sharing in governance of extractive industries
Is there a better way to measure resource-dependence? By Degol Hailu and Chinpihoi Kipgen
This piece is a summary of our full article published in the journal Resources Policy. See Degol Hailu and Chinpihoi Kipgen (2017) "The Extractives Dependence Index (EDI)", Resources Policy, Volume 51, Pages 251–264. https://authors.elsevier.com/a/1UROZ_6sd-UEcL
High and persistent dependence on the extraction of oil, gas and minerals for export earnings and fiscal revenues are a concern for the sustainability of growth in resource-rich countries. Not so much a reliance on unexploited abundant resources in the ground, but dependency on extracted commodities for generating incomes.
There are strong arguments for reducing resource-dependence − from declining terms of trade for commodity exports and volatility in their prices to potential weak governance and poor environmental and social safeguards associated with extraction.
Although initial reliance on the sector is inevitable to generate income, it is the eventual moving away from this dependency through diversification into other sectors (particularly towards manufacturing) that denotes successful resource-based development.
Several researchers came up with indicators to measure resource-dependency. They look at shares of resource exports in GDP or in total exports; resource revenue as a share of total government revenue and extractive value-added in GDP. These traditional measures however do not take into account the contribution of other sectors to foreign income, taxes or to domestic value addition. Dependence on resource incomes is only problematic if other sectors are relatively weaker.
This is what our Index tries to correct. We call it the Extractives Dependence Index (EDI). The EDI is a composite index consisting of six indicators. Three of them are well recognized in the literature: 1) the share of oil, gas and minerals in total export revenue; 2) the share of resources in total government revenue and; 3) oil, gas and mineral value-added in GDP.
However, we adjust each of the above three indicators to capture the productive environment under which the resource sector strives. To account for the productive capacity of an economy to generate additional foreign exchange (other than resources) we use a fourth indicator: “export revenue from high-skill and technology-intensive manufactured (HTM) exports as a share of total global HTM exports”. This indicator takes into consideration the productivity and competitiveness of a country's export basket. The same productive capabilities and human capital can be used to diversify into a range of export products, hence lessening dependence on the resource sector.
To account for an economy’s capacity to generate alternative sources of tax revenue, we use a fifth indicator: “total non-resource taxes from incomes, profits and capital gains as a share of GDP”. This is a proxy for non-resource revenue base and also reflects higher institutional capacity required for tax collection and administration.
To adjust for a country's ability to domestically process its raw materials, we use a final indicator: “per capita manufacturing value added”. Greater forward linkages from the resource sector imply higher levels of transferable skills that can increase technology transfer and employment mobility within and between sectors. In a nutshell, this indicator is a proxy for domestic industrial capability.
Using the above six indicators, we constructed an Index that ranges between 0 and 100, with 100 being the highest dependence score. The Index values are calculated for a total of 81 countries between 2000 and 2011, although not all countries have data for all years.
The comparison between Zambia and Norway illustrates the contribution of our Index. In 2011, the two countries collected a similar share of revenues from the extractive sector, which contributed to 76% and 74.5% of total export revenues and 25% and 23.5% of fiscal revenues, respectively. Without accounting for Zambia’s relatively lower domestic productive capacity, the traditional measures of resource-dependence would consider the two countries as being equally dependent on the sector. However, our EDI values for Norway and Zambia in 2011 were 34 and 45 and the countries were ranked 33rd and 41th, respectively.
Our Index also implies a possible inverted-U shaped trajectory in countries with successful strategies that decrease resource-dependence over time. The cases of Mongolia, Nigeria and Botswana demonstrate this point. Mongolia's EDI value in year 2000 was 26. With the discovery of the Oyu copper and gold deposits, extraction intensified and by 2011, the EDI score increased to 63. Hence, Mongolia is becoming more dependent on its minerals, implying the country is may be in the rising part of the inverted-U.
Despite over 60 years of resource extraction, Nigeria has not undergone the structural transformation required to decrease its dependence on the sector and has maintained an EDI score greater than 80 in both 2000 and 2011. The economy continues to be dominated by the oil sector providing over 90% of foreign exchange earnings and financing 77% of total government revenues over the past decade. The country seems to be stuck in the flatter part of the inverted-U.
In the case of Botswana, the EDI score declined from 71 to 62 between 2000 and 2011. Although diamonds, nickel, copper, gold and other resources continue to bring in an average of 85% of total export earnings, the country’s efforts to promote downstream value addition, including diamond beneficiation, agriculture and tourism, is slowly moving it towards decreasing dependence on the mineral sector. The country may have begun the downward journey on the inverted-U.
It is well established that persistent dependence on resource incomes subjects an economy to volatile growth. And knowing where the dependence originates from, through the use of measures such as the Index we introduced here, allows policy makers to design better diversification policies and strategies.
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