Xiaoyan Wen

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 firms shares, which, in turn, affects the efficiency of the firms 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 output-based accounting measure is highly noisy and easy to manipulate in practice, the induced investment efficiency can be quite low. On the other hand, an input-based accounting 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 twofold. 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 Economic Consequences of Expanding Accounting Recognition

Explicitly or not, an accounting measurement system must choose whether or not to exclude, from its scope consideration, any economic activities yet to occur. We provide a model where such a scope distinction between measurements has both accounting and economic meanings. In particular, we represent measurements limited to past actions with an assets-in-place (AIP) accounting measurement in contrast to a Full accounting measurement which represents measurements anticipating future actions. We then embed the accounting model into a …rm’s accounting choice problem in which the …rm rationally recognizes that its accounting choice may change its own investment e¢ ciency as well as the risk premium in its share price. We analyze how the optimal choice between the two measurements depends on the investment environment (e.g., growth opportunities) as well as the inherent measurement characteristics (e.g., measurement noise). We show the optimal choice can be subtle if the …rm’s investment is endogenous to the accounting regime itself. For example, Full accounting may be preferable even if the noise in Full accounting is high in some cases. Similarly, AIP accounting may become preferable even if the …rm-growth may be sizeable. The underlying driving force is that the endogenous investment makes endogenous the total uncertainty of the …rm’s cash ‡ows as well as the resolution of the =

Information Quality and Endogenous Project Outcomes

In this paper, we examine the role of information quality in a setting in which a firm needs capital injection from a perfectly-competitive debt market to fund a profitable project. A representative creditor determines the debt repayment based on a noisy public signal about the projects state to break even, and the firm can make ex-post input to improve the project outcome. We find that higher information quality of the signal discourages the firms input and thus decreases the overall efficiency. This result is mainly driven by the nature of debt contracting: the creditor cares more about the downside risk than the upside potential of the project outcome. When the information quality becomes higher, the creditor makes asymmetric adjustments in debt terms upon good and bad signals, thereby impacting the firms input decisions asymmetrically upon different signals. Specifically, upon a bad signal, higher information quality significantly increases the debt repayment and thus discourages the firms input, whereas upon a good signal, higher information quality does not reduce the debt repayment much and can barely encourage the firms input. In addition, we find that this negative effect of higher information quality is even more pronounced when there is no information asymmetry between the firm and the creditor. This is because when the firm itself does not know its state, its input decision merely depends on the signal, whereas when the firm observes its state, its input decision relies less on the signal.