Measuring the Utility of Losses by Means of the Tradeoff Method

This paper investigates the shape of the utility function for losses. From a rational point of view it can be argued that utility should be concave. Empirically, measurements of the utility for losses show mixed results but most evidence supports convex rather than concave utilities. However, these measurements use methods that are either biased by the certainty effect or require complex parametrical estimations. This paper re-examines utility for losses, avoiding the mentioned pitfalls by using the tradeoff method. We find that utility for losses is convex. This is contrary to common assumption in the economics literature. Also, we investigate properties of the tradeoff method showing a new violation of procedure invariance. Our findings demonstrate that diminishing sensitivity is an important phenomenon for utility elicitation.     

LEADERSHIP BY EXAMPLE IN THE WEAK‐LINK GAME

We investigate the effects of leadership in a four‐player weak‐link game. A weak‐link game is a coordination game with multiple Pareto‐ranked Nash equilibria. Because the more efficient equilibria involve a degree of strategic uncertainty groups typically find it difficult to coordinate on more efficient equilibria. We wanted to see whether leadership by example, in the form of one player acting publicly before the rest of the group, could help groups do better. Our results suggest that leadership can increase efficiency but is far from being a guarantee of success. Specifically, in a significant number of groups we observed successful leadership and increased efficiency, but in most groups efficiency was low despite the efforts of leaders. We did not find any difference between voluntary leaders and leaders that are randomly assigned. (JEL C72, H41)     

Comparison of Regression Curves with Censored Responses

Abstract.  In this article, we introduce a procedure to test the equality of regression functions when the response variables are censored. The test is based on a comparison of Kaplan–Meier estimators of the distribution of the censored residuals. Kolmogorov–Smirnov- and Cramér–von Mises-type statistics are considered. Some asymptotic results are proved: weak convergence of the process of interest, convergence of the test statistics and behaviour of the process under local alternatives. We also describe a bootstrap procedure in order to approximate the critical values of the test. A simulation study and an application to a real data set conclude the paper.     

Dynamic Prediction by Landmarking in Event History Analysis

Abstract.  This article advocates the landmarking approach that dynamically adjusts predictive models for survival data during the follow up. This updating is achieved by directly fitting models for the individuals still at risk at the landmark point. Using this approach, simple proportional hazards models are able to catch the development over time for models with time-varying effects of covariates or data with time-dependent covariates (biomarkers). To smooth the effect of the landmarking, sequences of models are considered with parametric effects of the landmark time point and fitted by maximizing appropriate pseudo log-likelihoods that extend the partial log-likelihood to cover the landmarking approach.     

CENTRAL BANK SECRECY, INTEREST RATES, AND MONETARY CONTROL

We construct a dynamic rational expectations model of the federal funds and deposit market that provides a rationale for central bank secrecy about current monetary aggregate objectives. In this analysis, the Trading Desk values secrecy because it reduces the influence of monetary control policy on interest rates. We then examine actual U.S. experience with monetary control and determine that the reserve bias predicted by the model is present in the data from 1978 to 1985. Finally, we demonstrate that central bank secrecy may not lower the value of commercial banks.     

Erratum

In our article entitled "The Social Bases of Environmental Concern:A Review of Hypotheses, Explanations and Empirical Evidence"(POQ 44:181–97), two rows of correlations were reversedin Table 1. Under the study by Van Liere and Dunlap, 1978, figuresfor the environmental funding scale appear where figures forthe environmental regulations scale should be, and vice versa.We regret the error and hope it has not caused undue confusionfor anyone using these data.