Shyam Sunder, Relationship between Accounting Changes and Stock Prices: Problems of Measurement and Some Empirical Evidence, Journal of Accounting Research, Vol. 11, Empirical Research in Accounting: Selected Studies 1973 (1973), pp. 1-45
Presents a linear aggregation model of valuation of assets to help understand how the minimum mean squared error valuation rule is affected by various parameters that characterize the economy and the circumstances under which historical-cost valuation rule yields a statistically more precise estimate of the unobserved economic value of firms' assets than the current valuation rule.
[Errors arise in measuring changes in prices of assets due to imperfection and incompleteness of asset markets. Furthermore, the rates of price-change, and the magnitudes of errors of measurement vary and are often correlated across assets. Suppose we characterize an economy by means and variances of price changes for individual goods and of measurement errors in these changes as well as by the degree of diversification in the asset portfolios held by individual firms. In such an economy, the linear valuation rule that yields the most efficient estimate of change in the economic value of these asset portfolios is the one that minimizes the mean squared error (MSE). This paper presents a linear aggregation model of valuation to help understand how the minimum MSE valuation rule is affected by various parameters that characterize the economy, and the circumstances under which historical-cost valuation rule yields a (statistically) more precise estimate of the unobserved economic value of firms' assets than the current valuation rule. The analytical findings of the paper are consistent with the reluctance of accountants to depart from historical cost in spite of the existence of low inflation, and in spite of scholarly critiques of this valuation rule by Chambers (1966), Edwards and Bell (1961), Sterling (1970) and others. They are also consistent with the use of specific price indexes by most firms to prepare SFAS 33 disclosures. Several testable implicatons of the results are provided. A direct comparison of the characteristics of valuation rules is complicated by the heterogeneity of the decision contexts in which accounting numbers are used. We use the mean squared error (MSE) between the principal value and its various estimators to rank the latter. Using this criterion, previous simpler models that ignore the presence of measurement errors in price changes have shown that the use of increasingly detailed price indexes yields more precise valuation; current valuation is the most precise valuation rule because it uses the most detailed set of indexes (Sunder 1978). We show that this basic result does not hold when the measurement of price changes is subject to errors. As the magnitude of these measurement errors increases relative to the magnitude of price changes, the most accurate valuation rule requires a less detailed set of price indexes. A key implication of this result is that the existence of inflation or deflation is not sufficient for general-price-level valuation, specific-price-index valuation, or current valuation to dominate historical-cost valuation as an estimator of the economic value of firms' assets. Historical-cost valuation is dominated by others only when the magnitude of price changes are large relative to the errors of measurement in price changes.]
This paper tests traditional capital structure models against the alternative of a pecking order model of corporate financing. The basic pecking order model, which predicts external debt financing driven by the internal financial deficit, has much greater time-series explanatory power than a static tradeoff model, which predicts that each firm adjusts gradually toward an optimal debt ratio. We show that our tests have the power to reject the pecking order against alternative tradeoff hypotheses. The statistical power of some usual tests of the tradeoff model is virtually nil.
We report market experiments in which human traders are replaced by "zero-intelligence" programs that submit random bids and offers. Imposing a budget constraint (i.e., not permitting traders to sell below their costs or buy above their values) is sufficient to raise the allocative efficiency of these auctions close to 100 percent. Allocative efficiency of a double auction derives largely from its structure, independent of traders' motivation, intelligence, or learning. Adam Smith's invisible hand may be more powerful than some may have thought; it can generate aggregate rationality not only from individual rationality but also from individual irrationality.
The study reports on the ability of competing models of market information integration and dissemination to explain the behavior of simple laboratory markets for a one-period security. Returns to the security depended upon a randomly drawn state of nature. Some agents (insiders), whose identity was unknown to other agents, knew the state before the markets opened. With replication of market conditions the predictions of a fully revealing rational-expectations model are relatively accurate. Prices adjusted immediately to near rational-expectations prices; profits of insiders were virtually indistinguishable from noninsiders; and efficiency levels converged to near 100 percent.
Predictions of the noisy rational expectations equilibrium (REE) model are found to be relatively accurate for both asset and information markets in the laboratory. When information about an asset's uncertain dividend is sold to a fixed number of highest bidders, prices, allocations, efficiency, and distribution of profit predictions of the full revelation REE model in the asset market dominate the predictions of the Walrasian model; demand for information shifts to the left and its price declines close to zero. When the price of information is fixed at a relatively high level, the number of informed agents and the informativeness of the asset market tends to adjust to permit the informed agents to recover their investment in information.
A model for estimating the change in the economic value of a firm due to the adoption and use of last in, first out (LIFO) under conditions of certainty has been presented. The model requires single-point estimates of three parameters: the marginal tax rate, the cost of the basic inventory and the ratio of the cost of capital of the firm to the anticipated rate of inflation. In estimating the effect of LIFO on the economic value of the firm, the analysis has been limited to the net present value of future cash flows. Any additional risk that the firm may have to bear due to uncertainty in the future rates of inflation and, therefore, in the effect of LIFO on the firm has not been considered. Indeed, there is some empirical evidence available to indicate that the adoption of LIFO is accompanied not only by an increase in the market value of the firm, but also by an increase in the market risk of its ownership shares. The critical assumptions of the model are that the physical quantity of inventory remains constant and the rates of price change, discount and taxation are known deterministically.
The article focuses on properties of accounting numbers in costing in petroleum industries. Financial reporting and accounting practices used in the petroleum industry differ both among firms within the industry and also from practices of other industries in several respects. One area of difference is accounting for prediscovery costs. Because such costs are relatively large and because a large degree of uncertainty is associated with the potential benefits sought by incurrence of such costs, this area has provoked many practices; most can be grouped either as successful-efforts costing or full-costing practices. The practice of capitalizing only those prediscovery costs, which are directly identifiable with discovery of a commercial reserve and treating all other costs as operating expense is referred to as successful-efforts costing. On the other hand, the practice of capitalizing all prediscovery costs irrespective of their result is called the full-costing method. The study described in the paper is an attempt to analyze the effect of using the alternative methods on various accounting variables.