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Earnings management - Profili teorici ed evidenze empiriche nell'applicazione del metodo Expected Credit Loss (IFRS9 )

Authors: Raffaela Casciello;

Earnings management - Profili teorici ed evidenze empiriche nell'applicazione del metodo Expected Credit Loss (IFRS9 )

Abstract

Il presente scritto propone una disamina delle caratteristiche dell’earnings management e delle sue implicazioni per l’attendibilità della comunicazione economico-finanziaria delle imprese. L’inquadramento della ricerca è finalizzato ad indagare se il processo di accantonamento per perdite attese sui crediti di tipo Expected Credit Loss (ECL) per le imprese IFRS-compliant, derivante dall’applicazione del principio contabile IFRS 9 ‘Financial Instruments’, possa aver creato condizioni di incentivo o ostacolo al ricorso alle politiche di earnings management. Attraverso un’analisi dettagliata delle peculiarità del processo di stima delle perdite attese sui crediti secondo il metodo ECL, si pone in evidenza l’esistenza di taluni margini valutativi discrezionali nel processo di loan loss provisioning potenzialmente sfruttabili per l’alterazione del risultato economico dell’esercizio. La trattazione teorica è supportata da un’analisi empirica nel contesto delle imprese finanziarie quotate europee, volta ad indagare se la variabilità delle tempistiche di riconoscimento delle perdite attese sui crediti secondo il metodo ECL è associata alle operazioni di earnings management.

Country
Italy
Related Organizations
Keywords

Earnings management; Expected Credit Loss (IFRS 9), Earnings management, Expected Credit Loss (IFRS 9)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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