Tag Archives: Mihály Fazekas

New Podcast Episode, Featuring Mihaly Fazekas

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A new episode of KickBack: The Global Anticorruption Podcast is now available. In the new episode, my ICRN colleagues Nils Kobis and Christopher Starke interview Mihaly Fazekas, Assistant Professor of Public Policy at the Central European University. Professor Fazekas explains how he became interested in the study of corruption and describes some of his lines of research, including his work on measurement of corruption, particularly in the context of public procurement, and the challenges of scaling up the best corruption measures. The interview also covers additional topics such as the role of investigative journalism in fighting corruption, and the anticorruption potential impact of new technologies, including big data analysis and artificial intelligence.

You can also find both this episode and an archive of prior episodes at the following locations:

A quick note: We will be going on summer break, so we will not be releasing any new episodes over the next six weeks, but KickBack will return with new episodes in September. KickBack is a collaborative effort between GAB and the Interdisciplinary Corruption Research Network (ICRN). If you like it, please subscribe/follow, and tell all your friends! And if you have suggestions for voices you’d like to hear on the podcast, just send me a message and let me know.

Guest Post: Turning Big Data Into a Useful Anticorruption Tool in Africa

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GAB is delighted to welcome back Dr. Elizabeth Dávid-Barrett of the University of Sussex, who contributes today’s guest post:

Many anticorruption advocates are excited about the prospects that “big data” will help detect and deter graft and other forms of malfeasance. As part of a project in this vein, titled Curbing Corruption in Development Aid-Funded Procurement, Mihály Fazekas, Olli Hellmann, and I have collected contract-level data on how aid money from three major donors is spent through national procurement systems; our dataset comprises more than half a million contracts and stretching back almost 20 years. But good data alone isn’t enough. To be useful, there must be a group of interested and informed users, who have both the tools and the skills to analyse the data to uncover misconduct, and then lobby governments and donors to listen to and act on the findings. The analysis of big datasets to find evidence of corruption – for example, the method developed by Mihály Fazekas to identify “red flags” of corruption risks in procurement contract data—requires statistical skills and software, both of which are in short supply in many parts of the developing world, such as sub-Saharan Africa.

Yet some ambitious recent initiatives are trying to address this problem. Lately I’ve had the privilege to be involved in one such initiative, led by Oxford mathematician Balázs Szendrői, that helps empower a group of young African mathematicians to analyse “big data” on public corruption. Continue reading →

Guest Post: Is Sunlight Really the Best Disinfectant? Evidence on Procurement Transparency from Europe

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GAB is delighted to welcome back Mihály Fazekas, of the University of Cambridge and the Government Transparency Institute, who contributes the following guest post:

Public procurement, which accounts for roughly one-third of government spending in OECD countries and up to 50% in developing economies, is well-known as an area associated with high corruption risk. Hence, it is hardly a surprise that a range of policy recommendations from international organizations (such as the OECD), civil society networks (such as the Open Contracting Data Standard), and research projects (e.g. Digiwhist) have emerged to promote anticorruption in public procurement. And one of the most popular prescriptions for achieving this goal is increased transparency. Transparency, of course, can mean different things. For purposes of the discussion here, we will follow the OECD and World Bank in defining “public procurement transparency” as entailing the timely, free, and accurate publication of public procurement documents in a central e-procurement portal in a machine-readable format, with this publication requirement applying to every major step of the contracting process, and disclosing all key characteristics of the tender and contract. (For a comprehensive data template see here).

