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Technical efficiency as a factor of Russian industrial companies’ risks of financial distress

Author

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  • Mogilat , Anastasia

    (Central Bank of the Russian Federation, Moscow, Russian Federation)

  • Ipatova, Irina

    (National Research University Higher School of Economics; The Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russian Federation)

Abstract

The paper proposes a two-step methodology of investigation the impact of technical efficiency (estimated by stochastic frontier model) on Russian industrial companies’ risks of financial distress (estimated by bankruptcy prediction model — see King, Zeng, 2001). We show that growth of technical efficiency has robust, significant and large impact on the expected probability of financial distress. We also extend the «benchmark» specification of bankruptcy prediction model by including dummy variables for structural breaks in bankruptcy dynamics associated with significant changes in Bankruptcy law.

Suggested Citation

  • Mogilat , Anastasia & Ipatova, Irina, 2016. "Technical efficiency as a factor of Russian industrial companies’ risks of financial distress," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 42, pages 05-29.
  • Handle: RePEc:ris:apltrx:0289
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    References listed on IDEAS

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    1. Becchetti, Leonardo & Sierra, Jaime, 2003. "Bankruptcy risk and productive efficiency in manufacturing firms," Journal of Banking & Finance, Elsevier, vol. 27(11), pages 2099-2120, November.
    2. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    3. Fiordelisi, Franco & Mare, Davide Salvatore, 2013. "Probability of default and efficiency in cooperative banking," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 30-45.
    4. Koetter, Michael & Porath, Daniel, 2007. "Efficient, profitable and safe banking: an oxymoron? Evidence from a panel VAR approach," Discussion Paper Series 2: Banking and Financial Studies 2007,02, Deutsche Bundesbank.
    5. Afanasiev, Mikhail, 2006. "A Model of the Production Potential with Managed Factors of Inefficiency," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 4(4), pages 74-89.
    6. Shchetynin, Yevhenii, 2015. "Effects of imports on technical efficiency in Russian food industry," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 37(1), pages 27-42.
    7. Koutsomanoli-Filippaki, Anastasia & Mamatzakis, Emmanuel, 2009. "Performance and Merton-type default risk of listed banks in the EU: A panel VAR approach," Journal of Banking & Finance, Elsevier, vol. 33(11), pages 2050-2061, November.
    8. Малахов Дмитрий Игоревич & Пильник Николай Петрович, 2013. "Методы Оценки Показателя Эффективности В Моделях Стохастической Производственной Границы," Higher School of Economics Economic Journal Экономический журнал Высшей школы экономики, CyberLeninka;Федеральное государственное автономное образовательное учреждение высшего образования «Национальный исследовательский университет «Высшая школа экономики», vol. 17(4), pages 660-686.
    9. Subal Kumbhakar & Anatoly Peresetsky, 2013. "Cost efficiency of Kazakhstan and Russian banks: results from competing panel data models-super-1," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 6(1), pages 88-113, March.
    10. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    11. Aivazian, Sergei & Afanasiev, Mikhail, 2009. "Estimation of the Economic Efficiency of a Shift to the Achievable Production Potential," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 15(3), pages 43-55.
    12. du Jardin, Philippe, 2010. "Predicting bankruptcy using neural networks and other classification methods: the influence of variable selection techniques on model accuracy," MPRA Paper 44375, University Library of Munich, Germany.
    13. Li, Xiaofei & Escalante, Cesar L. & Epperson, James E. & Gunter, Lewell F., 2012. "Technical Efficiency and the Probability of Bank Failure among Agricultural and Non-Agricultural Banks," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124591, Agricultural and Applied Economics Association.
    14. Демешев Борис Борисович & Тихонова Анна Сергеевна, 2014. "Прогнозирование Банкротства Российских Компаний: Межотраслевое Сравнение," Higher School of Economics Economic Journal Экономический журнал Высшей школы экономики, CyberLeninka;Федеральное государственное автономное образовательное учреждение высшего образования «Национальный исследовательский университет «Высшая школа экономики», vol. 18(3), pages 359-386.
    15. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    16. Heshmati, Almas & Kumbhakar, Subal C. & Hjalmarsson, Lennart, 1995. "Efficiency of the Swedish pork industry: A farm level study using rotating panel data 1976-1988," European Journal of Operational Research, Elsevier, vol. 80(3), pages 519-533, February.
    17. Salnikov, V. & Mogilat, A. & Maslov, I., 2012. "Stress Testing for Russian Real Sector: First Approach," Journal of the New Economic Association, New Economic Association, vol. 16(4), pages 46-70.
    18. Shchetynin, Yevhenii & Nazrullaeva, Eugenia, 2012. "Effects of fixed capital investments on technical efficiency in food industry," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 28(4), pages 63-84.
    19. Altman, Edward I. & Haldeman, Robert G. & Narayanan, P., 1977. "ZETATM analysis A new model to identify bankruptcy risk of corporations," Journal of Banking & Finance, Elsevier, vol. 1(1), pages 29-54, June.
    20. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    21. Harlan D. Platt & Marjorie B. Platt, 2008. "Financial Distress Comparison Across Three Global Regions," JRFM, MDPI, vol. 1(1), pages 1-34, December.
    22. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    23. Ipatova, Irina & Peresetsky, Аnatoly, 2013. "Technical efficiency of Russian plastic and rubber production firms," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 32(4), pages 71-92.
    24. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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    Cited by:

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    3. Aliya Alimhanova & Andrey Vazhdaev & Artur Mitsel & Anatoly Sidorov, 2022. "Dynamic Model of Enterprise Revenue Management Based on the SFA Model," Mathematics, MDPI, vol. 11(1), pages 1-13, December.

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    More about this item

    Keywords

    technical efficiency; bankruptcy prediction model; Russian industrial companies; SFA; logit analysis.;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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