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Sovereign Credit Risk: An Open Database

Marc Joffe - January 31, 2013 in Data Release, External Projects, Featured, Open Data, Open Economics, Open Research, Public Finance and Government Data, Public Sector Credit

Throughout the Eurozone, credit rating agencies have been under attack for their lack of transparency and for their pro-cyclical sovereign rating actions. In the humble belief that the crowd can outperform the credit rating oracles, we are introducing an open database of historical sovereign risk data. It is available at http://sovdefdata.appspot.com/ where community members can both view and edit the data. Once the quality of this data is sufficient, the data set can be used to create unbiased, transparent models of sovereign credit risk.

The database contains central government revenue, expenditure, public debt and interest costs from the 19th century through 2011 – along with crisis indicators taken from Reinhart and Rogoff’s public database.

Why This Database?

Prior to the appearance of This Time is Different, discussions of sovereign credit more often revolved around political and trade-related factors. Reinhart and Rogoff have more appropriately focused the discussion on debt sustainability. As with individual and corporate debt, government debt becomes more risky as a government’s debt burden increases. While intuitively obvious, this truth too often gets lost among the multitude of criteria listed by rating agencies and within the politically charged fiscal policy debate.

In addition to emphasizing the importance of debt sustainability, Reinhart and Rogoff showed the virtues of considering a longer history of sovereign debt crises. As they state in their preface:

“Above all, our emphasis is on looking at long spans of history to catch sight of ’rare’ events that are all too often forgotten, although they turn out to be far more common and similar than people seem to think. Indeed, analysts, policy makers, and even academic economists have an unfortunate tendency to view recent experience through the narrow window opened by standard data sets, typically based on a narrow range of experience in terms of countries and time periods. A large fraction of the academic and policy literature on debt and default draws conclusions on data collected since 1980, in no small part because such data are the most readily accessible. This approach would be fine except for the fact that financial crises have much longer cycles, and a data set that covers twenty-five years simply cannot give one an adequate perspective…”

Reinhart and Rogoff greatly advanced what had been an innumerate conversation about public debt, by compiling, analyzing and promulgating a database containing a long time series of sovereign data. Their metric for analyzing debt sustainability – the ratio of general government debt to GDP – has now become a central focus of analysis.

We see this as a mixed blessing. While the general government debt to GDP ratio properly relates sovereign debt to the ability of the underlying economy to support it, the metric has three important limitations.

First, the use of a general government indicator can be misleading. General government debt refers to the aggregate borrowing of the sovereign and the country’s state, provincial and local governments. If a highly indebted local government – like Jefferson County, Alabama, USA – can default without being bailed out by the central government, it is hard to see why that local issuer’s debt should be included in the numerator of a sovereign risk metric. A counter to this argument is that the United States is almost unique in that it doesn’t guarantee sub-sovereign debts. But, clearly neither the rating agencies nor the market believe that these guarantees are ironclad: otherwise all sub-sovereign debt would carry the sovereign rating and there would be no spread between sovereign and sub-sovereign bonds – other than perhaps a small differential to accommodate liquidity concerns and transaction costs.

Second, governments vary in their ability to harvest tax revenue from their economic base. For example, the Greek and US governments are less capable of realizing revenue from a given amount of economic activity than a Scandinavian sovereign. Widespread tax evasion (as in Greece) or political barriers to tax increases (as in the US) can limit a government’s ability to raise revenue. Thus, government revenue may be a better metric than GDP for gauging a sovereign’s ability to service its debt.

Finally, the stock of debt is not the best measure of its burden. Countries that face comparatively low interest rates can sustain higher levels of debt. For example, The United Kingdom avoided default despite a debt/GDP ratio of roughly 250% at the end of World War II. The amount of interest a sovereign must pay on its debt each year may thus be a better indicator of debt burden.

Our new database attempts to address these concerns by layering central government revenue, expenditure and interest data on top of the statistics Reinhart and Rogoff previously published.

A Public Resource Requiring Public Input

Unlike many financial data sets, this compilation is being offered free of charge and without a registration requirement. It is offered in the hope that it, too, will advance our understanding of sovereign credit risk.

The database contains a large number of data points and we have made efforts to quality control the information. That said, there are substantial gaps, inconsistencies and inaccuracies in the data we are publishing.

Our goal in releasing the database is to encourage a mass collaboration process directed at enhancing the information. Just as Wikipedia articles asymptotically approach perfection through participation by the crowd, we hope that this database can be cleansed by its user community. There are tens of thousands of economists, historians, fiscal researchers and concerned citizens around the world that are capable of improving this data, and we hope that they will find us.

