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Extractive IndustriesThe Management of Resources as a Driver of Sustainable Development$

Tony Addison and Alan Roe

Print publication date: 2018

Print ISBN-13: 9780198817369

Published to Oxford Scholarship Online: November 2018

DOI: 10.1093/oso/9780198817369.001.0001

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Mining’s Contribution to Low- and Middle-income Economies

Mining’s Contribution to Low- and Middle-income Economies

Chapter:
(p.51) 3 Mining’s Contribution to Low- and Middle-income Economies
Source:
Extractive Industries
Author(s):

Magnus Ericsson

Olof Löf

Publisher:
Oxford University Press
DOI:10.1093/oso/9780198817369.003.0003

Abstract and Keywords

In several low- and middle-income countries with important extractive sectors, gross national income has developed favourably. Africa has benefitted most, particularly West Africa. This chapter provides an up-to-date statistical analysis of the contribution of non-fuel minerals mining to low- and middle-income economies. Using the detailed data available for the minerals sector, an analysis is carried out of the current situation for 2014, and of trends in mining’s contribution to economic development for the years 1996–2014. The contribution of minerals and mining to gross domestic product and exports reached a maximum at the peak of the mining boom in 2011. Although the figures for mining’s contribution had declined for most countries by 2014, the levels were still considerably higher than in 1996. The results of this chapter contradict the widespread view that mineral resources create a dependency that might not be conducive to economic and social development.

Keywords:   extractive sectors, economic development, minerals, mining, gross national income, gross domestic product, exports, low-income countries, Africa

3.1 Introduction

This chapter is designed to provide an up-to-date statistical analysis of the scale of the current dependency of low- and middle-income economies on various extractive resources in dimensions such as production, income (GDP), exports, government revenues, exploration, and employment. The study also attempts to explain and document how country levels of minerals dependency have changed in the past twenty years.

Drawing on the detailed data available for the minerals sector, an analysis is carried out of the situation in 2014, and of recent trends in mining’s contribution to the economic development of low- and middle-income countries for the years 1996–2014. By using data on variables such as production, prices, mineral rents, exploration expenditure, government revenues, and employment, this chapter offers answers to questions such as:1

  • What is the magnitude of the statistical dependency on mining industries in low- and middle-income developing countries today?

  • Has that level of statistical dependency changed over the past twenty years, from 1996 to 2015?

  • Has the level of dependency changed as a result of the sharp drop in prices of most extracted commodities since about 2011, after the end of the so-called super-cycle?

(p.52) The methodology is based on earlier work coordinated by the ICMM, in which the authors participated in 2010 and 2014 (ICMM 2010, 2014).

3.2 Methodology

3.2.1 Mining Contribution Index WIDER

One existing approach to assessing the magnitude of the dependency of countries on extractive resources is the MCI developed by the ICMM (2010, 2014, 2016).

In this chapter MCI is updated and also further developed. Our revised version is called the Mining Contribution Index WIDER (MCI-W), and is based on four indicators:

  1. 1. exports of minerals including coal as a share of total merchandise exports

  2. 2. the total production value at mine stage of metallic minerals, industrial minerals, and coal, expressed as a percentage of GDP

  3. 3. mineral rents as a percentage of GDP

  4. 4. exploration expenditure.

MCI and MCI-W are similar, but use two different ways of combining some measurable indicators. MCI-W uses GDP purchasing power parity (PPP, real US$ with 2011 as the base year) from the World Bank.

3.2.2 Indicators

The rationale for including each of our four indicators is as follows.

3.2.2.1 Exports

International trade in metals reflects regional and national advantages and specializations along the value chain (Tercero Espinoza and Soulier 2016). Mineral and metal export contribution in 2014 provides a measure for the scale of mining in relation to other productive activities, in particular for small low- to middle-income countries. UNCTAD validates and compiles a wide range of data collected from national and international sources to provide reliable statistics to facilitate analyses of the most urgent and emerging issues. UNCTAD covers international trade and exports of metals and minerals. The specific trade groups used are: non-ferrous metals (Standard International Trade Classification (SITC) 68); other ores and metals (SITC 27 and 28); pearls, precious stones, and non-monetary gold (SITC 667 and 971); coal, whether or not pulverized, not agglomerated (SITC 321); (p.53) coke and semi-cokes of coal, lignite, or peat, and retort carbon (SITC 325) (UN Comtrade).

