IDEAS home Printed from https://ideas.repec.org/a/spr/eurase/v11y2021i2d10.1007_s40822-020-00163-0.html
   My bibliography  Save this article

COVID-19: stress-testing non-financial companies: a macroprudential perspective. The experience of Poland

Author

Listed:
  • Natalia Nehrebecka

    (Warsaw University
    National Bank of Poland)

Abstract

The main purpose of this article is to detail and supply a stress-testing framework at the individual level that investigates the impact of COVID-19 scenarios on non-financial firms’ probability of default as regards domestic and foreign-currency debt (a so-called new micro stress-test). The test addresses both the uniform and the asymmetrical transmission of shocks, in relation to sizes of firms and sectors of their activity. To allow for the running of micro stress-tests of this kind, a general model was constructed using a two-step approach comprising a microeconomic model and a macroeconomic module. Accompanying empirical analysis was based on individual data from different sources (relating to the years 2007–2020), i.e. prudential reporting, business registration, financial and behavioral data and balances of payments. In line with the factor of company size, the quality of loan portfolios is shown to deteriorate on the balance sheets of banks in all segments in the case of a negative scenario (for large and medium-sized enterprises the probability of default increases 1.5-fold, for small ones over threefold). While almost all industries will experience the impact of COVID-19, sections being hit particularly hard will involve services that, due to the ban on gatherings of people and the recommendation to avoid crowds, will lose most of their revenue and will fail to make up for this loss in the future.

Suggested Citation

  • Natalia Nehrebecka, 2021. "COVID-19: stress-testing non-financial companies: a macroprudential perspective. The experience of Poland," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(2), pages 283-319, June.
    • Handle: RePEc:spr:eurase:v:11:y:2021:i:2:d:10.1007_s40822-020-00163-0
    DOI: 10.1007/s40822-020-00163-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40822-020-00163-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s40822-020-00163-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Natalia Nehrebecka, 2016. "Approach to the assessment of credit risk for non-financial corporations. Evidence from Poland," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Combining micro and macro data for financial stability analysis, volume 41, Bank for International Settlements.
    2. King, Gary & Zeng, Langche, 2001. "Logistic Regression in Rare Events Data," Political Analysis, Cambridge University Press, vol. 9(2), pages 137-163, January.
    3. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    4. Patrick Sevestre & Laszlo Matyas, 2008. "The Econometrics of Panel Data," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00279977, HAL.
    5. Virolainen, Kimmo, 2004. "Macro stress testing with a macroeconomic credit risk model for Finland," Research Discussion Papers 18/2004, Bank of Finland.
    6. Susanne Emmer & Dirk Tasche, 2003. "Calculating credit risk capital charges with the one-factor model," Papers cond-mat/0302402, arXiv.org, revised Jan 2005.
    7. Mr. Paul Louis Ceriel Hilbers & Mr. Matthew T Jones & Mr. Graham L Slack, 2004. "Stress Testing Financial Systems: What to Do When the Governor Calls," IMF Working Papers 2004/127, International Monetary Fund.
    8. repec:zbw:bofrdp:2004_018 is not listed on IDEAS
    9. László Mátyás & Patrick Sevestre (ed.), 2008. "The Econometrics of Panel Data," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75892-1, February.
    10. Dirk Tasche, 2003. "A traffic lights approach to PD validation," Papers cond-mat/0305038, arXiv.org.
    11. Mr. Jorge A Chan-Lau & Cheng Hoon Lim & Jose Daniel Rodríguez-Delgado & Mr. Bennett W Sutton & Melesse Tashu, 2017. "Bottom-Up Default Analysis of Corporate Solvency Risk: An Application to Latin America," IMF Working Papers 2017/133, International Monetary Fund.
    12. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    13. Petr Jakubik & Christian Schmieder, 2008. "Stress Testing Credit Risk: Is the Czech Republic Different from Germany?," Working Papers 2008/9, Czech National Bank.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. repec:ers:journl:v:xxiv:y:2021:i:special3:p:719-736 is not listed on IDEAS
    2. Natalia Nehrebecka, 2021. "Internal Credit Risk Models and Digital Transformation: What to Prepare for? An Application to Poland," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 2), pages 719-736.
    3. Bekirova, Olga & Zubarev, Andrey, 2022. "Эконометрический Анализ Факторов Банкротств Российских Компаний В Обрабатывающем Секторе [Econometric Analysis of Bankruptcy Factors for Russian Companies in the Manufacturing Industry]," MPRA Paper 114969, University Library of Munich, Germany.
    4. Bekirova, Olga & Zubarev, Andrey, 2022. "Макроэкономические Факторы Банкротства Компаний Обрабатывающей Отрасли В Российской Федерации [Macroeconomic Factors of Corporate Bankruptcy in the Manufacturing Sector in the Russian Federation]," MPRA Paper 114968, University Library of Munich, Germany.
    5. Natalia Nehrebecka, 2021. "Climate Risk with Particular Emphasis on the Relationship with Credit-Risk Assessment: What We Learn from Poland," Energies, MDPI, vol. 14(23), pages 1-14, December.
    6. repec:ers:journl:v:xxiv:y:2021:i:4:p:977-996 is not listed on IDEAS
    7. Beata Bieszk-Stolorz & Iwona Markowicz, 2021. "Risk of Decline in Share Prices of Energy and Fuel Sector on the Warsaw Stock Exchange During the Two Waves of the COVID-19 Pandemic," European Research Studies Journal, European Research Studies Journal, vol. 0(4 - Part ), pages 977-996.
    8. Olga A. Bekirova & Andrey V. Zubarev, 2022. "Оценка Вероятности Банкротства Компаний Обрабатывающей Промышленности С Учетом Макроэкономической Конъюнктуры," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 12, pages 18-27, December.
    9. Jessica Birkholz & Jarina Kühn & Mariia Shkolnykova, 2022. "Exploration or Exploitation: Innovation Behavior of SMEs and Large Firms during the COVID-19 Crisis," Bremen Papers on Economics & Innovation 2203, University of Bremen, Faculty of Business Studies and Economics.
    10. Olga A. Bekirova & Andrey V. Zubarev, 2022. "Estimating the Bankruptcy Probability of Manufacturing Companies Considering Macroeconomic Conditions [Оценка Вероятности Банкротства Компаний Обрабатывающей Промышленности С Учетом Макроэкономичес," Russian Economic Development, Gaidar Institute for Economic Policy, issue 12, pages 18-27, December.

