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Ubernomics: Platform Monopolies & How to Fix Them

- September 6, 2018 in Open Economics, Open/Closed

First version: Dec 2016, updated Feb 2018. This blog is a summary of the full article at http://rufuspollock.com/ubernomics Around the world countries have struggled to work out how to deal with Uber, AirBnB and their like. Are these new apps something to be welcomed or something to be stopped? But how we treat Uber-like companies is largely dependent on how we see and understand them. There is, in fact, nothing especially digital about the underlying economics of Uber’s business model. In fact, Uber’s economics are very similar to businesses that have been with us for hundreds or even thousands of years: marketplaces / platforms. Because of the positive feedback between buyers and sellers, the initial free competition between marketplaces tends towards “one” – one dominant marketplace. And, hence, to monopoly if that one marketplace is exclusively owned and controlled. Monopoly is not inevitable though: we can have open platforms/marketplaces – just as we have free and open markets. To do this requires us to open the digital infrastructure and, where appropriate, to open the order book too. Note: we’ll use the term platform and marketplace interchangeably. Today, “platform” is the more common term in the digital world and in economics (“two-sided platforms” etc). However, here we often prefer “marketplace” because it connects this with something both familiar and ancient.

Market Day in Stockport in 1910s. Link

1. Uber-like companies are marketplace or platform companies

Stripped to their essence Uber, AirBnB and the like resemble a very old economic structure: the marketplace. Marketplaces are where buyers and sellers come together to exchange. On Uber this is riders and drivers. On AirBnB owners and renters etc. Marketplaces have existed for thousands of years, practically since civilization first began. More broadly, we have platforms. This includes companies like Facebook, Google, Microsoft and eBay. Facebook is a platform mediating between users – and advertisers. Google is a platform mediating between users and content – and advertisers. Microsoft’s Windows is an operating system platform mediating between apps and users. Strictly platforms as broader than marketplaces. For example, an operating system or social network is a platform but not, strictly, a marketplace. However, many of the same ideas apply and so the distinction does not matter much here.

2. Platforms tend to one because of positive feedback between buyers and sellers

Like a snowball down a mountain, marketplaces, once past a critical size, have the potential to grow rapidly thanks to positive feedback where buyers and sellers both value size because it offers:
  • liquidity: you will be able to trade e.g. book a taxi, rent an apartment etc
  • diversity: they have the product you want e.g. this particular fish is available, that stock has a market maker, there is a taxi in your area (not just central London)
Furthermore, buyers and sellers usually don’t want to have to participate in lots of different marketplaces (“multi-homing” is a pain). Combined with the positive feedback effects this creates a strong pressure for there to be just one marketplaces.

3. Marketplaces tend to monopoly (unless made open)

Because of snowball economics over time you converge on just one marketplaces – “marketplaces tend to one”. You don’t have ten fish markets in a town, you have one. You don’t have fifty stock exchanges, you have one. The question then is: is that marketplace “closed”: exclusively owned and controlled by one entity. If so it becomes a monopoly. Or is an “open” marketplace where anyone can participate on fair and equitable terms? Note: there can be substantial competition to become the monopolist. There may also be some competition between regional monopolies when there is enough geographic or preference diversity: if you live in Scotland you won’t go to London to buy your fish so several local fish markets can exist (with limited competition between them at the fringes).

4. These marketplaces are not “contestable”

It is not easy to build a new one and compete against the old one. Why? Because buyers are numerous and independent coordination between them is very hard. The same is true for sellers (though to a lesser extent because sellers are usually less numerous and diverse than buyers – fifty fishmongers at a market might supply thousands of fish-buyers). This makes coordinated action – such as switching to a different competing market – very hard: as a buyer I don’t want to head over to the new fish market only to discover all the fish sellers are still at the old marketplace. Similarly, no fish-seller wants to risk moving their stall to the new marketplace until they know the buyers will all be there – its a chicken and egg problem with thousands and chickens and eggs who all need to act simultaneously!

5. Thus, the monopoly marketplace owner has a lot of power

Thus, the owner of marketplace has a lot of power – once the marketplace is established. At an early stage marketplace industries will often be highly dynamic and competitive as firms fight to get critical mass and dominate the market. This can mislead policy-makers into believing the market is competitive which in turn prevents them from acting at a crucial early stage when it would be relatively easy to put in place long-term pro-competitive policies (e.g. establishing a neutral exchange, or regulated marketplace access rates).

6. That power is inevitably abused to the detriment of buyers and consumers

When an organization has a lot of power it will use it to its advantage. In the case of the marketplace, the obvious thing is for the owner to start aggressively charging the users of the marketplace for access. Depending exactly on how the marketplace works it can charge buyers, sellers or both. Often charging sellers is preferred because they are easier to identify, contract with and track (and they have a larger and better sense of the value of the marketplace per entity). Thus, it is Uber’s drivers who get charged the 20-25% fee by Uber (this fee, of course, gets passed on to consumers but they don’t directly see it). Note: a side benefit of charging sellers is that it makes the fees largely hidden to buyers which is good both for PR and politically: if buyers got upset they might start pushing politicians to regulate the marketplace. For example, most people think that Google is just wonderful because it provides them with a valuable service for “free”. They don’t see, of course, that they do pay – just indirectly through the sellers (advertisers and content providers) who have to pay Google or supply Google with free content.

