What drives the performance of different bank-ownership types in Indonesia? The pre- and post-GFC analysis

Abstract

PurposeThe Indonesian banks play crucial roles in the economy, especially because of less developed bond and stock markets. It has undergone drastic changes in bank-ownership composition over time. This paper aims to analyze the impact of bank-specific characteristics on the performance of different bank-ownership types in Indonesia to determine whether their profitability drivers differ.Design/methodology/approachFixed-effect panel data regression is applied to 1,649 bank-year observations (97 banks throughout 2003–2019). It encompasses the pre- and post-global financial crisis (GFC) period.FindingsThe findings show that age, liquidity, equity and credit risk are significant determinants of bank performance. The significance of these effects differs for each bank-ownership type and show changes between the pre-GFC and post-GFC periods.Research limitations/implicationsNotwithstanding the merit of this paper, the results are not without limitations. This paper only focuses on one country. Furthermore, the prominence of banks relative to bond and stock markets with consideration of the GDP of countries may result in different findingsPractical implicationsThese findings provide the owners and managers of banks with information that can be applied to compare and assess own bank drivers and performance to enhance their own efficiency. The findings also inform bank authorities and regulators about differences in performance drivers that could be considered in changes to policies aimed at improving the performance of different bank-ownership types.Originality/valueThis paper is a pioneer study that focuses on the drivers of bank performance for different ownership types during the pre- and post-GFC periods in a country where the financial market is overall small and bank credits dominate capital supply.

The dynamic relationships of credit risk, profitability, and capital: Evidence from Indonesia

“…This can be explained by the distinct borrower profile of state banks compared to private and foreign banks, as state banks primarily focus on providing financing for infrastructure projects. These findings align with previous studies conducted by Naili and Lahrichi (2022) and Atahau and Cronje (2022). The third robustness test (Table 10) aimed to examine the impact of the COVID-19 pandemic on credit risk by dividing the sample data into different periods.…”

“…First, we evaluated the robustness of our results under different model settings by running an extension model with constant and trend parameters. Second, based on literature Atahau and Cronje (2022) we categorized the sample data into three groups based on bank ownership in Indonesia, including private banks (Private), foreign subsidiary banks (Foreign), and state-owned banks (State). This test was done to assess the robustness of our findings across various types of bank ownership.…”

“…Moreover, in all models, the CD test yielded significant statistics, indicating the presence of cross-sectional dependence. For the second robustness test (Table 9) in this study, we conducted a dynamic regression analysis on the robustness test by dividing bank ownership into the three following parts: private owned banks (PRIVATE), foreign subsidiary banks in Indonesia (FOREIGN), and government banks (STATE) (Atahau & Cronje, 2022).…”

Effect of Ownership on the Performance of Licensed Commercial Banks in Sri Lanka

“…Using three indicators enables comparing performance among different ownership types in three performance dimensions because the literature suggests that the performance difference is sensitive to the dimension used. As illustrated in Table 1, these indicators are frequently used to measure bank performance in the literature (Abraham, 2013;Atahau & Cronje, 2022;Cornett et al, 2010).…”

Faktor Penentu Profitabilitas Bank Tercatat di Indonesia: Pendekatan dengan Regresi Kuantil

“…Aset bermasalah tidak menghasilkan pendapatan, memerlukan prosedur khusus dalam menentukan kelayakan kredit. Kualitas Aset sebagai penentu signifikan kinerja bank (Atahau & Cronje, 2022). Proxy yang paling banyak digunakan untuk kualitas aset adalah kredit bermasalah (NPL).…”