3.2.2.2 Value of mine production

This is non-fuel mineral production value expressed as a percentage of GDP (1996–2014). It provides a sense of the scale of value of production relative to the size of the economy. Note that it does not represent the contribution of mining to GDP—on average perhaps only a third of production value represents value addition to the national economy.

The value of mine production is based on figures obtained from Raw Materials Group data until 2013. Figures for 2014 were collected and computed by the authors using the same methodology (Raw Materials Group 1997: 497). A list of minerals and metals included is given in Figure 3.1. Uranium, aggregates, and limestone are not included.

Mining’s Contribution to Low- and Middle-income Economies

Figure 3.1. Value of mine production by commodity (%), 2014

Note: Others include: salt, lead, chromite, manganese ore, molybdenum, bauxite, tin, palladium, graphite, rare earth elements, kaolin, boron, fluorspar and feldspar.

Source: authors’ illustration based on data from British Geological Survey, US Geological Survey, World Mineral Statistics, and Raw Materials Data.

3.2.2.3 Mineral rents

Mineral rents are the difference between the value of production for a stock of minerals at world prices and their total costs of production including ‘normal’ profit. Minerals included in the calculation are tin, gold, lead, zinc, iron, copper, nickel, silver, bauxite, and phosphate. Mineral rent statistics are derived from the World Development Indicators created by the World Bank.

(p.54) 3.2.2.4 Exploration

The exploration expenditure data produced by SNL Mining & Metals (2016)2 provides a forward-looking indication of the likelihood of continued mining activity in a country.

3.2.3 Calculation

MCI-W is calculated as follows: countries are ranked in descending order for each of the four MCI indicators. Countries for which data do not exist are omitted from the ranking. As a result, indicator 1 is ranked out of 216 countries, indicator 2 is ranked out of 127 countries, indicator 3 is ranked out of 125, and indicator 4 is ranked out of 122 countries. For each country percentile ranks are calculated based on the four indicators, by dividing the country rank by the maximum rank within that indicator to generate a ranking between 0 and 1. Finally, the four MCI indicators are weighted equally at 1/4, summed up, and multiplied by 100 (ICMM 2014).

In this chapter the focus is on the low- and middle-income economies for the years 1996–2014.3

3.3 Current Levels of Mining Contribution to National Economies

Our MCI-W results confirm that mining is indeed the backbone of several nations’ economies. In some nations, mining accounts for a dominant share of the national wealth, with more than 50 per cent of exports and around 10–20 per cent of GDP: many of these countries are low- and middle-income economies. The distinction between different regions is shown graphically in Figure 3.2, the black areas showing the highest levels of dependency. Regions where mining makes a particularly high contribution are Western, Southern, and Central Africa, Oceania, Central Asia, and Latin America. Almost all countries have some, often small-scale, mining activity producing, for example, coal and aggregates for domestic use. These mineral products are most often not (p.55) exported, as their low value does not allow transport over longer distances, and hence the combined contribution by production and exports is small. There are some regions or countries where mining contributes less to national wealth: Western Europe, the Middle East and North Africa, Japan, and South-East Asia (lighter areas in Figure 3.2).

Mining’s Contribution to Low- and Middle-income Economies

Figure 3.2. MCI-W score by country, 2014

Source: authors’ calculations.

3.3.1 Country Rankings

In MCI-W based on the latest available data for 2014, the DRC is ranked as the country with the largest contribution of mining to its economy (Table 3.1). Mineral exports constitute 81 per cent of total exports there, and DRC is ranked the fourth most important country in relation to mineral export contribution. Mineral production value at the mine stage was US$8 billion in 2014, and the mineral production value as a percentage of GDP was 15 per cent: on this indicator, DRC is ranked number three. Exploration expenditure was US$300 million in 2014, placing DRC in tenth place globally. Mineral rents constituted 20 per cent of total GDP, and DRC is ranked number two in 2014. These four variables give the composite score of 97.6 out of 100 in (p.56) the index for DRC. The top ten countries in the 2014 MCI-W ranking in descending order are DRC, Chile, Australia, Mongolia, Papua New Guinea, Zambia, Peru, Burkina Faso, Mali, and Guyana.

