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Keywords:

  • dematerialization;
  • industrial ecology;
  • input−output analysis (IOA);
  • material flow analysis (MFA);
  • physical trade balance;
  • raw material consumption

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Methodology
  5. Results
  6. Concluding Remarks
  7. Acknowledgments
  8. References
  9. About the Authors

This article aims at estimating the raw material equivalents (RMEs)—the upstream used material flows required along the production chain—of imports and exports for some Latin American countries: Brazil, Chile, Colombia, Ecuador, and Mexico. Furthermore, the United States is included in the analysis as a reference for a high-income economy. The RME concept and the empirical evidence are articulated by use of an input−output methodology. Results are set out for the year 2003 for each of the countries and in time series for the years 1977, 1986, 1996, and 2003 in the case of Chile. The findings show not only the physical dimensions behind direct material traded but also how the previous exporter (importer) position of a country (based on standard material flow analysis indicators) deteriorates, alleviates, or changes. Implications for material consumption indicators, such as direct material consumption (DMC) and raw material consumption (RMC), are also drawn. The results suggest basing the discussion of material flows on a broader set of indicators to obtain a more comprehensive picture of the implications of international trade and its impacts on the environment.


Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Methodology
  5. Results
  6. Concluding Remarks
  7. Acknowledgments
  8. References
  9. About the Authors

In recent years, empirical evidence about international trade for some Latin American countries showed that these countries are net exporters in terms of direct material flows and consequently have a deficit in their physical trade balance (PTB; see Figure 1).1 Moreover, the data available indicate that the physical deficits for all these countries have been deteriorating more or less continuously in the last decades. For instance, in 1980 the cumulative PTB deficit for Chile, Colombia, Ecuador, and Mexico was around 46 million tonnes,2 whereas for 2003 the PTB deficit had almost tripled, to 136 million tonnes.3 Thus, the empirical evidence until now has revealed a tendency toward an increasing imbalance between exports and imports in physical terms for Latin American countries (Giljum 2004; Giljum and Eisenmenger 2004; Perez-Rincon 2006, Vallejo 2006; Russi et al. 2008). These physical aspects of international trade are often neglected in conventional economic analyses, although they are important if researchers are to understand ecological inequalities that take place through international trade. Imbalances in physical terms of trade are related to economic reforms in the region oriented toward liberalization, deregulation, and the promotion of exports as the main driving force for inducing economic growth (see, e.g., Gonzales-Martinez and Schandl 2008; Muñoz and Hubacek 2008).

image

Figure 1. Physical trade balance (PTB) of selected Latin American countries, various years. Sources: Giljum (2004), Giljum and Eisenmenger (2004), Perez-Rincon (2006), Vallejo (2006), Gonzales-Martinez and Schandl (2008), and Russi and colleagues (2008).

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It is important to highlight, however, that in some cases the production of commodities requires large quantities of materials that normally are not accounted for in statistics, because they relate only to direct material flows entering an economic system, either from nature or from another country through imports. This is mainly the case for some mining commodities, such as platinum or copper, for which considerable amounts of crude metal ores usually must be extracted to produce a small quantity of pure mineral. As Ayres and colleagues (2004, 60) commented,

a hundred tonnes of platinum used each year in the United States for industrial and automotive catalysts requires that a hundred million tonnes of crude ore (more or less) must be dug up and processed in South Africa.

A similar situation exists in some Latin American countries, as they also play an important role in satisfying world mineral demands. For instance, Chile is the leading copper supplier in the world; it exported 4.7 million tonnes of concentrated copper in 2003 (one third of the world market). This copper output required approximately 470 million tonnes of crude ores, which remained in the country as waste from metal processing. Moreover, this country is the fifth world silver supplier (1,312 tonnes and 7.1% of the world market in 2003). In 2003, Peru was the largest and Mexico the second largest silver supplier in the world, producing 2,920 tonnes and 2,551 tonnes, respectively. Furthermore, Peru was the world's fourth largest gold producer (173 tonnes and 7.3% of the world market in 2005; Cochilco 2006). Brazil and Venezuela are also important world suppliers of iron ore and crude oil, respectively, among other materials from the region.

Evidently, the physical exports and imports displayed in Figure 1 ignore significant indirect material flows—that is, flows that remain in the exporting countries. Considering PTBs only in terms of commodities that cross the borders thus neglects those considerable quantities of materials that were necessary upstream along the extraction and production stages of the life cycle. Accounting just for direct flows leads to a certain bias in the sense that exported and imported commodities are compared at different stages of processing than domestically extracted materials (Weisz 2007). Consequently, economy-wide indicators derived from standard material flow analysis (MFA), such as direct material consumption (DMC), attribute the ancillary mass of the production of concentrated copper for exports to the domestic “apparent consumption” of these economies.4 Thus, for example, a previous study of Chile (Giljum 2004) reports that the average Chilean citizen consumed about 44 tonnes of material per capita in 2000, which is far more than the average European citizen, who consumed around 15 tonnes per capita in the same year (Weisz et al. 2006). Therefore, estimating indirect flows linked to imports and exports allows researchers to reattribute crude metal ores to international trade flows instead of domestic demand.

