Nest design in a changing world: Great tit <Emphasis Type="Italic">Parus major</Emphasis> nests from a Mediterranean city environment as a case study

Investigations of urbanization effects on birds have focused mainly on breeding traits expressed after the nest-building stage (e.g. first-egg date, clutch size, breeding success, and offspring characteristics). Urban studies largely ignored how and why the aspects of nest building might be associated with the degree of urbanization. As urban environments are expected to present novel environmental changes relative to rural environments, it is important to evaluate how nest-building behavior is impacted by vegetation modifications associated with urbanization. To examine nest design in a Mediterranean city environment, we allowed urban great tits (Parus major) to breed in nest boxes in areas that differed in local vegetation cover. We found that different measures of nest size or mass were not associated with vegetation cover. In particular, nests located adjacent to streets with lower vegetation cover were not smaller or lighter than nests in parks with higher vegetation cover. Nests adjacent to streets contained more pine needles than nests in parks. In addition, in nests adjacent to streets, nests from boxes attached to pine trees contained more pine needles than nests from boxes attached to other trees. We suggest that urban-related alterations in vegetation cover do not directly impose physical limits on nest size in species that are opportunistic in the selection of nesting material. However, nest composition as reflected in the use of pine needles was clearly affected by habitat type and the planted tree species present, which implies that rapid habitat change impacts nest composition. We do not exclude that urbanization might impact other aspects of nest building behaviour not covered in our study (e.g. costs of searching for nest material), and that the strengths of the associations between urbanization and nest structures might differ among study populations or species.     

The use of detailed statistical data in customs reforms: The case of Madagascar

To carry out their various missions—collecting revenue, facilitating trade and ensuring security— many customs administrations have established a risk management unit. In developing countries, however, because of the lack of dedicated human and material resources, intelligence and risk analysis remain insufficiently developed. In view of the lack of resources, this article proposes a simple methodology aiming at detecting risky import operations. The mirror analysis first helps to identify and target products or sectors with the greatest risk. Based on the examination of customs declarations patterns (data mining), it is then possible to identify and target higher risk economic operators (importers and customs brokers). When implemented in Madagascar, this method has helped to reveal probable fraud cases in the context of current customs reforms.     

The extent of labour specialization in the extended family: A theoretical and empirical analysis

In this paper we present a simple model of labour supply that is cast within the framework of an extended family. The model emphasizes a Ricardian division of labour whereby the specialization is solely driven by marginal productivity and value of time differentials. The empirical implications of the model are derived and tested using data that was collected in France to study the extent of trade within the family network. We find evidence that the extent of specialization is sensitive to the value of time differentials. Received: 17 May 1995 / Accepted: 20 February 1997     

Sharing of Resources Within the Family and the Economics of Household Decision Making

Over the last 3 decades, economic models have been developed that recognize that potentially conflicting interests may shape household decisions and the sharing of resources within families. This article provides an overview of how decision making within households has been modeled within economics, presents the main benefits and limitations of those models, and critically assesses their usefulness to researchers from other disciplines interested in the within‐ household distribution of resources. The main focus is on the theory, empirical application, and results of the currently dominant collective models, but the authors also look at developments that led up to them and some subsequent extensions and alternative approaches. Given the weight placed by policymakers and others on economic and quantitative evidence, it is incumbent on researchers of all disciplines to understand the achievements and limitations of the models used, explicitly or implicitly, to produce such evidence and the assumptions that lie behind them.     

Revenue diversification among non-profits

Although the non-profit literature has grown substantially, the issue of how revenue diversification affects non-profits has not been fully explored. This paper presents several disciplinary perspectives regarding the financing of non-profits, what determines their ability to diversify, and the consequent effects on their behaviour. It first develops an index for measuring revenue diversification and applies it to a national sample of charitable non-profits. The results indicate that, while the perception that most non-profits rely on a single revenue source is exaggerated, the institutions in our sample have somewhat concentrated revenue. Our findings also suggest that the activity of a non-profit and the proportion of its expenditures that it devotes to fund-raising affect its ability to diversify its revenues concentration. While a number of anomalies exist, the weight of our evidence suggests that diversified revenue sources are more likely to be associated with a strong financial position than are concentrated revenue sources. Researchers interested in studying the life-cycle of non-profits, the factors that give rise to stability and growth, and the constraints on non-profit behaviour would do well to consider the diversification index presented in this paper.     

Robust Inference in Two‐phase Sampling Designs with Application to Unit Nonresponse

Influential units occur frequently in surveys, especially in business surveys that collect economic variables whose distributions are highly skewed. A unit is said to be influential when its inclusion or exclusion from the sample has an important impact on the sampling error of estimates. We extend the concept of conditional bias attached to a unit and propose a robust version of the double expansion estimator, which depends on a tuning constant. We determine the tuning constant that minimizes the maximum estimated conditional bias. Our results can be naturally extended to the case of unit nonresponse, the set of respondents often being viewed as a second‐phase sample. A robust version of calibration estimators, based on auxiliary information available at both phases, is also constructed.     

Why Do Women's Wages Increase So Slowly Throughout Their Career? A Dynamic Model of Statistical Discrimination

Abstract. The aim of this paper is to explain the growing wage differentials between men and women during their working careers. We provide a dynamic model of statistical discrimination, which integrates specific human capital decisions: on‐the‐job training investment and wages are endogenously determined. We reveal a small wage differential at the beginning of women's career, but women's wages increase more slowly; this is partly due to a lower level of human capital investment by women and partly because firms smooth training costs between different periods.