7. The solution is to open the marketplace

The solution to marketplace monopolies is to make the marketplace open: accessible to all buyers and sellers on equitable and non-discriminatory terms. This involves two parts:
  • Opening the software, protocols and non-personal data that power the marketplace.
  • Universal, equitable access to the order book database with pricing set to cover the cost of maintenance. Preferably this would involve the order book being run and managed by an independent third-party with governance in place to ensure a transparent and equitable pricing and access policy.
It is worth emphasizing that competition between proprietary, closed, marketplaces is not sufficient. Openness is essential.

8. Remuneration rights can pay for open

It costs money to create the software, protocols and (non-personal) data that power a marketplace. Traditionally, entrepreneurs and investors fund the creation of these based on the hope of becoming a marketplace monopolist and making it rich. Without the monopoly why would they invest? One option would be farsighted funding by the state – as with the Internet. However, this is problematic: how can the state know exactly which entrepreneurs should be backed with what ideas? Instead, we can use remuneration rights. These provide a free-market-like but open-compatible way to fund innovators. In essence, remuneration rights combine a common subscription payment from citizens organized by the government combined with a market-based payment of those monies to innovators based on whose innovations get used. You can read more about these ideas in my book The Open Revolution. Finally, actually running the platform itself costs money even if the protocols and software are free and open to use – you still need data centers and sysadmins to keep the servers running. With the software and protocols being free, service providers can freely compete and users will have a choice of who they use – just as we choose today between different “Internet Service Providers” who operate the Internet and provide us with access to it.

9. Pro-activity is essential

Policymakers and stakeholders need to take a pro-active approach. It is far easier to shape a marketplace towards openness early in its development than it is to handle an entrenched and powerful monopolist marketplace once in place. Read on  

Joint Submission to UN Data Revolution Group

- October 16, 2014 in Featured, News, Open Data, Open Economics, Open Government Data, Open Government Partnership, Open Knowledge, open-government, OpenSpending, Policy, Science, United Nations, www foundation

The following is the joint Submission to the UN Secretary General’s Independent Expert Advisory Group on a Data Revolution from the World Wide Web Foundation, Open Knowledge, Fundar and the Open Institute, October 15, 2014. It derives from and builds on the Global Open Data Initiative’s Declaration on Open Data.

To the UN Secretary General’s Independent Expert Advisory Group on a Data Revolution

Societies cannot develop in a fair, just and sustainable manner unless citizens are able to hold governments and other powerful actors to account, and participate in the decisions fundamentally affecting their well-being. Accountability and participation, in turn, are meaningless unless citizens know what their government is doing, and can freely access government data and information, share that information with other citizens, and act on it when necessary. A true “revolution” through data will be one that enables all of us to hold our governments accountable for fulfilling their obligations, and to play an informed and active role in decisions fundamentally affecting their well-being. We believe such a revolution requires ambitious commitments to make data open; invest in the ability of all stakeholders to use data effectively; and to commit to protecting the rights to information, free expression, free association and privacy, without which data-driven accountability will wither on the vine. In addition, opening up government data creates new opportunities for SMEs and entrepreneurs, drives improved efficiency and service delivery innovation within government, and advances scientific progress. The initial costs (including any lost revenue from licenses and access charges) will be repaid many times over by the growth of knowledge and innovative data-driven businesses and services that create jobs, deliver social value and boost GDP. The Sustainable Development Goals should include measurable, time-bound steps to:

1. Make data open by default

Government data should be open by default, and this principle should ultimately be entrenched in law. Open means that data should be freely available for use, reuse and redistribution by anyone for any purpose and should be provided in a machine-readable form (specifically it should be open data as defined by the Open Definition and in line with the 10 Open Data Principles).
  • Government information management (including procurement requirements and research funding, IT management, and the design of new laws, policies and procedures) should be reformed as necessary to ensure that such systems have built-in features ensuring that open data can be released without additional effort.
  • Non-compliance, or poor data quality, should not be used as an excuse for non-publication of existing data.
  • Governments should adopt flexible intellectual property and copyright policies that encourage unrestricted public reuse and analysis of government data.

2. Put accountability at the core of the data revolution

A data revolution requires more than selective release of the datasets that are easiest or most comfortable for governments to open. It should empower citizens to hold government accountable for the performance of its core functions and obligations. However, research by the Web Foundation and Open Knowledge shows that critical accountability data such as company registers, land record, and government contracts are least likely to be freely available to the public. At a minimum, governments endorsing the SDGs should commit to the open release by 2018 of all datasets that are fundamental to citizen-state accountability. This should include:
  • data on public revenues, budgets and expenditure;
  • who owns and benefits from companies, charities and trusts;
  • who exercises what rights over key natural resources (land records, mineral licenses, forest concessions etc) and on what terms;
  • public procurement records and government contracts;
  • office holders, elected and un-elected and their declared financial interests and details of campaign contributions;
  • public services, especially health and education: who is in charge, responsible, how they are funded, and data that can be used to assess their performance;
  • constitution, laws, and records of debates by elected representatives;
  • crime data, especially those related to human rights violations such as forced disappearance and human trafficking;
  • census data;
  • the national map and other essential geodata.
    • Governments should create comprehensive indices of existing government data sets, whether published or not, as a foundation for new transparency policies, to empower public scrutiny of information management, and to enable policymakers to identify gaps in existing data creation and collection.

