Modeling of Credit Institution License Withdrawal Based on Panel Data

Authors

  • Domashova D.V. National Research Nuclear University MEPhI (Moscow Engineering Physics Institute), Kashirskoe shosse 31, Moscow, 115409
  • Kripak Е.М. Orenburg State University, Orenburg
  • Pisarchik Е.Е. National Research Nuclear University MEPhI (Moscow Engineering Physics Institute), Kashirskoe shosse 31, Moscow, 115409
  • Ulanova Zh.U. National Research Nuclear University MEPhI (Moscow Engineering Physics Institute), Kashirskoe shosse 31, Moscow, 115409

DOI:

https://doi.org/10.18502/kss.v3i2.1558

Abstract

The research paper involves the construction of panel data binary response models to forecast the probability of a credit institution's license withdrawal based on its financial performance, including the construction of logit and probit models using various sets of source data offers a technique for shaping a general model.

 

Keywords: credit institutions, panel data, binary response models, license withdrawal

References

Central Bank of the Russian Federation URL: https://www.cbr.ru/

Banki.ru info portal URL: http://www.banki.ru/

Federal State Statistics Service of the Russian Federation URL: http://www.gks.ru/

J.R. Magnus, Econometrics. Introduction Course: Manual. 6

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Published

2018-02-15

How to Cite

D.V., D., Е.М. K., Е.Е. P., & Zh.U., U. (2018). Modeling of Credit Institution License Withdrawal Based on Panel Data. KnE Social Sciences, 3(2), 309–317. https://doi.org/10.18502/kss.v3i2.1558

Issue

Vol. 3 No. 2 (2018): III Network AML/CFT Institute International Scientific and Research Conference "FinTech and RegTech"

Section

Articles