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Macroeconomic Modelling of a Firm's Default

Author

Listed:
  • Michal Řičař
Abstract
Enormous development of firm valuation from many aspects can be seen in the recent period. One of the main fields is scoring, which provides a probability verdict about the future development of a firm: its probability of default. This article focuses on introducing macroeconomic modelling using VEC models to predict the future level of default in the Czech economy. Our results have proven a general connection between corporate defaults and the macroeconomic condition of the economy, which is going through a convergence process. The specific findings are new and have not been observed yet. A connection between the GDP and defaults revealed a positive relationship, which is probably a consequence of the convergence process, a development of the economy in many new fields. We have also found a long-term equilibrium among unemployment, loans, price of oil and defaults. We have revealed a higher level of defaults can be expected in 2013, which is connected with the economic contraction in the prediction period.

Suggested Citation

  • Michal Řičař, 2014. "Macroeconomic Modelling of a Firm's Default," Acta Oeconomica Pragensia, Prague University of Economics and Business, vol. 2014(1), pages 27-40.
    • Handle: RePEc:prg:jnlaop:v:2014:y:2014:i:1:id:424:p:27-40
    DOI: 10.18267/j.aop.424
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    References listed on IDEAS

    as
    1. Pesaran, M. Hashem & Schuermann, Til & Treutler, Bjorn-Jakob & Weiner, Scott M., 2006. "Macroeconomic Dynamics and Credit Risk: A Global Perspective," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1211-1261, August.
    2. Nickell, Pamela & Perraudin, William & Varotto, Simone, 2000. "Stability of rating transitions," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 203-227, January.
    3. Danny Miller & Peter H. Friesen, 1984. "A Longitudinal Study of the Corporate Life Cycle," Management Science, INFORMS, vol. 30(10), pages 1161-1183, October.
    4. Bangia, Anil & Diebold, Francis X. & Kronimus, Andre & Schagen, Christian & Schuermann, Til, 2002. "Ratings migration and the business cycle, with application to credit portfolio stress testing," Journal of Banking & Finance, Elsevier, vol. 26(2-3), pages 445-474, March.
    5. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    6. Gebhard Kirchgässner & Jürgen Wolters & Uwe Hassler, 2013. "Introduction to Modern Time Series Analysis," Springer Texts in Business and Economics, Springer, edition 2, number 978-3-642-33436-8, December.
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    Cited by:

    1. Latzer, Hélène, 2018. "A Schumpeterian theory of multi-quality firms," Journal of Economic Theory, Elsevier, vol. 175(C), pages 766-802.
    2. Enea Baselgia & Reto Foellmi, 2022. "Inequality and growth: a review on a great open debate in economics," WIDER Working Paper Series wp-2022-5, World Institute for Development Economic Research (UNU-WIDER).
    3. Sun, Tianyu & Tian, Liu, 2023. "No pain, no gain: implications in consumption and economic growth," MPRA Paper 118081, University Library of Munich, Germany.
    4. Gilles Saint-Paul, 2023. "The educated class and the fragility of consumer society," PSE Working Papers halshs-04129252, HAL.
    5. Sun, Tianyu & Tian, Liu, 2023. "No pain, no gain: implications in consumption and economic growth," SocArXiv 95fdm, Center for Open Science.

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    More about this item

    Keywords

    scoring; econometric modelling; VEC; corporate default;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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