The cost and technological structure of aluminium smelters worldwide

Abstract

A cost model is developed for the estimation of several technological parameters describing the production process of aluminium smelters worldwide. The model is similar to Baltagi and Griffin's (1988), but, instead of estimating technological change using a panel data set of firms, we estimate, among other things, the vintage effect, using a cross‐section of aluminium smelters in operation throughout 1994. The vintage effect is defined as the variable cost differential that may be attributed to the utilization of a specific technical vintage in the production of aluminium in relation to another. Other technological measurements are also discussed: the scale effect or returns to scale and technological characteristic effects, i.e. the variable cost elasticities with respect to pot size and current intensity. The results show that considerable cost reductions may be expected from the change of old technical vintages to more recent ones. Also, results show that for a majority of smelters in the sample, returns to scale seem to be exhausted. Finally, variable costs are very sensitive to pot size in the sense that large cost reductions can be expected from the increase in pot size, an important characteristic of the technology used by smelters. Copyright © 2000 John Wiley & Sons, Ltd.

Aluminum

“…Production capacities have exploded, with everlarger smelters. (22) Only about forty countries in the world produce primary aluminum.…”

Aluminum

“…Production capacities have exploded, with everlarger smelters. (22) Only about forty countries in the world produce primary aluminum.…”

Sensitivity of generalized translog model estimates to alternative Pythagorean means: Evidence from US healthcare

“…The GTL models are widely used in applied econometrics modeling of activities in the aggregate economy, manufacturing and service industries, and in establishments 1 [see, for example, energy (Boluk & Koc, 2010), banking (Horvath, Seidler, & Weill, 2016;Knott, Posen, & Wu, 2009), supply chain logistics (Liu, Wang, Yao, & Yue, 2016), agriculture (Kavoi, Hoag, & Prichett, 2009), health systems (Granderson, 2011;Suraratdecha & Okunade, 2006), primary healthcare (Guiffrida, Gravelle, & Sutton, 2000), general cost modeling (Delis, Iosifidi, & Tsionas, 2014), aluminum smelting (Gagne & Nappi, 2000)], information technology (Chwelos, Ramirez, Kraemer, & Melville, 2010), and others. The widespread acceptance of the GTL is rooted in (Christensen, Jorgenson, & Lau, 1973), a landmark paper.…”

Evaluating the efficiency of the global primary aluminum smelting industry: a data envelopment approach

“…Electricity consumption is measured as the use in kilowatt hour per ton of finished aluminum in the electrolytic process itself, thus excluding any auxiliary electricity use in the plant. In some studies (e.g., Gagné and Nappi 2000;Bye and Førsund 1990), alumina is 12 To maintain the confidentiality of the CRU proprietary data, smelters will never be named, and all efficiency scores and other results pertains only to geographical groups of smelters. 13 However, even though CRU claims that this number represents the entire population of smelters, there might be small scale smelters (most likely in China) not accounted for.…”

“…The curve shows the cumulative capacity of smelters in a region from the lowest to the highest cost operations, i.e., indicating the competitive position of individual smelters. 5 According toGagné and Nappi (2000), 60% of the variability in variable production cost across smelters emanate from differences in electricity costs 6 See for instance, Murillo-Zamorano and Vega-Cervera(2001),Murillo-Zamorano (2004),Yin (2000),Cubbin and Tzanidakis (1998), andHjalmarsson et al (1996) for an overview of the pros and cons of each of the methods.…”

“…Thus, these studies miss out on the fact that the plant or mill might operate far off from what is the industry's most 1 The studies that do exist focus on other topics related to the aluminium production technology and use other methods. For example, some studies uses econometric techniques to estimate (among other things) factor substitution elasticities (e.g., Lindquist 1995;Tsekouras and Zagouras 1998;Larsson 2003 andBlomberg andSöderholm 2010), technological vintage effects (e.g., Gagné and Nappi 2000) and pricing and investment behavior in the primary aluminium industry (e.g., Figuerola-Ferretti, 2005). Another strand of research is represented by Førsund and Jansen (1983) and Bye and Førsund (1990) who derive short-run production functions in a puttyclay framework for the Norwegian primary aluminium industry using linear-programming like techniques.…”

Aluminum

“…Production capacities have exploded, with everlarger smelters. (22) Only about forty countries in the world produce primary aluminum.…”

Sensitivity of generalized translog model estimates to alternative Pythagorean means: Evidence from US healthcare

“…The GTL models are widely used in applied econometrics modeling of activities in the aggregate economy, manufacturing and service industries, and in establishments 1 [see, for example, energy (Boluk & Koc, 2010), banking (Horvath, Seidler, & Weill, 2016;Knott, Posen, & Wu, 2009), supply chain logistics (Liu, Wang, Yao, & Yue, 2016), agriculture (Kavoi, Hoag, & Prichett, 2009), health systems (Granderson, 2011;Suraratdecha & Okunade, 2006), primary healthcare (Guiffrida, Gravelle, & Sutton, 2000), general cost modeling (Delis, Iosifidi, & Tsionas, 2014), aluminum smelting (Gagne & Nappi, 2000)], information technology (Chwelos, Ramirez, Kraemer, & Melville, 2010), and others. The widespread acceptance of the GTL is rooted in (Christensen, Jorgenson, & Lau, 1973), a landmark paper.…”

