Gender differences in willingness to compete: The role of public observability

A recent literature emphasizes that gender differences in the labor market may in part be driven by a gender gap in willingness to compete. However, whereas experiments in this literature typically investigate willingness to compete in private environments, real world competitions often have a more public nature, which introduces potential social image concerns. If such image concerns are important, and men and women differ in the degree to which they want to be seen as competitive, making tournament entry decisions publicly observable may further exacerbate the gender gap. We test this prediction using a laboratory experiment (N = 784) that varies the degree to which the decision to compete, and its outcome, is publicly observable. We find that public observability does not alter the magnitude of the gender gap in willingness to compete in an economically or statistically significant way.     

Cognitive abilities,self-efficacy,and financial behavior

This paper investigates the effect of cognitive abilities on financial behavior among older adults. Using the U.S. Health and Retirement Study, I find that cognitive abilities significantly affect financial behavior through two channels: ability and self-efficacy. People with higher cognition scores achieve better financial outcomes. This positive association is especially strong in tasks having high demand of cognitive abilities, which confirms the ability channel of the cognitive ability effect. In addition, there is evidence for the self-efficacy channel as a secondary source of cognitive influence. Lower cognitive abilities decrease people’s sense of self-efficacy, which, in turn, significantly decreases financial management efficiency. The findings have important policy implications, specifically that more effort is needed to assist the growing older population through the cognitive aging process and that noncognitive skills, as a secondary source of influence, also warrant attention.     

‘Public toilets for a diverse neighborhood’: Spatial purification practices in community development discourse

This paper explores the dialectic of place and community identity in Mount Pleasant, a multi–ethnic and multi–class U.S. neighborhood where definitions of place are hotly contested among its residents. In a grant proposal for public toilets, Mount Pleasant writers use linguistic strategies such as presupposition, deixis, and contrast, coupled with discursive themes of filth and geography, to construct a core of the Mount Pleasant community. The writers place themselves and people who share their values in that core, and immigrants at the margins. These strategies serve as a discursive type of spatial purification practice (cf. Sibley 1988) through which the grantwriters set up a moral and spatial order where they and other core community members are deemed to use space ‘appropriately’, and thus inhabit positive moral positions, while immigrant community members’ imputed ‘inappropriate’ use of space is used to construct negative moral positions for them.     

促性腺激素、V_(D_3)、V_E亚硒酸钠对母兔繁殖力的影响

选择成年、健康、未孕母兔 32只 ,随机分成 8组 ,分别给予促性腺激素 (Ⅰ组 )、VD3(Ⅱ组 )、VE 亚硒酸钠 (Ⅲ组 ) ,促性腺激素 +VD3(Ⅳ组 )、VD3+VE 亚硒酸钠 (Ⅴ组 )、促性腺激素 +VE 亚硒酸钠(Ⅵ组 )、促性腺激 +VD3+VE 亚硒酸钠 (Ⅶ组 ) ,空白对照 8种处理。试验结果表明 ,母兔经药物处理后 ,其繁殖性能 (发情状况、排卵数、正常受精卵数 )都比对照组显著地提高 ,但Ⅰ、Ⅳ、Ⅵ组有畸形卵子存在 ,以处理Ⅶ组效果最好 ,其排卵数达 4 7± 2 0 .3个 ,正常受精卵 35个 ,分别比对照组多 36 .5个、30个。     

A class of count models and a new consistent test for the Poisson distribution

We define a class of count distributions which includes the Poisson as well as many alternative count models. Then the empirical probability generating function is utilized to construct a test for the Poisson distribution, which is consistent against this class of alternatives. The limit distribution of the test statistic is derived in case of a general underlying distribution, and efficiency considerations are addressed. A simulation study indicates that the new test is comparable in performance to more complicated omnibus tests.     

Lower bounds on expectations of positive L-statistics from without-replacement models

We consider samples drawn without replacement from finite populations. We establish optimal lower non-negative and upper non-positive bounds on the expectations of linear combinations of order statistics centered about the population mean in units generated by the population central absolute moments of various orders. We also specify the general results for important examples of sample extremes, Gini mean differences and sample range. The paper completes the results of Papadatos and Rychlik [2004. Bounds on expectations of L-statistics from without replacement samples. J. Statist. Plann. Inference 124, 317–336], where sharp negative lower and positive upper bounds on the expectations of the combinations were presented for the without-replacement samples.     

Wilcoxon–Mann–Whitney test for stratified samples and Efron's paradox dice

Two-treatment multi-center clinical trials are the most common type of clinical trials in practice. The aim of this paper is to discuss a curious property of certain standard nonparametric procedures used in the analysis of such clinical trials. Different analyses of a simulated data example are presented, which lead to contrasting and surprising results. The source of the potentially misleading outcome is then explored while relating the simulated data with the concept of Efron's paradox dice and the notion of nontransitivity. With the root of the problem established, an alternate nonparametric method from the literature is shown to address the problem. Finally, pointing out an interpretational concern of using the alternate procedure, a modification to this procedure is also suggested and corresponding theoretical results are presented.     

Two-stage Huber estimation

In this paper we propose a new robust estimator in the context of two-stage estimation methods directed towards the correction of endogeneity problems in linear models. Our estimator is a combination of Huber estimators for each of the two stages, with scale corrections implemented using preliminary median absolute deviation estimators. In this way we obtain a two-stage estimation procedure that is an interesting compromise between concerns of simplicity of calculation, robustness and efficiency. This method compares well with other possible estimators such as two-stage least-squares (2SLS) and two-stage least-absolute-deviations (2SLAD), asymptotically and in finite samples. It is notably interesting to deal with contamination affecting more heavily the distribution tails than a few outliers and not losing as much efficiency as other popular estimators in that case, e.g. under normality. An additional originality resides in the fact that we deal with random regressors and asymmetric errors, which is not often the case in the literature on robust estimators.     

Generalized Laplacian approximations in Bayesian inference

This paper presents a new Laplacian approximation to the posterior density of η = g(θ). It has a simpler analytical form than that described by Leonard et al. (1989). The approximation derived by Leonard et al. requires a conditional information matrix R_η to be positive definite for every fixed η. However, in many cases, not all R_η are positive definite. In such cases, the computations of their approximations fail, since the approximation cannot be normalized. However, the new approximation may be modified so that the corresponding conditional information matrix can be made positive definite for every fixed η. In addition, a Bayesian procedure for contingency-table model checking is provided. An example of cross-classification between the educational level of a wife and fertility-planning status of couples is used for explanation. Various Laplacian approximations are computed and compared in this example and in an example of public school expenditures in the context of Bayesian analysis of the multiparameter Fisher-Behrens problem.     

Test for homogeneity in Hardy–Weinberg normal mixture model

The phenotype of a quantitative trait locus (QTL) is often modeled by a finite mixture of normal distributions. If the QTL effect depends on the number of copies of a specific allele one carries, then the mixture model has three components. In this case, the mixing proportions have a binomial structure according to the Hardy–Weinberg equilibrium. In the search for QTL, a significance test of homogeneity against the Hardy–Weinberg normal mixture model alternative is an important first step. The LOD score method, a likelihood ratio test used in genetics, is a favored choice. However, there is not yet a general theory for the limiting distribution of the likelihood ratio statistic in the presence of unknown variance. This paper derives the limiting distribution of the likelihood ratio statistic, which can be described by the supremum of a quadratic form of a Gaussian process. Further, the result implies that the distribution of the modified likelihood ratio statistic is well approximated by a chi-squared distribution. Simulation results show that the approximation has satisfactory precision for the cases considered. We also give a real-data example.