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Academic literature on the topic 'Bank Efficiency. JEL Classification: E44'
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Journal articles on the topic "Bank Efficiency. JEL Classification: E44"
1
Zeb, Shumaila, and Abdul Sattar . "Financial Regulations, Profit Efficiency, and Financial Soundness: Empirical Evidence from Commercial Banks of Pakistan." Pakistan Development Review 56, no. 2 (2017): 85–103. http://dx.doi.org/10.30541/v56i2pp.85-103.
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The purpose of this paper is threefold. First, it measures profit efficiency and financial stability of commercial banks of Pakistan. Second, it empirically estimates the effect of the already implemented financial regulations on the profit efficiency and financial stability of banks. Third, it examines the differential effect of financial regulations on profitability and financial soundness across bank size. To carry out the empirical analysis, a balanced bank-level panel data covering the period 2008-2014 is used. To gauge the profit efficiency of commercial banks, Data Envelopment Analysis (DEA) is utilised, while, to proxy the financial soundness, the Z-score is calculated for each bank. The panel regression approach is used to examine the effects of financial regulations on the profit efficiency and financial soundness of banks. We find that the financial regulations enforced by State Bank of Pakistan (SBP) have significant impacts on the profit efficiency and financial stability of banks. The results indicate that the non-performance loans to assets ratio (NPLL) and the reserve ratio (RR) impact positively, whereas, the liquidity ratio (LIQR) and the loans to deposits ratio (LODEPOSIT), significantly and negatively affect the profit efficiency of banks. However, only LR and RR are positively and significant related to the financial stability. The results also suggest that the financial regulations have significant differential effects on the profit efficiency and financial soundness of banks across bank size. JEL Classification: C23, E44, G21, G28 Keywords: Profit Efficiency, Financial Soundness, Financial Regulations, Data Envelopment Analysis, Z-Score, Differential Effects
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Studinska, G., and V. Prosov. "PROBLEMS OF MODELING THE MORTGAGE MARKET OF UKRAINE." Financial and credit activity: problems of theory and practice 2, no. 37 (2021): 55–61. http://dx.doi.org/10.18371/fcaptp.v2i37.229691.
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Abstract. The evolution of mortgage market modeling in the context of implementing the strategy of technological development of the national economy is analyzed, that allowed to take into account the disadvantages and advantages of all models, modern socio-economic problems and implement the mortgage market as a mechanism for achieving structural changes in the national economy. Approaches to solving modern problems of mortgage lending in Ukraine through the introduction of specialized mortgage-industrial centers are reasoned: 1) diversification of primary sources of financing in order to maximize them and reduce risks; 2) the presence of an industrial partner company that ensures high production efficiency and has a permanent demand for goods or services; 3) finding the management of the model in the same business hands, in particular the bank, which ensures coordination and optimal distribution of profits between the participants; 4) the need for permanent control over the operation of the model in order to reduce technical, financial and moral risks for mortgage market participants. The universality of the proposed model of mortgage lending for industry (industrialization: renewal of the fleet of equipment and facilities, introduction of technological innovations), agro-industrial complex (modernization of agricultural machinery, development of agricultural science, introduction of world technologies in crop and livestock production, raising food production standards), housing construction and united territorial communities (replacement of the fleet of public transport equipment — buses, trolleybuses, trams) to address the issue of investing current tasks. Keywords: mortgage lending market, mortgage risks, national economy, development strategy, mortgage-industrial center. JEL Classification A13, E17, E44, E69 Formulas: 1; fig.: 2; tabl.: 0; bibl.: 10.
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Widyastuti, Ratna Sri, and Boedi Armanto. "BANKING INDUSTRY COMPETITION IN INDONESIA." Buletin Ekonomi Moneter dan Perbankan 15, no. 4 (2013): 401–34. http://dx.doi.org/10.21098/bemp.v15i4.433.
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This paper analyzes the competition level of banking industry, prior and after the introduction of Indonesian Banking Architecture (API). Using panel data, the result shows the competition of banking decreased after the introduction of API, with large tendency to monopoly or collusive olligopoly. For the bank with niche market such as regional bank and mix bank, the introduction of API did not affect much, while the competition level for foreign bank is the lowest one. Non price variable would be the main determinant on banking competition in the future, including number of branches, wage and credit volume. Keywords: banking competition, market structure, Indonesian Banking Architecture (API).JEL Classification: C23, D40, E44, E58, G21, L11
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Widyastuti, Ratna Sri, and Boedi Armanto. "KOMPETISI INDUSTRI PERBANKAN INDONESIA." Buletin Ekonomi Moneter dan Perbankan 15, no. 4 (2013): 417–39. http://dx.doi.org/10.21098/bemp.v15i4.74.