Evaluating the efficiency of the global primary aluminum smelting industry: a data envelopment approach

“…Electricity consumption is measured as the use in kilowatt hour per ton of finished aluminum in the electrolytic process itself, thus excluding any auxiliary electricity use in the plant. In some studies (e.g., Gagné and Nappi 2000;Bye and Førsund 1990), alumina is 12 To maintain the confidentiality of the CRU proprietary data, smelters will never be named, and all efficiency scores and other results pertains only to geographical groups of smelters. 13 However, even though CRU claims that this number represents the entire population of smelters, there might be small scale smelters (most likely in China) not accounted for.…”

“…The curve shows the cumulative capacity of smelters in a region from the lowest to the highest cost operations, i.e., indicating the competitive position of individual smelters. 5 According toGagné and Nappi (2000), 60% of the variability in variable production cost across smelters emanate from differences in electricity costs 6 See for instance, Murillo-Zamorano and Vega-Cervera(2001),Murillo-Zamorano (2004),Yin (2000),Cubbin and Tzanidakis (1998), andHjalmarsson et al (1996) for an overview of the pros and cons of each of the methods.…”

“…Thus, these studies miss out on the fact that the plant or mill might operate far off from what is the industry's most 1 The studies that do exist focus on other topics related to the aluminium production technology and use other methods. For example, some studies uses econometric techniques to estimate (among other things) factor substitution elasticities (e.g., Lindquist 1995;Tsekouras and Zagouras 1998;Larsson 2003 andBlomberg andSöderholm 2010), technological vintage effects (e.g., Gagné and Nappi 2000) and pricing and investment behavior in the primary aluminium industry (e.g., Figuerola-Ferretti, 2005). Another strand of research is represented by Førsund and Jansen (1983) and Bye and Førsund (1990) who derive short-run production functions in a puttyclay framework for the Norwegian primary aluminium industry using linear-programming like techniques.…”

Aluminum

“…Production capacities have exploded, with everlarger smelters. (22) Only about forty countries in the world produce primary aluminum.…”

Sensitivity of generalized translog model estimates to alternative Pythagorean means: Evidence from US healthcare

“…The GTL models are widely used in applied econometrics modeling of activities in the aggregate economy, manufacturing and service industries, and in establishments 1 [see, for example, energy (Boluk & Koc, 2010), banking (Horvath, Seidler, & Weill, 2016;Knott, Posen, & Wu, 2009), supply chain logistics (Liu, Wang, Yao, & Yue, 2016), agriculture (Kavoi, Hoag, & Prichett, 2009), health systems (Granderson, 2011;Suraratdecha & Okunade, 2006), primary healthcare (Guiffrida, Gravelle, & Sutton, 2000), general cost modeling (Delis, Iosifidi, & Tsionas, 2014), aluminum smelting (Gagne & Nappi, 2000)], information technology (Chwelos, Ramirez, Kraemer, & Melville, 2010), and others. The widespread acceptance of the GTL is rooted in (Christensen, Jorgenson, & Lau, 1973), a landmark paper.…”

Evaluating the efficiency of the global primary aluminum smelting industry: a data envelopment approach

“…Electricity consumption is measured as the use in kilowatt hour per ton of finished aluminum in the electrolytic process itself, thus excluding any auxiliary electricity use in the plant. In some studies (e.g., Gagné and Nappi 2000;Bye and Førsund 1990), alumina is 12 To maintain the confidentiality of the CRU proprietary data, smelters will never be named, and all efficiency scores and other results pertains only to geographical groups of smelters. 13 However, even though CRU claims that this number represents the entire population of smelters, there might be small scale smelters (most likely in China) not accounted for.…”

“…The curve shows the cumulative capacity of smelters in a region from the lowest to the highest cost operations, i.e., indicating the competitive position of individual smelters. 5 According toGagné and Nappi (2000), 60% of the variability in variable production cost across smelters emanate from differences in electricity costs 6 See for instance, Murillo-Zamorano and Vega-Cervera(2001),Murillo-Zamorano (2004),Yin (2000),Cubbin and Tzanidakis (1998), andHjalmarsson et al (1996) for an overview of the pros and cons of each of the methods.…”

“…Thus, these studies miss out on the fact that the plant or mill might operate far off from what is the industry's most 1 The studies that do exist focus on other topics related to the aluminium production technology and use other methods. For example, some studies uses econometric techniques to estimate (among other things) factor substitution elasticities (e.g., Lindquist 1995;Tsekouras and Zagouras 1998;Larsson 2003 andBlomberg andSöderholm 2010), technological vintage effects (e.g., Gagné and Nappi 2000) and pricing and investment behavior in the primary aluminium industry (e.g., Figuerola-Ferretti, 2005). Another strand of research is represented by Førsund and Jansen (1983) and Bye and Førsund (1990) who derive short-run production functions in a puttyclay framework for the Norwegian primary aluminium industry using linear-programming like techniques.…”