IDEAS home Printed from
   My bibliography  Save this paper

Determinantes dos Deságios Nos Leilões de Transmissão de Energia Elétrica no Brasil Entre 1999 e 2010


  • Katia Rocha
  • Ajax Moreira
  • Rodrigo Limp


O estudo analisa os determinantes dos altos deságios no setor de transmissão de energia elétrica no Brasil entre 1999 e 2010 através de um modelo econométrico baseado no modelo de Roy e estimador de Heckman (1979) que considera a heterogeneidade entre os lances vencedores e perdedores, e a endogeneidade desta clivagem. A partir do conjunto total de lances, explicita-se a heterogeneidade entre os grupos e corrige-se o respectivo viés devido à endogeneidade desta classificação. O objeto de pesquisa se justifica uma vez que estudos que se focam apenas nos lances vencedores e que ignoram a correção em virtude da endogeneidade da seleção do grupo vencedor podem conduzir a conclusões impróprias. Conclui-se que: i) lances realizados por estatais (líderes ou isoladas) têm 50% de probabilidade de vencer o lote; ii) na maioria dos lances vencedores, as estatais têm entrado em consórcios com grupos privados nacionais; iii) a probabilidade de vencer os leilões está relacionada a ganhos de escala devido à existência prévia de investimentos na região do lote a ser leiloado; iv) os altos deságios são em parte explicados pelo menor risco Brasil e maior rentabilidade do empreendimento, sendo mais importantes na determinação dos deságios dos lances vencedores que dos perdedores, provavelmente devido ao seu melhor conjunto de atributos e informações; v) o grau de concorrência aumenta os deságios com efeito não linear; e vi) a média dos deságios dos lances classificados como destoantes (36%) é praticamente o dobro da média dos demais deságios (23%), sendo praticados principalmente pela estatal líder que apresentar o maior número (57%) de lances destoantes com deságios médios da ordem de 40%, indicando maior propensão à característica conhecida como "maldição do vencedor". This study investigates the determinants of the great difference between winning bids and reserve prices in the transmission electricity sector in Brazil between 1999- 2010, through an econometric approach based on Heckman (1979) that considers the heterogeneous among the winner`s and loser`s bids, and the endogeneity of that selection. Given the whole data of winner`s and loser`s bids, the heterogeneity of the groups is modeled and endogeneity bias classification is corrected. The object of i. The versions in English of the abstracts of this series have not been edited by Ipea`s editorial department. As versões em língua inglesa das sinopses (abstracts) desta coleção não são objeto de revisão pelo Editorial do Ipea. this research is justified since studies that focus just on winning bids or ignore the endogeneity of the winning group selection could lead to misleading conclusions. Results can be summarize as follows: i) bids made by state public companies have 50% probability to win the auction; ii) the majority of winning bids come from state public companies in partnership to private national groups; iii) winning probability is related to previous investments made in the bid area due to economies of scale; iv) the great difference between reserve price and winning bids are partly explained by the improvements in Brazil country risk and the profitability of the project, being more important for winners than losers probably due to the better set of information and effectiveness of the winning group; v) the number of competitors decreases the bids but with non linear effects; and vi) outlier bids made by public companies represent 57% of total outliers with an average bid of 40% less than the reserve price, indicating the winner`s curse characteristic.

Suggested Citation

  • Katia Rocha & Ajax Moreira & Rodrigo Limp, 2012. "Determinantes dos Deságios Nos Leilões de Transmissão de Energia Elétrica no Brasil Entre 1999 e 2010," Discussion Papers 1703, Instituto de Pesquisa Econômica Aplicada - IPEA.
  • Handle: RePEc:ipe:ipetds:1703

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Alex Anas & Richard Arnott & Kenneth A. Small, 1998. "Urban Spatial Structure," Journal of Economic Literature, American Economic Association, vol. 36(3), pages 1426-1464, September.
    2. Daniel P. McMillen, 2004. "Employment Densities, Spatial Autocorrelation, and Subcenters in Large Metropolitan Areas," Journal of Regional Science, Wiley Blackwell, vol. 44(2), pages 225-244.
    3. Daniel Griffith & David Wong, 2007. "Modeling population density across major US cities: a polycentric spatial regression approach," Journal of Geographical Systems, Springer, vol. 9(1), pages 53-75, April.
    4. Tim Schwanen & Frans M. Dieleman & Martin Dijst, 2004. "The Impact of Metropolitan Structure on Commute Behavior in the Netherlands: A Multilevel Approach," Growth and Change, Wiley Blackwell, vol. 35(3), pages 304-333.
    5. Giuliano, Genevieve & Small, Kenneth A., 1991. "Subcenters in the Los Angeles region," Regional Science and Urban Economics, Elsevier, vol. 21(2), pages 163-182, July.
    6. repec:brs:ecchap:02 is not listed on IDEAS
    7. H. Kelejian, Harry & Prucha, Ingmar R., 2001. "On the asymptotic distribution of the Moran I test statistic with applications," Journal of Econometrics, Elsevier, vol. 104(2), pages 219-257, September.
    8. David Levinson & Ajay Kumar, 1997. "Density and the Journey to Work," Working Papers 199701, University of Minnesota: Nexus Research Group.
    9. Anderson, John E., 1982. "Cubic-spline urban-density functions," Journal of Urban Economics, Elsevier, vol. 12(2), pages 155-167, September.
    10. Catherine Baumont & Cem Ertur & Julie Le Gallo, 2003. "Spatial Analysis Of Employment And Population Density: The Case Of The Agglomeration Of Dijon, 1999," Urban/Regional 0310003, EconWPA.
    11. Fujita, Masahisa & Ogawa, Hideaki, 1982. "Multiple equilibria and structural transition of non-monocentric urban configurations," Regional Science and Urban Economics, Elsevier, vol. 12(2), pages 161-196, May.
    12. Nicholas Crafts & Abay Mulatu, 2005. "What explains the location of industry in Britain, 1871–1931?," Journal of Economic Geography, Oxford University Press, vol. 5(4), pages 499-518, August.
    13. McMillen, Daniel P., 2001. "Nonparametric Employment Subcenter Identification," Journal of Urban Economics, Elsevier, vol. 50(3), pages 448-473, November.
    14. K.H. Midelfart & H.G. Overman & S.J. Redding & A.J. Venables, 2000. "The location of European industry," European Economy - Economic Papers 2008 - 2015 142, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    Full references (including those not matched with items on IDEAS)

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ipe:ipetds:1703. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Fabio Schiavinatto). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.