Thus, if the aim is to measure the physical terms of trade (and investigate their ecological implications), it seems appropriate to consider not only direct flows of exports or imports but also the indirect flows associated with trade. To measure the indirect flows associated with international trade, Eurostat (2001, 23–24) suggests estimating the “up-stream indirect flows expressed as the Raw Material Equivalent (RME) of the exported and imported products” (see also OECD 2007). It is important to note that the concept of RME refers only to “used materials”—that is, those material flows that enter economic processes. The other component of these indirect flows, unused extraction, is not included in RME and, despite its ecological relevance, is not considered here. Material inputs included in RME are therefore necessary to produce an output. A certain portion of such inputs, however, is embodied in the final outputs, whereas the rest of the material is dissipated along the production chain or recycled.

The objective of this article is to estimate the direct and indirect (in terms of used extraction) material flows—that is, the RME of the export and import commodities of some Latin American countries (Brazil, Chile, Colombia, Ecuador, and Mexico) as an empirical measure of the physical exchange for these economies. Subsequently, taking into account the RME of imports and exports as well as the final domestic demand, we can estimate the material “consumption” for those countries in terms of RME, also called raw material consumption (RMC) in the Eurostat (2001) terminology. The RMC indicator thus differs from the standard indicator of DMC, as it includes trade flows as RMEs instead of only direct trade flows. These indicators based on RMEs offer a different perspective than other indicators derived in previous studies on Latin America as well as empirical evidence of concepts developed in the Eurostat (2001) guidebook for material flow accounting.

This article is structured as follows: The next section presents the method we used to estimate the RME of imports and exports; techniques related to input−output analysis (IOA) are described. Subsequently, we present the results for the RME associated with exports and imports for the economies under analysis and discuss the trade balances and material consumption of the countries. Finally, we make some concluding remarks.

Methodology

  1. Top of page
  2. Summary
  3. Introduction
  4. Methodology
  5. Results
  6. Concluding Remarks
  7. Acknowledgments
  8. References
  9. About the Authors

In the past few years, a number of studies were conducted that highlight the importance of considering the environmental impacts of internationally traded products (Ahmad and Wyckoff 2003; Nijdam et al. 2005; Peters and Hertwich 2006; Helm et al. 2007). Such studies assess indicators of the environmental performance of countries, also taking into account those impacts that take place beyond the boundaries of the countries themselves. In this respect, analytical measures of environmental responsibilities suggest a change from a production-based principle (PBP), such as that implemented in the Kyoto Protocol, to a consumption-based principle (CBP). In the PBP, environmental responsibilities are restricted to geographical borders. This means that indicators only capture the environmental pressures that are linked to the production of national goods and exports. The CBP implies a reattribution of embodied environmental pressures associated with exports to foreign countries and the addition to domestic environmental responsibilities those impacts that take place abroad (for further details, see the work by Munksgaard and Pedersen [2001]; Lenzen et al. [2007]; Peters [2008]).

These two concepts have an increasing importance in the context of inventories of national emissions. When indicators are based on the CBP, countries’ performance may change considerably. For instance, Helm and colleagues (2007) emphasize that the United Kingdom's carbon dioxide (CO2) emission record relies on commodity imports from developing countries, which are carbon intensive. A more detailed discussion in this realm has also been carried out by Ahmad and Wyckoff (2003), who highlight that emissions of the OECD countries measured by a CBP were 5% higher than emissions determined with the PBP. Peters and Hertwich (2006) also identified the specific region where the major environmental pressures take place, to satisfy Norway's consumption. They found that CO2 emissions embodied in imports were 67% of Norway's domestic emissions. Around half of this embodied pollution originated in developing countries. Serrano and Roca (2008) analyzed the emissions for various atmospheric pollutants embodied in Spanish imports and exports. They conclude that, for most of the contaminants, Spain is a “net exporter” of pollution, so the emissions embodied in the imports are higher than those contained in the exports.