 3. Provide no-cost access to government data

One of the greatest barriers to access to ostensibly publicly-available information is the cost imposed on the public for access–even when the cost is minimal. Most government information is collected for governmental purposes, and the existence of user fees has little to no effect on whether the government gathers the data in the first place.
  • Governments should remove fees for access, which skew the pool of who is willing (or able) to access information and preclude transformative uses of the data that in turn generates business growth and tax revenues.

  • Governments should also minimise the indirect cost of using and re-using data by adopting commonly owned, non-proprietary (or “open”) formats that allow potential users to access the data without the need to pay for a proprietary software license.

  • Such open formats and standards should be commonly adopted across departments and agencies to harmonise the way information is published, reducing the transaction costs of accessing, using and combining data.

4. Put the users first

Experience shows that open data flounders without a strong user community, and the best way to build such a community is by involving users from the very start in designing and developing open data systems.

  • Within government: The different branches of government (including the legislature and judiciary, as well as different agencies and line ministries within the executive) stand to gain important benefits from sharing and combining their data. Successful open data initiatives create buy-in and cultural change within government by establishing cross-departmental working groups or other structures that allow officials the space they need to create reliable, permanent, ambitious open data policies.
  • Beyond government: Civil society groups and businesses should be considered equal stakeholders alongside internal government actors. Agencies leading on open data should involve and consult these stakeholders – including technologists, journalists, NGOs, legislators, other governments, academics and researchers, private industry, and independent members of the public – at every stage in the process.
  • Stakeholders both inside and outside government should be fully involved in identifying priority datasets and designing related initiatives that can help to address key social or economic problems, foster entrepreneurship and create jobs. Government should support and facilitate the critical role of both private sector and public service intermediaries in making data useful.

5. Invest in capacity

Governments should start with initiatives and requirements that are appropriate to their own current capacity to create and release credible data, and that complement the current capacity of key stakeholders to analyze and reuse it. At the same time, in order to unlock the full social, political and economic benefits of open data, all stakeholders should invest in rapidly broadening and deepening capacity.
  • Governments and their development partners need to invest in making data simple to navigate and understand, available in all national languages, and accessible through appropriate channels such as mobile phone platforms where appropriate.
  • Governments and their development partners should support training for officials, SMEs and CSOs to tackle lack of data and web skills, and should make complementary investments in improving the quality and timeliness of government statistics.

6. Improve the quality of official data

Poor quality, coverage and timeliness of government information – including administrative and sectoral data, geospatial data, and survey data – is a major barrier to unlocking the full value of open data.
  • Governments should develop plans to implement the Paris21 2011 Busan Action Plan, which calls for increased resources for statistical and information systems, tackling important gaps and weaknesses (including the lack of gender disaggregation in key datasets), and fully integrating statistics into decision-making.
  • Governments should bring their statistical efforts into line with international data standards and schemas, to facilitate reuse and analysis across various jurisdictions.
  • Private firms and NGOs that collect data which could be used alongside government statistics to solve public problems in areas such as disease control, disaster relief, urban planning, etc. should enter into partnerships to make this data available to government agencies and the public without charge, in fully anonymized form and subject to robust privacy protections.

7. Foster more accountable, transparent and participatory governance

A data revolution cannot succeed in an environment of secrecy, fear and repression of dissent.
  • The SDGs should include robust commitments to uphold fundamental rights to freedom of expression, information and association; foster independent and diverse media; and implement robust safeguards for personal privacy, as outlined in the UN Covenant on Civil and Political Rights.
  • In addition, in line with their commitments in the UN Millennium Declaration (2000) and the Declaration of the Open Government Partnership (2011), the SDGs should include concrete steps to tackle gaps in participation, inclusion, integrity and transparency in governance, creating momentum and legitimacy for reform through public dialogue and consensus.

Colophon

This submission derives and follows on from the Global Open Data Inititiave’s Global Open Data Declaration which was jointly created by Fundar, Open Institute, Open Knowledge and World Wide Web Foundation and the Sunlight Foundation with input from civil society organizations around the world. The full text of the Declaration can be found here: http://globalopendatainitiative.org/declaration/

Newsflash! OKFestival Programme Launches

- June 4, 2014 in Events, Featured, Free Culture, Join us, network, News, OKFest, OKFestival, Open Access, Open Data, Open Development, Open Economics, Open GLAM, Open Government Data, Open Humanities, Open Knowledge Foundation, Open Knowledge Foundation Local Groups, Open Research, Open Science, Open Spending, Open Standards, open-education, Panton Fellows, privacy, Public Domain, training, Transparency, Working Groups

At last, it’s here! Check out the details of the OKFestival 2014 programme – including session descriptions, times and facilitator bios here! Screen Shot 2014-06-04 at 4.11.42 PM

We’re using a tool called Sched to display the programme this year and it has several great features. Firstly, it gives individual session organisers the ability to update the details on the session they’re organising; this includes the option to add slides or other useful material. If you’re one of the facilitators we’ll be emailing you to give you access this week.

