By Miles Litvinoff, Publish What You Pay - United Kingdom
This post originally appeared on PublishWhatYouPay.org on June 25, 2018
PWYP UK’s short practical multi-lingual guide to accessing 90 UK-based extractive companies’ payments to governments reports is available now in English, French and Spanish.
More than 90 oil, gas and mining companies incorporated in the United Kingdom or listed on the London Stock Exchange (LSE) now publish their reports on payments to governments each year under UK law every year. Forty more extractive companies report in other European Union countries, 700 in Canada and 8 in Norway. Equivalent reporting legislation awaits implementation in the United States. Similar laws have been drafted and proposed in Switzerland, Ukraine and Australia. The UK government has recently concluded a positive initial review of its payments to governments regulations.
Publish What You Pay has campaigned for years for laws requiring extractive companies to disclose their payments to governments worldwide, country by country and project by project, every year, as a complement to the EITI. Now that we have a growing body of public mandatory payment data, it would be good to increase our use of the data.
New two-page guide from PWYP UK
To help PWYP coalitions, member organisations and others in civil society access and use the 90-plus UK-based extractive companies’ payments to governments reports, PWYP UK has produced a short practical multi-lingual guide to accessing these reports. The two-page guide is available in English, French and Spanish, with links to UK-incorporated company reports here and UK-listed (London Stock Exchange) company reports here.
The guide shows how to access data on payments made to governments in 2015, 2016 and 2017 all over the world. Companies that have published their payments this way include Aggregate Industries/LafargeHolcim, Anglo American, Antofagasta, BHP Billiton, BP, China Petroleum & Chemical (Sinopec), Gazprom, Glencore, Lonmin, Lukoil, Premier Oil, Randgold, Rio Tinto, Rosneft, Royal Dutch Shell, Seplat, Soco, South32, Total, Tullow and Vedanta.
As well as explaining how to access reports via the two official UK web portals, the guide also briefly explains NRGI’s www.resourceprojects.org portal. This provides access to mandatory payment data published across the EU (including in the UK) and in Canada and Norway.
Why should civil society access the reports and use the data?
Payments to governments reporting helps deter and prevent corruption and fiscal mismanagement. Companies that are required to publish their payments are less likely to enter into corrupt or questionable deals with governments. Governments are less likely to mismanage the revenues knowing that the money received is publicly reported.
Civil society can achieve more by understanding and publicising the payments made and reported by companies in particular countries and for specific projects. Knowledge empowers. If we detect surprising or questionable payments, we can call for the government and company involved to explain. We can use the data to help citizens and local communities judge if individual oil, gas or mining projects are good value and to demand accountability for how each government spends the money. This includes judging whether a project’s public revenues and how they are spent compensate fairly for negative social and environmental impacts at national or subnational level.
Fiscal transparency is also potentially a step towards greater transparency and accountability for extractive industry impacts on livelihoods, human rights and the environment. If we can also achieve full beneficial ownership disclosure and contract transparency (better still, open contracting) – as well as disclosure of payments to governments for the first sale oil, gas and minerals (commodity trading) – we will be well on the way to opening up the extractive sector.
The UK government, the European Commission and others have asked civil society for evidence that payments to governments reports really do help improve extractive industry governance and ultimately citizens’ lives. The more we can make this happen and demonstrate it is happening, the more secure will be the political achievement of opening up extractive company payments and government revenues to public scrutiny.
Data-based advocacy partnerships
Building on its 2016 Data Extractors project, PWYP UK is interested in working with other PWYP coalitions and members around the world to analyse payments and conduct data-based advocacy focused on UK-based extractive companies’ transparency reports. To discuss possible collaboration, please contact firstname.lastname@example.org in English, French or Spanish.
In 2014, Niger announced it had successfully renegotiated uranium extraction contracts with French state-owned company Areva to secure a greater share of the wealth deriving from their uranium resources. Three years later, an analysis carried out by Oxfam based on data released by Areva calls into question the benefits for Niger in the contract renegotiation.
This analysis was carried out as part of the data extractor program developed by Publish What You Pay.
You can read more about Areva in Niger and more in the English version of “Beyond Transparency: Investigating the Investigating the New Extractive Industry Disclosures.” This report was published by Publish What You Pay France, Oxfam France, ONE, and Sherpa.
Understanding the context: why is Nigerien uranium so important for Areva?
Uranium is a strategic commodity for France. More than 75% of electricity produced in France comes from nuclear power. Most of the uranium used for nuclear combustion in France is supplied by Areva. Up to 1 in 5 lightbulbs in France would be lit up thanks to Nigerien uranium.
For years, civil society organizations have called out Areva for the uneven partnership with Niger. Despite vast resources in uranium, Niger has yet to convert this valuable resource into tangible wealth: the country still ranks second to last in the Human Development Index.
The renegotiation: a game-changer for Niger?
In 2013, Oxfam and ROTAB, a Nigerien NGO – both members of Publish What You Pay – launched a campaign denouncing the unbalanced partnership between Areva and Niger and calling for the renegotiation of the contracts. Oxfam and ROTAB specifically pointed that Areva’s contracts included a sweetheart clause enabling Areva to pay a lower rate of royalty than the applicable regime in Niger. Royalties make up the majority of uranium mining revenues to the Nigerien government.
In 2014, after months of pressure from civil society organizations around the world, Areva and Niger agreed to a new contract without the sweetheart clause. In June 2014, a Strategic Partnership Agreement signed between Areva and Niger stressed that Areva would be subject to the legal royalty regime, raising hopes of a fairer share of the revenues for Niger. This agreement was published on the Journal Officiel- the official gazette of the Republic of Niger where major legal official information are published.
