2021
DOI: 10.2308/tar-2017-0244
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Credit Information Sharing and Loan Loss Recognition

Abstract: Does enhancing banks' information sets and understanding of credit risks improve loan loss recognition? We study this question using a global dataset of staggered initiations and coverage increases of public credit registries (PCRs). Mandated by national regulators, PCRs collect borrower and loan information from lenders and share it with the banks in the financial system. This setting represents a significant improvement in banks' assessment of loss events. We find that PCR initiations and coverage reforms en… Show more

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Cited by 27 publications
(9 citation statements)
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“…Each observation is a firm-year. Post is a dummy variable that equals to one if at or after the year the establishment of PCR in an economy (or its matched control economy) and the data is taken from Djankov, McLiesh & Shleifer (2007), supplemented by Ertan (2017) and(2020). Treatment is a dummy variable equals to one if the economy where the firm operates set up a PCR within the sample period, and zero otherwise.…”
Section: Table 3 Baseline Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Each observation is a firm-year. Post is a dummy variable that equals to one if at or after the year the establishment of PCR in an economy (or its matched control economy) and the data is taken from Djankov, McLiesh & Shleifer (2007), supplemented by Ertan (2017) and(2020). Treatment is a dummy variable equals to one if the economy where the firm operates set up a PCR within the sample period, and zero otherwise.…”
Section: Table 3 Baseline Resultsmentioning
confidence: 99%
“…Our empirical analyses are based a novel global data set of firm financial characteristics merged with patent information and country-specific details of credit reporting systems. We obtain data on the establishment year of PCRs from Djankov, McLiesh and Shleifer (2007), supplemented by Ertan (2017) and(2020). Table 1 presents PCRs introduction years in the sample countries.…”
Section: Research Design and Datamentioning
confidence: 99%
“…This enables the management to come to the awareness of the losses made due to unpaid loans. Loan loss provision projects the potential of credit risk as well as the general financial outlook of the bank (Balakrishnan and Ertan, 2019 ). As the volume of credit increases, it does so with credit risk.…”
Section: Literature Reviewmentioning
confidence: 99%
“…In a study carried out by Balakrishnan and Ertan (2021) on Credit information sharing and recognition of loss on loan showed that CIS improves recognition of bank loss on timely basis due to revelation of NPLs. In another study conducted by Son, Khanh and Liem (2020) on financial development, corruption and credit information sharing between 2004 and 2017 in 120 republics.…”
Section: Empirical Reviewmentioning
confidence: 99%