Bank liquidity creation and asset market liquidity

Chatterjee, Ujjal

doi:10.1016/j.jfs.2015.03.006

Cited by 47 publications

(29 citation statements)

References 35 publications

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“…Berger and Bouwman (2009a) found that large US banks created 81 % of total liquidity while medium sized banks generated 5 %, and small banks produced 14 % of the overall liquidity. Similarly, many studies have found that the relationship of bank liquidity creation with other variables also differ for the banks of different sizes (Berger and Bouwman 2009a;Distinguin et al 2013;Imbierowicz and Rauch 2014;Chatterjee 2015). So, following the norm in the existing literature and our findings for the overall sample, we have conducted the analysis on the basis of bank size to determine whether there exists a relationship between NPLs and liquidity creation for small and large banks.…”

Section: Regression Analysis On the Basis Of Bank Sizementioning

confidence: 76%

“…Many studies regarding bank liquidity conclude that banks of different sizes behave differently (Berger and Bouwman 2009a;Distinguin et al 2013;Chatterjee 2015). So, we control for the bank size in our regression by including LN_TA.…”

Section: Control Variablesmentioning

confidence: 99%

“…Similarly, there are many studies which provided different models and theories regarding bank liquidity creation. The number of studies which provide empirical evidence regarding bank liquidity creation and its relationship with bank capital has surged after the important paper of Berger and Bouwman (2009a) (Hackethal et al 2010;Lei and Song 2013;Horvath et al 2014;Chatterjee 2015). To the best of our knowledge, none of the existing studies investigates the a moral hazard problem by analyzing the relationship between bank liquidity creation and NPLs.…”

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confidence: 99%

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Non-performing loans (NPLs), liquidity creation, and moral hazard: Case of Chinese banks

Umar

Sun

2016

China Financ. and Econ. Rev.

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Background: This study analyzes the impact of non-performing loans (NPLs) on bank liquidity creation to investigate the existence of moral hazard problem in Chinese banks. Methods: It uses data from 197 listed and unlisted Chinese banks, spanning the period 2005 to 2014. Generalized method of moments (GMM) estimation, fixed and random effect model, and pool data techniques have been used for analysis. Results: Total liquidity creation by Chinese banks is declining, and NPLs ratio has started to increase following a continuous decline between 2005 and 2012. We find that liquidity creation by Chinese banks does not depend on NPLs ratio. We repeated the analysis for small and large banks and the results of these subsamples reinforced our findings for the aggregate sample. Conclusions: We did not find the evidence of moral hazard problem in Chinese banks.

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Section: Regression Analysis On the Basis Of Bank Sizementioning

confidence: 76%

Section: Control Variablesmentioning

confidence: 99%

mentioning

confidence: 99%

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Non-performing loans (NPLs), liquidity creation, and moral hazard: Case of Chinese banks

Umar

Sun

2016

China Financ. and Econ. Rev.

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“…Further, (Fernandez de Lis, Pag es, & Jesus, 2000;Hu, Li, & Chiu, 2004) find a negatively significant relationship between assets and non-performing loans in Spain, which means that the size of a bank's assets could decrease the incidence of NPLs. Also, several studies address and use banks' assets as a microeconomic proxy for banks, (Distinguin, Roulet, & Tarazi, 2013;Imbierowicz & Rauch, 2014, Chatterjee, 2015Ono & Uesugi, 2009;Swamy, 2018).…”

Section: Hypothesis Developmentmentioning

confidence: 99%

The causal relationship between SME sustainability and banks’ risk

Shihadeh

Gamage

Hannoon

2019

Economic Research-Ekonomska Istraživanja

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This study aims to examine the influence of banks' credit to SMEs on non-performing loans. Many studies find that access to financial sources has become an obstacle to the growth and sustainability of SMEs. This study uses theoretical and empirical approaches to support the study's hypothesis. Data are presented for 15 banks in Palestine, covering the period 2006 to 2016.The study uses empirical techniques regarding to examine the relationship between the variables. Evidence shows that encouraging banks to lend more money to SMEs through the use of a guarantee fund could decrease their risk. Thus, enhancing credit to SMEs could improve the growth and sustainability of these firms. The study recommending policymakers and bank's managers could develop their strategies according to SME's needing. Therefore, enhancing the growth in these firms and reducing the bank's risk. Furthermore, adopting the guarantee funds in developing countries could decrease the bank's risk, thus lending more to SME. The value of this paper comes from the importance of SME in the economic growth and development sustainability. Therefore, there is a need to convince banks to enhance SME credit through a guarantee fund and that extending this type of credit would positively influence banks' activities.

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“…This situation is too risky for banks because it places them in a liquidity disequilibrium, which affects their asset and liability management and could lead to a serious financial crisis. See [ 42 , 43 ]; i.e., in the real world, the liquidity issue is closely related to the function of the central bank (we intentionally do not introduce a central bank in this model). Model 3, as shown in Figs 7 and 8 , allows for the complete recovery of the economy, the maintenance of a low liquidity ratio (lower than that in model 2) and low NPL growth (lower than that in model 1).…”

Section: Analysis Of the Effects Of Negative Shocks On The Economy Usmentioning

confidence: 99%

A model of the indirect losses from negative shocks in production and finance

et al. 2020

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Economies are frequently affected by natural disasters and both domestic and overseas financial crises. These events disrupt production and cause multiple other types of economic losses, including negative impacts on the banking system. Understanding the transmission mechanism that causes various negative second-order post-catastrophe effects is crucial if policymakers are to develop more efficient recovery strategies. In this work, we introduce a credit-based adaptive regional input-output (ARIO) model to analyse the effects of disasters and crises on the supply chain and bank-firm credit networks. Using real Japanese networks and the exogenous shocks of the 2008 Lehman Brothers bankruptcy and the Great East Japan Earthquake (March 11, 2011), this paper aims to depict how these negative shocks propagate through the supply chain and affect the banking system. The creditbased ARIO model is calibrated using Latin hypercube sampling and the design of experiments procedure to reproduce the short-term (one-year) dynamics of the Japanese industrial production index after the 2008 Lehman Brothers bankruptcy and the 2011 Great East Japan earthquake. Then, through simulation experiments, we identify the chemical and petroleum manufacturing and transport sectors as the most vulnerable Japanese industrial sectors. Finally, the case of the 2011 Great East Japan Earthquake is simulated for Japanese prefectures to understand differences among regions in terms of globally engendered indirect economic losses. Tokyo and Osaka prefectures are the most vulnerable locations because they hold greater concentrations of the above-mentioned vulnerable industrial sectors.

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Bank liquidity creation and asset market liquidity

Cited by 47 publications

References 35 publications

Non-performing loans (NPLs), liquidity creation, and moral hazard: Case of Chinese banks

Non-performing loans (NPLs), liquidity creation, and moral hazard: Case of Chinese banks

The causal relationship between SME sustainability and banks’ risk

A model of the indirect losses from negative shocks in production and finance

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