POLITICAL REPUTATIONS AND CAMPAIGN PROMISES

We analyze conditions under which candidates' reputations may affect voters' beliefs over what policy will be implemented by the winning candidate of an election. We develop a model of repeated elections with complete information in which candidates are purely ideological. We analyze an equilibrium in which voters' strategies involve a credible threat to punish candidates who renege on their campaign promises and in which all campaign promises are believed by voters and honored by candidates. We characterize the maximal credible campaign promises and find that the degree to which promises are credible in equilibrium is an increasing function of the value of a candidate's reputation. (JEL: D8)     

Joint Ordering and Pricing Strategies for Managing Substitutable Products

Starr and Rubinson (1978) develop a model to establish the relationship between product demand and relative prices. The notion of relative prices motivates us to consider a situation in which a retailer would either charge the same retail price for all products if he adopts a ‘fixed’ pricing strategy or charge different prices for different products if he adopts a ‘variable’ pricing strategy. In this paper, we develop a base model with deterministic demand that is intended to examine how a retailer should jointly determine the order quantity and the retail price of two substitutable products under the fixed and variable pricing strategies. Our analysis indicates that the optimal retail price under the variable pricing strategy is equal to the optimal retail price under the fixed pricing strategy plus or minus an adjustment term. This adjustment term depends on product substitutability and price sensitivity. We also present two different extensions of our base model. In the first extension, our analysis indicates that the underlying structure of the optimal retail price and order quantity is preserved when there is a limit on the total order quantity. The second extension deals with the issue of retail competition. Relative to the base case, we show that the underlying structure of the optimal retail price and order quantity is preserved in a duopolistic environment. Moreover, our analysis suggests that both retailers would adopt the variable pricing strategy at the equilibrium.     

A Periodic Inventory Model for Stocking Modular Components

We study the benefit obtained by exploiting modular product design in fulfilling exogenous demand for both a complete assembly and its components in a service parts inventory system. Our goal is to reduce overall service system costs by allowing assembly and/or disassembly (A/D) to occur at some unit cost per A/D action. In an extensive set of computational experiments, we compare a naïve stocking and operating policy that treats all items independently and ignores the modular product structure and related A/D capability to the optimal base stock policy, and to a policy that allows A/D from the naïve stocking levels. While extensive computational analysis shows that the optimal base stock policy improves the system cost between 3 to 26% over the naïve approach, simply allowing A/D from the naïve stocking levels captures a significant portion (an average of 67%) of the naïve–optimal gap. Our computational results demonstrate that the optimization shifts the component‐assembly mix from the naïve levels and that limiting A/D capacity affects this mix. Limiting A/D capacity can actually increase the expected number of A/D actions (versus the uncapacitated case), since the optimization shifts stocking levels to reduce the probability that “too many” actions will be required.     

Multistage sampling for latent variable models

I consider the design of multistage sampling schemes for epidemiologic studies involving latent variable models, with surrogate measurements of the latent variables on a subset of subjects. Such models arise in various situations: when detailed exposure measurements are combined with variables that can be used to assign exposures to unmeasured subjects; when biomarkers are obtained to assess an unobserved pathophysiologic process; or when additional information is to be obtained on confounding or modifying variables. In such situations, it may be possible to stratify the subsample on data available for all subjects in the main study, such as outcomes, exposure predictors, or geographic locations. Three circumstances where analytic calculations of the optimal design are possible are considered: (i) when all variables are binary; (ii) when all are normally distributed; and (iii) when the latent variable and its measurement are normally distributed, but the outcome is binary. In each of these cases, it is often possible to considerably improve the cost efficiency of the design by appropriate selection of the sampling fractions. More complex situations arise when the data are spatially distributed: the spatial correlation can be exploited to improve exposure assignment for unmeasured locations using available measurements on neighboring locations; some approaches for informative selection of the measurement sample using location and/or exposure predictor data are considered.     

新世纪管理与组织研究面临的挑战

近一个世纪来,管理理论和组织学研究促进了一系列根本性改变的表述,使得管理者们在其职业生涯中必须大量地学习、学习、再学习。人们会认为,在大学商学院里,应该是组织学研究者们而不是其他领域的专家,引导着适应变化环境的新范式的发展。然而,本文将指出组织学范式的研究与经营实践迄今为止基本上是相互分离的。本文还将详细说明,尽管存在着这种分离,经营范式文献对组织学研究和引导它的理论范式还是产生了相当大的影响,特别是在这个“实用知识”越来越受重视的年代。     

Einkommen, Gesundheit und Mortalität in Deutschland, Grossbritannien und den USA

The paper examines the effect of income on mortality with respect to different health statuses and institutional characteristics of the health care system in the USA, Great Britain and West Germany. It is hypothesized that the nature of the theoretical contribution of income in explaining mortality risks changes on whether good or poor health is considered. Taking into account that the health care systems of the countries in question vary by their degree of household out-of-pocket expenditure, we expect an association between income and mortality that differs by country. The analysis is based on the German Socio-economic Panel (GSOEP), the British Household Panel Study (BHPS), and the Panel Study of Income Dynamics (PSID). The effect of income on mortality is found to be weakest when medical services are sought in the presence of poor health within the framework of a national health insurance that renders free primary health care (Great Britain, Germany). The effect is strongest when the provision of primary health care depends strongly on private expenditures (USA).     

Adaptive Estimation Using Weighted Least Squares

This paper proposes an adaptive estimator that is more precise than the ordinary least squares estimator if the distribution of random errors is skewed or has long tails. The adaptive estimates are computed using a weighted least squares approach with weights based on the lengths of the tails of the distribution of residuals. Smaller weights are assigned to those observations that have residuals in the tails of long-tailed distributions and larger weights are assigned to observations having residuals in the tails of short-tailed distributions. Monte Carlo methods are used to compare the performance of the proposed estimator and the performance of the ordinary least squares estimator. The estimates that were studied in this simulation include the difference between the means of two populations, the mean of a symmetric distribution, and the slope of a regression line. The adaptive estimators are shown to have lower mean squared errors than those for the ordinary least squares estimators for short-tailed, long-tailed, and skewed distributions, provided the sample size is at least 20. The ordinary least squares estimator has slightly lower mean squared error for normally distributed errors. The adaptive estimator is recommended for general use for studies having sample sizes of at least 20 observations unless the random errors are known to be normally distributed.