Sched also enables every user to create their own personalised programme to include the sessions they’re planning to attend. We’ve also colour-coded the programme to help you when choosing which conversations you want to follow: the Knowledge stream is blue, the Tools stream is red and the Society stream is green. You’ll also notice that there are a bunch of sessions in purple which correspond to the opening evening of the festival when we’re hosting an Open Knowledge Fair. We’ll be providing more details on what to expect from that shortly!

Another way to search the programme is by the subject of the session – find these listed on the right hand side of the main schedule – just click on any of them to see a list of sessions relevant to that subject.

As you check out the individual session pages, you’ll see that we’ve created etherpads for each session where notes can be taken and shared, so don’t forget to keep an eye on those too. And finally; to make the conversations even easier to follow from afar using social media, we’re encouraging session organisers to create individual hashtags for their sessions. You’ll find these listed on each session page.

We received over 300 session suggestions this year – the most yet for any event we’ve organised – and we’ve done our best to fit in as many as we can. There are 66 sessions packed into 2.5 days, plus 4 keynotes and 2 fireside chats. We’ve also made space for an unconference over the 2 core days of the festival, so if you missed out on submitting a proposal, there’s still a chance to present your ideas at the event: come ready to pitch! Finally, the Open Knowledge Fair has added a further 20 demos – and counting – to the lineup and is a great opportunity to hear about more projects. The Programme is full to bursting, and while some time slots may still change a little, we hope you’ll dive right in and start getting excited about July!

We think you’ll agree that Open Knowledge Festival 2014 is shaping up to be an action-packed few days – so if you’ve not bought your ticket yet, do so now! Come join us for what will be a memorable 2014 Festival!

See you in Berlin! Your OKFestival 2014 Team

Open model of an oil contract

- October 22, 2013 in External Projects, Featured, Open Data, Open Economics

Please come and kick the tires of our open model of an oil contract! In the next month or so, OpenOil and its partners will publish what we believe will be the first financial model of an oil contract under Creative Commons license. We would like to take this opportunity to invite the Open Economics community to come and kick the wheels on the model when it is ready, and help us improve it. We need you because we expect a fair degree of heat from those with a financial or reputational stake in continued secrecy around these industries. We expect the brunt of attacks to be on the basis that we are wrong. And of course we will be wrong in some way. It’s inevitable. So we would like our defence to be not, “no we’re never wrong”, but “yes, sometimes we are wrong, but transparently so and for the right reasons – and look, here are a bunch of friends who have already pointed out these errors, which have been corrected. You got some specific critiques, come give them. But the price of criticism is improvement – the open source way!” We figure Open Economics is the perfect network to seek that constructive criticism. screengrab Ultimately, we want to grow an open source community which will help grow a systematic understanding of the economics of the oil and gas industry independent of investor or government stakes, since the public policy impact of these industries and relevant flows are too vital to be left to industry specialists. There are perhaps 50 countries in the world where such models could transform public understanding of industries which dominate the political economy. The model itself is still being fine-tuned but I’d like to take this chance to throw out a few heuristics that have occurred in the process of building it. Public interest modelling. The model is being built by professionals with industry experience but its primary purpose is to inform public policy, not to aid investment decisions or serve as negotiation support for either governments or companies. This has determined a distinct approach to key issues such as management of complexity and what is an acceptable margin of error. Management of complexity. Although there are several dozen variables one could model, and which typically appear in the models produced for companies, we deliberately exclude a long tail of fiscal terms, such as ground rent and signature bonuses, on the basis that the gain in reduction of margin of error is less than the loss from increasing complexity for the end user. We also exclude many of the fine tuning implementations of the taxation system. We list these terms in a sheet so those who wish can extend the model with them. It would be great, for example, to get tax geek help on refining some of these issues. A hierarchy of margins of error. Extractives projects can typically last 25 years. The biggest single margin of error is not within human power to solve – future price. All other uncertainties or estimates pale in comparison with its impact on returns to all stakeholders. Second are the capex and opex going into a project. The international oil company may be the only real source of these data, and may or may not share them in disaggregated form with the government – everyone else is in the dark. For public interest purposes, the margin of error created by all other fiscal terms and input assumptions combined is less significant, and manageable. Moving away from the zero-sum paradigm. Because modelling has traditionally been associated with the negotiation process, and perhaps because of the wider context surrounding extractive industries, a zero-sum paradigm often predominates in public thinking around the terms of these contracts. But the model shows graphically two distinct ways in which that paradigm does not apply. First, in agreements with sufficient progressivity, rising commodity prices could mean simultaneous rise of both government take and a company’s Internal Rate of Return. Second, a major issue for governments and societies depending on oil production is volatility – the difference between using minimal and maximal assumptions across all of the inputs will likely produce a difference in result which is radical. One of a country’s biggest challenges then is focusing enough attention on regulating itself, its politicians’ appetite for spending, its public’s appetite for patronage. We know this of course in the real world. Iraq received $37 billion in 2007, then $62 billion in 2008, then $43 billion or so in 2009. But it is the old journalistic difference between show and tell. A model can show this in your country, with your conditions. The value of contract transparency. Last only because self-evident is the need for primary extractives conracts between states and companies to enter the public domain. About seven jurisdictions around the world publish all contracts so far but it is gaining traction as a norm in the governance community. The side-effects of the way extractive industries are managed now are almost all due to the ill-understood nature of rent. Even corruption, the hottest issue politically, may often simply be a secondary effect of the rent-based nature of the core activities. Publishing all contracts is the single biggest measure that would get us closer to being able to address the root causes of Resource Curse. See http://openoil.net/ for more details.

