Strategic Choice of Variability in Multiround Contests and Contests with Handicaps

Variability can be an important strategic variable in a contest. We study optimal strategies involving choice of variability in contests with fixed and probabilistic targets, one-round and multiround contests, contests with and without handicaps, and situations where one contestant can modify variability as well as those in which all contestants have this opportunity. A contestant should maximize variability in a weak position (low mean, high handicap, or low previous performance) and minimize variability in a strong position. In some cases, only these extremes should be used. In other cases, intermediate levels of variability are optimal when the contestant's position is neither too weak nor too strong.     

Token Presence or Substantive Participation? A Study of Labor Trustees on Pension boards

In contrast to their absence from corporate boards in North America, labor representatives do have a seat on many pension boards. Given the lack of research on the role of labor participation in these fora, this study reports findings from a survey of labor trustees. We find that labor trustees make greater contributions to procedure-oriented processes such as information sharing, rule-making and rule interpretation; and, fewer contributions to investment-oriented processes such as investment decisions, fund performance and manager selection. Gender does not seem to matter in explaining participation in board activities. Accountability in terms of a requirement to report back to their union did increase labor trustee contribution but only to procedural issues, not investment issues. Short board tenure, lack of multiple labor seats and lack of training appear to limit labor trustees’ contribution to investment-based issues. Prior exposure to pension issues, and longer tenure appear to increase contributions to procedure-based issues. Exclusionary board dynamics hinder both types of contributions by labor trustees. These findings suggest that labor trustees do take advantage of their position to make procedural contributions but they find it hard to expand into newer, non-traditional roles such as investment-related activities of the Board.     

A synthesis of stein-rule and mixed regression procedures inlinear regression models under non-normality

Stein-rule philosophy and mixed regression technique are combined to develop two families of improved estimators of regression coefficients in the linear regression model under incomplete prior information. The properties of these estimators are studied when disturbances are small and non-normal. Conditions for their dominance over mixed regression estimator are derived taking risk as the criterion for performance.     

Asymmetric endogenous prize contests

We consider a two-player contest in which one contestant has a headstart advantage, but both can exert further effort. We allow the prize to depend on total performance in the contest and consider the respective cases in which efforts are productive and destructive of prize value. When the contest success function takes a logit form, and marginal cost is increasing in effort, we show that a Nash equilibrium exists and is unique both in productive and destructive endogenous prize contests. In equilibrium, the underdog expends more resources to win the prize, but still his probability of winning remains below that of the favorite. In a productive contest, the underdog behaves more aggressively and wins the prize more often in comparison to a fixed-value contest. Thus, the degree of competitive balance—defined as the level of uncertainty of the outcome—depends upon the (fixed or endogenous) prize nature of the contest.     

Spatial estimation and rescaled spatial bootstrap approach for finite population

In this study, an attempt has been made to improve the sampling strategy incorporating spatial dependency at estimation stage considering usual aerial sampling scheme, such as simple random sampling, when the underlying population is finite and spatial in nature. Using the distances between spatial units, an improved method of estimation, viz. spatial estimation procedure, has been proposed for the estimation of finite population mean. Further, rescaled spatial bootstrap (RSB) methods have been proposed for approximately unbiased estimation of variance of the proposed spatial estimator (SE). The properties of the proposed SE and its corresponding RSB methods were studied empirically through simulation.     

A class of k-sample distribution-free tests for location against ordered alternatives

This paper introduces a new class of distribution-free tests for testing the homogeneity of several location parameters against ordered alternatives. The proposed class of test statistics is based on a linear combination of two-sample U-statistics based on subsample extremes. The mean and variance of the test statistic are obtained under the null hypothesis as well as under the sequence of local alternatives. The optimal weights are also determined. It is shown via Pitman ARE comparisons that the proposed class of test statistics performs better than its competitor tests in case of heavy-tailed and long-tailed distributions     

Information theoretic approaches to income density estimation with an application to the U.S. income data

The size distribution of income is the basis of income inequality measures which in turn are needed for evaluation of social welfare. Therefore, proper specification of the income density function is of special importance. In this paper, using information theoretic approach, first, we provide a maximum entropy (ME) characterization of some well-known income distributions. Then, we suggest a class of flexible parametric densities which satisfy certain economic constraints and stylized facts of personal income data such as the weak Pareto law and a decline of the income-share elasticities. Our empirical results using the U.S. family income data show that the ME principle provides economically meaningful and a very parsimonious and, at the same time, flexible specification of the income density function.     

Performance of nonparametric multiple comparison tests under heteroscedasticity,dependency, and skewed error distribution

In this article, an extensive Monte Carlo simulation study is conducted to evaluate and compare nonparametric multiple comparison tests under violations of classical analysis of variance assumptions. Simulation space of the Monte Carlo study is composed of 288 different combinations of balanced and unbalanced sample sizes, number of groups, treatment effects, various levels of heterogeneity of variances, dependence between subgroup levels, and skewed error distributions under the single factor experimental design. By this large simulation space, we present a detailed analysis of effects of the violations of assumptions on the performance of nonparametric multiple comparison tests in terms of three error and four power measures. Observations of this study are beneficial to decide the optimal nonparametric test according to requirements and conditions of undertaken experiments. When some of the assumptions of analysis of variance are violated and number of groups is small, use of stepwise Steel-Dwass procedure with Holm's approach is appropriate to control type I error at a desired level. Dunn's method should be employed for greater number of groups. When subgroups are unbalanced and number of groups is small, Nemenyi's procedure with Duncan's approach produces high power values. Conover's procedure successfully provides high power values with a small number of unbalanced groups or with a greater number of balanced or unbalanced groups. At the same time, Conover's procedure is unable to control type I error rates.     

The new German citizenship law and its impact on German demographics: research notes

The processes of marginalization and inclusion of immigrants vary widely among industrialized welfare states. Models of citizenship, as a mechanism of both inclusion and exclusion, shape, to a large degree, the outcome of these processes. They affect the way immigrant and ethnic groups identify themselves within the mainstream society. This research note discusses whether or not institutional approaches to naturalization developed in the United States apply to the German case in the wake of the German citizenship reform of 1999. It also demonstrates how the introduction of birthright citizenship has caused a dramatic change in such demographic trends as the number of births to immigrants at both the federal and local levels. Berlin will provide the context at the local level for the impact of the citizenship reform on local official statistics.