sharing in governance of extractive industries
Originally Published on the OpenOil Blog: http://wp.me/p14Gk1-1jq
This year’s introduction of mandatory disclosures in France and the UK will bring about a considerable amount of reports listing extractive companies’ payments to governments.
The mandatory disclosures promise increased transparency, however, we are only at the beginning of a debate on how to best make use of the new data. One idea has already become apparent: comparing the mandatory disclosure data to EITI figures in order to find irregularities.
In the context of our involvement in Publish What You Pays “Data Extractors” programme, we have simulated how such a comparison could look like and formulated a few first thoughts, as detailed in this document. In this, we try to assess how these different sources referring to the same project relate to each other, in fact, how comparable they are after all. In the following, we would like to highlight a few aspects one has to take into account when comparing the two datasets.
Since the most actual EITI reports date from 2014, we needed to make sure the company reports were also covering that same year. This limited our comparison to the four companies in the Oil & Gas sector, that had both published payments to the government reports and that are operating in one of the few countries for which there already is a 2014 EITI report available. In total, we had six cases. The graph above represents the comparison between the EITI data (in blue) and the figures put forward by the companies (in red) on payments to government. In all cases, we found that the two reports had diverging figures. Deviations range from 0.84% (Mnazi Bay) up to almost 200% (Tullow in Rovuma Area 2&5). This begs the question as to why both reports fail to show the same results:
This exercise has shown one methodology to analyse the data around EITI reports and the new incoming data from the EU mandatory disclosures. Although such a comparison proves to be challenging, it might help to prepare a thorough analysis that could lead to a more transparent and standardised reporting, as well as, in the best case scenario, helping to find the missing millions.
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