2018
DOI: 10.1016/j.frl.2017.10.031
|View full text |Cite
|
Sign up to set email alerts
|

Loan loss provisions and macroeconomic shocks: Some empirical evidence for italian banks during the crisis

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

2
22
0

Year Published

2019
2019
2024
2024

Publication Types

Select...
7
1
1

Relationship

0
9

Authors

Journals

citations
Cited by 22 publications
(24 citation statements)
references
References 9 publications
2
22
0
Order By: Relevance
“…Kanagaretnam et al (2005) show that US banks use LLPs to signal information about banks' future prospects but the propensity to use provisions for signaling purposes is greater among smaller banks. In Italy, Caporale et al (2018) examine the determinants of loan loss provisions among 400 Italian banks during 2001 to 2015. They find that loan loss provisions in Italian banks were significantly influenced by the non-discretionary components of loan loss provisions.…”
Section: Literature Review and Hypothesis Development 21 Literature Reviewmentioning
confidence: 99%
“…Kanagaretnam et al (2005) show that US banks use LLPs to signal information about banks' future prospects but the propensity to use provisions for signaling purposes is greater among smaller banks. In Italy, Caporale et al (2018) examine the determinants of loan loss provisions among 400 Italian banks during 2001 to 2015. They find that loan loss provisions in Italian banks were significantly influenced by the non-discretionary components of loan loss provisions.…”
Section: Literature Review and Hypothesis Development 21 Literature Reviewmentioning
confidence: 99%
“…In our baseline regressions, we exclude the lag of the LLP as a potential right-hand side variable as some previous studies in the banking sector have done (e.g., Bikker & Metzemakers, 2005). However, to analyze the determinants of loan loss provisioning in the banking sector, some other studies specify a dynamic adjustment framework model for at least two reasons: first, to capture the speed of adjustment of loan loss provisions by assuming that banks progressively adjust their level of provisions toward a target level of provisions; and second, to account for the time dependency of provisions (Bouvatier et al, 2014;Bouvatier & Lepetit, 2012;Caporale et al, 2018;Laeven & Majnoni, 2003). However, no such evidence exists in the microfinance literature.…”
Section: Dynamic Panel Estimationmentioning
confidence: 99%
“…The existing banking literature examining cyclical pattern of bank loan loss provisioning document either a countercyclical 3 provisioning behaviour (Bikker & Metzemakers, 2005;Laeven & Majnoni, 2003;Shim, 2013) or a procyclical provisioning behaviour (Caporale, Alessi, Di Colli, & Lopez, 2018;Cummings & Durrani, 2016). One assumption being that banks' borrowers are sensitive to macroeconomic conditions, and that banks' failures and economic performance are intertwined.…”
Section: Introductionmentioning
confidence: 99%
“…In the loan loss provisions model in equation 1, the NPL variable controls for the impact of nonperforming loans on loan loss provisions. The literature show that non-performing loan is a major nondiscretionary determinant of loan loss provisions in the banking sector (see Ozili and Outa, 2017;Caporale et al, 2018;Danisman et al, 2021). Many studies report a positive relationship between loan loss provisions and non-performing loans because banks will increase loan loss provisions when they expect high non-performing loans.…”
Section: Variable Justificationmentioning
confidence: 99%