Table 3.1. MCI-W top 20, 2014

Country

Ranking

MCI-W score

DRC

1

97.6

Chile

2

95.2

Australia

3

95.0

Mongolia

4

93.9

Papua New Guinea

5

93.4

Zambia

6

92.6

Peru

7

91.4

Burkina Faso

8

90.5

Mali

9

89.9

Guyana

10

89.9

South Africa

11

89.2

Botswana

12

89.0

Guinea

13

88.6

Mauritania

14

88.5

Eritrea

15

86.4

Namibia

16

86.2

Ghana

17

84.5

Lao PDR

18

83.5

Sierra Leone

19

82.5

Uzbekistan

20

81.2

Source: authors’ calculations.

Of the top fifty countries in MCI-W 2014, there are only four high-income economies (HIE), but sixteen upper-middle-income economies (UMIE), eighteen lower-middle-income economies (LMIE), and twelve low-income economies (LIE).

While there are two high-income countries, Chile and Australia, among the five countries with the highest MCI-W scores, there are only two additional high-income countries among the top fifty (Canada and the Russian Federation). It should also be noted that all five of the BRICS countries (Brazil, the Russian Federation, India, China, and South Africa) are among the MCI-W top forty-five.

In Figure 3.3 we present a four-dimensional chart with the export contribution shown on the x-axis and mineral value as percentage of GDP on the y-axis. The size of the circles is proportional to the value of mine production in absolute terms (US dollars). The fourth dimension is time, the data being presented only for 2014 in Figure 3.3. The figure shows the top twenty MCI-W countries. Australia has by far the largest mining industry by value of production, and the high value is represented by the size of the circle. The export contribution ranking is topped by Mongolia, DRC, and Botswana at levels of 80–90 per cent of total exports, followed by Zambia, Mauritania, and Mali (p.57) with export contribution levels at around 60–70 per cent. The graphic confirms that the countries with the highest levels of export contribution are mainly LIE or LMIE. Eritrea, with only one mine of industrial scale in operation in 2014, is represented by the small circle at production 9 per cent and export 48 per cent.

Mining’s Contribution to Low- and Middle-income Economies

Figure 3.3. MCI-W top 20, 2014

Source: authors’ calculations.

3.3.2 Value of Mine Production

While there are thirty LIE and LMIE among the top fifty MCI-W countries, the HIE and UMIE are substantially more important in terms of production value—for example, China, Australia, the United States, Canada, Chile, the Russian Federation, South Africa, and Brazil (Figure 3.4). It should be noted that the main engine of metal demand, China, is also by far the most important mining country when coal is included in the production total. If coal is not considered, but only metals and industrial minerals, Australia and China are roughly the same size. The absolute levels of production are relatively small for several of the states in the MCI-W top fifty—such as Guyana, Eritrea, and Guinea—but for the economy in the broader sense, mining is an important contributor to all the MCI-W top fifty states.

Mining’s Contribution to Low- and Middle-income Economies

Figure 3.4. Value of mine production by country, 2014

Notes: Circles are proportional to value of mine production. Coal accounts for 3/4 of Indian production value. Iron ore accounts for >3/4 of Brazilian production value. Gold accounts for approximately 1/3 of Peruvian production value.

Source: Raw Materials Data.

Figure 3.4 clearly shows that the total value of mineral production at the mine stage is dominated by coal. Coal constitutes roughly half of the total value of industry production globally. Iron ore (Fe), copper (Cu), and gold (Au) follow next. The industrially important metals nickel (Ni) and zinc (Zn) are each roughly an order of magnitude smaller. These metals are of the same (p.58) (p.59) value in total global production as the fertilizer minerals—i.e. phosphate and potash—at two to three per cent of the total value of production. Thereafter there are a number of metals and industrial minerals that each contribute less than one per cent of total global value. (See Figure 3.1 for a complete list of the minerals included in total mine production value.) China is by far the most important country in terms of total production value, followed by Australia and the United States. The top ten countries in terms of the value of their mine production contribute almost 80 per cent of the total value of non-fuel mineral production at the mine stage globally.