In August 2016, Areva released for the first time the payments the company makes to governments where it mines uranium, as part of new EU regulations. In Niger, it was the first time the public had access to Areva’s payments since the renegotiation took place in Niger. And the results are surprising:
This tutorial is the first in a series that will help you learn how to analyse data about the extractives industry using Python.
We start off with a few FAQs before diving into the tutorial.
What are Python, R, Jupyter Notebooks, and Pandas?
Python and R are the most widely used programming languages for data science.
Python and R are just the languages, but you need a program on your computer where you can write, test, and run programs using those languages. For that purpose, you need a Development Environment, which is a program that lets you write, test and run code. For Python, the most popular Development Environment is called Jupyter Notebooks (which run right on a web browser), and for R, the most popular Development Environment is called RStudio.
On top of these languages, there are libraries which allows you to do specialised things. In Python, for example, the Pandas library is the most widely used library for data analysis.
Why are they useful?
How are they better than Excel, Tableau, etc?
What is the difference between R and Python?
Python is a general purpose programming language, which means that in addition to doing data science, you can write anything in Python ranging from web apps to online games. People with a background in programming usually find Python to be easier to learn than R.
R is a programming language that is especially made for data science. As a result you can’t write all kinds of things like games and apps with it, but it is awesome if you want to work on data. People coming from a data analysis or statistics background usually find R to be easier to learn than Python.
In terms of working with data, such as wrangling, analysing, and visualising, both Python and R works great for pretty much anything you can think of. The two languages are very different in terms of style and syntax, but their functionality is very similar.
What do I need to get started?
For this tutorial, we will just stick to Python, and we will just run it using an online version of Jupyter Notebooks that does not require installing anything on your computer. You can get started by going here: https://try.jupyter.org/
To learn more, head over to GitHub for the full tutorial.
A change in government often brings significant shifts in policy. Major initiatives taken up by a previous administration can be slowed or reversed, and information that was once publicly available may be taken down or censored. The White House webpage provides some clear examples of this phenomenon. Following the inauguration this past January, press reported that the Trump Administration White House homepage underwent some changes, such as striking references to climate change and removing a spanish language option. Fortunately, if a user wants to view the content from the White House homepage of President Barack Obama, it is still possible to do so by navigating to https://obamawhitehouse.archives.gov.
Citizens can also use the Internet Archive “Wayback Machine” to access www.WhiteHouse.gov and see content for any given day going back several years. These archive solutions are helpful for viewing web content, but hosted files on these pages still have the potential to get lost. Documents that are hosted on pages can become inaccessible as other content is changed.
Since 2010 the Publish What You Pay coalition, academics, industry, investors and other actors submitted hundreds of comment letters to the Securities and Exchange Commission (SEC) to influence the agency’s Section 1504 rulemaking. Every single comment that has been submitted to the SEC is available on the regulatory agency’s website. The comments are available as pdf files on four separate comment records: 2010, 2010-2012, 2013-2015, and 2015-2016. Because of the current wave of government self-censorship, we wanted to make sure we could preserve the evidence in the Section 1504 record. This post will provide the steps to download all linked documents, such as pdf files, from a website. The SEC comment record will be used as an example, but the same steps can be used to download and preserve files hosted on any site.
As with other data scraping and organizing processes, the steps described in this post could be carried out manually. For example, scraping data from a company pdf report can be done manually, with a user entering in data line by line into a spreadsheet, but that is a time-consuming process. As we described previously on Extract-A-Fact, there are tools to help speed up data scraping. To automate the downloading of all linked files on a website, we will use the Google Chrome extension, Chrono Download Manager - see the tutorial below.
Step 1 - Install the Chrome extension
Navigate to the Chrome web store page for the Chrono Download Manager and click the ‘Add to Chrome’ button in the upper right. A notice will pop up and you can safely click ‘Add extension’ to confirm installation. When the installation completes you should find a new icon in the upper right corner of your Chrome browser.
Step 2 - Download linked files
Before proceeding, we recommend you set a dedicated folder for downloads. Navigate to chrome://settings in your Chrome browser and set a specific downloads folder. See the image below for an example.
Next, navigate to the page with the files you intend to download. In this case we will use the most recent 1504 comment record. Once on the page, click the Chrono Download Manager icon in the upper right. Select the ‘Document’ tab in the window that pops up.
The ‘Document’ window presents a list of all the links on the page that are interpreted as documents. In this case, we are only concerned with downloading the pdf files. To narrow the selection, click the ‘pdf’ check box as shown below.
Once you’ve selected all the relevant documents you can click ‘Start all’ in the lower right of the window to download the files into the folder you selected in the Chrome browser settings.
*Optional Step 3 - Categorize the downloaded files
If you follow the steps above you will be able to successfully download all of the files from a webpage, which will simply be listed by their filename (e.g. s72515-1.pdf). To help organize the files, you can have Chrono Download Manager automatically attach the descriptive text corresponding to each file. Click the first document highlighted in green (see image above), scroll down to the last pdf and press shift+left mouse button on the last highlighted pdf. With all of the pdf files checkmarked and selected, click the ‘Task Properties’ tab as shown below.
Click the text box next to ‘Naming Mask’ and select ‘*text*.*ext*’ then click ‘Start All’ to download all of the files. You’ll find that the downloaded files will now appear in the folder with a descriptive title (e.g. Jana L. Morgan, Director, Publish What You Pay – United States) rather than the numbered file name.
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