Corruption risk indicators in public procurement. What we have, should have, and what to do with them Mihály Fazekas University of Cambridge and Government Transparency Institute [email protected]2017.04.12. Using indicators to inform policy and measure progress on anti- corruption, DG HOME, 31/3/2017 This project has received funding from the European Union’s Horizon 2020 research and innovation Programme under grant agreement No 645852
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Corruption risk indicators in public procurement....Corruption Risks: Investigating the impact of bureaucratic meritocracy on public procurement processes. Journal of Politics, 79(1),
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Corruption risk indicators in
public procurement. What we have, should have, and what to do with them
2. Crucial role in development (e.g. capital accumulation)
3. Indicates the broader quality of institutions
4. Very corrupt (at least perceivet to be...)
5. And of course: LOTS OF DATA
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I. Public procurement data
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The DIGIWHIST data template
• Public procurement data
• Company data: registry, financials, ownership
• Political officeholder data
• Treasury accounts of public organisations
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Where is that data? Minimum threshold for publication supplies and services (EUR), 2015
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Where is that data?
Covering the full
tender cycle
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Where is that data?
Knowing the
actors
Administrative error: missing information
Average % missing information (13 mandatory fields), 2009-2015, TED data
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Where is that data?
0% 5% 10% 15% 20% 25% 30% 35%
SK
IS
RO
HU
CZ
LV
PL
EE
SI
HR
LT
CY
AT
GR
BG
BE
EU AVG.
IT
DE
DK
UK
NL
ES
PT
FR
LU
CH
FI
SE
II. Proxying corruption
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Corruption definition
In public procurement, the aim of corruption is to steer the contract to the favored bidder without detection. This is done in a number of ways, including:
– Avoiding competition through, e.g., unjustified sole sourcing or direct contract awards.
– Favoring a certain bidder by tailoring specifications, sharing inside information, etc.
See: World Bank Integrity Presidency (2009) Fraud and Corruption. Awareness Handbook, World Bank, Washington DC. pp. 7.
Note the difference from legal definitions
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Conceptualizing public
procurement corruption indicators
April 12, 2017 12
Contracting
body Supplier Contract
Particularistic tie
Tendering Risk Indicators
(TRI)
Supplier Risk
Indicators (SRI)
Contracting Body
Risk Indicators
(CBRI) Political
Connections
Indicators (PCI)
Source: Fazekas, M., & Kocsis, G. (2015). Uncovering High-Level Corruption: Cross-National Corruption Proxies Using Government Contracting Data. GTI-WP/2015:02, Government Transparency Institute, Budapest.
Corruption proxy building approach
1. Clear definition of corruption
2. Dictionary of corruption technologies
3. Statistical modelling of corrupt contracting
4. Indicator validation: triangulation
Corruption risks are only approximated! 2017.04.12. 13
(BAD) Alternative approaches
• Naive summation of expert-suggested red
flags
• Arbitrary cut-points
• Fixation on selected indicators
• Others which might work: PCA, SEM,
machine learning
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Selected examples
1. Single bidding on competitive markets
2. Swings in company market shares when
governments change
3. Supplier anomalies
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2017.04.12.
Modelling corrupt
contracting: single bidding
16
Distribution of contracts according to
the advertisement period
Probability of single bid submitted for contracts
compared with the market norm of 48+ days
Source: EU’s Tenders
Electronic Daily (TED),
Portugal , 2009-2014
Single bidding
Tight deadline
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Macro validity:
Corruption perceptions & single bidding
Single bidding correlates with subjective indicators of corruption
Source: Fazekas, M., & Kocsis, G. (2015). Uncovering High-Level Corruption: Cross-National Corruption Proxies Using Government Contracting Data. GTI-WP/2015:02, Government Transparency Institute, Budapest.
