CORRUPTION: TOP DOWN OR BOTTOM UP?

This article studies the impact of corruption on an economy with a hierarchical government. In particular, we study whether centralizing corruption within the higher level of government increases or decreases the total amount of corruption. We show that when the after-tax relative profitability of the formal sector as compared to that of the informal sector is high enough, adding a layer of government increases the total amount of corruption. By contrast, for high-enough public wages and/or an efficient monitoring technology of the bureaucratic system, centralization of corruption at the top of the government hierarchy redistributes bribe income from the lower level to the upper level. In the process, total corruption is reduced and the formal sector of the economy expands.     

Examples of the use of an equivalence theorem in constructing optimum experimental designs for random-effects nonlinear regression models

The problem considered is that of finding an optimum measurement schedule to estimate population parameters in a nonlinear model when the patient effects are random. The paper presents examples of the use of sensitivity functions, derived from the General Equivalence Theorem for D-optimality, in the construction of optimum population designs for such schedules. With independent observations, the theorem applies to the potential inclusion of a single observation. However, in population designs the observations are correlated and the theorem applies to the inclusion of an additional measurement schedule. In one example, three groups of patients of differing size are subject to distinct schedules. Numerical, as opposed to analytical, calculation of the sensitivity function is advocated. The required covariances of the observations are found by simulation.     

Horwitz's rule, transforming both sides and the design of experiments for mechanistic models

Summary. The paper develops methods for the design of experiments for mechanistic models when the response must be transformed to achieve symmetry and constant variance. The power transformation that is used is partially justified by a rule in analytical chemistry. Because of the nature of the relationship between the response and the mechanistic model, it is necessary to transform both sides of the model. Expressions are given for the parameter sensitivities in the transformed model and examples are given of optimum designs, not only for single-response models, but also for experiments in which multivariate responses are measured and for experiments in which the model is defined by a set of differential equations which cannot be solved analytically. The extension to designs for checking models is discussed.     

Catalogue of Group Structures for Three-level Fractional Factorial Designs

Taguchi (1959) introduced the concept of split-unit design to sort the factors into different groups depending upon the difficulties involved in changing the levels of factors. Li et al. (1991) renamed it as split-plot design. Chen et al. (1993) have given a catalogue of small designs for two- and three-level fractional factorial designs pertaining to a single type of factors. Aggarwal et al. (1997) have given a catalogue of group structure for two-level fractional factorial designs developed under the concept of split-plot design. In this paper, an algorithm has been developed for generating group structure and possible allocations for various 3^n-k fractional factorial designs.     

Job displacement effects of Canadian immigrants by country of origin and occupation

"Some previous Canadian studies have shown that considering the labor market as a whole and also pooling all immigrants as a group, immigrants do not have any job displacement effects on the Canadian born. This study presents some new evidence. It disaggregates immigrants by country of origin and by occupation groups and provides an analysis of job displacement effects of immigrants on the native-born Canadians by these dimensions. The study finds that (1) U.S. immigrants and the Canadians are substitutes [for] competing groups in the labor market and the effect is quite significant; (2) Canadians and Europeans are competing groups in certain occupations, while they have complementary skills in others; and (3) immigrants from the Third World and the Canadians are slightly competing groups in certain occupations."     

A Network-Based Measure of the Socio-Economic Roots of the Migration Flows

Social Indicators Research - This paper provides a unified view for defining a measure of the reasons behind migration flows whose nature is of social and economic type. To this aim, worldwide...     

Never easy to say “sorry”: Exploring the interplay of crisis involvement,brand image,and message appeal in developing effective corporate apologies

This study examines how the interplay among crisis involvement, brand image, and message appeal impacts the effectiveness of an apology in the context of a corporate crisis. To determine apology effectiveness, a 2 (crisis involvement: high vs. low) × 2 (brand image: symbolic vs. functional) × 2 (message appeal type: emotional vs. informational) experimental design was employed. The results demonstrate that the three-way interaction is significant, especially in the low-crisis involvement condition. The study concludes with a discussion of theoretical and practical implications and directions for future research.     

A new algorithm to estimate monotone nonparametric link functions and a comparison with parametric approach

The generalized linear model (GLM) is a class of regression models where the means of the response variables and the linear predictors are joined through a link function. Standard GLM assumes the link function is fixed, and one can form more flexible GLM by either estimating the flexible link function from a parametric family of link functions or estimating it nonparametically. In this paper, we propose a new algorithm that uses P-spline for nonparametrically estimating the link function which is guaranteed to be monotone. It is equivalent to fit the generalized single index model with monotonicity constraint. We also conduct extensive simulation studies to compare our nonparametric approach for estimating link function with various parametric approaches, including traditional logit, probit and robit link functions, and two recently developed link functions, the generalized extreme value link and the symmetric power logit link. The simulation study shows that the link function estimated nonparametrically by our proposed algorithm performs well under a wide range of different true link functions and outperforms parametric approaches when they are misspecified. A real data example is used to illustrate the results.