IDEAS home Printed from https://ideas.repec.org/a/alu/journl/v2y2012i14p18.html
   My bibliography  Save this article

Study Regarding The Influence Of The Unemployment Rate Over Non-Performing Loans In Romania Using The Correlation Indicator

Author

Listed:
  • Iulia Iuga
  • Ruxandra Lazea

Abstract

In this paper it is studied the influence of unemployment rate on non-performing loans in Romania. The following issues are presented: the definition of nonperforming loans, the criteria used by Romania in the definition of nonperforming loans (NPL), Romanian legislation that regulates nonperforming loans, the causes leading to nonperforming loans and the national regulates regarding unemployment. The paper contains also graphic representation of the analysis: 1) nonperforming loans in the world, 2) credits in Romania by the five risk classes for years 2006- 2011; 3) nonperforming loans based on the unemployment rate in Romania. Finally, we established the correlation between unemployment rate and nonperforming loans in Romania, with the usage of the "Pearson" correlation coefficient.

Suggested Citation

  • Iulia Iuga & Ruxandra Lazea, 2012. "Study Regarding The Influence Of The Unemployment Rate Over Non-Performing Loans In Romania Using The Correlation Indicator," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 2(14), pages 1-18.
  • Handle: RePEc:alu:journl:v:2:y:2012:i:14:p:18
    as

    Download full text from publisher

    File URL: http://oeconomica.uab.ro/upload/lucrari/1420122/18.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rainer Haselmann & Paul Wachtel, 2007. "Risk Taking by Banks in the Transition Countries," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 49(3), pages 411-429, September.
    2. Robert B. Avery & Paul S. Calem & Glenn B. Canner, 2004. "Consumer credit scoring: do situational circumstances matter?," BIS Working Papers 146, Bank for International Settlements.
    3. Socol Adela & Iuga Iulia, 2010. "Study Of Correlation Between Average Interest Rate And Non-Performing Loans In The Romanian Banking System During 2006- February 2010," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(2), pages 777-782, December.
    4. de Haas, Ralph & van Lelyveld, Iman, 2006. "Foreign banks and credit stability in Central and Eastern Europe. A panel data analysis," Journal of Banking & Finance, Elsevier, vol. 30(7), pages 1927-1952, July.
    5. Avery, Robert B. & Calem, Paul S. & Canner, Glenn B., 2004. "Consumer credit scoring: Do situational circumstances matter?," Journal of Banking & Finance, Elsevier, vol. 28(4), pages 835-856, April.
    6. Carling, Kenneth & Jacobson, Tor & Linde, Jesper & Roszbach, Kasper, 2007. "Corporate credit risk modeling and the macroeconomy," Journal of Banking & Finance, Elsevier, vol. 31(3), pages 845-868, March.
    7. Foos, Daniel & Norden, Lars & Weber, Martin, 2010. "Loan growth and riskiness of banks," Journal of Banking & Finance, Elsevier, vol. 34(12), pages 2929-2940, December.
    8. Ali, Asghar & Daly, Kevin, 2010. "Macroeconomic determinants of credit risk: Recent evidence from a cross country study," International Review of Financial Analysis, Elsevier, vol. 19(3), pages 165-171, June.
    Full references (including those not matched with items on IDEAS)

