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Reinhart-Rogoff Revisited: Why we need open data in economics

- April 18, 2013 in Featured, Open Data, Open Economics, Open Research, Public Finance and Government Data

Another economics scandal made the news this week. Harvard Kennedy School professor Carmen Reinhart and Harvard University professor Kenneth Rogoff argued in their 2010 NBER paper that economic growth slows down when the debt/GDP ratio exceeds the threshold of 90 percent of GDP. These results were also published in one of the most prestigious economics journals – the American Economic Review (AER) – and had a powerful resonance in a period of serious economic and public policy turmoil when governments around the world slashed spending in order to decrease the public deficit and stimulate economic growth.

Carmen Reinhart

Kenneth Rogoff

Yet, they were proven wrong. Thomas Herndon, Michael Ash and Robert Pollin from the University of Massachusetts (UMass) tried to replicate the results of Reinhart and Rogoff and criticised them on the basis of three reasons:
  • Coding errors: due to a spreadsheet error five countries were excluded completely from the sample resulting in significant error of the average real GDP growth and the debt/GDP ratio in several categories
  • Selective exclusion of available data and data gaps: Reinhart and Rogoff exclude Australia (1946-1950), New Zealand (1946-1949) and Canada (1946-1950). This exclusion is alone responsible for a significant reduction of the estimated real GDP growth in the highest public debt/GDP category
  • Unconventional weighting of summary statistics: the authors do not discuss their decision to weight equally by country rather than by country-year, which could be arbitrary and ignores the issue of serial correlation.
The implications of these results are that countries with high levels of public debt experience only “modestly diminished” average GDP growth rates and as the UMass authors show there is a wide range of GDP growth performances at every level of public debt among the twenty advanced economies in the survey of Reinhart and Rogoff. Even if the negative trend is still visible in the results of the UMass researchers, the data fits the trend very poorly: “low debt and poor growth, and high debt and strong growth, are both reasonably common outcomes.”

Source: Herndon, T., Ash, M. & Pollin, R., “Does High Public Debt Consistently Stifle Economic Growth? A Critique of Reinhart and Rogoff, Public Economy Research Institute at University of Massachusetts: Amherst Working Paper Series. April 2013.

What makes it even more compelling news is that it is all a tale from the state of Massachusetts: distinguished Harvard professors (#1 university in the US) challenged by empiricists from the less known UMAss (#97 university in the US). Then despite the excellent AER data availability policy – which acts as a role model for other journals in economics – has failed to enforce it and make the data and code of Reinhart and Rogoff available to other researchers. Coding errors happen, yet the greater research misconduct was not allowing for other researchers to review and replicate the results through making the data openly available. If the data and code were available upon publication already in 2010, it may not have taken three years to prove these results wrong, which may have probably influenced the direction of public policy around the world towards stricter austerity measures. Sharing research data means a possibility to replicate and discuss, enabling the scrutiny of research findings as well as improvement and validation of research methods through more scientific enquiry and debate.

Get in Touch

The Open Economics Working Group advocates the release of datasets and code along with published academic articles and provides practical assistance to researchers who would like to do so. Get in touch if you would like to learn more by writing us at economics [at] okfn.org and signing for our mailing list.

References

Herndon, T., Ash, M. & Pollin, R., “Does High Public Debt Consistently Stifle Economic Growth? A Critique of Reinhart and Rogoff, Public Economy Research Institute at University of Massachusetts: Amherst Working Paper Series. April 2013: Link to paper | Link to data and code

Sovereign Credit Risk: An Open Database

- January 31, 2013 in credit risk, Data Release, External Projects, Featured, open analysis, Open Data, Open Economics, Open Research, Public Finance and Government Data, Public Sector Credit, sovereign debt crisis

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://www.publicsectorcredit.org/sovdef 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. CentralGovernmentInterestToRevenue2010

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.

The Statistical Memory of Brazil

- January 14, 2013 in Crowd Sourcing, data digitalisation, Data Digitalization, data mining, data systems, economics profession, External Projects, Featured, historical data, Open Data, Open Economics, Public Finance and Government Data, Statistical Memory of Brazil

This blog post is written by Eustáquio Reis, Senior Research Economist at the Institute of Applied Economic Research (Ipea) in Brazil and member of the Advisory Panel of the Open Economics Working Group. The project Statistical Memory of Brazil aims to digitize and to make freely available and downloadable the rare book collections of the Library of the Minister of Finance in Rio de Janeiro (BMF/RJ). The project focuses on the publications containing social, demographic, economic and financial statistics for the nineteenth and early twentieth century Brazil. At present, approximately 1,500 volumes, 400,000 pages and 200,000 tables have been republished. Apart from democratizing the contents to both the scientific community and the general public, the project intends the physical preservation of the collection. The rarity, age and precarious state of conservation of the books strongly recommend to restrict physical access to them, limiting their handling to specific bibliographical purposes. For the Brazilian citizen, free access to the contents of rare historical collections and statistics provides a form of virtual appropriation of the national memory, and as such a source of knowledge, gratification and cultural identity.

The Library of the Minister of Finance in Rio de Janeiro (BMF/RJ)

Inaugurated in 1944, the BMF/RJ extends over 1,200 square meters in the Palacio da Fazenda in downtown Rio de Janeiro, the seat of the Minister of Finance up to 1972 when it was moved to Brasilia. The historical book collection dates back to the early 19th century when the Portuguese Colonial Administration was transferred to Brazil. Thereafter, several libraries from other institutions — Brazilian Customs, Brazilian Institute of Coffee, Sugar and Alcohol Institute, among others — were incorporated to the collection which today comprises over 150,000 volumes mainly specialized in economics, law, public administration and finance.