Open model of an oil contract

- October 22, 2013 in External Projects, Featured, Open Data, Open Economics

Please come and kick the tires of our open model of an oil contract!

In the next month or so, OpenOil and its partners will publish what we believe will be the first financial model of an oil contract under …

Open Economics: the story so far…

- August 30, 2013 in Advisory Panel, Announcements, Events, Featured, Open Data, Open Economics, projects

A year and a half ago we embarked on the Open Economics project with the support of the Alfred P. Sloan Foundation and we would like a to share a short recap of what we have been up to. Our goal was to define what open data means for the economics profession and to become a central point of reference for those who wanted to learn what it means to have openness, transparency and open access to data in economics.

Advisory Panel of the Open Economics Working Group: openeconomics.net/advisory-panel/

Advisory Panel

We brought together an Advisory Panel of twenty senior academics who advised us and provided input on people and projects we needed to contact and issues we needed to tackle. The progress of the project has depended on the valuable support of the Advisory Panel.

1st Open Economics Workshop, Dec 17-18 ’12, Cambridge, UK: openeconomics.net/workshop-dec-2012/

2nd Open Economics Workshop, 11-12 June ’13, Cambridge, MA: openeconomics.net/workshop-june-2013

International Workshops

We also organised two international workshops, first one held in Cambridge, UK on 17-18 December 2012 and second one in Cambridge U.S. on 11-12 June 2013, convening academics, funders, data publishers, information professionals and students to share ideas and build an understanding about the value of open data, the still persisting barriers to opening up information, as well as the incentives and structures which our community should encourage.

Open Economics Principles

While defining open data for economics, we also saw the need to issue a statement on the openness of data and code – the Open Economics Principles – to emphasise that data, program code, metadata and instructions, which are necessary to replicate economics research should be open by default. Having been launched in August, this statement is now being widely endorsed by the economics community and most recently by the World Bank’s Data Development Group.

Projects

The Open Economics Working Group and several more involved members have worked on smaller projects to showcase how data can be made available and what tools can be built to encourage discussions and participation as well as wider understanding about economics. We built the award-winning app Yourtopia Italy – http://italia.yourtopia.net/ for a user-defined multidimensional index of social progress, which won a special prize in the Apps4Italy competition.

Yourtopia Italy: application of a user-defined multidimensional index of social progress: italia.yourtopia.net

We created the Failed Bank Tracker, a list and a timeline visualisation of the banks in Europe which failed during the last financial crisis and released the Automated Game Play Datasets, the data and code of papers from the Small Artificial Agents for Virtual Economies research project, implemented by Professor David Levine and Professor Yixin Chen at the Washington University of St. Louis. More recently we launched the Metametrik prototype of a platform for the storage and search of regression results in the economics.

MetaMetrik: a prototype for the storage and search of econometric results: metametrik.openeconomics.net

We also organised several events in London and a topic stream about open knowledge and sustainability at the OKFestival with a panel bringing together a diverse range of panelists from academia, policy and the open data community to discuss how open data and technology can help improve the measurement of social progress.

Blog and Knowledge Base

We blogged about issues like the benefits of open data from the perspective of economics research, the EDaWaX survey of the data availability of economics journals, pre-registration of in the social sciences, crowd-funding as well as open access. We also presented projects like the Statistical Memory of Brazil, Quandl, the AEA randomized controlled trials registry. Some of the issues we raised had a wider resonance, e.g. when Thomas Herndon found significant errors in trying to replicate the results of Harvard economists Reinhart and Rogoff, we emphasised that while such errors may happen, it is a greater crime not to make the data available with published research in order to allow for replication.

Some outcomes and expectations

We found that opening up data in economics may be a difficult matter, as many economists utilise data which cannot be open because of privacy, confidentiality or because they don’t own that data. Sometimes there are insufficient incentives to disclose data and code. Many economists spend a lot of resources in order to build their datasets and obtain an advantage over other researchers by making use of information rents. Some journals have been leading the way in putting in place data availability requirements and funders have been demanding data management and sharing plans, yet more general implementation and enforcement is still lacking. There are now, however, more tools and platforms available where researchers can store and share their research content, including data and code. There are also great benefits in sharing economics data: it enables the scrutiny of research findings and gives a possibility to replicate research, it enhances the visibility of research and promotes new uses of the data, avoids unnecessary costs for data collection, etc. In the future we hope to concentrate on projects which would involve graduate students and early career professionals, a generation of economics researchers for whom sharing data and code may become more natural.

Keep in touch

Follow us on Twitter @okfnecon, sign up to the Open Economics mailing list and browse our projects and resources at openeconomics.net.

Open Economics: the story so far…

- August 30, 2013 in Advisory Panel, Announcements, Events, Featured, Open Data, Open Economics, projects

A year and a half ago we embarked on the Open Economics project with the support of the Alfred P. Sloan Foundation and we would like a to share a short recap of what we have been up to.