A small number of studies have focused on the material requirements of traded commodities. Explanations could be found in the urgent need to mitigate climate change effects, the explicit link between emissions and environmental impacts, and data availability. Giljum and colleagues (2008) showed that although per capita resource extraction levels are, in general, significantly lower in developing countries compared to developed countries, from a consumption perspective, a further shift from developing to developed countries through international trade can be observed, due to the high indirect material flows of developing countries’ exports. Using a static input–output approach, researchers have shown that the Chilean exports required around 80% of the direct material inputs (DMI) in 1996 (Muñoz and Roca 2006). Weisz (2007) estimates the indirect material flows of Denmark's imports as being roughly twice as large as its exports. Nijdam and colleagues (2005) point out that a large number of indicators of environmental pressure (land use, fish extraction, water use) take place in non-OECD countries. In a similar perspective, Schütz and colleagues (2004) argue that considering the total material requirements in international trade of the European Union (EU) leads one to reconsider material decoupling trends for this region, given that the EU has increasingly shifted environmental burdens to the countries of the South. Thus, recent studies have added a CBP to the traditional PBP to consider environmental aspects of international trade. This allows for a more accurate picture of the environmental responsibilities and a better understanding of phenomena such as dematerialization or decarbonization trends for some countries or regions.

The Model

At a methodological level, IOA offers a suitable analytical framework for operationalizing the RME concept and empirical evidence, tracing back the material requirements of traded commodities at the different stages of production and extraction.5 The analysis begins with a static and open IOA, in which the balance between total supply and total commodity use is represented by equation (1). The supply side is reflected by the total domestic production and total imports, contained in vector xt. The demand side, represented by the right-hand side of equation (1), displays information about commodity use. Matrix Zt denotes the total commodities (including imports and domestic production) for intermediate use (IU); i is an auxiliary vector of ones; and yt is the vector of total final demand (FD), which also includes exports and domestic final demand.

  • image(1)

Moreover, it is also possible to split up equation (1) between domestically produced and imported commodities, as shown in equations (2) and (3), respectively:

  • image(2)
  • image(3)

Likewise, variables are defined similarly as in equation (1), but their origins and use are differentiated between national production and imports. Thus, xd is the vector of domestic production; Zd is the matrix of domestic IU; vector yd describes the final demand for domestically produced commodities, including household consumption, investment in fixed capital, government expenditure, and exports; m is a vector of total imports—that is, imports for IU and FD; Zm is the matrix of imported commodities for IU, which reflects the imported commodities that are necessary to produce other commodities within the system; and ym is a vector of imported commodities for final demand.

Furthermore, when we express the quantities of commodities Zd and Zm, as a proportion of the domestic output,6xd, the so-called matrix of technical coefficients, Ai, is obtained:

  • image(4)

From the former equations it is possible, as indicated by Pulido and Fontella (1993, 92–97), to estimate the sectoral production requirements distinguishing between nationally produced commodities and imports needed to satisfy a certain level of final demand. To obtain this, we must rewrite equations (2) and (3) in terms of the technical coefficients matrix and break down the final demand for domestically produced commodities, yd, into its exported share, e, and its share for domestic final demand, f, (i.e., yd minus exports). Thus, it is gathered that

  • image(5)
  • image(6)

From equations (5) and (6), it is feasible to estimate the domestic production requirements for any level of domestic final demand (f) and exports (e), with consistency in IU import requirements (Pulido and Fontella 1993).

Environmental Extended IOA

We can extend equation (5) to MFA by adding a domestic vector of material intensity, in which the domestic material requirements are expressed per unit of commodity output. Although standard economy-wide MFA does not provide information on sectoral material flows, data on domestic material extraction (DE) can be linked to the respective economic sectors. For example, the extraction of agricultural products is linked to the agriculture sector, the extraction of metal ores and minerals is linked to the mining sector, and so on. (See a more detailed explanation of the link between physical and monetary statistics in the Data subsection). This extension of the model is represented by equation (7):

  • image(7)

where inline image is a diagonalized intensity vector of DE per unit of domestic commodity output, xd. The term q*DE in equation (7) gives information about the domestic material requirement reattributed to the domestic final demand as well as the foreign demand. Additionally, it is possible to separate the components of the final demand, which provides the DE necessary to satisfy domestic final demand, by equation (8):

  • image(8)

The DE necessary to produce exports is given by equation (9):

  • image(9)

The import model presented in equation (6) accounts for import requirements of an economy. To identify the upstream material requirements of the commodities imported, it is necessary to incorporate the technology used for producing them, expressed in the Leontief inverse matrix (I−At)−1, as well as the linkage between the production output and material used, inline image. Tracing import flows back to their country of origin requires considerable data, however. It is not sufficient to know only the technology and the material intensities of the commodities imported from different countries; it is also necessary to include data of the bilateral trade interrelations among these regions.