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This paper analyzes the competition level of banking industry, prior and after the introduction of Indonesian Banking Architecture (API). Using panel data, the result shows the competition of banking decreased after the introduction of API, with large tendency to monopoly or collusive olligopoly. For the bank with niche market such as regional bank and mix bank, the introduction of API did not affect much, while the competition level for foreign bank is the lowest one. Non price variable would be the main determinant on banking competition in the future, including number of branches, wage and credit volume. Keywords: banking competition, market structure, Indonesian Banking Architecture (API).JEL Classification: C23, D40, E44, E58, G21, L11
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Restrepo, María Isabel, and Diana Constanza Restrepo. "El canal del crédito bancario en Colombia: 1995-2005. Una aproximación mediante modelos de umbral." Lecturas de Economía, no. 67 (July 31, 2009): 99–118. http://dx.doi.org/10.17533/udea.le.n67a2022.
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El canal del crédito bancario, que amplifica los efectos del canal tradicional de la política monetaria, hace énfasis en la estructura y las fricciones del mercado financiero como determinantes del gasto agregado. Este artículo analiza y verifica la existencia del canal del crédito bancario en Colombia estimando un modelo propuesto por Michael Gibson en 19971997, quien utiliza regresiones de umbral para determinar el impacto de la política monetaria sobre la demanda agregada. Los resultados obtenidos no permiten descartar la existencia de este mecanismo de transmisión en Colombia durante el periodo analizado, aunque éste parece operar solo a través de la política monetaria contraccionista. Palabras clave: política monetaria, mecanismos de transmisión, canal de crédito bancario, modelos de umbral. Clasificación JEL: C12, C52, E44, E52, G11. Abstract: The Bank Credit Channel, which amplifies the effects of the traditional channel of monetary policy, emphasizes on the structure and frictions of financial markets as determinants of aggregate spending. This paper aims at analyze and verify the existence of the bank credit channel in Colombia estimating a model proposed by Gibson (1997) which uses threshold regressions as a way to determine the impact of monetary policy on aggregate demand. Results do not allow dismissing the existence of this transmission mechanism in Colombia during the analyzed period, although it seems to operate only through contractionary monetary policy. Keywords: monetary policy, transmission mechanisms, bank lending channel, threshold regressions. JEL classification: C12, C52, E44, E52, G11. Résumé: Le canal du crédit bancaire amplifie les effets du canal traditionnel de la politique monétaire et met l.accent sur la structure et sur les frictions du marché financier, lesquels constituent les éléments qui déterminent de la dépense agrégée. L.objectif de cet article est d.analyser et de vérifier l.existence du canal du crédit bancaire en Colombie en estimant le modèle proposé par Michael Gibson en 1997, lequel utilise des régressions à seuil pour déterminer l.impact de la politique monétaire sur la demande agrégée. Les résultats obtenus ne permettent pas d.écarter l.existence d.un mécanisme de transmission pendant la période analysée, malgré le fait qu.il ne paraisse agir qu.à travers une politique monétaire restrictive. Mots clef: politique monétaire, mécanismes de transmission, canal du crédit bancaire, modèles à seuil. Classification JEL: C12, C52, E44, E52, G11.
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Malherbe, Frederic. "Optimal Capital Requirements over the Business and Financial Cycles." American Economic Journal: Macroeconomics 12, no. 3 (2020): 139–74. http://dx.doi.org/10.1257/mac.20160140.