To encourage participation, we have added Wiki-style capabilities to the user interface. Users who wish to make changes can log in with an OpenID and edit individual data points. They can also enter comments to explain their changes. User changes are stored in an audit trail, which moderators will periodically review – accepting only those that can be verified while rolling back others.

This design leverages the trigger functionality of MySQL to build a database audit trail that moderators can view and edit. We have thus married the collaborative strengths of a Wiki to the structure of a relational database. Maintaining a consistent structure is crucial for a dataset like this because it must ultimately be analyzed by a statistical tool such as R.

The unique approach to editing database fields Wiki-style was developed by my colleague, Vadim Ivlev. Vadim will contribute the underlying Python, JavaScript and MySQL code to a public GitHub repository in a few days.

Implications for Sovereign Ratings

Once the dataset reaches an acceptable quality level, it can be used to support logit or probit analysis of sovereign defaults. Our belief – based on case study evidence at the sovereign level and statistical modeling of US sub-sovereigns – is that the ratio of interest expense to revenue and annual revenue change are statistically significant predictors of default. We await confirmation or refutation of this thesis from the data set. If statistically significant indicators are found, it will be possible to build a predictive model of sovereign default that could be hosted by our partners at Wikirating. The result, we hope, will be a credible, transparent and collaborative alternative to the credit ratings status quo.

Sources and Acknowledgements

Aside from the data set provided by Reinhart and Rogoff, we also relied heavily upon the Center for Financial Stability’s Historical Financial Statistics. The goal of HFS is “to be a source of comprehensive, authoritative, easy-to-use macroeconomic data stretching back several centuries.” This ambitious effort includes data on exchange rates, prices, interest rates, national income accounts and population in addition to government finance statistics. Kurt Schuler, the project leader for HFS, generously offered numerous suggestions about data sources as well as connections to other researchers who gave us advice.

Other key international data sources used in compiling the database were:

International Monetary Fund’s Government Finance Statistics
Eurostat
UN Statistical Yearbook
League of Nation’s Statistical Yearbook
B. R. Mitchell’s International Historical Statistics, Various Editions, London: Palgrave Macmillan.
Almanach de Gotha
The Statesman’s Year Book
Corporation of Foreign Bondholders Annual Reports
Statistical Abstract for the Principal and Other Foreign Countries
For several countries, we were able to obtain nation-specific time series from finance ministry or national statistical service websites.

We would also like to thank Dr. John Gerring of Boston University and Co-Director of the CLIO World Tables project, for sharing data and providing further leads as well as Dr. Joshua Greene, author of Public Finance: An International Perspective, for alerting us to the IMF Library in Washington, DC.

A number of researchers and developers played valuable roles in compiling the data and placing it on line. We would especially like to thank Charles Tian, T. Wayne Pugh, Amir Muhammed, Anshul Gupta and Vadim Ivlev, as well as Karthick Palaniappan and his colleagues at H-Garb Informatix in Chennai, India for their contributions.

Finally, we would like to thank the National University of Singapore’s Risk Management Institute for the generous grant that made this work possible.

Tags: credit risk, open analysis, open data, sovereign debt crisis 2 Comments »

Reputation Factor in Economic Publishing

Daniel Scott - November 1, 2012 in Featured, Open Access

“The big problem in economics is that it really matters in which journals you publish, so the reputation factor is a big hindrance in getting open access journals up and going”. Can the accepted norms of scholarly publishing be successfully challenged?

This quotation is a line from the correspondence about writing this blogpost for the OKFN. The invitation came to write for the Open Economics Working Group, hence the focus on economics, but in reality the same situation pertains across pretty much any scholarly discipline you can mention. From the funding bodies down through faculty departments and academic librarians to individual researchers, an enormous worldwide system of research measurement has grown up that conflates the quality of research output with the publications in which it appears. Journals that receive a Thomson ISI ranking and high impact factors are perceived as the holy grail and, as is being witnessed currently in the UK during the Research Excellence Framework (REF) process, these carry tremendous weight when it comes to research fund awards.

Earlier this year, I attended a meeting with a Head of School at a Russell Group university, in response to an email that I had sent with information about Social Sciences Directory, the ‘gold’ open access publication that I was then in the first weeks of setting up. Buoyed by their acceptance to meet, I was optimistic that there would be interest and support for the idea of breaking the shackles of existing ranked journals and their subscription paywall barriers. I believed then – and still believe now – that if one or two senior university administrators had the courage to say, “We don’t care about the rankings. We will support alternative publishing solutions as a matter of principle”, then it would create a snowball effect and expedite the break up of the current monopolistic, archaic system. However, I was rapidly disabused. The faculty in the meeting listened politely and then stated categorically that they would never consider publishing in a start up venture such as Social Sciences Directory because of the requirements of the REF. The gist of it was, “We know subscription journals are restrictive and expensive, but that is what is required and we are not going to rock the boat”.