Due to data limitations and to keep the calculation method simple, we have made a restrictive assumption in the model, which assumes that the import commodities are produced with the same technology and input coefficients as the country under analysis. This assumption of a similar technology could be interpreted as the materials “saved” through imports. This is, to some extent, a rather unrealistic assumption, given that the main trade partners of these countries are developed countries with different production technologies and structures. Therefore, it is expected that technology and intensities are dissimilar. As a consequence, one might expect that the environmental responsibilities abroad are less than the estimates here, as technology in developed countries is expected to be less material intensive than in developing countries. Researchers have relaxed this kind of assumption in recent studies by using multiregional IOA (Nijdam et al. 2005; Peters and Hertwich, 2006; Giljum et al. 2008). This approach is out of the scope of this article, however. Another aspect not captured by the model is the feedback trade loops that refer to the production dependency between countries. In this model, “autonomous trade flows” are assumed (for details, see the work by Lenzen et al. [2004] or Munksgaard et al. [2005]). Moreover, we have used a matrix A in monetary terms; results may change when the coefficient matrix is based on a physical IO table or on a hybrid table, in which primary and manufacturing sectors are expressed in physical units and the service sectors are expressed in monetary units (Weisz 2007). Further assumptions are intrinsic to the general IO technique (see Miller and Blair 1985).

Thus, if we assume that the technology of production, (IAt)−1, and the material intensity, inline image, are the same as the economy under analysis, we can obtain equation (10) by premultiplying equation (6) by these terms:

  • image(10)

where the term I provides general information about the RME needed to meet total imports. Intermediate inputs have not yet been reattributed to final demand in this term. Splitting up I into II, III, and IV gives insights of the “final destinations” of the material import requirements: II provides information about the upstream material requirements for producing a unit of imports, whereas III allows us to estimate the import needs for the intermediate use of domestic production, and IV represents the RME for satisfying the final demand of imported goods.

Therefore, from equation (10), it is feasible to estimate the RME that is necessary abroad to satisfy the domestic final demand of domestically produced commodities:

  • image(11)

It is also possible to account for imported materials necessary to produce exports, which are a kind of “transit” flows in this analytical framework, given by

  • image(12)

Finally, the material requirements necessary to satisfy the final demand of imports are estimated as follows:

  • image(13)

Raw Material Trade Balance and RMC Indicators

As we have already mentioned in the introduction, the PTB is defined as direct imports minus direct exports. From previous methodological analysis, the imports and exports in terms of RME can be derived as shown in Table 1. These indicators are the basis for calculating raw material trade balances (RTBs)—that is, RME of imports minus RME of exports.

Table 1.  Estimates of imports and exports in terms of raw material equivalents (RME)
 Raw material trade balance
RME of imports RME of exports
Equation (11)Imported materials necessary to produce domestic final demand for domestically produced commoditiesEquation (9)Domestic material extraction necessary to produce exports
Equation (12)Imported materials needed to produce exports, which are a sort of “transit” flowEquation (12)Imported materials needed to produce exports, which are a sort of “transit” flow
Equation (13)Imported materials required to meet the goods and services that are directly imported to satisfy the final demand--

Note that it is possible to use solely the term I in equation (10) for import estimates. The right-hand side of equation (10) is preferred, however, due to the fact that all intermediate material imports were reattributed to the final demand, thus allowing a comparison of the environmental pressures for the different components of final use.

Finally, the RMC is estimated for each country as follows:

RMC = DE + RME of imports, equations (11), (12) and (13)− RME of exports, equations (9) and (12)

Data

The model is fixed to 2003 because this is the most recent and common year that supply and use tables (SUTs) are available for a considerable number of Latin American countries. Using the same base year allows comparison between countries that fulfill these data requirements: Brazil, Chile, Colombia, Ecuador, and Mexico. The United States is also included in the analysis, as an empirical case of a high-income economy. Additionally, Chile is analyzed in time series for 1977, 1986, 1996, and 2003.

SUTs are developed and provided by the corresponding institutes of statistics or central banks of the countries7 under investigation. In some cases, however, SUTs were converted from purchasers’ prices into basic prices to reflect as accurately as possible the inputs required by each sector, because purchasers’ prices include taxes and transport margins. This was particularly the situation for the SUTs of Brazil, Colombia, and Ecuador. For Chile and Mexico, the SUTs were available in basic prices, whereas for the United States, the SUT was utilized in producer's prices. Furthermore, in the cases of Brazil, Colombia, Ecuador, and the United States, we needed to split the SUTs into the domestic table and the import table by using a straightforward proportionality assumption, which implies that each industry used the imported commodity in proportion to the total quantity used of this product. For further details about these two data harmonization tasks, see the working paper by Yamano and Ahmad (2006). We used IOTs in a commodity-by-commodity formulation obtained from SUTs by applying the industry-based technology assumption.8