Our …

Open Economics: the story so far…

- August 30, 2013 in Featured, Open Economics

A year and a half ago we embarked on the Open Economics project with the support of the Alfred P. Sloan Foundation and we would like a to share a short recap of what we have been up to. Our goal was to define what open data means for the economics profession and to become a central point of reference for those who wanted to learn what it means to have openness, transparency and open access to data in economics.

Advisory Panel of the Open Economics Working Group: openeconomics.net/advisory-panel/

Advisory Panel

We brought together an Advisory Panel of twenty senior academics who advised us and provided input on people and projects we needed to contact and issues we needed to tackle. The progress of the project has depended on the valuable support of the Advisory Panel.

1st Open Economics Workshop, Dec 17-18 ’12, Cambridge, UK: openeconomics.net/workshop-dec-2012/

2nd Open Economics Workshop, 11-12 June ’13, Cambridge, MA: openeconomics.net/workshop-june-2013

International Workshops

We also organised two international workshops, first one held in Cambridge, UK on 17-18 December 2012 and second one in Cambridge U.S. on 11-12 June 2013, convening academics, funders, data publishers, information professionals and students to share ideas and build an understanding about the value of open data, the still persisting barriers to opening up information, as well as the incentives and structures which our community should encourage.

Open Economics Principles

While defining open data for economics, we also saw the need to issue a statement on the openness of data and code – the Open Economics Principles – to emphasise that data, program code, metadata and instructions, which are necessary to replicate economics research should be open by default. Having been launched in August, this statement is now being widely endorsed by the economics community and most recently by the World Bank’s Data Development Group.

Projects

The Open Economics Working Group and several more involved members have worked on smaller projects to showcase how data can be made available and what tools can be built to encourage discussions and participation as well as wider understanding about economics. We built the award-winning app Yourtopia Italy – http://italia.yourtopia.net/ for a user-defined multidimensional index of social progress, which won a special prize in the Apps4Italy competition.

Yourtopia Italy: application of a user-defined multidimensional index of social progress: italia.yourtopia.net

We created the Failed Bank Tracker, a list and a timeline visualisation of the banks in Europe which failed during the last financial crisis and released the Automated Game Play Datasets, the data and code of papers from the Small Artificial Agents for Virtual Economies research project, implemented by Professor David Levine and Professor Yixin Chen at the Washington University of St. Louis. More recently we launched the Metametrik prototype of a platform for the storage and search of regression results in the economics.

MetaMetrik: a prototype for the storage and search of econometric results: metametrik.openeconomics.net

We also organised several events in London and a topic stream about open knowledge and sustainability at the OKFestival with a panel bringing together a diverse range of panelists from academia, policy and the open data community to discuss how open data and technology can help improve the measurement of social progress.

Blog and Knowledge Base

We blogged about issues like the benefits of open data from the perspective of economics research, the EDaWaX survey of the data availability of economics journals, pre-registration of in the social sciences, crowd-funding as well as open access. We also presented projects like the Statistical Memory of Brazil, Quandl, the AEA randomized controlled trials registry. Some of the issues we raised had a wider resonance, e.g. when Thomas Herndon found significant errors in trying to replicate the results of Harvard economists Reinhart and Rogoff, we emphasised that while such errors may happen, it is a greater crime not to make the data available with published research in order to allow for replication.

Some outcomes and expectations

We found that opening up data in economics may be a difficult matter, as many economists utilise data which cannot be open because of privacy, confidentiality or because they don’t own that data. Sometimes there are insufficient incentives to disclose data and code. Many economists spend a lot of resources in order to build their datasets and obtain an advantage over other researchers by making use of information rents. Some journals have been leading the way in putting in place data availability requirements and funders have been demanding data management and sharing plans, yet more general implementation and enforcement is still lacking. There are now, however, more tools and platforms available where researchers can store and share their research content, including data and code. There are also great benefits in sharing economics data: it enables the scrutiny of research findings and gives a possibility to replicate research, it enhances the visibility of research and promotes new uses of the data, avoids unnecessary costs for data collection, etc. In the future we hope to concentrate on projects which would involve graduate students and early career professionals, a generation of economics researchers for whom sharing data and code may become more natural.

Keep in touch

Follow us on Twitter @okfnecon, sign up to the Open Economics mailing list and browse our projects and resources at openeconomics.net.

Introducing the Open Economics Principles

- August 7, 2013 in Featured, Open Economics, WG Economics

The Open Economics Working Group would like to introduce the Open Economics Principles, a Statement on Openness of Economic Data and Code. A year and a half ago the Open Economics project began with a mission of becoming central point of reference and support for those interested in open economic data. In the process of identifying examples and ongoing barriers for opening up data and code for the economics profession, we saw the need to present a statement on the guiding principles of transparency and accountability in economics that would enable replication and scholarly debate as well as access to knowledge as a public good. We wrote the Statement on the Open Economics Principles during our First and Second Open Economics International Workshops, receiving feedback from our Advisory Panel and community with the aim to emphasise the importance of having open access to data and code by default and address some of the issues around the roles of researchers, journal editors, funders and information professionals.
Second Open Economics International Workshop, June 11-12, 2013

Second Open Economics International Workshop, June 11-12, 2013

Read the statement below and follow this link to endorse the Principles.