Research suggests that this sort of transparency does make a difference in terms of bidder numbers and composition. Yet it remains an open question whether public procurement transparency is necessary or sufficient for controlling corruption in public procurement. Indeed, if one looks at a sample of European countries’ public procurement transparency and their suspected corruption risks, one finds a surprising result: the best governed countries in Europe have the lowest levels of transparency in public procurement. Continue reading →

Guest Post: Using Big Data to Detect Collusive Bidding in Public Procurement

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Bence Tóth and Mihály Fazekas of the Corruption Research Center Budapest (CRCB) contribute the following guest post:

As several earlier posts on this blog have discussed (see, for example, here, here, and here), collusion and corruption in public procurement is a significant problem, one that is extremely difficult to detect and combat. The nature of public procurement markets makes collusion easier to sustain, as pay-offs are higher (demand is often inelastic due to the auction mechanisms used), administrative costs increase entry barriers, and the transparency of procurement contract awards–often intended as an anticorruption device–can actually make it easier for cartel members to monitor one another and punish cheating. Law enforcement agencies have tried various techniques for breaking these cartels, for example by offering leniency to the first company that “defects” on the other cartel members by exposing the collusive arrangement. However, although leniency policies have sometimes proven to be an effective tool to fight coordinated company behavior, the efficacy of this approach is limited given the relative unlikelihood that the government will ever acquire convincing evidence of collusion absent such a defection by an insider. Hence, there is great need for alternative methods to identify collusive rings and guide tradition investigation.

In many markets, using quantitative indicators to detect collusion has not been feasible, as gathering meaningful tender-level data (or even market-level data) is too costly, or simply impossible. However, in the case of public procurement markets, there is a huge amount of publicly available data, which makes the use of “Big Data” techniques to pinpoint collusion-related irregularities more feasible. Indeed, in collaboration with our colleagues at CRCB, we have developed a simple, yet novel approach for detecting collusive behavior. Continue reading →

When Transparency Makes Corruption Worse: Cartels in Public Procurement

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Yesterday Matthew commended the work of Mihály Fazekas, István János Tóth, and their colleagues to those concerned with corruption in public procurement.  I second that recommendation.  In their July 2013, slyly-named “Corruption Manual for Beginners”, the authors describe better than anyone yet how a government buyer can connive to steer a contract to a particular seller — from skewing the contract specifications so that only the favored firm can meet them, to failing to notify others about the procurement, to disqualifying on specious grounds firms that submit bids lower than the favored firm’s bid.

Yet despite the value of the contribution, the authors have not (yet) provided a similarly penetrating analysis of another form of public procurement corruption: that which results not from a conspiracy between a government buyer and one seller but that between the buyer and a group of sellers organized into an industry cartel.  Judging from the results of investigations in settings as different as the American states, the Netherlands, the Philippines, Nepal, France, Columbia, Uganda, Slovakia, and India, this type of corruption maybe be at least as common as the single seller form.  Costly too.  More than half the time, the price a buyer pays in a cartelized market is 25 percent or more higher than what it would have been had there been no collusion among the sellers.

The distinction between these two types of collusion–one involving a single favored seller, the other involving a cartel of sellers–is important, because the appropriate policy response is quite different. When the procurement process is corrupted by a cartel, the standard prescription for combating corruption–transparency–is not only ineffective but self-defeating.  Continue reading →

The U4 Proxy Challenge–some quick reactions

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One of the big challenges in anticorruption work, which I suspect we will be discussing quite a bit on this blog, concerns the measurement of corruption. After all, there are a bunch of different theories about the causes and consequences of corruption, and about the best way to combat it. Testing these theories requires some way of measuring the extent of corruption (or different forms of the corruption problem). And for folks actually doing anticorruption work (donors, governments, NGOs, etc.), it would be nice to be able to assess how well programs are working. Yet all of the existing measures have significant problems.

To try to inspire some creative thinking about new ways to measure corruption, the good people at the U4 Anti-Corruption Resources Centre (affiliated with the Christian Michelsen Institute in Bergen, Norway), with the assistance of the UK’S Department for International Development (DFID), recently sponsored a competition (the “Proxy Challenge”) to come up with new proxies that would help track the progress of anticorruption reform initiatives. U4 hosted a one-day workshop last month to let the five finalists present their proxies, to choose a winner, and to promote some general discussion of the challenges of developing useful proxies for corruption in a variety of contexts. I was able to attend. I’ll try to post a some more substantive thoughts in a later post, but here are a few quick reactions. Continue reading →