Optimal Design of the Online Auction Channel: Analytical,Empirical, and Computational Insights*

The focus of this study is on business‐to‐consumer (B2C) online auctions made possible by the advent of electronic commerce over an open‐source, ubiquitous Internet Protocol (IP) computer network. This work presents an analytical model that characterizes the revenue generation process for a popular B2C online auction, namely, Yankee auctions. Such auctions sell multiple identical units of a good to multiple buyers using an ascending and open auction mechanism. The methodologies used to validate the analytical model range from empirical analysis to simulation. A key contribution of this study is the design of a partitioning scheme of the discrete valuation space of the bidders such that equilibrium points with higher revenue structures become identifiable and feasible. Our analysis indicates that the auctioneers are, most of the time, far away from the optimal choice of key control factors such as the bid increment, resulting in substantial losses in a market with already tight margins. With this in mind, we put forward a portfolio of tools, varying in their level of abstraction and information intensity requirements, which help auctioneers maximize their revenues.     

Facility Dispersion Problems Under Capacity and Cost Constraints

The MAX-MIN dispersion problem, which arises in the placement of undesirable facilities, involves selecting a specified number of sites among a set of potential sites so as to maximize the minimum distance between any pair of selected sites. We consider different versions of this dispersion problem where each potential site has an associated storage capacity and a storage cost. A typical problem in this context is to choose a subset of potential sites so that the total capacity of the chosen sites is at least a given value, the total storage cost is within the specified budget and the minimum distance between any pair of chosen sites is maximized. Since these constrained optimization problems are NP-hard in general, we consider whether there are efficient approximation algorithms for them with good performance guarantees. Our results include approximation algorithms for some versions, approximation schemes for some geometric versions and polynomial algorithms for special cases. We also present results that bring out the intrinsic difficulty of obtaining near-optimal solutions to some versions.     

Does philanthropy reduce inequality?

Wealthy individuals often voluntarily provide public goods that the poor also consume. We show that, rather than reducing it, such philanthropy may aggravate absolute inequality in welfare achievement, while leaving the change in relative inequality ambiguous. Additionally, philanthropic preferences may increase the effectiveness of policies to redistribute income, instead of weakening them. Our results thus suggest that philanthropy and direct redistribution may often be better viewed as complements, rather than substitutes, in the context of inequality reduction. In so doing, they also bring into question the general normative case for large tax deductions for charitable contributions.     

Approximation Algorithms for Certain Network Improvement Problems

We study budget constrained network upgrading problems. Such problems aim at finding optimal strategies for improving a network under some cost measure subject to certain budget constraints. Given an edge weighted graph G = (V, E), in the edge based upgrading model, it is assumed that each edge e of the given network also has an associated function ce (t) that specifies the cost of upgrading the edge by an amount t. A reduction strategy specifies for each edge e the amount by which the length (e) is to be reduced. In the node based upgrading model, a node v can be upgraded at an expense of c(v). Such an upgrade reduces the delay of each edge incident on v. For a given budget B, the goal is to find an improvement strategy such that the total cost of reduction is at most the given budget B and the cost of a subgraph (e.g. minimum spanning tree) under the modified edge lengths is the best over all possible strategies which obey the budget constraint.After providing a brief overview of the models and definitions of the various problems considered, we present several new results on the complexity and approximability of network improvement problems.     

Challenging the Black Church Narrative: Race,Class, and Homosexual Attitudes

In recent years, scholars have pointed to the Black church as the driving force behind Blacks’ more conservative lesbian, gay, bisexual, and transgendered (LGBT) attitudes. Although evidence suggests a robust association between religiosity and LGBT attitudes, contemporary scholarship has not examined the role of class or the extent to which religiosity actually explains these trends. Using the 2004–2014 waves of the General Social Survey, we find that class moderates in the effect of race on negative LGBT attitudes, resulting in a noticeably larger gap between middle-class Blacks and Whites than in the top or the bottom of the class distribution. Although religiosity and moralization explain a portion of racial differences in homosexual attitudes across class groups, we find that neither fully accounts for the more conservative attitudes of the Black middle class. We conclude by discussing the shortcomings of these narratives for understanding Blacks’ more conservative LGBT attitudes.     

