International Journal of Science and Society (IJSOC)
Vol 2 No 4 (2020): International Journal of Science and Society (IJSOC)

Analysis of the Effect of Governance and Research and Development on Probability of Default

Ani Nuraini (Economics Doctoral Program Students, Faculty of Economics and Business, Trisakti University, Jakarta, Indonesia)
Farah Margaretha Leon (Faculty of Economics and Business, Trisakti University, Jakarta, Indonesia)
Bahtiar Usman (Faculty of Economics and Business, Trisakti University, Jakarta, Indonesia)



Article Info

Publish Date
02 Nov 2020

Abstract

Research on the probability of default is always very interesting because it is related to the goals of companies that want to live on, this study aims to examine and analyze which variables are important in this study consisting of the audit committee and managerial ownership who are members of governance, as well as the R & D variables. In influencing the probability of default either directly or indirectly by using the mediating variable Current Ratio estimated results (CRh), to predict the probability of default. This study uses Multiple Discriminant Analysis (MDA) in determining the value of the default probability, while the estimation analysis uses two-stage regression. The regression estimation results conclude that the governance variable on the audit committee has no direct effect on the probability of default, while the CRh mediation becomes significant. The managerial ownership variable which is part of the governance variable has a significant effect both directly and indirectly through CRh mediation, as well as the R&D variable which also has a significant effect on the probability of default either directly or indirectly. This study produces a model in which CRh as a mediator can signal the probability of default on non-financial variables such as governance and R&D. The results of this study contribute to early detection of the probability of default of any non-financial variables that affect both governance and R&D. This model was developed to anticipate the occurrence of bankruptcy by detecting the probability of default by using non-financial variables with CRh as mediation which is supported by model tests with Hosmer-Lemeshow and ROC.

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