Optimal demogrants and taxes in a federal welfare state

This paper provides a framework for the simultaneous calculation of optimal commodity and income taxes in a federal framework with demogrants. The optimal income tax rate is shown to depend on a range of demographic and economic variables. Alternative models of fiscal federalism are proposed, and their implications for optimal commodity taxes and demogrants considered. Illustrative empirical evidence on Indian data confirms sensitivity of tax magnitudes to federal specification, and to assumptions about resource transfer between the federal and provincial authorities.Much of the work in this paper was done during my visit to the Scuola Superiore, S. Anna in Pisa (Italy) in the summer of 1991. The paper was revised during my visit to the Economics Research Centre, University of Western Australia, during May/June 1992. I am grateful to the staff and students of both institutions for their hospitality. I also thank two anonymous referees for helpful remarks. The disclaimer applies.     

Into the Community: A Comparison of Care Management and Traditional Approaches to Resettlement1

The resettlement of people with learning disabilities (mental handicap) from long-stay hospitals has been under way for a number of years in England. This process has generally been dominated by the exigencies of the available services. A needs-led approach, emphasized in recent community care legislation, in which new services are sought on the basis of the specific requirements of service users, has been used infrequently for this purpose. This paper compares the process of implementing a needs-led care management approach to resettlement with the implementation of a more traditional service-led approach. It also suggests some important lessons for the application of a needs-led approach to hospital resettlement.     

A meta-analytic framework to adjust for bias in external control studies

While randomized controlled trials (RCTs) are the gold standard for estimating treatment effects in medical research, there is increasing use of and interest in using real-world data for drug development. One such use case is the construction of external control arms for evaluation of efficacy in single-arm trials, particularly in cases where randomization is either infeasible or unethical. However, it is well known that treated patients in non-randomized studies may not be comparable to control patients—on either measured or unmeasured variables—and that the underlying population differences between the two groups may result in biased treatment effect estimates as well as increased variability in estimation. To address these challenges for analyses of time-to-event outcomes, we developed a meta-analytic framework that uses historical reference studies to adjust a log hazard ratio estimate in a new external control study for its additional bias and variability. The set of historical studies is formed by constructing external control arms for historical RCTs, and a meta-analysis compares the trial controls to the external control arms. Importantly, a prospective external control study can be performed independently of the meta-analysis using standard causal inference techniques for observational data. We illustrate our approach with a simulation study and an empirical example based on reference studies for advanced non-small cell lung cancer. In our empirical analysis, external control patients had lower survival than trial controls (hazard ratio: 0.907), but our methodology is able to correct for this bias. An implementation of our approach is available in the R package ecmeta .     

Risk,Ambiguity, and Decision Choice: Some Additional Evidence*

This paper extends prior research by jointly assessing the roles of risk attitude and tolerance for ambiguity in predicting choice. An experiment examined the effects of these variables on decisions made in four different scenarios. The four scenarios (treatment combinations) were generated by manipulating risk and ambiguity into two levels (high and low). The context was defined in terms of a sample size selection problem. The second issue explored was the effect of attitudes toward risk and ambiguity on decision confidence. The results indicate that (1) both risk attitude and ambiguity intolerance determined choice behavior, (2) the roles of these individual attitudes depend on the levels of the two treatment variables of risk and ambiguity, (3) the presence of ambiguity accentuates the perception of risk in individual subjects, and (4) decision makers who are less risk averse, and have more tolerance for ambiguity, display greater confidence in their choice. The paper discusses some of the managerial implications of the results.     

The Design of Feature‐Limited Demonstration Software: Choosing the Right Features to Include

Today, software supports many important tasks in a variety of industries. In the specialized nature of these environments, a common problem faced by software vendors is to correctly signal the true value of a software product to the end users. For example, telecommunications equipment manufacturers design complex software for important functions like provisioning new users in the network. These software products automate various functions that would otherwise need to be done manually. In order to enable potential customers—telecommunications providers—to evaluate and recognize the full value of the product, equipment vendors often provide a free, feature‐limited version of the product to the customer. As the specific features included in the feature‐limited version influence whether the full product is purchased or not, it is essential that the features included in the feature‐limited version be selected judiciously. While the importance of identifying the best set of features has been well recognized, there has been little research to date that systematically addresses this fundamental business decision. This study fills this gap in the literature by providing an objective approach to the design of demonstration software. We illustrate the benefits of our approach through a case study involving the design of a feature‐limited demo for a wireless telecommunications equipment manufacturer.