Accounting Measurement Basis, Market Mispricing, and Firm Investment Efficiency

In this paper, we investigate how the accounting measurement basis affects the capital market pricing of a firm’s shares, which, in turn, affects the efficiency of the firm’s investment decisions. We distinguish two broad bases for accounting measurements: input-based and output-based accounting. We argue that the structural difference in the two measurement bases leads to a systematic difference in the efficiency of the investment decisions. In particular, we show that an output-based measure has a natural advantage in aligning investment incentives because of its comprehensiveness. The (first-) best investment is achieved when the output-based measure is noiseless and manipulation-free. In addition, under an output-based measure, more accounting noise/manipulation always leads to more inefficient investment choices. Therefore, if an outputbased measures is highly noisy and easy to manipulate in practice, the induced investment efficiency can be quite low. On the other hand, an input-based measure, while not as comprehensive, may induce more efficient investment decisions than an output-based measure if some noise is unavoidable in either measure. The reason is two-fold. First, input-based measures may be associated with less noise and limited manipulation in practice. Second and more importantly, we show that under an input-based measure, a slight increase in accounting noise/manipulation may lead to more efficient investment choices. In fact, the (first-) best result is achieved when the noise/manipulability is small but positive. In other words, for an input-based measure, being less comprehensive makes small but positive accounting noise/manipulability desirable. Two extensions of the basic model are also explored. ∗The authors gratefully acknowledge the suggestions from an anonymous referee, Joel Demski, Jon Glover, Burton Hollifield, Volker Laux, and members of an informal reading group at the Tepper School of Business, Carnegie Mellon University. All errors are ours. The current version of the paper is available at http://www.tepper.cmu.edu/andrew/liangj.