On Measuring the Value of a Nonmarket Good Using Market Data

We use line integral theory to lay out in a more general theoretical framework the conditions under which it is possible to measure with market data the welfare effects of a change in a nonmarket good. We present in detail a numerical method of measuring the value of nonmarket goods using market data, under either weak neutrality or weak complementarity. Our numerical method is more flexible than the existing analytical method because it can be used with any well-behaved Marshallian demand function, and can be used even when the willig condition does not hold.     

Manipulating uncertainty

Uncertainty about the distributional incidence of policy reforms may, if it impinges selectively on particular subsets of voters, alter the direction of the majority vote. This possibility should be a matter of special concern when subject to potential manipulation by a purposeful agent such as a Leviathan-like bureaucracy. This paper discusses a constitutional defense against such prospect. This paper was prepared for a conference on “Constitutional Status Quo and Prospects for Change” held at George Mason University in April, 1994. I am grateful to participants in that conference and to my colleagues at Nova, especially to Mário Páscoa, for their comments and criticisms. I also benefited from comments of an anonymous referee. Responsibility for errors remains with me.     

EARNINGS EXPECTATIONS, FIRM SIZE, AND THE INFORMATIVENESS OF STOCK PRICES

The notion that prices impound a wide array of information, including market expectations, has led to earnings forecast models conditioned on prices. Yet, presumably, analysts' forecasts capture both public information and certain private information not previously impounded in prices. Accordingly, price-based models are seemingly an inefficient, and less effective, source of expecta-tions. This article investigates this hypothesis using financial analysts', price-based, and naive forecasts. Results indicate that analysts' forecasts (1) are at least as accurate as price-based and naive models, and (2) yield better expectations for market tests relating returns and earnings. These inferences are robust across different information environments. The evidence suggests that analysts either possess private information or are more effective information processors, or both.     

Limiting Auditors' Liability: The Potential Consequences

The recent revival of interest in the issue of limiting auditors' liability raises questions about the potential effect of such a limitation on auditors' performance. This paper considers the consequences of limited liability from the perspectives of contracting theory and economic arguments. We examine the potential effect of a reduction in auditors' liability on the standard of care or quality of service they provide, emphasising the "calculus of negligence" concept used by Australian courts. We consider the potential impact of reduced liability on the auditor's decision to shirk responsibilities (the moral hazard problem) and on the value placed on audit services. The analysis shows that placing a statutory cap on auditors' liability has the potential to reduce the effectiveness of bonding mechanisms; provide an avenue for divergent behaviour; lower the level of care provided by auditors; and decrease the value of audit services.