Ampleur et modalités du non‐respect de la loi sur le travail dans l'industrie en Inde

S'il est notoire que le non‐respect du droit du travail est monnaie courante dans les pays en développement, on n'a guère d'éléments précis sur son ampleur. Les auteurs ont quantifé les violations de la loi indienne sur les établissements industriels: les entreprises contrevenantes sont le double de celles qui respectent la législation, mais aussi bien plus nombreuses que celles qui l'évitent. Ainsi ce non‐respect est‐il une caractéristique du «segment intermédiaire manquant» en Inde. Les auteurs explorent les grandes tendances et les modalités de ces violations et montrent les pistes à suivre par la recherche et pour l'action.     

Uncertainties in the CIIT Model for Formaldehyde-Induced Carcinogenicity in the Rat: A Limited Sensitivity Analysis–I

Scientists at the CIIT Centers for Health Research (Conolly et al., 2000, 2003; Kimbell et al., 2001a, 2001b) developed a two-stage clonal expansion model of formaldehyde-induced nasal cancers in the F344 rat that made extensive use of mechanistic information. An inference of their modeling approach was that formaldehyde-induced tumorigenicity could be optimally explained without the role of formaldehyde's mutagenic action. In this article, we examine the strength of this result and modify select features to examine the sensitivity of the predicted dose response to select assumptions. We implement solutions to the two-stage cancer model that are valid for nonhomogeneous models (i.e., models with time-dependent parameters), thus accounting for time dependence in variables. In this reimplementation, we examine the sensitivity of model predictions to pooling historical and concurrent control data, and to lumping sacrificed animals in which tumors were discovered incidentally with those in which death was caused by the tumors. We found the CIIT model results were not significantly altered with the nonhomogeneous solutions. Dose-response predictions below the range of exposures where tumors occurred in the bioassays were highly sensitive to the choice of control data. In the range of exposures where tumors were observed, the model attributed up to 74% of the added tumor probability to formaldehyde's mutagenic action when our reanalysis restricted the use of the National Toxicology Program (NTP) historical control data to only those obtained from inhalation exposures. Model results were insensitive to hourly or daily temporal variations in DNA protein cross-link (DPX) concentration, a surrogate for the dose-metric linked to formaldehyde-induced mutations, prompting us to utilize weekly averages for this quantity. Various other biological and mathematical uncertainties in the model have been retained unmodified in this analysis. These include model specification of initiated cell division and death rates, and uncertainty and variability in the dose response for cell replication rates, issues that will be considered in a future paper.     

All in the Family: How Do Social Capital and Material Wellbeing Affect Relational Wellbeing?

We use a unique dataset from Italy to investigate the impact of socioeconomic characteristics and social capital on family wellbeing and satisfaction. We assess wellbeing using four dimensions of satisfaction with family life: satisfaction with decision making processes, with relationships with partner and children, and with time spent with children. Social capital is measured through information about membership in organizations, trust, and interactions with others. We find that while socioeconomic characteristics in general do not have strong effects on family wellbeing, social capital matters for family life satisfaction.

     

Enforcement matters: The effective regulation of labour

The distinction between de jure and de facto regulation is well understood in theory, but has rarely been applied to cross‐country empirical work on the impact of labour regulation on labour market outcomes for lack of data. Policy debate has been based on measures of stringency of law, suggesting a negative correlation between labour regulation and labour market outcomes. This article provides new cross‐country measures of labour law enforcement and evidence of a negative correlation between stringency and intensity of enforcement. Previous results concerning the consequences of labour regulation and the legal origins theory no longer hold when a measure of effective labour regulation is used.