For each of the MCI-W top twenty LIE and middle-income economies (MIE), Figure 3.5 shows how metals and minerals contributed to the total value of their mine production in 2014. Gold mining is the major mineral contributor in no fewer than nine countries in this top twenty. In Mali, gold is the only mineral mined and hence contributes 100 per cent of the total value; in Burkina Faso, Guyana, Ghana, Uzbekistan, Suriname, and Tanzania, gold mining contributes between 75 and 94 per cent. Copper is the most important commodity in Zambia, DRC, and Lao PDR. In Namibia and Botswana, diamonds are the main contributor.

Mining’s Contribution to Low- and Middle-income Economies

Figure 3.5. Contribution by commodity to MCI-W top 20 LIE and MIE

Source: authors’ illustration based on Raw Materials Data.

(p.60) In 2014, the total global value of mine production at the mine stage including coal was around US$1,200 billion. Coal contributed US$650 billion, and iron ore is estimated at US$145 billion. The change over time in the total global value of mineral production follows the general metal/mineral prices, as seen in Figure 3.6. However, for some individual countries, the changes in the level of production have also been very important.4 For example, copper production in DRC has increased tenfold over the last ten years and is now twice as large as during the previous peak in the 1980s.

Mining’s Contribution to Low- and Middle-income Economies

Figure 3.6. Mining development trends, 1995–2015: prices, exports, exploration, value of mine production, mineral rents

Sources: authors’ compilation based on data from Raw Materials Group, World Bank, SNL Metals & Mining, and UNCTAD.

3.3.2.1 Change of mining contribution over time, 1996–2014

Metal and mineral prices reached a peak in 2011, but have since been in a five-year downturn that was showing some signs of correcting in 2016–17. It should be noted, however, that most metal prices in nominal terms are still higher than they were in the early 2000s. Our price index is made up by a variety of metals/minerals (coal, copper, gold, iron ore, nickel, and zinc). The weighting on the price index was calculated as an average based on the total (p.61) value of products of the mining industry. The weighting was used to combine the price development of different products into one index.

As Figure 3.6 shows, the price index has been on a downward trend since 2011, with a flattening-out beginning in early 2016. It is certain that the global production value will also have dropped for 2015, but we see several important indicators making us believe that the bottom in terms of production value was reached in late 2016 or early 2017. As can also be seen from Figure 3.6, mineral prices are an important but not the sole determinant of the changing levels of exports, value of mine production, mineral rents, and exploration expenditures.

3.3.3 Export Contribution

Non-fuel minerals and metals are the major contributor to many nations’ exports. Among the top fifty countries with the highest mineral exports relative to total exports in 2014, there were seventeen nations with a total mineral export of more than 50 per cent of the total. Among the top fifty ranked by export contribution, no fewer than 34 per cent are LIE and 28 per cent are LMIE. Only eight countries or 16 per cent are HIE. The export contribution to the MCI-W score in LIE and MIE is the most important factor explaining their high ranks. Sierra Leone is number one with a mineral export contribution of no less than 94 per cent of total exports. Botswana, DRC, Mongolia, and Zambia are all countries where mineral exports contribute more than 70 per cent.

3.3.4 Exploration

Exploration activity and spending is mainly driven by expectations of future, mostly short-term mineral demand and prices. In reality, exploration expenditure in a given year is closely related to metal prices in the preceding year (Canadian Intergovernmental Working Group on the Mineral Industry 2001: 20–1). This means that future metal demand, which should logically determine levels of exploration, is not a prime driver. This is a failure of the market for this specific service. Some attempts to stimulate exploration have been made in certain countries, with varying success. Examples are financial support to risk-willing investors in Canada and Australia (flow-through shares), and government-funded exploration work in China, India, and Finland.

3.3.5 Mineral Rents

It is important to note that diamonds are not included in the list of minerals for which the World Bank calculates mineral rent. Thus, countries such as Botswana and Namibia, where diamonds are the main mineral contributor to (p.62) the economy, will get a lower MCI-W score than if diamond rents were also included. Mineral rent is a theoretical approach to calculate some concept of the surplus from the mineral sector.

3.3.6 Other Factors

3.3.6.1 Government revenues from mining

The capturing by government of some part of total resource revenues as government revenues (mainly taxes and royalties) is crucial to generate development for many reasons, not least that mineral resources are considered non-renewable.

