Skip to main content
Log in

Using the Moran’s I to detect bid rigging in Brazilian procurement auctions

  • Original Paper
  • Published:
The Annals of Regional Science Aims and scope Submit manuscript

Abstract

In 2015, a supposed bid-rigging cartel that operated in the Brazilian implantable cardiac devices market was announced and public authorities began to investigate it. This paper evaluates if there is systematic correlation between the bids that are placed by competitors in the sealed phase of procurement auctions, which is a situation that may suggest coordinated and fraudulent behaviour. By applying Moran’s I statistic to the residuals of controlled bid regressions and using a novel and public database, we show that the bids that were placed by the investigated companies have positive and statistically significant autocorrelation. In addition, when we separate the data into two subperiods, namely, the period in which the cartel probably existed (2005–2015) and the period in which the cartel probably did not exist due to the conclusion of a leniency agreement (2015–2017), the Moran’s I statistic only points to autocorrelation in the first sub-sample. Our result has remained robust when we eliminate transitional periods and use alternative economic screens. Finally, we show the main practical advantages and disadvantages of the implementation of the screen based on Moran’s I statistic.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

Notes

  1. As emphasized by Harrington (2008), the objective of economic screens is to identify the markets with high probabilities of collusion. Thus, the screens do not definitively prove the existence of a cartel and, like any other statistical test, may result in false positives or false negatives. Therefore, economic screens function as a step to determine in which markets it is necessary to open an investigative process or to conduct searches and seizures.

  2. The implantable cardiac device market involves the following types of products: (I) implantable dual-chamber and unicameral defibrillator cardioverters; (II) cardiac resynchronizers; and (III) pacemakers and accessories, which include (IV) temporary and definitive endocardial electrodes, (V) sets of introducers and (VI) catheters.

  3. Only 18 of the 1351 ICD contracts that we analysed were from live auctions.

  4. An important advantage of using this row standardized matrix is that any operation with the weights can be associated as the averaging of neighbouring values (collusive bidders in our case), which facilitates the interpretation of the spatial parameters (Elhorst 2014).

  5. A single public procurement may involve several different contracts. Thus, competition occurs at the contract level.

  6. There are 366 different categories of implantable cardiac devices.

  7. The estimated value of the item or reference value is a cost estimate that the requesting public agency stipulates as a forecast of how much will be spent on the contract.

References

  • Abrantes-Metz RM, Bajari P (2012) Screens for conspiracies and their multiple applications. Compet Policy Int 8:177–193

    Google Scholar 

  • Abrantes-Metz RM, Froeb LM, Geweke J, Taylor CT (2006) A variance screen for collusion. Int J Ind Organ 24:467–486. https://doi.org/10.1016/j.ijindorg.2005.10.003

    Article  Google Scholar 

  • Abreu A (2018) Por dentro do cartel dos implantes. In: Piauí Folha

  • Aryal G, Gabrielli MF (2013) Testing for collusion in asymmetric first-price auctions. Int J Ind Organ 31:26–35. https://doi.org/10.1016/j.ijindorg.2012.10.002

    Article  Google Scholar 

  • Bajari P, Ye L (2003) Deciding between competition and collusion. Rev Econ Stat 85:971–989

    Article  Google Scholar 

  • Bergman MA, Lundberg J, Lundberg S, Stake JY (2019) Interactions across firms and bid rigging. Rev Ind Organ. https://doi.org/10.1007/s11151-018-09676-0

    Article  Google Scholar 

  • Boyer M, Kotchoni R (2015) How much do Cartel overcharge? Rev Ind Organ 47:119–153. https://doi.org/10.1007/s11151-015-9472-1

    Article  Google Scholar 

  • CADE (2017) CADE’s General Superintendence initiates administrative proceeding to investigate a cartel in the market of orthoses, prostheses and special medical supplies. In: Assessor. Comun. Soc

  • Elhorst JP (2014) Spatial Econometrics: from cross-sectional data to spatial panels, 1st edn. Springer, Berlin

    Book  Google Scholar 

  • Erutku C (2012) Testing post-cartel pricing during litigation. Econ Lett 116:339–342. https://doi.org/10.1016/j.econlet.2012.03.033

    Article  Google Scholar 

  • Günster A, Carree M, Dijk M van (2011) Do Cartels undermine economic efficiency? In: The American Economic Association

  • Harrington JE (2008) Detecting cartels. In: Buccirossi P (ed) Handbook of antitrust economics. MIT Press, London

    Google Scholar 

  • Imhof D (2017) Simple statistical screens to detect bid rigging. Faculty of Economics and Social Sciences, University of Fribourg (Switzerland)

  • Imhof D, Karagök Y, Rutz S (2018) Screening for bid rigging-does it work? J Compet Law Econ 14:235–261. https://doi.org/10.1093/JOCLEC/NHY006

    Article  Google Scholar 

  • Ishii R (2009) Favor exchange in collusion: empirical study of repeated procurement auctions in Japan. Int J Ind Organ 27:137–144. https://doi.org/10.1016/j.ijindorg.2008.05.006

    Article  Google Scholar 

  • Jakobsson M (2007) Bid rigging in Swedish procurement auctions. Department of Economics, Uppsala University, Sweden

  • LeSage JP, Pace K (2009) Introduction to spatial econometrics, 1st edn. Taylor & Francis Group, Boca Raton

    Book  Google Scholar 

  • Lundberg J (2017) On cartel detection and Moran’s I. Lett Spat Resour Sci 10:129–139. https://doi.org/10.1007/s12076-016-0176-4

    Article  Google Scholar 

  • Mattos C (2014) Modalidades de licitação e cartéis no Brasil. Consult Legis da Câmara dos Deputados, pp 1–17

  • Moran PA (1948) The interpretation of statistical maps. J R Stat Soc Ser B 10:243–251

    Google Scholar 

  • Ragazzo C, Silva RM (2006) Aspectos econômicos e jurídicos sobre cartéis na revenda de combustíveis: uma agenda para investigações

  • Vasconcelos S, Vasconcelos C (2005) Investigações e obtenção de provas de cartel: porque e como observa o paralelismo de conduta. Ensaios FEE 26:1–20

    Google Scholar 

Download references

Acknowledgements

Funding was provided by Escola Superior do Ministério Público da União (ESMPU) (Grant No. 01129/2017).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ricardo Carvalho de Andrade Lima.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

de Andrade Lima, R.C., Resende, G.M. Using the Moran’s I to detect bid rigging in Brazilian procurement auctions. Ann Reg Sci 66, 237–254 (2021). https://doi.org/10.1007/s00168-020-01018-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00168-020-01018-x

JEL Classification

Navigation