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On modeling Korean corporate bankruptcy using macroeconomic variables
Journal of the Korean Data & Information Science Society 2019;30:1037-50
Published online September 30, 2019;  https://doi.org/10.7465/jkdi.2019.30.5.1037
© 2019 Korean Data and Information Science Society.

Nuri Gwon1 · Young Min Kim2 · Kwangshin Choi3

12Department of Statistics, Kyungpook National University
3Macroprudential Supervision Department, Financial Supervisory Service
Correspondence to: Assistant professor, Department of Statistics, Kyungpook National University, Daegu 41566, Korea. E-mail: kymmyself@knu.ac.krkymmyself@knu.ac.kr

This research was supported by the National Research Foundation of Korea (NRF-2016R1D1A1B03932212).
Received June 10, 2019; Revised August 27, 2019; Accepted August 27, 2019.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
This manuscript developed corporate bankruptcy prediction models considering market, accounting and macroeconomic variables because listed companies in Korea strongly rely on global economic change. We observed companies from Jan. 1st 2001 to May 31st 2016. If a company is merged during the following period or can not be observed with any reasons, we decided that the end observing time was the last observed date. Since some variables have missing observations, the multiple imputation and Lasso variable selection methods are utilized to construct the bankruptcy prediction models. The goal of this research is to consider macroeconomic variables and apply missing data analysis techniques to construct corporate bankruptcy prediction models. The proposed models including market, accounting and macroeconomic variables in this manuscript have overd 95% of Hit-Ratio.
Keywords : Bankruptcy prediction, Lasso, logistic regression, macroeconomic variables, multiple imputation.