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Review of Quantitative Finance and Accounting

Erschienen in:

08.08.2019 | Original Research

Bank earnings management and analyst coverage: evidence from loan loss provisions

verfasst von: Yongtao Hong, Fariz Huseynov, Sabuhi Sardarli, Wei Zhang

Erschienen in: Review of Quantitative Finance and Accounting | Ausgabe 1/2020

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Abstract

We investigate the role of loan loss provisions in analysts’ decision to follow banks. We find that abnormal loan loss provisions (ALLP), regardless of whether it is income-increasing or income-decreasing, reduce analyst coverage. We interpret this effect with the finding that the greater magnitude of ALLPs decreases the accuracy and increases the dispersion of analysts’ forecasts. In addition, the volatility in ALLPs leads to the decrease in analyst coverage as well. We also find a pecking order for lead analysts’ decisions in a noisy information environment. Lead analysts prefer to follow financial institutions with more accurate loan loss provisions first, then with more positive (incoming-decreasing) ALLPs, and are less likely to follow those with negative (income-increasing) ALLPs. Our findings are robust to endogeneity concerns and indicate that lead analysts are deterred from more aggressive bank earnings management.

Vorheriger Artikel Foreign institutional ownership and demand for accounting conservatism: evidence from an emerging market

Nächster Artikel Credit information sharing and loan default in developing countries: the moderating effect of banking market concentration and national governance quality

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As a comparison, Kanagaretnam et al. (2010a) reports the sample size of 1740 bank-year observations with 301 unique banks in their study of the period from 1996 to 2006.

The reasons why we use ALLP as the proxy of bank earnings management are twofold. First, in the earnings management literature, the modified cross-sectional Jones (1991) model, as described by Dechow et al. (1995) and modified by Kothari et al. (2005) is commonly used to capture discretionary accruals for industries other than the financial industry due to the significant differences in the composition of accruals. Second, focusing on one accrual reduces measurement errors as documented by Guay et al. (1996), McNichols (2000, 2002), Jones et al. (2008).

If both positive and negative ALLP decrease analyst following, statistically, it is an indication that the relations between ALLP and analyst following might be nonlinear. This nonlinear relationship also justifies the use of absolute value in model (2).

Due to the control of Section 36, we do not control for the fixed year effects in our model. Since we are examining the banking industry only, there is no control for the fixed industry effects either.

Cooper et al. (2001) use the top decile of differences between forecasted and actual EPS to define accurate lead analysts. We take a more stringent measure by examining the top 5%. The mean (median) EPS for our sample is $1.58 (1.54). A 5% difference means analyst forecast is $0.08 higher or lower than the reported EPS.

We develop the measure of lead analysts by identifying unique lead analysts in each quarter first. Then, the total number of unique lead analysts in a given year are summed and divided by the total number of unique analysts in 1 year. Given that we are using unique lead analysts in this model, the potential for shifting sample of analysts does not have an effect on the calculation the dependent variable.

Use of absolute values for positive and negative ALLP enables us to make a better comparison across these two groups.

We also conduct Durbin-Wu-Hausman test of exogeneity to determine whether we reject that banks earnings management and analyst following are exogenous. Our test results indicate that we cannot reject exogeneity as the p-values range between 0.69 and 0.99, when we use raw and abnormal values of loan loss provisions. Therefore, our study focuses on the impact of bank earnings management on analysts’ decisions to follow the bank.

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Titel: Bank earnings management and analyst coverage: evidence from loan loss provisions
verfasst von: Yongtao Hong
Fariz Huseynov
Sabuhi Sardarli
Wei Zhang
Publikationsdatum: 08.08.2019
Verlag: Springer US
Erschienen in: Review of Quantitative Finance and Accounting / Ausgabe 1/2020
Print ISSN: 0924-865X
Elektronische ISSN: 1573-7179
DOI: https://doi.org/10.1007/s11156-019-00835-2

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