Functional Estimation of a Density Under a New Weak Dependence Condition

The purpose of this paper is to prove, through the analysis of the behaviour of a standard kernel density estimator, that the notion of weak dependence defined in a previous paper (cf. Doukhan & Louhichi, 1999) has sufficiently sharp properties to be used in various situations. More precisely we investigate the asymptotics of high order losses, asymptotic distributions and uniform almost sure behaviour of kernel density estimates. We prove that they are the same as for independent samples (with some restrictions for a.s. behaviours). Recall finally that this weak dependence condition extends on the previously defined ones such as mixing, association and it allows considerations of new classes such as weak shifts processes based on independent sequences as well as some non-mixing Markov processes.     

A BAYESIAN INTERPRETATION OF MULTIPLE POINT ESTIMATES

Consider a large number of econometric investigations using different estimation techniques and/or different subsets of all available data to estimate a fixed set of parameters. The resulting empirical distribution of point estimates can be shown - under suitable conditions - to coincide with a Bayesian posterior measure on the parameter space induced by a minimum information procedure. This Bayesian interpretation makes it easier to combine the results of various empirical exercises for statistical decision making. The collection of estimators may be generated by one investigator to ensure the satisfaction of our conditions, or they may be collected from published works, where behavioral assumptions need to be made regarding the dependence structure of econometric studies.     

DENSITY ESTIMATION FOR CLUSTERED DATA

The commonly used survey technique of clustering introduces dependence into sample data. Such data is frequently used in economic analysis, though the dependence induced by the sample structure of the data is often ignored. In this paper, the effect of clustering on the non-parametric, kernel estimate of the density, f(x), is examined. The window width commonly used for density estimation for the case of i.i.d. data is shown to no longer be optimal. A new optimal bandwidth using a higher-order kernel is proposed and is shown to give a smaller integrated mean squared error than two window widths which are widely used for the case of i.i.d. data. Several illustrations from simulation are provided.     

具有非负密度的粘性不可压缩流体运动的初边值问题的广义解的唯一性

本文讨论了一类具有非负密度的不可压缩流体运动的初边值问题,用积分估值法证明了这一模型广义解的唯一性.     

Teenage Pregnancy and Female Educational Underachievement: A Prospective Study of a New Zealand Birth Cohort

This paper examines the relationship between teenage pregnancy and educational underachievement in a cohort of 520 young women studied from birth to 21 years. Results showed that young women who became pregnant by the age of 18 years were at increased risk of poor achievement in the national School Certificate examinations, of leaving school without qualifications, and of failing to complete their sixth‐form year at high school. In addition, pregnant teenagers had lower rates of participation in tertiary education and training than their nonpregnant peers. Subsequent analyses showed that the links between teenage pregnancy and tertiary educational participation were largely noncausal and reflected the earlier academic ability, behavior, and family circumstances of young women who became pregnant. In contrast, antecedent child and family factors only partially explained associations between teenage pregnancy and high school participation and achievement. After adjustment for these factors, significant associations remained between teenage pregnancy and educational achievement at high school. An examination of the diverse life histories of young women who became pregnant revealed that for the majority of young women, pregnancy occurred after they had left school before finishing. These findings suggest that rates of teenage pregnancy might be elevated among young women who leave school early, rather than rates of early school leaving being elevated among young women who become pregnant during their teenage years.     

Group Images and Possible Selves Among Adolescents: Linking Stereotypes to Expectations by Race and Ethnicity

The study is motivated by the differential alignment of educational achievement and aspirations along race and ethnic lines. Specifically, black and Hispanic students have comparable educational aspirations relative towhites, yet earn much lower grades and test scores. On the other hand, compared to white students, Asian youth overperform in their grades and test scores given their aspirations. Focus groups and interviews of high school students reveal prevalent stereotypes that link ethnic group membership to academic ability as well as other skills. Specifically, Asian youth are believed to be especially gifted in their academic abilities, while blacks are seen as less successful in academic endeavors. Stereotypes about Hispanics focused less on their academic performance and more on their occupational concentration in manual labor. These images form the reference point for the construction of success among ethnic youth; specifically, blacks speak of academic goals in terms of avoiding failure, Hispanic youth aim primarily to avoid factory or manual labor, and Asians focus on keeping up with high expectations of their academic pursuits. Hence, I argue that adolescents define their goals primarily in terms of the stereotypical images attached to their ethnic group. Specifically, minority youth focused on avoiding failure defined by prevalent group stereotypes. Moreover, these images maintain racially and ethnically segregated extracurricular activities that reinforce segregated peer groups. Finally, socialization with same-race peers promote comparable conceptions of success within racial groups.     

Teachers,Schools, and Academic Achievement

This paper disentangles the impact of schools and teachers in influencing achievement with special attention given to the potential problems of omitted or mismeasured variables and of student and school selection. Unique matched panel data from the UTD Texas Schools Project permit the identification of teacher quality based on student performance along with the impact of specific, measured components of teachers and schools. Semiparametric lower bound estimates of the variance in teacher quality based entirely on within‐school heterogeneity indicate that teachers have powerful effects on reading and mathematics achievement, though little of the variation in teacher quality is explained by observable characteristics such as education or experience. The results suggest that the effects of a costly ten student reduction in class size are smaller than the benefit of moving one standard deviation up the teacher quality distribution, highlighting the importance of teacher effectiveness in the determination of school quality.     

On the Bootstrap of the Maximum Score Estimator

This paper shows that the bootstrap does not consistently estimate the asymptotic distribution of the maximum score estimator. The theory developed also applies to other estimators within a cube‐root convergence class. For some single‐parameter estimators in this class, the results suggest a simple method for inference based upon the bootstrap.     

Statistical inference for start-up demonstration tests with rejection of units upon observing d failures

In this paper, we consider the statistical inference for the success probability in the case of start-up demonstration tests in which rejection of units is possible when a pre-fixed number of failures is observed before the required number of consecutive successes are achieved for acceptance of the unit. Since the expected value of the stopping time is not a monotone function of the unknown parameter, the method of moments is not useful in this situation. Therefore, we discuss two estimation methods for the success probability: (1) the maximum likelihood estimation (MLE) via the expectation-maximization (EM) algorithm and (2) Bayesian estimation with a beta prior. We examine the small-sample properties of the MLE and Bayesian estimator. Finally, we present an example to illustrate the method of inference discussed here.     

双重分层抽样中的校正估计

校正估计法已被大量运用于抽样调查中,它利用辅助信息构造的校正权重提高了对总体总值（或均值）的估计精度。本文提出了分层抽样中的校正组合比率估计量,并推广到分层双重抽样中。同时给出新估计量的近似方差表达式。最后利用计算机随机模拟验证较正估计量对估计精度的改进。