3.3.6.2 Employment

The direct contribution of mining to the total formal employment of a country is seldom more than 1–4 per cent in countries with large mining sectors. The number of direct jobs created is normally relatively small, as mining is capital-intensive; but mining also generates indirect jobs, which are more difficult to measure. Furthermore, mines are often located in remote areas with limited other opportunities. However, the jobs created by large mining companies are normally well paid compared with other similar jobs in the same country. This means that the mining contribution to the total wage bill of a country is often proportionately larger than its contribution to job numbers.

To sum up, direct employment in the mining sector most often varies between 1 and 3 per cent, but there are examples of much higher levels. This is invariably the case, in particular, if informal/artisanal-sector employment is also included. Employment is an important stabilizing factor in the contribution of mining in many mineral-rich countries. Employment has also been generally rising in the past ten years, and has not declined as much recently as the value of mine production, exports, and other factors directly related to commodity prices. Employment is also somewhat less volatile than the other factors under study, and there was for example only a marginal dip during the global financial crisis in 2008–9.

3.4 Changes in MCI-W since 1996

The 1996 value of mineral production at the mine stage was US$300 billion (in nominal terms), equivalent to 0.6 per cent of total world GDP PPP (World Bank 2016). In 2011 mine value peaked at US$1,800 billion (1.9 per cent of global GDP); it has since fallen back to US$1,200 billion and 1.2 per cent of world total GDP. The super-cycle—the long boom in metal and mineral markets and prices beginning in 2003—made mining a more important part (p.63) of GDP in almost all mining countries. The share of mining in global GDP doubled in four years, and peaked at three times higher in 2011 than in 1996. These dramatic changes in the preconditions for mining’s contribution to national economies also had strong effects on MCI-W. In 1996 Chile was number one in the MCI-W ranking while DRC, which is number one in 2014, was ranked only at number 24.

Among the twenty LIE and MIE which had the highest MCI-W ranking in 1996, no fewer than thirteen economies have climbed up one step in the World Bank’s income group classification by 2014. In 1996 the MCI-W top fifty included six HIE, five UMIE, twenty-one LMIE, and eighteen LIE. By contrast, in 2014 the numbers are: four HIE, sixteen UMIE, eighteen LMIE, and twelve LIE. Zambia, Ghana, Guyana, Mauretania, Mongolia, and Tajikistan were classified as LIE in 1996 but LMIE in 2014. Countries classified as LMIE in 1996 but UMIE in 2014 are: Peru, Kazakhstan, Suriname, Botswana, Namibia, Fiji, Cuba, and Venezuela. Chile and the Russian Federation became HIE between 1996 and 2014.5 There are of course many factors influencing these gradual economic developments, but it seems likely that the contribution of mining and minerals is one important factor.

When comparing the mining contribution to national economies between 1996 and 2014 at the global level, we see a broadly similar picture. There are, however, regions and specific countries that have climbed up the rankings very significantly. West Africa, for example, is a region that has now moved to the top of the MCI-W rankings.

Individual countries which have climbed most in the MCI-W rankings are in following order: Lao PDR, Eritrea, Côte d’Ivoire, Burkina Faso, Sudan, Mozambique, Serbia, Togo, Mali, and DRC. Lao PDR and Eritrea did not have any industrial-scale mining in 1996, so when mining started they went from almost zero to a point today where mining is contributing considerably to their economies. African mining countries in particular have gained an increase in MCI-W score. Among the sixteen countries whose MCI-W score increased more than 25 per cent between 1996 and 2014, no fewer than thirteen are in Africa.

In summary, mining quite clearly increased its contribution to economic activity in the low- and middle-income countries between 1996 and 2014. The increase in contribution is higher in LIE than in MIE. Mining’s share of GDP tripled during these years for these two categories of country. The share was 3.1 per cent in 2014, compared with 1.1 per cent in 1996. Mineral exports’ share of total exports in those countries increased by 50 per cent in the same period. Mineral rents followed the general price developments and reached a (p.64) peak in 2011, but have declined since, although they were still higher in 2014 than they were in the 1990s. Exploration spending in the countries studied increased over the period as a whole, but has been declining steeply since 2013. Several LIE and MIE with high MCI-W scores in 1996 have developed successfully and risen in the World Bank GNI classification from LIE to MIE and from LMIE to UMIE. The MCI-W index for individual countries has moved up and down depending on the performance of their mining sector relative to other sectors of the economy. It is difficult to draw any general conclusions from this relative index. There is a need to further develop the contribution index with this in mind.

