Constrained allocation problems with single-peaked preferences: An axiomatic analysis

We introduce a new class of problems that contains two existing classes: allocation problems with single-peaked preferences and bankruptcy problems. On this class, we analyze the implications of well-known properties such as Pareto optimality, strategy-proofness, resource-monotonicity, no-envy, equal treatment of equals, and two new properties we introduce, hierarchical no-envy and independence of nonbinding constraints. Unlike earlier literature, we consider rules that allow free-disposability. We present characterizations of a rule we introduce on this domain. We relate this rule to well-known rules on the aforementioned subdomains. Based on this relation, we present a characterization of a well-known bankruptcy rule called the constrained equal awards rule. Received: 22 June 2000/Accepted: 21 March 2002 This paper is based on the first chapter of my Ph.D. thesis submitted to the University of Rochester. I wish to thank my advisor, William Thomson, for helpful comments and suggestions.     

Goodness‐of‐fit methods for matched case‐control studies

The authors propose graphical and numerical methods for checking the adequacy of the logistic regression model for matched case‐control data. Their approach is based on the cumulative sum of residuals over the covariate or linear predictor. Under the assumed model, the cumulative residual process converges weakly to a centered Gaussian limit whose distribution can be approximated via computer simulation. The observed cumulative residual pattern can then be compared both visually and analytically to a certain number of simulated realizations of the approximate limiting process under the null hypothesis. The proposed techniques allow one to check the functional form of each covariate, the logistic link function as well as the overall model adequacy. The authors assess the performance of the proposed methods through simulation studies and illustrate them using data from a cardiovascular study.     

International Tax Competition: A Case for International Cooperation in Globalization

The liberalization of international financial flows and foreign direct investment has induced countries to use diverse measures to attract inflow of foreign capital and foreign direct investment, which is expected to have a positive effect on the growth of GDP and thus a positive effect on social welfare. Tax exemption, reduction of tax rate, tax holiday, or diverse subsidies are some of the most important measures used. In this paper we study international tax cooperation, i.e., countries change and especially reduce tax rate for corporate income or for asset revenues to attract inflow of foreign direct investment. Both theoretical and empirical studies have shown the sensibility of foreign direct investment decision with respect to tax rate differences between home countries and host countries. In general, more inflow of foreign direct investment can be expected if the tax rate of the home country is lower than that of foreign countries. This is the main reason for international tax cooperation. In this paper we propose a simple model to prove the sub-optimal Nash non cooperative solution in a two-country tax-competition game. The model shows that international tax cooperation can improve welfare of the participating countries. How to reach a cooperative solution for an international tax competition game (ITCG) is therefore an important issue for further discussions and studies. International institutions can play a crucial role to reach international tax cooperation or international tax harmonization.     

A Bayesian Hierarchical Model for the Evaluation of a Website

Consider a website and the surfers visiting its pages. A typical issue of interest, for example while monitoring an advertising campaign, concerns whether a specific page has been designed successfully, i.e. is able to attract surfers or address them to other pages within the site. We assume that the surfing behaviour is fully described by the transition probabilities from one page to another, so that a clickstream (sequence of consecutively visited pages) can be viewed as a finite-state-space Markov chain. We then implement a variety of hierarchical prior distributions on the multivariate logits of the transition probabilities and define, for each page, a content effect and a link effect. The former measures the attractiveness of the page due to its contents, while the latter signals its ability to suggest further interesting links within the site. Moreover, we define an additional effect, representing overall page success, which incorporates both effects previously described. Using WinBUGS, we provide estimates and credible intervals for each of the above effects and rank pages accordingly.