With regard to the combination of biophysical and economic data, a certain level of uncertainty remains. Because the different material data are compiled separately from the industry in which the materials have been extracted, assigning materials to industries carries a lack of certainty. This is mainly due to the fact that not only does the main or primary industry extract a specific material, but other industries also deal with the same material in secondary production. For this reason, a commodity-by-commodity formulation is applied whereby secondary production is reattributed to the main (primary) industry, which reduces the risk of incorrect allocations (see the work by Miller and Blair [1985] for further details). Subsequently, the biophysical data have been aggregated by material descriptions into the same disaggregation level as the SUT and combined with the corresponding commodities. In addition, material allocations allow us to obtain the material intensity of different industries by dividing the material vector by the total output vector (see equation 7). Note that these intensities refer not to the tonnes of materials that result as an output from the economic system (e.g., tonnes of refined copper) but rather to the total materials that cross the border of the environmental−economic system when they are extracted (e.g., copper ore with a concentration of approximately 1% of the metal).

Given the base year, 2003, the corresponding material data are also restricted to this time period. Chile's material flow data are based on the estimates made by Giljum (2004). In addition, we have updated MFA indicators for Chile from 2001 until 2005 and combined particularly 2003 data with the IOT for that specific period. The global material flow database by the Sustainable Europe Research Institute (SERI 2008; see http://www.materialflows.net), which was developed and is currently updated in EU research projects and which reports DE of all countries in the world on the basis of international statistics,9 is used for the rest of the countries. The model estimates the RME in terms of “used” domestic materials. This implies that unused extraction has not been taken into account in this study. It is also important to mention that the DE used in this study does not entail water or air, consistent with most MFA studies.

Furthermore, the DE indicator is aggregated from a list of more than 200 materials, according to the commodity classification provided in the SUTs. All the empirical outcomes should be taken cautiously, because they are dependent on the data quality. Moreover, each SUT was kept with its own classification; this implies that sectoral comparisons between countries should be even more cautiously understood, because each nation uses its own commodity or industry classification, such as the Central Product Classification (CPC), the International Standard Industrial Classification (ISIC), or the North American Industry Classification System (NAICS).

Results

  1. Top of page
  2. Summary
  3. Introduction
  4. Methodology
  5. Results
  6. Concluding Remarks
  7. Acknowledgments
  8. References
  9. About the Authors

The RME of Exports and Imports

Considering RME of imports and exports is crucial for understanding the environmental pressures of international trade. The physical dimensions behind the direct trade flows change considerably in some cases. As a starting point, Table 2 presents the RME, direct material flows, and indirect material flows attributed to imports and exports10 of the countries under analysis. RME stems from the methodological framework presented in the previous section. Direct material flows that cross the system boundaries (or country borders) are obtained from previous studies (see Figure 1). Finally, we estimate indirect flows, as Eurostat (2001) suggested, by subtracting the direct flows from the RME.

Table 2.  Physical trade flows in terms of raw material equivalents (RME), direct flows, and indirect flows in millions of tonnes (Mt) for 2003
CountryExportsImports
RME aDirect flows bIndirect flows a–bRME cDirect flows dIndirect flows c–d
  1. aDirect material flows for Brazil and the United States are our own estimates based on the previous works of Machado (2001) and Rogich and colleagues (2008).

Brazila1,164341 823 817108 709
Chile  700 27 673   66 26   40
Colombia  178 76  101   55 14   41
Ecuador   29 21    8   20  7   14
Mexico  411244  167  421185  236
United Statesa1,3343191,0151,9704881,482

The findings indicate that, on average, each ton exported by Chile needs around 25 tonnes of indirect flows that remain in the country in the form of waste and emissions. Part of the indirect flows could eventually be recycled, however. The relation is significantly less when fossil fuels are a considerable part of exports, as, for example, in Ecuador (0.4 t of indirect flows for each ton of direct flows) or Mexico (0.7 t). When exports are led by biomass, the coefficients are 4.6 and 1.3 for Brazil and Colombia, respectively. The quantity of indirect flows related to imports tends to be less variable, ranging between 0.1 t for Brazil and 0.8 t for Mexico. For the rest of the countries, the coefficients are contained in that interval.