3.5 The Impact of the End of the Super-cycle

Over the first decade of the new millennium, the global mining industry moved from a long period of low prices, unacceptable levels of return, and limited investments to a boom with record high metal prices, improved profitability, and a flurry of new projects. The main driving force behind this change back in 2003–4 was strong demand for metals and minerals, especially from China. This spurred high levels of investment into the extractive industry in order to increase supply to meet growing demand. Since 2011–12 metal prices have dropped, but, excluding nickel, not to pre-boom price levels.

Among the most important metals, gold stands out in that its price has not fallen as precipitously as those of the other minerals, and indeed has already started to move upwards again.

As shown in Figure 3.5, gold is the single most important metal for the LIE and MIE with the highest MCI-W rankings. Forty-five per cent of their total mine value is from gold mining, and it is the main contributor in nine of these twenty individual countries. In seventeen countries in the MCI-W top fifty ranking, gold mining contributed more than 50 per cent of the total value of all mineral production. In Côte d’Ivoire, Mali, Nicaragua, and Sudan, gold contributed 100 per cent of total value. Among all the LIE and MIE together, there are a total of thirty-one nations where gold mining is the main contributor. When small-scale/artisanal gold mining is also considered (such production is not always fully accounted for in the national statistics used), the importance of gold production and the significance of the relative stability of the gold price are even greater. This is also valid for a number of LIE such as Sudan, Burundi, and Cameroon, where small-scale/artisanal gold production is considerable.

One conclusion is that LIE and MIE dependent on gold mining have not been affected as severely by the end of the super-cycle as countries producing certain other metals, such as nickel and iron ore. An example is visualized in (p.65) Figure 3.7. The figure shows a circle for each year between 2000 and 2014 for Burkina Faso’s position on the x-axis (mineral export as a percentage of total exports) and y-axis (production value as a percentage of GDP). The line joins these together in chronological order. Other circles in Figure 3.7 represent other countries and their position in 2014. The size of the circles represents the magnitude of mining. In 2000 Burkina Faso had limited mining, the production value as a percentage of GDP was close to zero, and exports were just a few per cent. By 2014 production value as a percentage of GDP was around 6 per cent, and exports as a percentage of total exports were 50 per cent. Gold output in Burkina Faso was fairly constant between 2011 and 2014 at around 30–35 tonnes, while the gold price decreased 24 per cent between 2012 and 2014. However, the levels of mine value as a percentage of GDP and mineral exports were roughly the same in 2012 as in 2014. The example confirms that the impact of the end of the super-cycle has been smaller for Burkina Faso and other LIE and MIE where gold mining is important.

Mining’s Contribution to Low- and Middle-income Economies

Figure 3.7. Burkina Faso, development in export and production values, 2000–14

Note: Circles are proportional to value of mine production.

Source: authors’ calculations.

To sum up, the end of the super-cycle has hit countries in different ways, depending on the composition of their mineral production and many other factors. Gold mining countries are experiencing slower but still continuing growth. The level of export dependency and mining’s share of GDP reached a maximum at the peak of the mining boom in 2011, when the GDP contribution reached as high as 25 per cent for some countries and export dependency went over 85 per cent. Naturally these figures had declined for some countries (p.66) by 2014, but the situation for most countries was still a significantly larger contribution of/dependency on mining than in 1996. For some countries, production value as a percentage of GDP and mineral exports was even higher in 2014 after the price peak in 2011, because of a strong growth in production: this is the case for DRC, Sierra Leone, and Eritrea. Countries with a higher share of mineral exports in 2014 compared with 2011 are Burkina Faso, Mali, Guyana, Ghana, Namibia, Mauritania, Guinea, and Botswana.

