Analysts’ use of dividends in earnings forecasts

Somnath Das (), Philipp D. Schaberl () and Pradyot K. Sen ()
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Somnath Das: University of Illinois Chicago
Philipp D. Schaberl: University of Northern Colorado
Pradyot K. Sen: University of Washington Bothell

Review of Accounting Studies, 2024, vol. 29, issue 2, No 6, 1192-1234

Abstract: Abstract This paper investigates the association between current dividends and analysts’ subsequent earnings forecast errors. This investigation is motivated by the evidence on analyst optimism and Ohlson’s (1991, 1995) fundamental valuation theory that dividends displace future permanent earnings. For the sample period 1985–2016, we document that current dividends are positively correlated with analysts’ future forecast errors, suggesting that analysts potentially ignore the displacement effect of dividends on future earnings. Consistent with theory, this association persists in settings with stable dividends, (i.e., where dividends have limited or no signaling implications) and varies predictably with dividend payouts and cost of capital. We also find that this empirical regularity that analysts do not fully incorporate the effect of dividends on future earnings provides opportunities for arbitrage. More interestingly, we find that the strength of the association between dividends and analysts’ forecast errors has declined over the sample period; this decline appears to correspond with the underlying change in the discount rate over time. The finding that analysts’ do not fully incorporate the implications of current dividends on future earnings is consistent with previously documented inefficiencies in analysts’ use of publicly available information. However, such a systematic association with dividends also suggests that it may be a source of the persistence in analysts’ optimistic bias and thus offers new insights into analyst behavior.

Keywords: Analysts’ forecast errors; Analyst inefficiency; Analysts’ optimistic Bias; Dividends; Dividend displacement; Earnings forecasts; Median regression; Theil-Sen estimator (search for similar items in EconPapers)
JEL-codes: G17 G35 M40 M41 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11142-022-09735-8

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