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I study economies where banks do not fully internalize the social costs of their lending decisions, which leads to real overinvestment. The bank capital requirement that restores investment efficiency varies over time. During booms, more investment is desirable, so the banking sector must be allowed to expand. This suggests a loosening of the requirement. However, there is also more bank capital. Since the banking sector exhibits decreasing returns to scale, this suggests a tightening instead. I find that the latter effect, which I dub the “bank capital channel,” dominates: the optimal capital requirement is tighter during booms than in recessions. (JEL E32, E44, G21, G28, G32)
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Harmanta, Harmanta, Nur M. Adhi Purwanto, and Fajar Oktiyanto Oktiyanto. "INTERNALISASI SEKTOR PERBANKAN DALAM MODEL DSGE." Buletin Ekonomi Moneter dan Perbankan 17, no. 1 (2014): 23–60. http://dx.doi.org/10.21098/bemp.v17i1.43.
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We build DSGE model for small open economy with financial friction in the form of collateral constrain on banking sector, designed for Indonesian economy. The constructed model is capable to simulate the monetary policy (Bank Indonesia rate) and macroprudential policy (reserve requirement, capital adequacy ratio – CAR, and loan to value – LTV). By internalizing banking sector into the model, this model also enable us to simulate the impact of any shock originated from banking sector. Keywords: monetary policy, DSGE with banking sector, macroprudential policy JEL Classification: E32, E44, E52, E58
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Fajar, Hanifan, and Umanto. "The impact of macroeconomic and bank-specific factors toward non-performing loan: evidence from Indonesian public banks." Banks and Bank Systems 12, no. 1 (2017): 67–74. http://dx.doi.org/10.21511/bbs.12(1).2017.08.
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The present study focuses on the need for banking sector to be more reactive when facing globalization that could bring impact on banking industries complexity. Based on empirical studies, there is a need to analyze non performing loan determinants comprehensively using macroeconomic and bank-specific factors to make a good condition on bank, because combining macroeconomic and bank-specific variable as NPL determinants has made a big improvement to analyze NPL. The object of present study is 20 Banks listed in Indonesia Stock Exchange (IDX) between q12005-q42014. Using dynamic panel data GMM-system method shows that the previous period of NPL (non performing loan), change of PDB (Gross Domestic Product) and inflation rate have a significantly negative impact on NPL. However, BOPO (Operations Expenses to Operations Income) and ROE (Return on Equity) has a significantly positve relationship to NPL. On the other hand, this research does not find any significance on BI rate (interest rate), solvency ratio, and size to NPL. From the result, it can be concluded that combining macroeconomic and bank-specific variable could be an alternative method to analyze NPL determinants on bank. Keywords: nonperforming loans, banks, credit risk, globalization, dynamic panel data, banking industries. JEL Classification: G21, E44, E51, E5, F60
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Das, Anupam, and Syeed Khan. "Financial Development and Output: A Synthesis of Time Series Cointegration and Causality Tests for Bangladesh." South Asian Journal of Macroeconomics and Public Finance 5, no. 2 (2016): 113–32. http://dx.doi.org/10.1177/2277978716670788.
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Since the 1980s, financial liberalization in developing countries has been an important policy prescription of many international organizations including the World Bank (WB) and International Monetary Fund (IMF). It is argued that the liberalization of the financial sector would allocate productive resources in the most efficient way and increase economic growth. However, the relationship between financial liberalization and output is not clear in the existing empirical literature. Applying the cointegration and Granger causality tests within the vector error correction model (VECM) to a data set from 1974 to 2013, our results suggest that output per capita Granger causes financial development, and vice versa. Hence, we find the evidence of bidirectional causality between financial development and GDP in Bangladesh. These results will help policymakers design financial policies in Bangladesh and other developing countries, which face the dilemma of financial liberalization while maintaining a high and stable output growth. JEL Classification: E44, O40, C22
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Firmansyah, Irman. "DETERMINANT OF NON PERFORMING LOAN: THE CASE OF ISLAMIC BANK IN INDONESIA." Buletin Ekonomi Moneter dan Perbankan 17, no. 2 (2015): 241–58. http://dx.doi.org/10.21098/bemp.v17i2.51.
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This paper analyzes the non-performing loan and its determinant. Using the monthly data of Islamic banks during 2010-2012, this paper found that size and efficiency of the banks do not affect the non-performing loan. On the other hand, GDP and inflation negatively affect the non-performing loan, while the liquidity of the bank positively affects the non-performing loan. The liquidity of also does not mediate the relationship between the size of the bank, their efficiency, the GDP and the inflation to the non-performing loan. Keywords: non-performing loan, liquidity, bank size, efficiency, sobel test, Islamic bank. JEL Classification: C12, G21