3.6 Future Implications of Extractives Dependency

Metal and mineral prices are at present low relative to the peaks of 2011, but still well above the low levels of the early 2000s. Exploration expenditure is also low, and investments into new mines are also at a relatively low level. At the same time, it is clear that demand for metals and minerals in general has not dropped as much as prices have. There are clear indications that the price trough is generated more by an oversupply situation than by a fall in demand (see e.g. Worstall 2015). With the gradual improvement in standards of living, increased life expectancy, and continuing urbanization, which constitute the three major long-term drivers of metal and mineral use, it seems as if there will be a continuing, slow, and gradual increase in metal demand (McKinsey Global Institute 2013). Increased recycling and alternative energy sources might change this situation in the long-term future, but will not affect mid-term scenarios. One of the major reasons for the 2003–11 super-cycle was the slow response of the mining industry to increased demand. It takes a minimum of three to five years to increase mine capacity, and this time lag is increasing all the time due to the increasing advantages of scale economies, i.e. bigger mines with larger investments and longer and more difficult permitting processes. In short there are no signs of the lag time decreasing—rather the opposite. In principle, the global mining industry faces a similar situation during the next few years as it did in the early 2000s: slowly increasing demand, but some hesitancy about investing, and hence a low elasticity in mine production in response to demand. There is today less indication of such a strong growth in demand as was seen in the early 2000s. Nevertheless, metal prices might shoot up when supply gets short. The situation might also be exacerbated by the fact that investments into exploration have dropped dramatically in the recent past, and this might be a factor slowing the opening of new mines when new capacity is needed.

In the second half of 2016 (the time of writing) there are some indications that the bottom of the present cycle has been reached. However, the question remains as to how long prices will remain at their present relatively low levels. (p.67) The possibility of a steeper upturn than expected is not completely unrealistic (see e.g. Keen 2016). Given the long lead times for a mining project to get into production, it is important for mineral-rich countries not to focus too much on present metal prices, but to maintain a long-term approach to their national mineral resources.

As noted earlier, of the twenty LIE and MIE economies with the highest MCI-W scores in 1996, no fewer than sixteen have climbed one step on the Word Bank economic development classification. At the other end of the MCI-W rankings, when we compare the World Bank classification of the bottom twenty LIE and MIE in 1996 and 2014, there are only nine countries that have moved up one step. There are certainly many reasons why countries have not developed in this period, and naturally not only because of a lack of mining activity. Nevertheless, a statistical conclusion from this chapter is that mining can and has triggered development in several countries. When the analysis is expanded to include how the Gini coefficient has developed in the mineral-rich countries, it further seems as if inequalities have decreased. In this sample of the twenty LIE and MIE with the highest MCI-W scores in 1996, the Gini coefficient has remained constant or decreased, i.e. inequalities have diminished in fourteen countries and increased in six countries. Further, in one of the countries exhibiting a higher Gini coefficient in 2014, the increase was marginal.6

3.7 Conclusions

‘Contribution’ or ‘dependency’: even the choice of words to describe the relationship between national economies and the extractive sector poses a fundamental choice between good and bad. The traditional perspective in many historically resource-rich countries—such as our own country, Sweden—has been to view mineral resources as fountains from which wealth flows and development grows. To express it poetically, ‘Through Swedish history sounds a mighty ringing of iron and copper from medieval times until today’ (Furuskog 1935: 65)—clearly an analysis of the contribution of minerals to Swedish development.

From the 1990s until just a few years ago, however, the dependency approach was the dominant norm. The resource curse paradigm was the starting point for critical analyses in a host of works on mining during the past twenty years. (p.68) During the super-cycle of high metal prices and high oil prices, this a priori negative starting point was sometimes abandoned. There was an increasingly important view based on the hypothesis that the problem might not be the minerals as such, but rather the way the economic results they created were handled. McKinsey Global Institute’s (2013) report entitled ‘Reverse the Curse’ is but one example of this recent turnaround in thinking. Another example is the discussion about mining’s potential role as a catalyst for the diversification of national economies (Bastida 2014), the World Bank report on ‘The Contribution of the Mining Sector to Socioeconomic and Human Development’ (McMahon and Moreira 2014), and the study ‘Local Industrial Shocks, Female Empowerment and Infant Health: Evidence from Africa’s Gold Mining Industry’ (Tolonen 2014).

This chapter provides backing for this reversal and reorientation by presenting a thorough statistical analysis of almost all countries in the world, including in particular all metal- and industrial mineral-producing countries. We therefore prefer the word ‘contribution’, as we cannot imagine a world without metals and minerals, and hence mineral resources need not be viewed as a curse if managed carefully.

