This study aims to identify banking vulnerabilities and analyze the factors that influence them. The tool used to identify bank vulnerabilities uses modification crisis and default index (C&D Index) while hypothesis testing uses logit regression. Commercial banks in Indonesia from 2008 to 2018 was taken as sample. As a result, in 2008 and 2013 were the most vulnerable conditions for banks in Indonesia. The reason most banks have been identified as vulnerable is due to decreased profits, increased liabilities in foreign currencies and increased Non Performing Loan (NPL). Logit regression test show that banking fragility is negatively related to capital, liquid assets, and financial assets. ------------------------------ Penelitian ini bertujuan untuk mengidentifikasi kerentanan perbankan dan menguji faktor yang diduga memengaruhinya. Kerentanan bank diidentifikasi menggunakan modifikasi crisis and default index (C&D Index), sedangkan pengujian hipotesis menggunakan regresi logit. Sampel penelitian ini adalah 27 bank komersil di Indonesia periode 2008 sampai 2018. Hasilnya, tahun 2008 dan 2013 adalah kondisi yang paling rentan bagi perbankan di Indonesia. Penyebab sebagian besar bank teridentifikasi rentan adalah karena penurunan profit, peningkatan pinjaman dalam mata uang asing, dan peningkatan Non Performing Loan (NPL). Hasil uji regresi logit menunjukkan kerentanan perbankan di Indonesia berhubungan negatif dengan permodalan bank, aset likuid bank, dan aset keuangan bank.
Penelitian ini bertujuan untuk mengidentifikasi kerentanan perbankan dan menguji faktor yang diduga memengaruhinya. Kerentanan bank diidentifikasi menggunakan modifikasi crisis and default index (C&D Index), sedangkan pengujian hipotesis menggunakan regresi logit. Sampel penelitian ini adalah 27 bank komersil di Indonesia periode 2008 sampai 2018. Hasilnya, tahun 2008 dan 2013 adalah kondisi yang paling rentan bagi perbankan di Indonesia. Penyebab sebagian besar bank teridentifikasi rentan adalah karena penurunan profit, peningkatan pinjaman dalam mata uang asing, dan peningkatan Non Performing Loan (NPL). Hasil uji regresi logit menunjukkan kerentanan perbankan di Indonesia berhubungan negatif dengan permodalan bank, aset likuid bank, dan aset keuangan bank.
Banking sector has close relationship with economic growth. At the end of 2015 condition of global economic has influence from China slowdown, fall down crude oil price, and rasie interest rate by the fed. These had bad impact for developing counties like Indonesia. In the fact financials crisis in Asia at 1998, sub prime mortage crisis in USA at 2008, and goverment debt crisis in Greece at 2011 made many bank in Indonesia collapse. From past crisis banking sector must have more attention to avoid sistemic crisis. This study aim to make prediction banking crisis models from three group of variable. There are internal bank, macroeconomic, and global economic. This research use Crisis and Default index to measure and identificate probably crisis in indivual bank. All of bank were listed in Indonesian Stock Exchange at 2009 until 2014 has taken as sample. This research chose logit model as a probability crisis models and use logistic regression to testing hypothesis. The result from internal factor with non performing loans, labor cost ratio, and loan to deposits ratio was positive relationship with probability banking crisis. Futhermore net interest margin and interest income to total aset was negative influence for banking crisis. Then from macroeconomic and global economic these are domestic inflation and USA real interest rate was positive influence for banking crisis. After that M2 to reserved ratio, USA growth, and oil price was negative impact to make banking crisis in Indonesia
This research aims to identified the banking fragility using index and test the factors that influence the banking fragility. This study uses banks in Indonesia which listed in JKSE for the period 2009 to 2014 as samples. The result is that bank internal factors proxy by non-performing loans, labor cost ratios and loans to deposits ratios have a positive relationship with the banking crisis, while net interest margins and interest income have a negative relationship with the banking crisis. Macroeconomic and global economic variables proxy by domestic inflation and US interest rates have a positive effect on the banking crisis while M2 growth, and GDP growth in the USA have a negative effect on the possibility of a banking crisis in Indonesia.
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