Micro validity:
Number of bidders & prices • Price savings by the number of bidders
• 543,705 contracts, EU27, 2009-2014
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19
Surprise success
goes together with
procurement red
flags (CRI)
Politically driven company success: Hungary a paradigmatic case
Companies lose/win
surprisingly when
government changes
Hungary, 2009-2012
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20
Few companies
lose/win surprisingly
when government
changes
UK, 2009-2012
Surprise success
sometimes goes
together with
procurement red flags
(CRI)
Politically driven company success: UK exception to the rule
Source: Fazekas, M., Lukács, P. A., & Tóth, I. J. (2015). The Political Economy of Grand Corruption in Public Procurement in the Construction Sector of Hungary. In A. Mungiu-Pippidi (Ed.), Government Favouritism in Europe. The Anticorruption Report 3 (pp. 53–68). Berlin: Barbara Budrich Publishers.
Limitations
• Data, data, data!
• You get what you measure: no general
indicator of corruption!
• Only lower bound estimate: sophisticated
actors can avoid detection (e.g. cartels)
• Variance-driven: corruption is deviation
from a norm
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III. Some conclusions
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Objective proxies are better in tracking trends
• One example: Hungary 2009-2012 – ‚Something has changed’
– WGI CoC reports NO CHANGE (improvement not sign.)
Differences in the average number of bids submitted between non-restricted
and restricted procedures, OECD-Europe, 2013, c.value>58k eur
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Beware of the context use of restricted procedures
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Single bidder
ratio, TED, EU,
2009-2014
Monitoring can invalidate indicators Single bidding & organised criminality
For more information check out
digiwhist.eu/resources
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Furher readings
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Charron, N., Dahlström, C., Fazekas, M., & Lapuente, V. (2017). Careers, Connections, and Corruption Risks: Investigating the impact of bureaucratic meritocracy on public procurement processes. Journal of Politics, 79(1), p. 89–103.
Fazekas, M. & Cingolani, L. (2017), Breaking the cycle? How (not) to use political finance regulations to counter public procurement corruption. Slavonic & East European Review, 95(1)
Fazekas, M. & Tóth, B. (2017), Infrastructure for whom? Corruption risks in infrastructure provision across Europe. In Hammerschmid, G, Kostka, G. & Wegrich, K. (Eds.), The Governance Report 2016 . Oxford University Press, ch 11.
Fazekas, M., & Tóth, I. J. (2017). Corruption in EU Funds? Europe-wide evidence on the corruption effect of EU-funded public contracting. In J. Bachtler, P. Berkowitz, S. Hardy, & T. Muravska (Eds.), EU Cohesion Policy. Reassessing performance and direction. London: Routledge, ch. 13.
Rasmus Broms, Carl Dahlström and Mihaly Fazekas (2017). Entrenched parties and control of public procurement in Sweden. University of Gothenburg-Quality of Government Institute, manuscript
Fazekas, M. and Tóth, I. J. (2016). From corruption to state capture: A new analytical framework with empirical applications from Hungary. Political Research Quarterly, 69(2), p. 320-334
Fazekas, M., Cingolani, L., & Tóth, B. (2016). A comprehensive review of objective corruption proxies in public procurement: risky actors, transactions, and vehicles of rent extraction: GTI-WP/2016:03. Government Transparency Institute. Budapest.
Fazekas, M., Tóth, I. J., & King, L. P. (2016). Anatomy of grand corruption: A composite corruption risk index based on objective data. Eu. Journal of Criminal Policy and Research, 22(3), 369–397.
Fazekas, M. (2015). The Cost of One-Party Councils: Lack of Electoral Accountability and Public Procurement Corruption. London: Electoral Reform Society.
Fazekas, M., & Kocsis, G. (2015). Uncovering High-Level Corruption: Cross-National Corruption Proxies Using Government Contracting Data. GTI-WP/2015:02, Government Transparency Institute, Budapest.
Fazekas, M., Lukács, P. A., & Tóth, I. J. (2015). The Political Economy of Grand Corruption in Public Procurement in the Construction Sector of Hungary. In A. Mungiu-Pippidi (Ed.), Government Favouritism in Europe The Anticorruption Report 3 (pp. 53–68). Berlin: Barbara Budrich Publishers.
Fazekas, M. (2015). The Cost of One-Party Councils: Lack of Electoral Accountability and Public Procurement Corruption. London: Electoral Reform Society.