Long-term Examination of Bank Crashes Using Panel Logistic Regression: Turkish Banks Failure Case

Erdogan, Bi̇rsen Eygi

doi:10.5539/ijsp.v5n3p42

Cited by 8 publications

(4 citation statements)

References 19 publications

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“…Therefore, a logit regression model estimation method was used, which assumes that the error term is a linear probability model of a logistic distribution rather than a normal distribution (Khan & Shaw, 2011). Compared to the cross‐sectional logit regression model, the panel logit regression model can resolve the retro‐causality issue because it can control for the unobserved characteristics of the study subject, using various medical expenses as an independent variable and the debt burden appearing between T‐1 and T as a dependent variable (Erdogan, 2016). Fixed‐effect panel models and random‐effect panel models exist—unlike the former, the latter obtains estimates of stable characteristics (Larsen & Merlo, 2005).…”

Section: Methodsmentioning

confidence: 99%

Effects of various medical expense characteristics on the occurrence of household debt burden

Choi

Yoo

2022

Int J Consumer Studies

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Medical expenses can aggravate the debt burden of households and in severe cases also lead to household bankruptcy. Using longitudinal data, this study identified various characteristics of medical expenses that could lead to household debt burden. In particular, we investigated whether household debt burden varied according to the beneficiary of medical expenses based on mental accounting. Data of 5007 households (number of observations = 34,071) from 2010 (13th wave) to 2018 (21st wave) surveys of the Korean Labor Panel were analysed using descriptive statistics and a random effect logistic regression model. Descriptive statistics showed that 8.3% of households began to feel debt burden during the survey period. The results of the random effects model revealed that the size of medical expense and debt impacted the probability of debt burden. Although medical expense support for parents or children living separately did not affect the household debt burden significantly, medical expense support for the spouse's parents increased the debt burden probability. The results showed that the household conducted mental accounting and it was driven by the subject with whom the household had a relationship. These results imply the necessity of expanding the medical insurance coverage to reduce the burden of medical expenses, and policies to supplement the gap or decrease in income caused by the occurrence of a medical event.

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Section: Methodsmentioning

confidence: 99%

Effects of various medical expense characteristics on the occurrence of household debt burden

Choi

Yoo

2022

Int J Consumer Studies

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“…The study showed that bank profitability per employee, ability of bank to repay its debt, leverage ratio and the banking operations has a negative impact on the bank`s failure. Erdogan (2016) attempted to develop an early warning system for the banking sector in Turkey using panel data during the period 2002 to 2012. The study used random panel logistic regression versus pooled logistic regression.…”

Section: Literature Reviewmentioning

confidence: 99%

Early Warning of Bank Failure in the Arab Region: A Logit Regression Approach

Obeid

2022

AJEER

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The global financial crisis of 2008 taught the biggest lesson of anticipating a financial crisis. The current study aimed to highlight the importance of central banks to build early warning systems to reduce the costs of resolution procedures of weak banks. The data was obtained from published annual reports and balance sheets of 60 commercial banks in the Arab region for the period 2000-2010. Using the logistic regression model to predict the performance of banks or anticipating the possibility of bank failure and build an early warning system, the study identified a few financial indicators such as Capital Adequacy Ratio (CAR); Liquidity (LIQ); Cost to Income Ratio CIR; Return On. Assets (ROA); and Non-Performing Loans (NPL). The impact of the GDP variable on bank`s failure was also determined to capture economic risks. The results showed that financial soundness indicators (FSI) can be used efficiently to predict bank failure, that the variables of ROA and CAR had the greatest impact on the probability of the bank’s survival, while no statistical significance was seen for the GDP variable. The paper recommends the importance of the financial stability and banking supervision departments to build early warning systems. The study would provide useful insights to both household and corporate sectors to look for early warning signs that predict the performance of the banking sector in the Arab countries. The FSIs suggested in the study would also play a prominent role in predicting the success or failure of banks in the Arab region.

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“…For example, in Pakistan, adopting the e-banking service had a significant positive impact on ROE which meant the adoption of e-banking reduced the cost of bank operations and increased customer satisfaction and bank profitability (Rauf & Ismatullaevich, 2013). Erdogan (2016) presented panel logistic regression models containing different financial ratios (e.g. loan due ratio and cost to income ratio) to…”

Section: Bank Performancementioning

confidence: 99%

“…Therefore, banks can compare their current and historical performance in investments and earnings (MacDonld & Koch, 2006). Similar to Bailey et al (2011), Erdogan (2016) and Rauf & Ismatullaevich (2013), this research uses both ROA and ROE as dependent variables.…”

Section: = ≤ 15%mentioning

confidence: 99%

Comparative bank financial risk management models in fintechs and challenger banks

Zhao¹

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Risk management in banking operations is a popular topic among researchers in the fields of management and banking. Due to developments in technology, research on financial technology has also become a hot topic. Banks and financial technology companies (fintechs) need to learn what risks impact their operations and how to manage these risks effectively. The aim of this study is to investigate the relationship between risk management and bank performance, compare it between traditional banks and challenger banks/fintechs, and make suggestions on how to improve performance by analysing historical data. This thesis adopts a mixed-method approach, estimating risk variables and their impacts on bank performance through panel data regression models (random-effects and generalised method of moments) and conducting case studies to contribute to knowledge in theory and practice. This research investigates the relationship between five main types of risks (credit risk, market risk, liquidity and capital risk, reputational risk, and operational risk) and bank performance measured by three variables (ROA, ROE and EPS). This study confirms the importance of risk management in bank performance. For example, credit risk variables show negative impacts on all banks, which suggests that reducing credit risks could increase bank performance. Market risk variables are complex with both positive and negative effects on bank performance. Thus, banks should keep market risk at a balanced level to receive better performance. Moreover, bank performance could be increased by increasing liquidity, capital and reputation as well as reducing debt, operational issues and costs. The contributions of this research include the enhancement of literature on the relationship between bank performance and risk management. Also, this research creates a greater awareness of risk management for challenger banks and fintechs. Moreover, it fills gaps in the literature by comparing results for traditional banks with those for challenger banks and fintechs. The results of this research offer new insights into risk management for both traditional banks and challenger banks and fintechs for iii academics and have the potential to assist traditional banks and challenger banks and fintechs in managing their risks and improving their efficiency in practice.

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Long-term Examination of Bank Crashes Using Panel Logistic Regression: Turkish Banks Failure Case

Cited by 8 publications

References 19 publications

Effects of various medical expense characteristics on the occurrence of household debt burden

Effects of various medical expense characteristics on the occurrence of household debt burden

Early Warning of Bank Failure in the Arab Region: A Logit Regression Approach

Comparative bank financial risk management models in fintechs and challenger banks

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