Rare book collections

For the purposes of the project, the collection of rare books includes a few thousand statistical reports and yearbooks. To mention just a few, the annual budgets of the Brazilian Empire, 1821-1889; annual budgets of the Brazilian Republic since 1890; Ministerial and Provincial reports since the 1830s; foreign and domestic trade yearbooks since 1839; railways statistics since the 1860s; stock market reports since the 1890s; economic retrospects and financial newsletters since the 1870s; the Brazilian Demographic and Economic Censuses starting in 1872 as well as the Brazilian Statistical Yearbooks starting in 1908. En passant, it should be noted that despite their rarity, fragility, and scientific value, these collections are hardly considered for republication in printed format.

Partnerships and collaborations

Under the initiative of the Research Network on Spatial Analysis and Models (Nemesis), sponsored by the Foundation for the Support of Research of the State of Rio de Janeiro and the National Council for Scientific and Technological Development, the project is a partnership between the Regional Administration of the Minister of Finance in Rio de Janeiro (MF/GRA-RJ); Institute of Applied Economic Researh (IPEA) and the Internet Archive (IA). In addition to the generous access to its library book collection, The Minister of Finance provides the expert advice on their librarians as well as the office space and facilities required for the operation of the project. The Institute of Applied Economic Research provides advisory in economics, history and informatics. The Internet Archive provides the Scribe® workstations and digitization technology, making the digital publications available in several different formats on the website. The project also makes specific collaborations with other institutions to supplement the collections of the Library of the Minister of Finance. Thus, the Brazilian Statistical Office (IBGE) supplemented the collections of the Brazilian Demographic and Economic Censuses, as well as of the Brazilian Statistical Yearbooks; the National Library (BN) made possible the republication of the Budgets of the Brazilian Empire; the Provincial and Ministerial Reports; the Rio News; and the Willeman Brazilian Review, the latter in collaboration with and the Department of Economics of the Catholic University of Rio de Janeiro.

Future developments an extensions

Based upon open source software designed to publish, manage, link and preserve digital contents (Drupal, Fedora and Islandora), a new webpage of the project is under construction including two collaborative / crowdsourcing platforms. The first crowdsourcing platform will create facilities for the indexing, documentation and uploading of images and tabulations of historical documents and databases compiled by other research institutions or individuals willing to make voluntary contributions to the project. The dissemination of the digital content intends to stimulate research innovations, extensions, and synergies based upon the historical documents and databases. For such purpose, an open source solution to be considered is the Harvard University Dataverse Project. The second crowdsourcing platform intends to foster online decentralized collaboration of volunteers to compile or transcribe to editable formats (csv, txt, xls, etc.) the content of selected digital republications of the Brazil’s Statistical Memory project. Whenever possible, optical character recognition (OCR) programs and routines will be used to facilitate the transcription of the image content of the books. The irregular typography of older publications, however, will probably require visual character recognition and manual transcription of contents. Finally, additional routines and programs will be developed to coordinate, monitor and revise the compilations made, so as to avoid mistakes and duplications.

Project Team

Eustáquio Reis, IPEA, Coordinator
Kátia Oliveira, BMF/RJ, Librarian
Vera Guilhon, BMF/RJ, Librarian
Jorge Morandi, IPEA, TI Coordinator
Gemma Waterston, IA, Project Manager
Ana Kreter, Nemesis, Researcher
Gabriela Carvalho, FGV, Researcher
Lucas Mation, IPEA, Researcher

Interns:
Fábio Baptista
Anna Vasconcellos
Ana Luiza Freitas
Amanda Légora

Timeline of Failed European Banks

- January 7, 2013 in banks, Crowd Sourcing, data visualisation, Failed Banks, Featured, financial markets, Open Data, Public Finance and Government Data

A few months back Open Economics launched a project to list the European banks which have failed recently. After a successful online data sprint and follow up research, we have now collected data on 122 bank failures and bailouts since 1997. To visualize the data collected on bank failures I created this timeline. The data collection was initiated as neither the EU Commission, Eurostat nor EBA were able to provide any specific data. We decided to include a broad range of bank crisis measures beyond bankruptcy filing such as bank nationalisations and government bailouts. We also added some bank mergers,and finally we have added several cases where banks entered temporary closure (ie. “extraordinary administration” under Italian law). For each failed bank we have attempted to gather basic details such as the date of collapse, a news source and a news clip explaining the circumstances of the collapse. We need your help to improve the failed bank tracker? Here’s how you can help.
  • Bank failures are still missing from the list. So if you know of any failures missing from the list, please go ahead and add the information directly in the sheet. If you have corrections to any of the bank appearing, please add them with an attached source and information. If news clips are not available in English, add information in the original language.
  • Descriptions and sources for several of the banks on the list are still missing – in particular on Italian and Portuguese.
  • Additional info. We hope to add more data to each bank failure, in particular a) The total assets prior to collapse and b) The auditor who signed off on the latest annual report. Let us know if you wish to help digging up any of this information.
  • We are eager to hear your view on the approach or any of the listed bank failures. Join the discussion on our mailing-list.