Finding an accurate measure of corruption is a problem that has puzzled anti-corruption researchers for some years now. In the framework of the ANTICORRP project, researchers are currently trying to produce a new generation of indicators which allow comparisons across countries and time while being more concrete and specific than the first generation which are based on perception aggregates (for instance the Corruption Perception Index).
This new European paper takes an important step in that direction by using a technique known in audit studies as data mining. Under this method, researchers look for deviations from an ordinary, normal pattern to identify corrupt behaviour. In this paper, Fazekas et al.[i] use a newly created database of public procurement procedures in Central and Eastern European countries to reach three objectives:
- Create an instrument based on data mining to assess procurement risk which can be used to estimate across countries and time (to see, for instance, if reforms are working);
- Compare corruption risks of EU funded and national public procurement as well as estimate the value of EU funds allocated in a particularistic way; and
- Make recommendations on how to monitor EU funds more effectively.
Fazekas et al produced a series of studies [ii] developing new corruption measures, of which “Are EU funds a corruption risk? The impact of EU funds on grand corruption in Central and Eastern Europe” is only the first to have major findings. These are as follows:
- The authors prove that public market domination by certain companies or bids won by single bidders are significantly related to irregularities in the procurement process. They furthermore infer that an early sanction of such irregularities would be able to curb corruption. Using a database of over 120 000 public procurement procedures in the Czech Republic, Hungary, and Slovakia they look for anomalies on two sides of each procedure: 1) at entry, unusual processes (e.g. an exceptionally short bidding period) and 2) at exit, unusual outcomes (e.g. the winning bid had no competition, or the winning company frequently wins bids, both indicating favouritism). Using inferential statistics they manage to link the former to the latter.
- Fazekas et al. use their analysis of procurement process anomalies to calculate a corruption risk index (CRI) which expresses the probability of particularistic allocation of public procurement contracts. Particularistic resource allocation implies that prior explicit rules of spending are bent in order to benefit a closed circle while excluding others. Comparing CRI of EU funded and similar nationally funded procurement contracts, they assess the effectiveness of EU institutions to curb corruption. They find that EU funds represent higher corruption risks in Czech Republic (3%) and Hungary (8%) than comparable national spending, while in Slovakia EU funds are less risky than national funds (13%). Although Slovakia has a much higher level of corruption than the two other countries to start with.
- In order to better gauge corruption risks in EU funds, the authors calculate the expected value of public resources allocated in a particularistic way by combining the probability of particularism and the value of procurement spending. They estimate that throughout 2009-2012 particularistic resource allocation affected 0.94% of GDP in Czech Republic, 1.15% of GDP in Hungary, and 1.61% of GDP in Slovakia. In total, they argue that the funds affected by particularism may reach up to 1.2% of their combined GDP which is an impressive figure especially when compared to the total amount of EU funds allocated to these countries: 3.3% of their combined GDP.
- Despite coming with theoretically better legal protection attached, EU funds proved a double liability for public procurement as presented in this paper. First, because as the first ANTICORRP policy report, “Controlling Corruption in Europe” already warned, EU funds stimulate discretionary public spending (as compared to more predictable rule based spending, for instance on pensions). Second, because they seem to be targeted more by rent seekers resulting in a higher risk of funds being captured by a ‘favourite’ company.
Estimated value of national and EU funded public procurement disbursed in a particularistic way, by country, % of 2009-2012 total GDP
Note: In order to arrive at an approximate total public procurement spending figure, spending values based on announcements in the National Public Procurement Bulletins were approximated to total public procurement spending estimated by the OECD based on the system of national accounts (OECD, 2013). As the total public procurement spending figures are upper bound estimations and the proportion of EU funding within public procurement spending not reported in the National Public Procurement Bulletin is unknown, figures in the graph may be overestimations.
Given the high risks, what can the EU do to better protect its investment and ensure that funds are disbursed in a more competitive and transparent manner? The ANTICORRP policy team offers the following recommendations:
- Introduce an EU-wide, real-time monitoring mechanism of EU funds spending designed to detect systematic fraud and corruption in public procurement using data mining techniques.
- Increase national civil society capability for monitoring governance and controlling corruption at both national and local levels especially with regard to EU funds.
- Consider re-allocating EU funding from discretionary investment projects which typically constitute high corruption risk, towards non-discretionary spending such as education.
[i] Mihály Fazekas, Jana Chvalkovska, Jiri Skuhrovec, István Janos Tóth, and Lawrence Peter King, (2013), Are EU funds a corruption risk? The impact of EU funds on grand corruption in Central and Eastern Europe. Published as through the Corruption Research Centre Budapest as CRCB-WP/2013:03 and through the European Research Centre for Anti-Corruption and State-Building as WP No.39
[ii] Key publications are: Fazekas, M., Tóth, I. J., & King, L. P. (2013). Anatomy of grand corruption: A composite corruption risk index based on objective data. CRCB-WP/2013:02, Budapest: Corruption Research Centre.
Fazekas, M., Tóth, I. J., & King, L. P. (2013c). Corruption manual for beginners: Inventory of elementary “corruption techniques” in public procurement using the case of Hungary. CRCB-WP/2013:01, Corruption Research Centre, Budapest.
Fazekas, Mihály, István János Tóth, and Lawrence Peter King. 2013c. “Hidden Depths.The Case of Hungary.” In Controlling Corruption in Europe vol. 1, ed. Alina Mungiu-Pippidi. Berlin: Barbara Budrich Publishers, 74–82. ERCAS WP 37.