Internal Factors Affecting Commercial Bank Lending: Symmetric and Asymmetric Effects of Macro-Level Data Evidence

Arintoko, Arintoko

doi:10.26905/jkdp.v25i3.5760

Cited by 8 publications

(14 citation statements)

References 26 publications

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“…Bank capital, apart from being a reserve to cover losses, can also be used for financing, provided that the CAR should not be less than the minimum requirement of 8%. These results contradict Arintoko [8], who studied conventional banks and Azizah et al [9], who conclude a positive effect of CAR on financing. However, it is supported by Pratikno & Ratnasari [16], Sutrisno [18]; and Ali et al [5], who show that there is no effect of CAR on financing, even though the effect is negative.…”

Section: Hypothesis Testing Resultscontrasting

confidence: 67%

“…These results contradict the theory and the results of previous studies, which show a negative effect between OEIR and financing [4,5,9]. However, Arintoko [8] supports these results as his study shows no effect of OEIR on loans in conventional banks.…”

Section: Hypothesis Testing Resultscontrasting

confidence: 62%

“…These results are in line with Riyadi et al [4], Hisan et al [11], Sudarsono et al [14], Azizah et al [9], and Pratikno & Ratnasari [16], who reveal a significant and negative effect of NPF on financing. In conventional banks, NPL also affects loans [8,17]. FDR has a significance value of 0.588 for PMF and 0.442 for PSF, greater than 0.05, meaning that FDR has no effect on the two financing schemes.…”

Section: Hypothesis Testing Resultsmentioning

confidence: 99%

“…The amount of bank capital can also be used by banks to increase financing, so that CAR can have a positive effect on financing. Azizah, Inayati, & Hapsari [9] find a positive influence between CAR and financing, and Arintoko [8] also finds the effect of CAR on loans in conventional banks. Thus, the formulation of the hypotheses:…”

Section: Financing Scheme and Capitalmentioning

confidence: 99%

“…Thus, the CAR will have a positive effect on the financing provided. Arintoko [8] at conventional banks and Azizah, Inayati, & Hapsari [9] at Islamic banks reveal a positive influence between CAR and financing. Bank profits also affect financing; the higher the bank's profits, the more funds can be channeled as financing.…”

Section: Introductionmentioning

confidence: 99%

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Financing Scheme and Determinant Factors

Sutrisno¹

2022

Advances in Economics, Business and Management Research

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This study aims to examine the factors that influence the financing scheme of Islamic Rural Banks (IRBs) in Indonesia. The financing scheme consists of profit margin financing (PMF) and profit-sharing financing (PSF). Factors thought to influence the financing scheme are non-performing financing (NPF), financing to deposit ratio (FDR), capital adequacy ratio (CAR), return on assets (ROA), operating to income ratio (OEIR), and company size (Size). The population in this study was 163 IRBs in Indonesia with a sample of 100 IRBs. The observation period was 4 years, with quarterly data. Hypothesis testing applied multiple regression. The results show that the factors influencing the financing scheme between PMF and PSF are the same, namely, NPF and Size have a significant negative effect, while FDR, CAR, ROA and OEIR have no effect. One variable is OEIR; if the significance level is 10%, then OEIR has a significant and negative effect on the profit-sharing financing scheme, but the profit-margin financing scheme has no effect.

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Section: Hypothesis Testing Resultscontrasting

confidence: 67%

Section: Hypothesis Testing Resultscontrasting

confidence: 62%

Section: Hypothesis Testing Resultsmentioning

confidence: 99%

Section: Financing Scheme and Capitalmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Financing Scheme and Determinant Factors

Sutrisno¹

2022

Advances in Economics, Business and Management Research

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The Asymmetric Effects of Global Energy and Food Prices, Exchange Rate Dynamics, and Monetary Policy Conduct on Inflation in Indonesia

Arintoko,

Badriah,

Kadarwati

2024

ECO

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This research analyzes the asymmetric effects of global energy and food prices and monetary variables, including the exchange rate and money supply, on the consumer price index (CPI). The model is intended to differentiate the influence of increases and decreases in global energy and food prices, exchange rates, and money supply which cause inflation/deflation from changes in the CPI. The analysis uses the Nonlinear Autoregressive Distributed Lag (NARDL) and Quantile Regression models on data from January 2001 to February 2023. The study results show that the decline in global energy prices significantly reduces the CPI in the long run. Energy subsidies allow increases in international energy prices not to increase the CPI significantly. Meanwhile, the increase in global food prices causes inflation in the short run. The exchange rate has the most significant effect on the CPI. Depreciation of the rupiah significantly increases the CPI, which means it causes inflation, while appreciation of the rupiah does not have a significant effect. Finally, increases and decreases in the money supply have a considerable positive effect on the CPI, which confirms the logic of the monetarist view that inflation is a monetary phenomenon. Efforts to reduce dependence on imports of food and energy commodities are the key to reducing risks when importing energy and food due to rupiah depreciation. Efforts to consistently stabilize the exchange rate can support controlling and stabilizing import prices. Energy and food subsidy policies are vital in controlling inflation due to increased world energy and food prices.

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The Impact of Macroeconomic Variables on Credit Risk: Evidence Regarding Sustainable Lending in ASEAN Countries

Arintoko,

Badriah,

Rahajuni

et al. 2024

IJSDP

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This research examines the hypotheses that macroeconomic variables and environmental factors impact credit risk. This study focuses on the relationship between macroeconomics, environmental issues, and credit risk in ASEAN countries. This study applies a panel Autoregressive Distributed Lag (ARDL) model to data from the World Bank for the 2008-2019 period. The variables studied include non-performing loans (NPLs), Gross Domestic Product (GDP) growth, interest rates, inflation, and carbon emissions. The research results show that environmental factors do not affect NPLs, while macroeconomic factors do. GDP growth and inflation reduce NPLs while rising credit interest rates increase NPLs. The results imply credit risk is not considered sustainable lending. Credit risk does not consider environmental degradation as measured by increases in carbon emissions. From cross-country evidence, the effect of environmental degradation on credit quality is not found in all countries. Indeed, if environmental quality is considered, environmental degradation will be detrimental to operational and financial performance, especially for heavily polluting firms. However, poor ecological quality will harm operational and financial performance. In addition, business entities within the framework of sustainable loans have collateral consequences for business activities aimed at reducing pollution, which has implications for increasing costs. For decision-makers, both regulators and banks, in the future, banking credit distribution must seriously consider implementing sustainable lending through green credit policy schemes. Green credit schemes need to involve collaboration with banks and incorporate environmental factors into the loan portfolio. Empirically implementing green credit can improve bank financial performance and firm environmental, social, and governance (ESG) performance.

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Internal Factors Affecting Commercial Bank Lending: Symmetric and Asymmetric Effects of Macro-Level Data Evidence

Cited by 8 publications

References 26 publications

Financing Scheme and Determinant Factors

Financing Scheme and Determinant Factors

The Asymmetric Effects of Global Energy and Food Prices, Exchange Rate Dynamics, and Monetary Policy Conduct on Inflation in Indonesia

The Impact of Macroeconomic Variables on Credit Risk: Evidence Regarding Sustainable Lending in ASEAN Countries

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