Bias and Aggregation in Accounting : The Effects on Creditors' Decision and Costs of Capital

This study investigates the effects of bias and aggregation in an accounting information system (AIS) on the creditor's rollover/foreclosure decision and a levered firm's costs of debt and equity capital. We make two innovations in modeling an AIS with bias. First, we decompose the overall effect of bias into a mean effect and a variance effect. Second, we use aggregation and normal approximation to convert discrete state and report spaces into continuous ones. We identify three main results. (1) The creditor's optimal incidence of foreclosure is U-shaped in the degree of bias. (2) A see-saw relation exists between the incidence of foreclosure and the cost of debt capital with respect to the degree of bias. (3) A levered firm's cost of debt capital and cost of equity capital move in the opposite direction when the AIS is moderately biased and in the same direction when the AIS is extremely biased. Hence, from the perspective of value creation and distribution, these results shed some light on the notion of neutrality in standard setters' conceptual frameworks for financial reporting