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We examine the impact on share prices of firms whose CEOs and CFOs certify their financial statements under oath, pursuant to the administrative order issued by the SEC on June 27, 2002. We hypothesize that (1) the certification provides assurance to investors by making disclosure more credible and by reducing information asymmetry between owners and management, and (2) the assurance value of certification is reflected in the stock price of the certifying company. Overall, the empirical results are consistent with our hypotheses. We observe, on average, positive abnormal returns for firms whose CEOs/CFOs certified their financial statements by August 14, 2002. Based on an analysis of bid-ask spreads, certifying firms experienced a significant decline in information asymmetry after certification. In cross-sectional analyses, we find abnormal returns are positively associated with firms that were under investigation, that used Andersen as their auditor, and that practiced aggressive revenue recognition.

Ohlson (1995) develops an equity valuation model based on the framework of dividend irrelevance proposition proposed by Miller and Modigliani (1961). He claims that a dividend payout lowers the current book value of equity but not the current earnings, and thus a firm's current market value is not influenced by its dividend policy. This dividend irrelevance proposition was initially developed under some assumptions or conditions such as perfect market, no tax effects, and no stock issue and transaction costs. Apparently, these assumptions are questionable in reality because dividends are normally related to earnings and influenced by the market and tax factors, and thus they are likely to affect the stock price and the firm value. As a result, Ohlson's equity valuation model has been recently extended to studying the broader valuation issues related to interest rate, risk, and the relationship between earnings and share prices. In this paper, we develop three equity valuation models by extending Ohlson's model to consider the relationship between earnings and dividends and investigate the information content of dividends in firm valuation. Specifically, the major characteristics of these extended valuation models are: Model 1 considers dividends as a fraction of the permanent component of earnings, Model 2 considers dividends as a fraction of the present discounted value of future expected earnings, and Model 3 considers dividends as a proportion of the current earnings. We empirically test the explanatory power of these theoretical models by using the available data from the NYSE firms. Our results indicate that for all three extended models, book value of equity, liabilities, and investment are significantly and positively related to stock prices for the whole sample. This result provides empirical support that these three accounting fundamentals are important determinants of firm values. Furthermore, a comparison of the models' predictive abilities reveals that Model 2, considering dividends as proportional to the present discounted value of future expected earnings, performs better than the other two models not only for the whole sample but also for the manufacturing industry and the service industry sub-samples. Taken together, our findings provide further evidence that accounting numbers are important determinants of the firm value and dividends are closely related to the present discounted value of future earnings and the firm value.

This paper develops a warning zone approach to make variance investigation decisions for a multiperiod process. The assumed cost generation process varies between an in-control and out-of-control state. These states cannot be directly observed, but must be inferred from the reported cost variances. Using the warning zone method of inference, the manager investigates the process whenever an upper threshold is exceeded or a lower threshold is exceeded for two consecutive periods. A four-state Markov chain models the resulting decision process. Steady state probabilities are derived for this chain and are used to obtain explicit formulas for the effectiveness and efficiency of the decision process. These formulas permit computation of the cost savings attainable by the warning zone method. Compared to other decision rules, the warning zone method is much simpler than the theoretically optimal Bayesian revision method, but uses more information than the Markovian control limit method. Numerical comparison of results shows that the warning zone method usually captures most of the available cost savings, even in cases where the Markovian control limit method does not perform well.

Learning curves have important implications for managerial planning and control. This paper considers the effect of learning on managerial planning models for productmix problems that can be handled by a linear-programming formulation. An approach to incorporate learning effects in the planning model is proposed in this paper. The feasibility and superiority of the proposed approach over the traditional approach are discussed through the use of a linear-programming problem.

The stochastic demand cost-volume-profit (CVP) model has recently received considerable attention. For this model, management must determine optimal production prior to knowing the actual demand, a stochastic variable with known distribution. Management must choose the production quantity to balance prospects for sales revenue against risks of losses from shortages and from unsold items. This paper develops an expected return on investment criterion model for determining the optimal production quantity. Formulas and solution methods applicable to general demand distributions are obtained. A special solution technique for normally distributed demand is presented. The resulting choice criterion offers the advantages inherent in return rate methods. In addition, compared to a profit maximization approach, the expected rate of return on investment criterion is more widely applicable. Resume. Le modele de demande stochastique cout-volume-profit (CVP), a recemment recu considerablement d'attention. Avec ce modele, la gestion doit determiner la production optimale avant de connaitre la demande actuelle, une variable stochastique ayant une distribution connue. La gestion doit choisir la quantite a produire afin d'equilibrer les perspectives de ventes et les risques de pertes resultant des penuries et des unites non vendues. Cet article developpe un modele base sur le rendement espere du capital investi pour determiner la quantite optimale a produire. On obtient des formules et des methodes pouvant s'appliquer a des distributions de demande generale. Une technique de solution particuliere pour une demande distribuee selon une loi normale est presentee. Ce modele offre les avantages inherents aux methodes du taux de rendement. De plus, comparativement a l'approche de la maximisation du profit, le critere du taux de rendement espere du capital investi, est applicable dans beaucoup plus de situations.