Revenue from natural resources can serve as a crucial tool for low- and middle-income countries to improve their development outcomes. However, these revenues are susceptible to mismanagement. A country’s newfound wealth is often squandered.
A key challenge for those seeking to ensure that resource revenues benefit citizens has been tracking resource flows. In the 2017 Resource Governance Index, NRGI assessed the management of resource sectors around the world. We set out to collect total oil, gas and mining revenue data for the countries included in the index to find out how many dollars flow to governments that botch the handling of their natural resources wealth.
This was challenging. Information on resource revenue in the public domain is incomplete and non-standardized. In many cases, this data was inconsistently measured across countries. Nevertheless, we were able to gather sufficient data to find that over USD 1.2 trillion in revenue is raised in countries with unsatisfactory (i.e., weak, poor or failing) scores in the index.
In order to calculate total resource revenue data for 78 countries included in the RGI (we excluded three countries with devolved governance of extractive industries), we collected figures from the following sources:
EITI data. The Extractive Industries Transparency Initiative’s (EITI) 50 member countries publish documents about resource revenues. These documents reconcile the amount of revenues that governments report receiving and the amount of payments that companies report making. This data is compiled and available on ResourceData.org.
IMF dataset. The World Commodity Exporters Database published by the International Monetary Fund (IMF) includes key macro-fiscal indicators from IMF primary sources. The dataset covers 51 countries whose exports of oil, gas and metals contribute 20 percent or more of total exports.
ICTD database. The International Centre for Tax and Development (ICTD) publishes a global tax dataset combining multiple sources on a range of policy relevant indicators and, where possible, figures inclusive and exclusive of natural resource revenues. The most recently available version of the government revenue dataset was released in partnership with UNU-WIDER.
National data. Where data were unavailable from global datasets, we used data published by the governments themselves.
Looking at 2014 revenue numbers (we chose 2014 as the sample due to the highest availability of data across sources), these centralized datasets have data for 78 countries, 62 of which were included in the 2017 RGI (data collection was completed in 2016). We obtained resource revenue data for a further four countries from government-published data, bringing the total coverage of the RGI sample to 66 countries, or 85 percent.
That left 12 RGI countries for which 2014 data is not available. We can group these remaining countries into the following categories:
Delayed reporting. For example, the latest EITI report for Myanmar covers 2013.
Lack of a total figure. Government reporting is disaggregated into resource and non-resource revenues at some level (e.g., only export custom duties are disaggregated for petroleum in India), but no total figure is published or can be calculated.
No data. For a number of countries—such as Argentina, Cuba, Morocco, Turkmenistan and Uzbekistan—we found no data. In the latter two of these countries, resource exports make up over 50 percent of total exports. Knowing what revenues they generate would be of high relevance. A number of extractive companies disclose granular information on the payments made in many of these countries due to payment disclosure legislation in Europe and Canada, However, this does not provide a figure for what the government received across the whole sector.
A lack of coverage was just one challenge. There was also discrepancy among data sources, which was caused by inconsistent and non-standardized data definitions and collection methodologies. Of the 38 countries included in more than one dataset, the difference between the highest and lowest data point is over 20 percent in 23.
For example, estimates of resource revenues for Zambia in 2014 reported by EITI are USD 1 billion, which is more than twice as high as the figure reported by the IMF and ICTD. Digging deeper, we found that most of this discrepancy can be attributed to the EITI’s inclusion of personal income tax, import taxes and VAT in resource revenues—all of which were omitted from IMF data.
In Nigeria, EITI estimates of 2014 oil revenue are 30 percent higher than the IMF’s. The IMF excludes national oil company proceeds from the sale of its equity stakes in oil projects. Instead, it captures only the dividends the national oil company elected to remit to the treasury. ICTD data is the lowest for Nigeria, at USD 37 billion, which lags the EITI total by a whopping USD 17 billion. (The ICTD dataset presents both central government and general government revenue data for Nigeria; NRGI used the higher general government figure.)
A detailed look at the data and discussions with some of the experts who compiled and had them revealed further differences in definitions and classifications.
Because EITI allows member countries to determine certain aspects of their reporting approach (such as the materiality threshold for the revenues it includes), EITI reports can vary in coverage from country to country, both in terms of revenue types and commodities covered. Also, the final EITI figure is based on a reconciliation process between government-reported extractive industry revenue and a company’s reported payment figures.
The IMF dataset focuses on on-budget payments, which may exclude revenues received by state-owned resource companies (in some countries these can be the largest revenue source for the country), resource funds and subnational governments. Other discrepancies may relate to cash and accrual accounting; differences in calendar and fiscal years; exchange rate conversions; and valuation of in-kind payments.
Despite these gaps, our data collection reveals that the level of coverage is steadily improving. Each initiative has been at least somewhat successful in assembling resource revenue information. But, between governments and sources of government statistics, more could be done to collect data in a comparable and standardized manner. The EITI International Secretariat now encourages countries to use Government Finance Statistics classification, but it doesn’t provide totals based on the standardized categories. The publication of revenue data by IMF is laudable, but it is unclear whether this is a one-off effort or will be continued.
Providing reliable, timely data on natural resource revenues is a first step in bringing more accountability to the sector. Our analysis found that in a handful of countries—including some of the most poorly governed—this basic information is still not available. It is crucial that the national governments of all countries with resource wealth disclose this information and participate in international data collection and standardization efforts.
Despite imperfections in the availability and comparability of resource revenue data, we were able to determine a sum total for 66 RGI countries: we estimate that resource revenue across the sample totaled USD 1.4 trillion in 2014. When we found multiple sources of revenue data for a single country, we used the average of the figures. Picking the lowest or highest of the multiple figures results in estimates of USD 1.3 and USD 1.5 trillion, respectively. This USD 233 billion range in total estimates exposes the challenges in attempting to combine resource revenue data.
The table below shows the results from resource revenue data collection based on the RGI banding system, which ranges from the highest rating of “good” to the lowest rating of “failing.”
Total resource revenue (bn USD)
Average contribution of resource revenue (% total revenue)
Countries in this group with data available
Total countries in this group
Average deviation across sources*
*Percentage distance between highest and lowest data point.
We find that:
The availability of public government resource revenue data is, on average, worse in countries that performed poorly in the RGI. We could only locate data for 50 percent of the countries that have “failing” resource governance ratings.
Over USD 1.2 trillion in revenue is managed by governments of countries that that have an unsatisfactory (i.e., weak, poor or failing) score in the RGI.
The most resource revenue-dependent countries (restricted to the sample of countries we have data on) scored lowest on the 2017 RGI. Across countries where over 50 percent of revenues come from extractives, almost all scored either weak (45-60 out of 100) or poor (30-45 out of 100) in the RGI.
The strong negative correlation between resource governance and resource dependence provides suggestive evidence of the resource curse and the failure of these countries to diversify their revenues. Our analysis also underscores that resource revenue data that is reliable, timely and has good coverage is much too scant.
This must change. The accountability of trillions of dollars of government revenues is at stake.
The resource revenue data collected for this blog is available at Resourcedata.org
Anna Fleming was a research assistant with the Natural Resource Governance Institute (NRGI). David Mihalyi is an economic analyst with NRGI.