    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. Škrabić Perić, Blanka & Rimac Smiljanić, Ana & Aljinović, Zdravka, 2018. "Credit risk of subsidiaries of foreign banks in CEE countries: Impacts of the parent bank and home country economic environment," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 49-69.
    2. Imad Jabbouri & Maryem Naili, 2020. "Determinants of Nonperforming Loans in Emerging Markets: Evidence from the MENA Region," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 22(04), pages 1-33, February.
    3. Paul Wachtel & Iftekhar Hasan & John Bonin, 2008. "Banking in Transition Countries," Working Papers 08-22, New York University, Leonard N. Stern School of Business, Department of Economics.
    4. Iulia Iuga, 2009. "The Assessment Procedure Of The Operational Risk Events," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 1(11), pages 1-49.
    5. Iulia Iuga, 2008. "Analysis On The Romanian Banking Legislation And The Banks Probability Of Default," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 1(10), pages 1-43.
    6. K Rajaratnam & P Beling & G Overstreet, 2010. "Scoring decisions in the context of economic uncertainty," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(3), pages 421-429, March.
    7. L N Allen & L C Rose, 2006. "Financial survival analysis of defaulted debtors," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(6), pages 630-636, June.
    8. Pejman Abedifar & Philip Molyneux & Amine Tarazi, 2013. "Risk in Islamic Banking," Review of Finance, European Finance Association, vol. 17(6), pages 2035-2096.
    9. Singh, Ramendra Pratap & Singh, Ramendra & Mishra, Prashant, 2021. "Does managing customer accounts receivable impact customer relationships, and sales performance? An empirical investigation," Journal of Retailing and Consumer Services, Elsevier, vol. 60(C).
    10. Geetesh Bhardwaj & Rajdeep Sengupta, 2011. "Credit scoring and loan default," Working Papers 2011-040, Federal Reserve Bank of St. Louis.
    11. Anastasios Petropoulos & Vasilis Siakoulis & Evaggelos Stavroulakis & Aristotelis Klamargias, 2019. "A robust machine learning approach for credit risk analysis of large loan level datasets using deep learning and extreme gradient boosting," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Are post-crisis statistical initiatives completed?, volume 49, Bank for International Settlements.
    12. Anastasios Petropoulos & Vasilis Siakoulis & Evaggelos Stavroulakis & Aristotelis Klamargias, 2019. "A robust machine learning approach for credit risk analysis of large loan-level datasets using deep learning and extreme gradient boosting," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
    13. Lei Shi & Neil Allan & John Evans & Yin Yun, 2018. "Significance of Controllable and Uncontrollable Drivers in Credit Defaults," Economic Papers, The Economic Society of Australia, vol. 37(1), pages 30-41, March.
    14. Chomsisengphet, Souphala & Elul, Ronel, 2006. "Bankruptcy exemptions, credit history, and the mortgage market," Journal of Urban Economics, Elsevier, vol. 59(1), pages 171-188, January.
    15. Evžen Kocenda & Martin Vojtek, 2011. "Default Predictors in Retail Credit Scoring: Evidence from Czech Banking Data," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 47(6), pages 80-98, November.
    16. Irving Fisher Committee, 2019. "The use of big data analytics and artificial intelligence in central banking," IFC Bulletins, Bank for International Settlements, number 50.
    17. Gush, Karon & Laurie, Heather & Scott, James, 2015. "Job loss and social capital: the role of family, friends and wider support networks," ISER Working Paper Series 2015-07, Institute for Social and Economic Research.
    18. Paulo V. Carvalho & José D. Curto & Rodrigo Primor, 2022. "Macroeconomic determinants of credit risk: Evidence from the Eurozone," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2054-2072, April.
    19. Cuccaro, Laura Muriel & Sangiácomo, Máximo & Tumini, Lucía, 2022. "El crédito formal en la Argentina: un análisis con perspectiva de género," Documentos de Proyectos 47813, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
    20. Chen, Minghua & Wu, Ji & Jeon, Bang Nam & Wang, Rui, 2017. "Do foreign banks take more risk? Evidence from emerging economies," Journal of Banking & Finance, Elsevier, vol. 82(C), pages 20-39.

    More about this item

    Keywords

    nonperforming loans; unemployment rate; analysis; correlation coefficient;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory

    Statistics

    Access and download statistics

    Corrections

    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:alu:journl:v:2:y:2012:i:14:p:18. See general information about how to correct material in RePEc.

    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: Dan-Constantin Danuletiu (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. RePEc uses bibliographic data supplied by the respective publishers.