Under the Surface - Looking into payments by oil, gas and mining companies to governments
The purpose of this publication is: a) to demonstrate the value of transparency by using the payment data produced under the Accounting Directive to carry out analyses of extractive sector projects; and b) to showcase how this data can be used to both strengthen accountability mechanisms and to improve the prospects that resource-rich governments secure a fair share of wealth from natural resources. This report also identifies shortcomings in company reporting against the existing regulations and shortcomings in the regulations themselves.
This report assesses project-level payments to governments by oil, gas and mining companies in four different countries of operation: Repsol in Bolivia; Tullow Oil in Equatorial Guinea; Vedanta in India; and a joint venture between Statoil, BP and ENI (with ExxonMobil as an operator) in Angola.
The selected projects were analysed as independent case studies highlighting the value of revenue payment disclosures and illustrating some of the specific opportunities that now exist for external monitoring. The case studies were drafted with the objective of demonstrating the value of the data contained in the reports on payments to government required by the EU Accounting Directive and of assessing to what extent the Directive facilitates transparency and accountability.
Projects were selected to illustrate the contribution of the Directive in terms of expanding transparency in some of the most opaque jurisdictions (non-EITI countries, such as Angola and Equatorial Guinea, where payment transparency depends solely on the EU legislation), and to bring transparency to companies domiciled outside of the EU (such as ExxonMobil). Priority was given to looking at a country’s situation where extractive sector revenues held great potential to contribute to wider development outcomes. Project selection was also guided by the availability of good quality project data (including access to project fiscal terms) and good operational data (including production volumes and commodity prices).