IDEAS home Printed from
   My bibliography  Save this paper

Risk of over-indebtedness and behavioural factors


  • Daniela VANDONE


The aim of this paper is to analyse the link between behaviour and overindebtedness and to shed light on the effectiveness of policy measures to tackle household financial fragility. Behaviour leading to overindebtedness is often put down to social and psychological factors that reduce an individual’s capacity to evaluate the consequences of his/her consumption and borrowing decisions. Such decisions may not be rational from a classic economic point of view. In fact individuals tend, on the one hand, to overestimate their capacity to manage domestic financial resources and, on the other hand, to underestimate the possibility of being affected by negative events. As a result, these individuals systematically underestimate the risk of not being able to meet their financial commitments. Furthermore, they overestimate the immediate benefits and undervalue the future costs; such behaviour leads to the decision to purchase, using debt if necessary, regardless of the effect this choice may have on the sustainability of future debt levels. The fact that overindebtedness may be caused by individuals’ irrational behaviour is relevant and has to be taken into account in order to devise appropriate measures to prevent or manage situations of financial difficulties and to evaluate their effectiveness. The empirical literature has shown how psychological factors have an impact on the effectiveness of policies adopted to prevent and manage financial difficulties arising from overindebtedness. Studies carried out within behavioural economics have also shown that individuals have little awareness of these psychological mechanisms. Indeed, individuals in financial difficulties tend to lay the blame on exogenous factors such as job or family difficulties, which reduce income level below expected. Rarely do individuals recognise that the causes for their difficulties lie principally - or at least also - with their inability to manage money and the decisions made regarding spending and indebtedness. Furthermore, many studies have shown how deviant behaviour patterns persist even when individuals are aware of the risks they face. Individuals’ incapacity to take corrective steps despite knowing the dangers of overindebtedness may have significant implication for designing effective policies to management situations of indebtedness that may become pathological.

Suggested Citation

  • Luisa ANDERLONI & Daniela VANDONE, 2010. "Risk of over-indebtedness and behavioural factors," Departmental Working Papers 2010-25, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
  • Handle: RePEc:mil:wpdepa:2010-25