I left feeling deflated, though not entirely surprised. I realised some time ago that the notion of profit & loss, or cost control, or budgetary management, was simply anathema to many academic administrators and that trying to present an alternative model as a good thing because it is a better deal for taxpayers is an argument that is likely to founder on the rocks of the requirements of the funding and ranking systems, if not apathy and intransigence. A few years ago, whilst working as a sales manager in subscription publishing, I attended a conference of business school deans and directors. (This in itself was unusual, as most conferences that I attended were for librarians – ALA, UKSG, IFLA and the like – as the ‘customer’ in a subscription sense is usually the university library). During a breakout session, a game of one-upmanship began between three deans, as they waxed lyrically about the overseas campuses they were opening, the international exchanges of staff and students they had fixed up, the new campus buildings that were under construction, and so on.

Eventually, I asked the fairly reasonable question whether these costly ventures were being undertaken with a strategic view that they would eventually recoup their costs and were designed to help make their schools self-funding. Or indeed, whether education and research are of such importance for the greater good of all that they should be viewed as investments. The discomfort was palpable. One of the deans even strongly denied that this is a question of money. That the deans of business schools should take this view was an eye-opening insight in to the general academic attitude towards state funding. It is an attitude that is wrong because ultimately, of course, it is entirely about the money. The great irony was that this conversation took place in September 2008, with the collapse of Lehman Brothers and the full force of the Global Financial Crisis (GFC) soon to impact gravely on the global higher education and research sector. A system that for years had been awash with money had allowed all manner of poor practices to take effect, in which many different actors were complicit. Publishers had seized on the opportunity to expand output massively and charge vast fees for access; faculty had demanded that their libraries

subscribe to key journals, regardless of cost; libraries and consortia had agreed to publishers’ demands because they had the money to do so; and the funding bodies had built journal metrics into the measurement for future financing. No wonder, then, that neither academia nor publishers could or would take the great leap forward that is required to bring about change, even after the GFC had made it patently clear that the ongoing subscription model is ultimately unsustainable. Change needs to be imposed, as the British government bravely did in July with the decision to adopt the recommendations of the Finch Report.

However, this brings us back to the central issue and the quotation in the title. For now, the funding mechanisms are the same and the requirement to publish in journals with a reputation is still paramount. Until now, arguments against open access publishing have tended to focus on quality issues. The argument goes that the premier (subscription) journals take the best submissions and then there is a cascade downwards through second tier journals (which may or may not be subscription-based) until you get to a pile of leftover papers that can only be published by the author paying a fee to some sort of piratical publisher. This does not stand much scrutiny. Plenty of subscription-based journals are average and have been churned out by publishers looking to beef up their portfolios and justify charging ever-larger sums. Good research gets unnecessarily dumped by leading journals because they adhere to review policies dating from the print age when limited pagination forced them to be highly selective. Other academics, as we have seen at Social Sciences Directory, have chosen to publish and review beyond the established means because they believe in finding and helping alternatives. My point is that good research exists outside the ‘top’ journals. It is just a question of finding it.

So, after all this, do I believe that the “big hindrance” of reputation can be overcome? Yes, but only through planning and mandate. Here is what I believe should happen:

The sheer number of journals is overwhelming and, in actuality, at odds with modern user behaviour which generally accesses content online and uses a keyword search to find information. Who needs journals? What you want is a large collection of articles that are well indexed and easily searchable, and freely available. This will enable the threads of inter-disciplinary research to spread much more effectively. It will increase usage and reduce cost-per-download (increasingly the metrics that librarians use to measure the return on investment of journals and databases), whilst helping to increase citation and impact.
Ensure quality control of peer review by setting guidelines and adhering to them.
De-couple the link between publishing and tenure & department funding.

In many cases, universities will have subscribed to a particular journal for years and will therefore have access to a substantial back catalogue. This has often been supplemented by the purchase of digitised archives, as publishers cottoned on to other sources of revenue which happened to chime with librarians’ preferences to complete online collections and take advantage of non-repeatable purchases. Many publishers also sell their content to aggregators, who agree to an embargo period so that the publisher can also sell the most up-to-date research directly. Although the axe has fallen on many print subscriptions, some departments and individuals still prefer having a copy on their shelves (even though they could print off a PDF from the web version and have the same thing, minus the cover). So, aside from libraries often paying more than once for the same content, they will have complete collections up to a given point in time. University administrators need to take the bold decision to change, to pick an end date as a ‘cut off’ after which they will publicly state that they are switching to new policies in support of OA. This will allow funds to be freed up and used to pay for institutional memberships, article processing fees, institutional repositories – whatever the choice may be. Editors, authors and reviewers will be encouraged to offer their services elsewhere, which will in turn rapidly build the reputation of new publications.

