Distribution and Poverty Impacts of Tax Structure Reform in Developing Countries: How Little We Know

The past two decades have witnessed widespread reforms of tax structures in developing countries. This article reviews available evidence on the effects of various taxes, and hence of tax structure reform, on distribution and the poor. Taxes on exports and goods consumed especially by the poor (e.g. kerosene) are the most consistently found to be regressive, whereas taxes on ‘luxury’ items such as cars, beverages and alcohol are the most likely to be progressive. Sales taxes are slightly more progressive, or less regressive, than taxes on imports. The reforms implemented are therefore unlikely to have worsened the effects of the tax structure on the poor.     

D-optimal mixture component-amount designs for quadratic and cubic models

When the total amount of a mixture of ingredients needs to be taken into account (in addition to the composition of its ingredients), an experimental design requires several levels of the amount. Designs for such situations are discussed, and D-optimal choices are made for fitting quadratic and cubic models, for various numbers of experimental units.     

Inspection errors in graff-roeloffs modification of hierarchical dorfman screening procedures

Graff and Roeloffs' (1972) modification of the Dorfman (1943) screening procedure, and their analysis of the effects of inspection error on properties of the procedure, is extended to hierarchical procedures, using the results of Kotz and Johnson (1982).     

Modeling Supply Chain Dynamics: A Multiagent Approach*

A global economy and increase in customer expectations in terms of cost and services have put a premium on effective supply chain reengineering. It is essential to perform risk-benefit analysis of reengineering alternatives before making a final decision. Simulation provides an effective pragmatic approach to detailed analysis and evaluation of supply chain design and management alternatives. However, the utility of this methodology is hampered by the time and effort required to develop models with sufficient fidelity to the actual supply chain of interest. In this paper, we describe a supply chain modeling framework designed to overcome this difficulty. Using our approach, supply chain models are composed from software components that represent types of supply chain agents (e.g., retailers, manufacturers, transporters), their constituent control elements (e.g., inventory policy), and their interaction protocols (e.g., message types). The underlying library of supply chain modeling components has been derived from analysis of several different supply chains. It provides a reusable base of domain-specific primitives that enables rapid development of customized decision support tools.     

Application of the Back Propagation Neural Network Algorithm with Monotonicity Constraints for Two-Group Classification Problems*

Neural network techniques are widely used in solving pattern recognition or classification problems. However, when statistical data are used in supervised training of a neural network employing the back-propagation least mean square algorithm, the behavior of the classification boundary during training is often unpredictable. This research suggests the application of monotonicity constraints to the back propagation learning algorithm. When the training sample set is preprocessed by a linear classification function, neural network performance and efficiency can be improved in classification applications where the feature vector is related monotonically to the pattern vector. Since most classification problems in business possess monotonic properties, this technique is useful in those problems where any assumptions about the properties of the data are inappropriate.     

Social context,spatial structure and social network structure

Frequently, social networks are studied in their own right with analyses devoid of contextual details. Yet contextual features – both social and spatial – can have impacts on the networks formed within them. This idea is explored with five empirical networks representing different contexts and the use of distinct modeling strategies. These strategies include network visualizations, QAP regression, exponential random graph models, blockmodeling and a combination of blockmodels with exponential random graph models within a single framework. We start with two empirical examples of networks inside organizations. The familiar Bank Wiring Room data show that the social organization (social context) and spatial arrangement of the room help account for the social relations formed there. The second example comes from a police academy where two designed arrangements, one social and one spatial, powerfully determine the relational social structures formed by recruits. The next example is an inter-organizational network that emerged as part of a response to a natural disaster where features of the improvised context helped account for the relations that formed between organizations participating in the search and rescue mission. We then consider an anthropological example of signed relations among sub-tribes in the New Guinea highlands where the physical geography is fixed. This is followed by a trading network off the Dalmatian coast where geography and physical conditions matter. Through these examples, we show that context matters by shaping the structure of networks that form and that a variety of network analytic tools can be mobilized to reveal how networks are shaped, in part, by social and spatial contexts. Implications for studying social networks are suggested.     

If Human Rights Mattered

This article is a response to Judith Blau's ( 2016 ) essay, “Human Rights: What the United States Might Learn from the Rest of the World and, Yes, from American Sociology.” Here, I argue that if human rights mattered, then liberty could be assured. And absent human rights, liberty is a sham.     

Development and Assessment of Measures of Adolescents' Attitudes about Sexual Relationship Rights

Objective: Develop and validate measures of adolescents' attitudes about sexual relationship rights. Methods: Items were completed by students in a large U.S. city (N = 655). The authors conducted an exploratory factor analysis, evaluated internal consistency, and assessed construct validity, including ability to predict sexual behavior at 1-year follow-up. Results: Factor analysis identified 2 distinct factors, comprising attitudes about rights to refuse unwanted sexual activity (5 items) and express sexual engagement needs (5 items) in a sexual relationship. The measures showed sound evidence of reliability and construct validity. Conclusions: The psychometric evidence supports the use of these measures in adolescent sexual health research.     

THE IMPACT OF PROBABILISTIC INFORMATION ON DECISION BEHAVIOR AND PERFORMANCE IN AN EXPERIMENTAL GAME

This research presents the results of a longitudinal experiment using experimental gaming. The results suggest that probabilistic information did change decision behavior and improve subject performance in the experiment. Moreover, there appeared to be a learning effect associated with the use of probabilistic information. Finally, the source of information (externally supplied by the researcher or generated by the subjects themselves) had an impact on decision behavior and performance in the experiment.