3.7.1 Contribution of Mining Industries in Low- and Middle-income Countries

Among the fifty countries with the highest MCI-W scores, thirty-four are middle-income countries, twelve low-income countries, and only four high-income countries. Clearly mining plays a particularly important role in many low- and middle-income countries. Among the top twenty countries, DRC has the highest score, followed by Mongolia, Papua New Guinea, Zambia, Peru, and Guyana among the middle-income countries, and by Burkina Faso and Mali among the low-income countries (rankings eight and nine). The high-income countries Chile and Australia are ranked two and three respectively, demonstrating that in high-income countries too, mining can and does remain an important contributor to the national economy. Among the twenty highest-ranking countries, Africa dominates with twelve countries. The vision of minerals as an important part of African economic development is clearly well founded. There are only three countries each from Asia and Latin America, and two from Oceania, in the top twenty.

Of the world’s ten largest mineral producers, in order of production value, China ranks 45th in MCI-W, Australia ranks at number 3, the United States is not even in the top fifty, the Russian Federation ranks 30, India ranks 42, South Africa ranks 11, Indonesia ranks 31, Brazil ranks 29, Chile ranks 2, and Canada ranks 27. This confirms that a high absolute value of mine production does not automatically translate into an important contribution to GDP and exports.

(p.69) 3.7.2 Change in Contribution over the Past Twenty Years

Among the twenty low- and middle-income countries with the highest MCI-W score in 1996, no fewer than thirteen have climbed up one step on the GNI development classification to the lower-middle-, upper-middle- or high-income category. There are of course many factors contributing to this development, but it seems likely that mining and minerals are one important factor. Geographically, Africa has benefitted most, and in particular West Africa—a region of growing mineral importance—is the prime example of this. Among the sixteen countries where the MCI-W score increased by more than 25 per cent between 1996 and 2014, no fewer than thirteen are in Africa.

The value of mineral production measured as a percentage of GDP grew from 1.1 per cent in 1996 to 3.1 per cent in 2014: on average, a growth of 200 per cent. In 1996 mineral exports as a percentage of total exports of the LIE and MIE taken together were 12.1 per cent. By 2014 that figure had increased to 17.4 per cent. Furthermore, the figures for both GDP and export share of minerals and mining are considerably higher on average for LIE than for MIE. The levels of GDP and export contribution in 2014 were still at a higher level than in 1996, in spite of the drop in metal prices since the end of the super-cycle.

It has not been possible to include employment in the mineral sector as one of the contributing factors to our mining contribution index, because of a lack of data. Nevertheless, the countries for which statistics are available clearly demonstrate that employment is a stabilizing factor, as it does not vary as rapidly as the other factors studied. Further, employment levels in general increased over the period 1996–2014.

3.7.3 Impact of the End of the Super-cycle

The contribution of minerals and mining to GDP and exports reached a maximum at the peak of the mining boom in 2011. Naturally, the figures for mining’s contribution had declined for most countries by 2014, but importantly the levels were still considerably higher than in 1996.

The results of this survey do not support the widespread view that mineral resources create a difficult dependency which might not be conducive to economic and social development—rather the opposite. Certainly, the indicators on which we base our chapter only shed light on some aspects of economic and social development. But we think we have enough substance to claim that if additional low- and middle-income countries could locate additional mineral resources, their chances of economic development would be better than they are at present, when only limited mineral resources are known.

(p.70) References

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Notes:

(1) This chapter complements an earlier paper examining similar questions for both mining and oil and gas (see Roe and Dodd 2016; Roe and Round 2017).

(2) SNL Metals & Mining (2016) focuses on corporate spending. In reality, if one adds metals and minerals not included by SNL Mining & Metals, and if one counts exploration undertaken by entities not surveyed, total exploration on either a national or a global basis is definitely higher than indicated by SNL for each country. In this chapter this difference is considered to be of minor importance.

(3) Low-income economies are defined by the World Bank as those with a gross national income (GNI) per capita of US$1,025 or less in 2015; lower-middle-income economies are those with a GNI per capita between US$1,026 and US$4,035; upper-middle-income economies are those with a GNI per capita between US$4,036 and US$12,475; high-income economies are those with a GNI per capita of US$12,476 or more.

(4) See e.g. Eritrea and some other high-ranking MCI-W countries. Annual production data by country for all of the countries covered are not yet available for 2015.

(5) The Russian Federation is among the UMIE again in 2015.

(6) The Gini coefficient is not updated every year for all countries by the World Bank or UNU-WIDER World Income Inequality Database. In cases where the years 1996 and 2014 were not available, the closest year was selected.