Open Economics Principles

Statement on Openness of Economic Data and Code

Economic research is based on building on, reusing and openly criticising the published body of economic knowledge. Furthermore, empirical economic research and data play a central role for policy-making in many important areas of our
economies and societies.

Openness enables and underpins scholarly enquiry and debate, and is crucial in ensuring the reproducibility of economic research and analysis. Thus, for economics to function effectively, and for society to reap the full benefits from economic research, it is therefore essential that economic research results, data and analysis be openly and freely available, wherever possible.

  1. Open by default: by default data in its different stages and formats, program code, experimental instructions and metadata – all of the evidence used by economists to support underlying claims – should be open as per the Open Definition1, free for anyone to use, reuse and redistribute. Specifically open material should be publicly available and licensed with an appropriate open licence2.
  2. Privacy and confidentiality: We recognise that there are often cases where for reasons of privacy, national security and commercial confidentiality the full data cannot be made openly available. In such cases researchers should share analysis under the least restrictive terms consistent with legal requirements, abiding by the research ethics and guidelines of their community. This should include opening up non-sensitive data, summary data, metadata and code, and facilitating access if the owner of the original data grants other researchers permission to use the data
  3. Reward structures and data citation: recognizing the importance of data and code to the discipline, reward structures should be established in order to recognise these scholarly contributions with appropriate credit and citation in an acknowledgement that producing data and code with the documentation that make them reusable by others requires a significant commitment of time and resources. At minimum, all data necessary to understand, assess, or extend conclusions in scholarly work should be cited. Acknowledgements of research funding, traditionally limited to publications, could be extended to research data and contribution of data curators should be recognised.
  4. Data availability: Investigators should share their data by the time of publication of initial results of analyses of the data, except in compelling circumstances. Data relevant to public policy should be shared as quickly and widely as possible. Funders, journals and their editorial boards should put in place and enforce data availability policies requiring data, code and any other relevant information to be made openly available as soon as possible and at latest upon publication. Data should be in a machine-readable format, with well-documented instructions, and distributed through institutions that have demonstrated the capability to provide long-term stewardship and access. This will enable other researchers to replicate empirical results.
  5. Publicly funded data should be open: publicly funded research work that generates or uses data should ensure that the data is open, free to use, reuse and redistribute under an open licence – and specifically, it should not be kept unavailable or sold under a proprietary licence. Funding agencies and organizations disbursing public funds have a central role to play and should establish policies and mandates that support these principles, including appropriate costs for long-term data availability in the funding of research and the evaluation of such policies3, and independent funding for systematic evaluation of open data policies and use.
  6. Usable and discoverable: as simply making data available may not be sufficient for reusing it, data publishers and repository managers should endeavour to also make the data usable and discoverable by others; for example, documentation, the use of standard code lists, etc., all help make data more interoperable and reusable and submission of the data to standard registries and of common metadata enable greater discoverability.
See Reasons and Background and a link to endorsing the Principles: http://openeconomics.net/principles/.
1. http://opendefinition.org/ 2. Open licences for code are those conformant with the Open Source Definition see http://opensource.org/licenses and open licences for data should be conformant with the open definition, see http://opendefinition.org/licenses/#Data. 3. A good example of an important positive developments in this direction from the United States is http://www.whitehouse.gov/sites/default/files/microsites/ostp/ostp_public_access_memo_2013.pdf

Open tax data, or just VAT ‘open wash’

- July 30, 2013 in Featured, Open Data, Open Economics, Open Government Data, Public Money, WG Open Government Data

This post is by Chris Taggart, the co-founder and CEO of OpenCorporates, the largest open database of companies in the world, and a member of the Open Government working group. [Disclosure: I am on the UK Tax Transparency Board, which has not yet discussed these proposals, but will be doing so at the next meeting in early September] A little over a week ago, Her Majesty’s Revenue & Customs (HMRC) published a consultation on publishing its data more widely, and in it stated its intention to join the open-data movement.
The UK helped secure the G8’s Open Data Charter, which presumes that the data held by Governments will be publicly available unless there is good reason to withhold it. It is important that HMRC plays a full part. HMRC’s relationship with businesses and individuals is unique, and this is reflected in the scope and depth of the information HMRC collects, creates and protects on behalf of taxpayers.