    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. Arturas Juodis, 2013. "Cointegration Testing in Panel VAR Models Under Partial Identification and Spatial Dependence," UvA-Econometrics Working Papers 13-08, Universiteit van Amsterdam, Dept. of Econometrics.
    2. Alexander Klemm & Stefan Parys, 2012. "Empirical evidence on the effects of tax incentives," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 19(3), pages 393-423, June.
    3. Patrizia Ordine & Giuseppe Rose, 2008. "Local Banks Efficiency and Employment," LABOUR, CEIS, vol. 22(3), pages 469-493, September.
    4. Francesco Venturini, 2009. "The long-run impact of ICT," Empirical Economics, Springer, vol. 37(3), pages 497-515, December.
    5. Celine Bonnefond, 2014. "Growth Dynamics And Conditional Convergence Among Chinese Provinces: A Panel Data Investigation Using System Gmm Estimator," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 39(4), pages 1-25, December.
    6. Niklas Potrafke, 2012. "Political cycles and economic performance in OECD countries: empirical evidence from 1951–2006," Public Choice, Springer, vol. 150(1), pages 155-179, January.
    7. Jochen Hartwig, 2009. "A panel Granger-causality test of endogenous vs. exogenous growth," KOF Working papers 09-231, KOF Swiss Economic Institute, ETH Zurich.
    8. Canarella, Giorgio & Miller, Stephen M. & Nourayi, Mahmoud M., 2013. "Firm profitability: Mean-reverting or random-walk behavior?," Journal of Economics and Business, Elsevier, vol. 66(C), pages 76-97.
    9. Laszlo Balazsi & Laszlo Matyas & Tom Wansbeek, 2018. "The estimation of multidimensional fixed effects panel data models," Econometric Reviews, Taylor & Francis Journals, vol. 37(3), pages 212-227, March.
    10. Joseph P. Byrne & Alexandros Kontonikas & Alberto Montagnoli, 2013. "International Evidence on the New Keynesian Phillips Curve Using Aggregate and Disaggregate Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(5), pages 913-932, August.
    11. Bertoldi, Paolo & Mosconi, Rocco, 2020. "Do energy efficiency policies save energy? A new approach based on energy policy indicators (in the EU Member States)," Energy Policy, Elsevier, vol. 139(C).
    12. Mohamed Douch & Binyam Solomon, 2016. "A dynamic panel analysis using SIPRI’s extended military expenditure data: The case of Middle Power nations," Economics of Peace and Security Journal, EPS Publishing, vol. 11(2), pages 45-49, October.
    13. José Durán-Cabré & Alejandro Esteller-Moré & Luca Salvadori, 2015. "Empirical evidence on horizontal competition in tax enforcement," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 22(5), pages 834-860, October.
    14. George Papadopoulos & Savas Papadopoulos & Thomas Sager, 2016. "Credit risk stress testing for EU15 banks: a model combination approach," Working Papers 203, Bank of Greece.
    15. Biørn, Erik, 2012. "The Measurement Error Problem in Dynamic Panel Data Analysis: Modeling and GMM Estimation," Memorandum 02/2012, Oslo University, Department of Economics.
    16. Costantini, Valeria & Martini, Chiara, 2010. "The causality between energy consumption and economic growth: A multi-sectoral analysis using non-stationary cointegrated panel data," Energy Economics, Elsevier, vol. 32(3), pages 591-603, May.
    17. Potrafke, Niklas, 2010. "The growth of public health expenditures in OECD countries: Do government ideology and electoral motives matter?," Journal of Health Economics, Elsevier, vol. 29(6), pages 797-810, December.
    18. Jan Babecky & Kamil Galuscak & Lubomir Lizal, 2011. "Firm-Level Labour Demand: Adjustment in Good Times and During the Crisis," Working Papers 2011/15, Czech National Bank.
    19. Jochen Hartwig, 2008. "Has Health Capital Formation Cured 'Baumol's Disease'? - Panel Granger Causality Evidence for OECD Countries," KOF Working papers 08-206, KOF Swiss Economic Institute, ETH Zurich.
    20. Badi H. Baltagi, 2021. "Dynamic Panel Data Models," Springer Texts in Business and Economics, in: Econometric Analysis of Panel Data, edition 6, chapter 0, pages 187-228, Springer.

    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:spr:eurase:v:11:y:2021:i:2:d:10.1007_s40822-020-00163-0. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.