The Work Program and Priorities of the AASB

The workload of the AASB has not diminished since adoption of the IASB's standards and will not diminish in the foreseeable future. However, the nature of the AASB's work has changed, with a particular focus on the public-sector and private not-for-profit sector priorities.     

Reinforcement Learning and Savings Behavior

We show that individual investors over‐extrapolate from their personal experience when making savings decisions. Investors who experience particularly rewarding outcomes from 401(k) saving—a high average and/or low variance return—increase their 401(k) savings rate more than investors who have less rewarding experiences. This finding is not driven by aggregate time‐series shocks, income effects, rational learning about investing skill, investor fixed effects, or time‐varying investor‐level heterogeneity that is correlated with portfolio allocations to stock, bond, and cash asset classes. We discuss implications for the equity premium puzzle and interventions aimed at improving household financial outcomes.     

In Defense of Usury Laws

Usury law is often criticized by economists for curtailing lending and thus creating deadweight costs. This paper shows that if moral hazard leads to credit rationing, a just-binding usury law creates a deadweight gain.  This property also holds in most market-clearing equilibria. Independent of social insurance benefits, or curbing present-biased preferences, interest rate caps have merit.     

Decision theory analysis of audit discovery sampling*

Abstract. Discovery sampling is a frequently used auditing technique. The objective of discovery sampling is to decide whether to accept or reject an audit population for which acceptance is appropriate only if the occurrence rate of serious errors is very low. This objective is met by auditing a sample and accepting only if the sample is free of serious errors. This paper first develops a Bayesian decision theory approach to the discovery sampling problem. Using this approach the auditor optimizes sampling effort according to a decision model that explicitly includes such factors as risk of failure of accepting too high an error rate, losses from wrong decisions, sampling costs, and prior distribution of the error rate. The form of the loss function used includes both linear and quadratic loss functions as special cases. Methods and formulas applicable to various prior distributions for the error rate are obtained. Detailed results are derived for two state-prior and gamma-prior distributions. A minimax approach that removes the need to elicit a complete prior distribution is then developed. Explicit formulas are obtained for both the admissible sample size range and for the minimax sample size. A comparison of results indicates that the minimax approach is nearly as efficient as approaches that require elicitation of prior problem rate distributions. Further analysis generalizes the methods by showing that for the Bayesian and minimax methods, analytical results can be derived for various forms of loss functions. Résumé. Le sondage de dépistage est une technique fréquemment utilisée en vérification qui a pour objectif de déterminer s'il faut accepter ou rejeter une population pour laquelle l'acceptation n'est appropriée que si la fréquence d'erreurs graves est très faible. L'objectif est réalisé au moyen de la vérification d'un échantillon et de son acceptation seulement si l'échantillon est exempt d'erreurs graves. L'auteur met d'abord au point une méthode inspirée de la théorie bayesienne de la décision, adaptée au problème du sondage de dépistage. En utilisant cette méthode, le vérificateur optimise le travail d'échantillonnage conformément à un modèle de décision qui comprend explicitement des facteurs tels que le risque d'échec ou le risque d'acceptation d'un taux d'erreur trop élevé, les pertes attribuables à de mauvaises décisions, les coûts d'échantillonnage et la distribution a priori du taux d'erreur. Des formes de fonction de perte utilisées, celles linéaires et quadratiques constituent des cas spéciaux. L'auteur obtient des méthodes et des formules applicables aux diverses distributions a priori du taux d'erreur. Il dérive les résultats analytiques pour les distributions a priori binômiale et gamma. L'auteur met ensuite au point une méthode minimax supprimant la nécessité d'obtenir une distribution a priori complète. Il obtient des formules explicites pour la fourchette de tailles d'échantillons admissibles ainsi que pour la taille de l'échantillon minimax. Une comparaison des résultats indique que la méthode minimax est presque aussi efficace que les méthodes qui exigent l'obtention de distributions a priori de taux d'erreurs. Le prolongement de l'analyse permet de généraliser les méthodes; il démontre en effet que pour les méthodes bayesienne aussi bien que minimax, les résultats analytiques peuvent être dérivés pour diverses formes de fonctions de perte.     

Is it an offence to overcharge?

This paper considers whether a trader commits an offence when he makes a mistake and overcharges a customer. It examines the offences found in section 20 of the Consumer Protection Act 1987 - as defined in section 21(1)(a) - and looks at the effect of a recent decision of the appeal courts.     

Risky Debt,Investment Incentives,and Reputation in a Sequential Equilibrium

The agency relationship of corporate insiders and bondholders is modeled as a dynamic game with asymmetric information. The incentive effect of risky debt on the investment policy of a levered firm is studied in this context. In a sequential equilibrium of the model, a concept of reputation arises endogenously resulting in a partial resolution of the classic agency problem of underinvestment. The incentive of the firm to underinvest is curtailed by anticipation of favorable rating of its bonds by the market. This anticipated pricing of debt is consistent with rational expectations pricing by a competitive bond market and is realized in equilibrium. Some empirical implications of the model for bond rating, debt covenants, and bond price response to investment announcements are explored.