Great. Well, no. The problem is that, despite what the above says, this consultation and the proposals within have little to do with open data or widening access, but instead are primarily about passing data, much of it personal data relating to ordinary individuals, to the anointed few. It also exposes some worrying data-related problems within HMRC that should be ringing alarm bells within government. So what exactly is being suggested? There are two parts:
  1. Proposals to do with sharing HMRC’s data, particularly aggregated and anonymised data. At the moment HMRC can, in general, only share such data if it relates to HMRC’s functions, even if it’s in the wider public benefit.
  2. Proposals to do with the VAT Register. The VAT Register is currently private, even though the a large extent much of the information is ‘out there’, on till receipts, on invoices, on websites, and in various private datasets, and in fact in many countries it’s already public.
Both have their issues, but for moment we’ll concentrate on the second. Now there has been no great clamour for the VAT Register from open-data activists (unlike say the postcode address file, company register, or Ordnance Survey data), so why is it being opened up? Well, why not? As the consultation says:
An underlying principle in developing the proposals in this chapter is brought out in the Shakespeare Review. Data belong to citizens and the presumption of government should be towards openness, unless this causes harm. It is not for government to dictate the nature of the opportunity. The corollary is that the Government will not always be aware of the range or scale of potential benefits, as the quotation below shows – this consultation will help to establish these.
So the proposal is to publish the VAT Register as open data, so that the wider community can do cool stuff with it? No. The consultation neatly elides from this lofty aim with something rather more grubby.
There has been public interest for some time, for example from credit reference agencies (CRAs), in the publication of VAT registration data as a resource to generate benefits.
Don’t the three big credit reference agencies (Experian, Equifax and Callcredit) already know a lot about companies? Surely they know the VAT numbers of many of them, and in any case know a lot more about most companies, especially active, trading companies (the sort that are registered for VAT)? What they don’t have, however, is much information about sole-traders, small partnerships, individuals trading on their own account and without the shield of limited liability, with the responsibilities for publishing information that comes with that. That’s why the VAT register is so important to them, and that’s what this consultation is proposing to give them. Of course they could just ask people for that information. But people might refuse, particularly if they don’t need to borrow money, and that would be a problem as far as building a monetisable dataset of them. If they could only get the government to give them access to that data – have the government act as their own data-collection arm, with the force of law to compel providing of the information – that would be great. For them. For individuals, and for the wider world, it’s not good at all. First, because what we’re talking about here are individuals, who have privacy and data protection rights, not companies, and there needs to be compelling reasons for making that public in the first place – just because the big three credit reference agencies, or CRAs (Experian, Equifax, CallCredit), think they can make money from it isn’t good enough. Second, because if open data is about one thing, it is about democratising access to data, about reversing the traditional position where, to use the words of the Chancellor, George Osborne, “Access to the world’s information – and the ability to communicate it – was controlled by an elite few”. And if there’s one thing that’s certain it’s that the CRAs have a lot of power. But wait, doesn’t the consultation also propose that some of the VAT register is published as open data, specifically “a very selective extract covering just three data fields – VAT registration number (VRN), trading name, and Standard Industry Code (SIC) classification number”. At first sight this might be seen as good, or better than nothing. In fact it shows that HMRC either doesn’t get data, or it’s just ‘openwash’ – an open-data figleaf to obscure the passing of personal and private data wholesale to the CRAs, and one that could potentially lead to greater fraud. Here’s why:
  • The three fields (VAT number, trading name, SIC code) together make up an orphan dataset, i.e. one that’s unconnected with any other data, and therefore is fundamentally useless… unless you want to fraudulently write an invoice calling yourself ‘AAA Plumbing’, charging VAT on it, and pocketing the 20%, knowing that either you will never be caught, or the real AAA Plumbing will be first place HMRC will come looking.
    Fraud is fundamentally about asymmetries of information flows (the fraudster knows more about you than you know about them). If, for example, you know that the real AAA Plumbing is a company with a registered address in Kirkcaldy, Scotland, for example, or the BBB Services is dissolved or has a website showing it works in the aircraft business, then you have a much greater chance of avoiding fraud.
  • Trading names are very problematic, and in general are not registered anywhere, so are little help. They also need have no relationship to the legal name, either of the person or the company. So if you want to find the company behind ZZZ Financial Experts, if indeed there is one, you’re out of luck. It’s puzzling that HMRC would even consider publishing the VAT Register without the legal form, and in the case of companies the company number.
  • One of the stated reasons for publishing the register is that “VAT registration data could also provide a foundation for private sector business registers”. Really? In this world of open data and the importance of core reference data, HMRC wants a private, proprietary identifier set to be created, with all the problems that it would entail? In fact, HMRC was supposed to working with the Department of Business, Innovation & Skills to build such a public dataset. Has it decided that it doesn’t understand data well enough to do this? Or would it rather shackle not just the government but the business sector as a whole to some such dataset?
  • Finally, it’s also rather surprising to discover that the VAT register appears to contain fields such as the company’s incorporation date and SIC codes. In the geek world we call this a denormalised dataset, meaning it’s duplicating data that rightfully belongs in another table or dataset. There are sometimes good reasons for doing this, but there are risks, such as the data becoming out of sync (which is the correct SIC code – the one on the VAT Register or on the Companies House record).
So what should HMRC be doing? First, it should abandon any plans to act as the Credit Reference Agencies’ data collectors, and publish the VAT register or part of the VAT register as a single open dataset, equal to all under the same terms. This would be a genuine spur for innovation, and may even result in increased competition and transparency. Second, it should realise that there’s a fundamental difference between an individual – a living, breathing person with human rights – and a company. As well as human rights, individuals have data protection rights, privacy rights and don’t exist on a public register; companies on the other hand are artificial entities given a distinct legal personality by the state for the good of society, and in return exist in public (on the public Register of Companies). In the case of the VAT register, the pragmatic approach would be to publish the register as open data, but only that part that relates to companies. Third, it needs to realise that it is fundamentally in the data business, like it or not, and it needs to quickly get to grips with the modern data world, including the power of data, for good, and for bad. The UK has probably the leading organisations in the world in this area, including OpenCorporates, the Open Knowledge Foundation and the Open Data Institute.