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Crook, Jonathan & Banasik, John, 2004. "Does reject inference really improve the performance of application scoring models?," Journal of Banking & Finance, Elsevier, vol. 28(4), pages 857-874, April.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Luisa ANDERLONI & Emanuele BACCHIOCCHI & Daniela VANDONE, 2011. "Household financial vulnerability: an empirical analysis," Departmental Working Papers 2011-02, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano, revised 03 Nov 2011.
    2. Elisabete Santos & Margarida Abreu, 2013. "Financial Literacy, Financial Behaviour and Individuals’ Over-indebtedness," Working Papers Department of Economics 2013/11, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    3. Luisa ANDERLONI & Daniela VANDONE, 2011. "Vulnerabilità e benessere delle famiglie italiane," Departmental Working Papers 2011-40, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    4. Michael Goedde-Menke & Carsten Erner & Michael Oberste, 2017. "Towards more sustainable debt attitudes and behaviors: the importance of basic economic skills," Journal of Business Economics, Springer, vol. 87(5), pages 645-668, July.
    5. Giovanni D’Alessio & Stefano Iezzi, 2013. "Household over-indebtedness - Definition and measurement with Italian data," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Proceedings of the Sixth IFC Conference on "Statistical issues and activities in a changing environment", Basel, 28-29 August 2012., volume 36, pages 496-517, Bank for International Settlements.
    6. Piotr Bialowolski & Dorota Weziak-Bialowolska, 2014. "The Index of Household Financial Condition, Combining Subjective and Objective Indicators: An Appraisal of Italian Households," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 118(1), pages 365-385, August.
    7. Giovanni D'Alessio & Stefano Iezzi, 2016. "Over-indebtedness in Italy: how widespread and persistent is it?," Questioni di Economia e Finanza (Occasional Papers) 319, Bank of Italy, Economic Research and International Relations Area.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhiyong Li & Xinyi Hu & Ke Li & Fanyin Zhou & Feng Shen, 2020. "Inferring the outcomes of rejected loans: an application of semisupervised clustering," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(2), pages 631-654, February.
    2. Kiefer, Nicholas M. & Larson, C. Erik, 2006. "Specification and Informational Issues in Credit Scoring," Working Papers 06-11, Cornell University, Center for Analytic Economics.
    3. Charitou, Andreas & Dionysiou, Dionysia & Lambertides, Neophytos & Trigeorgis, Lenos, 2013. "Alternative bankruptcy prediction models using option-pricing theory," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2329-2341.
    4. J Banasik & J Crook, 2010. "Reject inference in survival analysis by augmentation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(3), pages 473-485, March.
    5. Ha-Thu Nguyen, 2016. "Reject inference in application scorecards: evidence from France," EconomiX Working Papers 2016-10, University of Paris Nanterre, EconomiX.
    6. Dong-Her Shih & Ting-Wei Wu & Po-Yuan Shih & Nai-An Lu & Ming-Hung Shih, 2022. "A Framework of Global Credit-Scoring Modeling Using Outlier Detection and Machine Learning in a P2P Lending Platform," Mathematics, MDPI, vol. 10(13), pages 1-13, June.
    7. Y Kim & S Y Sohn, 2007. "Technology scoring model considering rejected applicants and effect of reject inference," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(10), pages 1341-1347, October.
    8. Bücker, Michael & van Kampen, Maarten & Krämer, Walter, 2013. "Reject inference in consumer credit scoring with nonignorable missing data," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 1040-1045.
    9. Pulina, Manuela & Paba, Antonello, 2010. "A discrete choice approach to model credit card fraud," MPRA Paper 20019, University Library of Munich, Germany.
    10. Banasik, John & Crook, Jonathan, 2007. "Reject inference, augmentation, and sample selection," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1582-1594, December.
    11. Crook, Jonathan N. & Edelman, David B. & Thomas, Lyn C., 2007. "Recent developments in consumer credit risk assessment," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1447-1465, December.
    12. Dorfleitner, G. & Just-Marx, S. & Priberny, C., 2017. "What drives the repayment of agricultural micro loans? Evidence from Nicaragua," The Quarterly Review of Economics and Finance, Elsevier, vol. 63(C), pages 89-100.
    13. J Banasik & J Crook, 2005. "Credit scoring, augmentation and lean models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(9), pages 1072-1081, September.
    14. Shen, Feng & Zhang, Xin & Wang, Run & Lan, Dao & Zhou, Wei, 2022. "Sequential optimization three-way decision model with information gain for credit default risk evaluation," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1116-1128.
    15. David J. Hand, 2018. "Statistical challenges of administrative and transaction data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(3), pages 555-605, June.
    16. Gero Szepannek, 2022. "An Overview on the Landscape of R Packages for Open Source Scorecard Modelling," Risks, MDPI, vol. 10(3), pages 1-33, March.
    17. Wu, I-Ding & Hand, David J., 2007. "Handling selection bias when choosing actions in retail credit applications," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1560-1568, December.
    18. Rogelio A. Mancisidor & Michael Kampffmeyer & Kjersti Aas & Robert Jenssen, 2019. "Deep Generative Models for Reject Inference in Credit Scoring," Papers 1904.11376,, revised Sep 2021.
    19. Mengnan Song & Jiasong Wang & Suisui Su, 2022. "Towards a Better Microcredit Decision," Papers 2209.07574,
    20. Lieli, Robert P. & White, Halbert, 2010. "The construction of empirical credit scoring rules based on maximization principles," Journal of Econometrics, Elsevier, vol. 157(1), pages 110-119, July.

    More about this item


    Households behavioural finance; overindebtedness; consumer credit;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages


    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:mil:wpdepa:2010-25. 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: . 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: DEMM Working Papers The email address of this maintainer does not seem to be valid anymore. Please ask DEMM Working Papers to update the entry or send us the correct address (email available below). General contact details of provider: .

    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.