Moreover, Figure 2 presents the net material trade balances—that is, physical material imports minus exports in terms of RME (RTB) and in terms of direct material flows (PTB) for the economies under analysis. Findings indicate that for some countries the deficit in PTB increases when the material trade balance is estimated from an RME perspective. This is especially the case for Chile, as we intuitively expected, given that large flows of ore minerals were assigned away from domestic consumption to exports: The equilibrium in terms of PTB thus turns into a huge deficit in terms of RTB. For Brazil and Colombia the situation is similar, although less evident: The deficits in material trade balances increase from 233 Mt (PTB) to 347 Mt (RTB) for Brazil and from 62 Mt (PTB) to 123 Mt (RTB) for Colombia. In the case of the United States, the surplus in material trade balances increases from 170 Mt (PTB) to 636 Mt (RTB). A different result is found for Ecuador, where the deficit decreases from 15 Mt (PTB) to 9 Mt (RTB) when it is measured in terms of RME. This is because of the indirect material flows of imports, driven by manufactured goods, which require more material inputs along the production chain than exports, which are dominated by oil. Mexico is an interesting case, because the material trade balance changes from a deficit in PTB to a surplus in RTB when indirect flows are accounted for with respect to traded goods and services. Interpretations of import results must be considered carefully, however, because of the restrictive assumption regarding the technology used for producing imported commodities (see the Methodology section).

image

Figure 2. Raw material trade balances and physical trade balances (in millions of tonnes for 2003).

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Figure 3 illustrates the RME of imports and exports of different commodity groups. In general, one observes a clear tendency toward exports of primary commodities for developing countries (more than 80% of total exports), especially for Chile, Colombia, Ecuador, and Mexico. The case of Brazil appears less clear; exports of primary commodities represent almost 40%. If the food industry is included, however (which is part of light industries in Figure 3), the proportion of primary commodity exports in total exports also increases to 60%. For the United States, the exports of primary commodities are around 48%, which may be surprising for a high-income economy and most probably cannot be generalized to the majority of the richer countries. Conversely, more than 50% of the imports of these countries, including the United States, are assigned to heavy industries and services as their final sectoral destination.

image

Figure 3. Import (m) and export (x) structures based on raw material equivalents RME for Brazil (BR), Chile (CL), Colombia (CO), Ecuador (EC), Mexico (MX), and the United States (US) in 2003. Sectoral comparisons between countries should be carefully interpreted due to countries’ dissimilar commodity classifications. Nevertheless, high aggregation levels as presented in this figure tend to match.

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Furthermore, Figure 4 presents the whole metabolism of each system, showing the economy-wide balances in physical and monetary terms for the countries under study. We also present balances in monetary units to contrast potential asymmetries between physical and monetary units. Moreover, Figure 4 shows an overview of how these economies are supplied with material resources, distinguishing between imports and domestic supply flows, on the one hand, and the final demand, on the other hand, and differentiating between domestic consumption and exports. Thus, the results give a general idea of how economies meet their needs, both in physical and in monetary terms, showing the key role of international trade for the different countries.

imageimage

Figure 4. Economy-wide physical and monetary balances in 2003. RME = raw material equivalent; RMC = raw material consumption; BUS$= Billions of U.S. dollars; GDP = gross domestic product.

The monetary trade balances (MTB) were more or less in equilibrium for Chile, Colombia, Ecuador, and Mexico, and the value of exports was in the same range as the value of imports, with a variation of a maximum of 9%. In comparison, Brazilian export values were 28% larger than imports, and the United States’ exports were 53% less than its imports. The physical side of international trade presents large asymmetries in the RTB for most of the countries, apart from Mexico. For instance, whereas Brazilian and Chilean exports were larger than imports in monetary terms, the RTB had a deficit of 42% and 1,000% (exports were around ten times larger than imports), respectively. Colombia and Ecuador not only show higher values of total imports than of exports but also present a deficit in RTB; the RME of exports was larger than that of imports. In the MTB, imports were around 9% larger than exports for these two countries, whereas Colombia's physical exports were three times as large as its imports, and Ecuador's exports were 44% larger than its imports. Finally, Mexico's and the United States’ MTBs exhibit higher imports than exports, by 5% and 53%, respectively, showing a surplus of 2% and 51% in the RTB (the RMEs of exported commodities were smaller than those of imported products).

RMC versus DMC

In general terms, material consumption is defined as DE plus imports minus exports. As it is clearly derived from this analysis, the way exports and imports are measured does matter for calculating the levels of material consumption of economies. Differences can be explained by exclusion versus inclusion of indirect material flows of trade. Whereas DMC considers only the direct material embodied in exports and imports, RMC adds the indirect flows required upstream along the production chain—that is, it accounts for imports and exports from the RME perspective. Thus, RMC can serve as an alternative analytical measure for material consumption, and it may be more precise than DMC for analyzing countries’ material needs for maintaining a specific standard of living.