Scholarly publishing is being subjected to a classic confrontation between tradition and modernity. For me, it is inevitable that modernity will win out and that the norms will be successfully challenged.

Tags: open access, open analysis, open research, reputation No Comments »

The Role of Government: Small Public Sector or Big Cuts?

Velichka Dimitrova - October 30, 2012 in Fact Checking Open Data, Featured, Public Finance and Government Data

This blog post is written for the School of Data Blog and is cross-posted from here.

Second Presidential Debate 2012

News stories based on statistical arguments emphasise a single fact but may lack the broader context. Would the future involve some more interactive form of media communication? Could tools like Google Fusion Tables allow us to delve into data and make our own data visualisations while discovering aspects of the story we are not told about?

There has rarely been an issue as controversial in economic policy as the role of government. Recently the role of government has been in the heart of the ideological divide of the US presidential debates. While Governor Romney advocates against a government-centred (small government) approach and threatens to undo the role of federal government in national life, President Obama supports the essential function of the state (big government) in promoting economic growth, empowering all societal groups with federal investments in education, healthcare and future competitive technology.

Graph 1: United Kingdom and other major country groups. Data Source: World Economic Outlook 2012. Download data from the DataHub

Two weeks ago the Guardian published an article about how the Tory government plans to shrink the state even below US levels, based on the recently-released data from the IMF’s World Economic Outlook. Let’s take the source data and take a look at the bigger picture. On the DataHub, I uploaded all data for “General Government Total Expenditure to GDP” for all countries as well as country groups [See the dataset]. You could use the Datahub Datastore default visualisation tools to build a line graph (select the dataset, then in Preview choose “Graph”) or try the Google Fusion Table with the all countries dataset to select the countries you are interested in exploring.

According to the data Britain would have a smaller public sector¹ than the average of all advanced economies by 2017: other country groups are added to show how regions in the world compare (see Graph 1). Even EU countries with staggering public debt – like Greece – would still have a higher relative total government expenditure to GDP according to the projections (see Graph 2).

Graph 2: United Kingdom and other European countries + United States. Data Source: World Economic Outlook 2012. Download data from the DataHub

But what is the bigger picture? And does shrinking the role of government in the economy mean that total government expenditures will fall? Not necessarily, because remember that percentages are relative numbers. The growth or decline of total government spending would ultimately depend on economic growth or the increase of the total output of the economy until 2017. If we take the data for “General Government Total Expenditure” in national currency and build the growth rates², we see that for the UK the growth rate is above zero, meaning that government expenditure would actually increase overtime, despite the diminishing role of government in the economy’s total output.

Debt-ridden countries like Greece, Portugal or Spain (dropping US and Italy to avoid an over-crowded graph) will have to slash spending first before reaching a positive growth despite their larger public sectors. The lesson is that the size of the public sector does not always equate to actual growth in government expenditures.

Graph 3: Growth in government expenditure for United Kingdom and other European countries. Data Source: World Economic Outlook 2012

Despite having a limited meaning for practical interpretational purposes, the government total expenditure to GDP is often an argument in ideological debates or a measure in policy papers which investigate the impact of government spending on consumption and economic growth or the optimal size of government. While lumped together, government total expenditure varies in composition between high-, middle- and low-income groups: richer societies tend to spend more on social security and welfare, middle- and low-income countries have higher relative capital expenditure and low-income societies tend to spend a larger share of their government budget on the military (e.g. See some examples from earlier IMF publications).

Even if no cuts are actually made, the public sector will eventually shrink: For example inflation could mean that the government will actually spend less in real terms. A smaller public sector in the long run will eventually mean that countries like UK will not be able to support an aging population or provide the same levels of infrastructure and public services as currently used to. Yet smaller public sector might also provide an opportunity to cut taxes, provide incentives for the business sector and boost economic growth. Policy choices about the size of government following the US presidential elections and the sovereign debt crisis in Europe would partly be choices of ideology, as it there is no clear evidence which recipe works for an individual case.

In the next piece in this series, we will look at some of the detailed data available on government staff salaries around the world.

¹ The size of the public sector is measured by the percentage of total government expenditure in GDP.

² How do I build growth rates? Add one column where you build natural logarithm of the absolute expenditure numbers, add another column where you lag all observations by one year: shift the entire column down by one row. In the third column take the difference between the current year logarithm and the lagged value. Growth rate = ln (x_t) – ln (x_t-1)

Tags: data journalism, data stories, open analysis, open data, size of government No Comments »