Idiosyncratic shocks to firm underlying economics and abnormal accruals Edward L. Owens, Joanna Shuang Wu & Jerold Zimmerman

Por: Colaborador(es): Tipo de material: ArtículoArtículoDescripción: Páginas 183 a la 219Tema(s): En: The accounting review 2017 V.92 No.2 (Mar)Incluye figuras, tablas, referencias bibliográficas y apéndicesResumen: Economics challenge the specification of discretionary accrual models. Since rent-seeking firms pursue differentiated business strategies, firms in the same industry experience idiosyncratic shocks due to heterogeneous economic fundamentals and hence have different accrual-generating processes. We present evidence that idiosyncratic shocks are widespread, propagate through multiple years of financial statements, and reduce accrual models' goodness of fit. This not only affects abnormal accrual estimates for the firm experiencing shocks, but also affects measurement of abnormal accruals for other firms in the industry. We show that idiosyncratic shocks not only add noise to abnormal accruals, but can also exacerbate bias in both unsigned and signed abnormal accruals. We propose ways to reduce accrual model misspecification.
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Revistas Central Bogotá Sala Hemeroteca Colección Hemeroteca 657 (Navegar estantería(Abre debajo)) 2017 V.92 No.2 (Mar) 1 Disponible 0000002032282

Economics challenge the specification of discretionary accrual models. Since rent-seeking firms pursue differentiated business strategies, firms in the same industry experience idiosyncratic shocks due to heterogeneous economic fundamentals and hence have different accrual-generating processes. We present evidence that idiosyncratic shocks are widespread, propagate through multiple years of financial statements, and reduce accrual models' goodness of fit. This not only affects abnormal accrual estimates for the firm experiencing shocks, but also affects measurement of abnormal accruals for other firms in the industry. We show that idiosyncratic shocks not only add noise to abnormal accruals, but can also exacerbate bias in both unsigned and signed abnormal accruals. We propose ways to reduce accrual model misspecification.

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