to the results of the table, random effects are more suitable than fixed effects on the basis of Hausman test. ...
This article utilizes the Divisia-moment approach to gauge price and income elasticity for seven major metals—steel, aluminum, copper, lead, nickel, tin, and zinc—in eight geographic regions—Africa, Asia, CIS, Europe, the Middle East, North and South America, Oceania—for the period of 1980-2015, and in the world for the period of 1960-2015. Based on various econometric techniques, this article presents new evidence of heterogeneous demand patterns across regions and metals. In particular, South America’s per capita consumption of steel, aluminum and copper is the most price-elastic (-0.18, -0.27, and -0.21, respectively). Other price-elastic regions are North America, Africa, Oceania, and Middle East with respect to nickel (-0.22, -0.46, -0.23, and -0.63, respectively) and CIS and Asia with respect to zinc (-0.26 and -0.14, respectively). This article also presents four extensions: measurement of price flexibility; use of instrumental variables to account for endogenous prices; price- and income-elasticity estimation by country; and, a characterization of mineral expenditure across geographic regions.
Studies by Nutting, Jacobson and Evans and Georgentalis et al. have all concluded, using panel data sets, that a number of metals appear to share a common demand curve that is stable over time. However, these studies have a number of theoretical and econometric limitations. This paper addresses these concerns and reassesses the hypothesis that some metals share such a common demand curve with the same price elasticity of demand. This is achieved within the framework of a random coefficients model. This model was applied to a dynamic metals demand function (DLR) and various estimation techniques were used including OLS, IV, Empirical Bayes (EB) and Instrumental Variables Empirical Bayes (IV-EB). It was found that each metal had its own individual short run demand function with statistically different own price and industrial activity elasticities of demand. In the long run, each metal appeared to be equally unresponsive to price changes, but had different industrial activity elasticities. The speeds of price adjustment to periods of market disequilibrium differed substantially between metals.
Previous studies have identified a single, stable and strong correlation between the price of metals and their consumption, such that low priced metals are always used in large amounts and visa versa. Some have interpreted this as evidence that metals share a common demand curve so that a single price elasticity of demand exists. This paper reviews and tests this hypothesis against a number of other possible explanations, including the idea that the relationship is an empirical curiosity. Modifications to the demand curve were tested by allowing metals to have different intercepts and price elasticities. The results from this analysis suggest that metals do not share a common demand curve and that the correlation identified between the price of metals and their level of consumption is an empirical curiosity. As such, the singular price elasticities published in past papers should not be used for assessing future rates of metals substitution.
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