Figure 5 shows Chile's material consumption from both perspectives, RMC and DMC. The DMC indicator for the Chilean economy increased by a factor of around 6 between 1977 and 2003. Over the same period of time, however, the RMC indicator only grew by a factor of about 2. This is a clear situation in which RMC should be used instead of DMC if the purpose is to reflect domestic material needs.

image

Figure 5. Chile's domestic consumption expressed in terms of direct material consumption (DMC) and raw material consumption (RMC) for 1977, 1986, 1996, and 2003. RME = raw material equivalent.

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Furthermore, DMC per capita in Chile rose from 13 tonnes in 1977 to 47 tonnes in 2003, whereas the RMC per capita increased from 7 tonnes per capita to 10 tonnes per capita for the periods under study. In 1986, it is possible to observe an absolute dematerialization. This is due to a global oil crisis that heavily affected the Chilean economy during this time. For example, household consumption (in constant prices) decreased by almost 30% in 1983 in relation to 1981. In 1986, it still remained 26% below the 1981 levels. In fact, it took 10 years for household consumption to reach the level of 1981.

From the analysis above, it seems to be more appropriate to use RMC than DMC. The differences between the approaches are particularly large for Chile. The use of the RMC indicator should especially be considered for other mineral-extractive economies, such as Peru, which had a DMC per capita of 18 tonnes in 2003 (Russi et al. 2008). For the rest of the countries, discrepancies between DMC and RMC are less clear: The differences in value between the indicators do not exceed ±2 tonnes. For Brazil and Colombia, DMC is still larger than RMC. In the case of Mexico and Ecuador the opposite is true, however, which means that the ratio of indirect flows is higher for imports than for exports (see Figure 6).

image

Figure 6. Raw material consumption (RMC) and direct material consumption (DMC) in tonnes per capita for Brazil, Chile, Colombia, Ecuador, Mexico, and the United States (2003).

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Concluding Remarks

  1. Top of page
  2. Summary
  3. Introduction
  4. Methodology
  5. Results
  6. Concluding Remarks
  7. Acknowledgments
  8. References
  9. About the Authors

RME adds interesting perspectives for measuring and analyzing the physical trade relations and the material consumption levels of countries in different regions of the world. First, it gives a different picture of the physical flows involved in international trade, including not only the direct but also the indirect materials required for the production of exports and imports. In general, indirect flows of exports tend to be larger and more variable between countries than flows of imports. This means that each traded ton leaves waste and emissions in the exporting countries. The quantities of waste and emissions left in exporting countries differs according to the structure of the economy but in some cases the quantities are considerable. This is especially evident in the case of exporters of metal ores, such as Chile (where each tonne of exports leaves behind, on average, 25 tonnes in the form of indirect flows).

Second, the RME approach provides further insights into the net material exporter (or importer) position of a country: That is, it offers a different analysis of the degree to which a country's level of consumption is sustained by the imports from other nations and articulated by international trade. As Figure 1 shows, there is a trend toward equilibrium in terms of the direct material imports and exports for Chile and toward a deficit for Brazil, Colombia, Ecuador, and Mexico. When we consider RMEs of trade, however, this trend is reversed in some cases. In the case of Chile, the material trade balance is exacerbated when RTB is used. Results show that Brazil and Colombia remain net exporters of materials. Although Ecuador persists with a deficit in the material trade balance, this deficit is alleviated when indirect flows are taken into account. The evidence for Mexico changes, because the material trade balance moves from a deficit in PTB to a surplus in RTB. The results should be carefully interpreted, however, both because of data quality and also due to the assumption of the model about imports, which is to some extent restrictive.

Additionally, the combination of indicators derived from an RME-based analysis and from standard MFA allows us to estimate indirect flows. These flows entail interesting measures of environmental load displacement, because they remain in the exporting country but are necessary for the provision of exports.

Moreover, the estimates of material consumption levels of an economy in terms of RMC and DMC suggest that RMC is more accurate in measuring domestic material needs, especially when mining and quarrying play an important role in the economy. In general, differences between DMC and RMC suggest that researchers reconsider dematerialization trends by measuring the environmental pressures beyond the geographical borders and including not only the direct flows imported or exported but also their associated indirect material requirements. In this way, one can get a more comprehensive perspective regarding whether delinking records really represents a change toward more sustainable societies or whether countries create clean and natural environments within their borders by merely displacing degrading production beyond their boundaries into other countries with richer endowments of natural resources and, in some cases, lower environmental standards. Empirical results coming from both approaches show that estimates change considerably in the case of Chile. For the rest of the countries, the difference between DMC and RMC is not excessive.

Finally, it is worth mentioning the asymmetries that occur as a consequence of international trade between monetary and physical analysis. Some of the countries under analysis exhibit a net importer position in monetary terms but a net exporter situation in physical ones. There is no doubt that the price relation between exported and imported commodities plays an important role in these results. As we have shown, South American exports are intensive in natural resources and are in many cases largely based on nonrenewable ones. Recent economic policies in the region, however, have been widely supporting the export-led growth hypothesis as the main driver for inducing economic growth in the region. The results of this article give an indication of the biophysical implications of these types of economic growth trajectories and their long-term sustainability, calling in general for a more integrated perspective of development in the region. Therefore, improvements in physical and monetary terms of trade, such as the support for downstream processing of raw materials and the implementation of a natural depletion tax to compensate for the loss of natural capital, should be supported for those countries. Additionally, the results suggest that developed countries should use a life cycle perspective to modify their environmental policies by integrating production stages outside their own territories to minimize environmental impacts along the entire supply chain.

Acknowledgments

  1. Top of page
  2. Summary
  3. Introduction
  4. Methodology
  5. Results
  6. Concluding Remarks
  7. Acknowledgments
  8. References
  9. About the Authors

Pablo Muñoz expresses his gratitude to Rita Strohmaier for constant feedback on earlier versions of this article. We also thank Martin Bruckner and three anonymous reviewers for valuable comments and suggestions. Pablo Muñoz and Jordi Roca also thank partial financial support from the Spanish Ministerio de Educación y Ciencia (project SEJ2006-15219).

Notes
  • 1

    According to Eurostat (2001), there is a deficit in PTB when exports are superior to imports (in contrast, the traditional definition is that there is a deficit in monetary trade balances when exports are inferior to imports).

  • 2

    The term tonne refers to metric tons. One tonne = 103 kg(SI) ≈ 1.1 short tonnes.

  • 3

    The figures are restricted to these countries due to time series data availability.

  • 4

    We use the term apparent consumption to indicate that consumption refers not only to final consumption (in the sense of satisfying different categories of final demand, e.g., household consumption and investment) but also to consumption by intermediate production.

  • 5

    For a very early application of the material balance principle and IOA, see the work by Victor (1972).

  • 6

    The symbol refers to a vector that has been diagonalized.

  • 7

    One could think about the reliability of Latin American economic statistics due to inflationary tendencies for some countries in the region. This is a relevant issue because prices play an important role in the so-called Leontief quantity model when monetary input−output tables (IOTs) are used instead of physical IOTs (see Weisz and Duchin, 2006). The inflation rates of the countries under analysis were relatively low for 2003 (less than 3.5%), however, measured on the basis of the consumer price index. The only exception was Brazil, which suffered a larger inflation rate of 9%; this requires a more careful interpretation of the results.

  • 8

    For a more detailed explanation of the commodity-by-commodity (or industry-by-industry) formulation, see the work by Miller and Blair (1985).

  • 9

    This global database on material extraction was first developed in the EU project MOSUS (see http://www.mosus.net) and is currently being improved and updated in the EU project EXIOPOL (see http://www.feem-project.net/exiopol). The database uses international statistics commonly applied in other international MFA studies, such as the United Nations Food and Agricultural Organization (FAO) database for biomass extraction, International Energy Agency (IEA) data for the extraction of fossil fuels, and British Geological Survey (BGS) and U.S. Geological Survey (USGS) data for extraction of metals and minerals. Differences from other global material extraction data sets (e.g., Schandl and Eisenmenger, 2006) result mainly from different assumptions about the concentration of metal ores in crude metal extraction and assumptions to fill missing data gaps—for example, regarding the extraction of construction minerals.

  • 10

    It is important to note that the materials required for internationally traded goods and services in this study make reference to “used” material. Thus, only a part of the total indirect flows is considered. As we have pointed out before, the unused materials (in the Eurostat [2001] terminology) are not considered.

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  2. Summary
  3. Introduction
  4. Methodology
  5. Results
  6. Concluding Remarks
  7. Acknowledgments
  8. References
  9. About the Authors
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About the Authors

  1. Top of page
  2. Summary
  3. Introduction
  4. Methodology
  5. Results
  6. Concluding Remarks
  7. Acknowledgments
  8. References
  9. About the Authors

Pablo Muñoz is a PhD candidate at the Institute of Environmental Science and Technology of Autonomous University of Barcelona, Barcelona, Spain. He is currently guest researcher at the Wegener Center for Climate and Global Change of Karl-Franzens-University of Graz, Graz, Austria. Stefan Giljum is a researcher at Sustainable Europe Research Institute (SERI) in Vienna, Austria. Jordi Roca is a professor at the Department of Economic Theory of the University of Barcelona, Barcelona, Spain.