The effect of divorce costs on marriage formation and dissolution

Exploiting the theoretical parallels between the matching of workers to jobs in the labour market and the matching of individuals in the marriage market, we use a search theoretic model of marriage formation and dissolution to examine the effect of divorce costs on both decisions. By introducing learning at both stages of the marital decision process, we show that divorce costs not only affect the probability of divorce but also the probability of marriage. Interestingly, to what extent divorce costs affect the marital status distribution depends on the information regarding the quality of the potential marriage that individuals receive while encountering marital offers. Received: 30 July 1996/Accepted: 7 December 1998     

Positive quadrant dependence tests for copulas

In this paper the interest is in testing the null hypothesis of positive quadrant dependence (PQD) between two random variables. Such a testing problem is important since prior knowledge of PQD is a qualitative restriction that should be taken into account in further statistical analysis, for example, when choosing an appropriate copula function to model the dependence structure. The key methodology of the proposed testing procedures consists of evaluating a “distance” between a nonparametric estimator of a copula and the independence copula, which serves as a reference case in the whole set of copulas having the PQD property. Choices of appropriate distances and nonparametric estimators of copula are discussed, and the proposed methods are compared with testing procedures based on bootstrap and multiplier techniques. The consistency of the testing procedures is established. In a simulation study the authors investigate the finite sample size and power performances of three types of test statistics, Kolmogorov–Smirnov, Cramér–von‐Mises, and Anderson–Darling statistics, together with several nonparametric estimators of a copula, including recently developed kernel type estimators. Finally, they apply the testing procedures on some real data. The Canadian Journal of Statistics 38: 555–581; 2010 © 2010 Statistical Society of Canada     

Measures of occupational status in a special population

Previous research has shown that indirect measures of occupational status such as the Duncan Socioeconomic Index (SEI) are more valid than direct measures of occupational prestige, such as those developed by the National Opinion Research Center and by Treiman, for analyses of social mobility. The Professional, Technical, and Kindred (PTK) occupations available for the SEI are a biased sample of all PTK occupations. Do findings on the validity of the SEI pertaining to the general population hold for special populations, such as college graduates? Confirmatory factor analysis comparing the validities of four measures of occupational SES—the SEI, a 1960 counterpart of the SEI developed by Siegel and based on all Census occupations, the NORC prestige scale, and the Treiman international prestige scale—showed that the indirect measure developed by Siegel was clearly more valid than the other three measures. Since these findings indicate that the predictors in a regression equation are more valid than the criterion, there is some question as to what the criterion should really be.     

Union–intersection principle and constrained statistical inference

Most statistical models arising in real life applications as well as in interdisciplinary research are complex in their designs, sampling plans, and associated probability laws, which in turn are often constrained by inequality, order, functional, shape or other restraints. Optimality of conventional likelihood ratio based statistical inference may not be tenable here, although the use of restricted or quasi-likelihood has spurred in such environments. S.N. Roy's ingenious union–intersection principle provides an alternative avenue, often having some computational advantages, increased scope of adaptability, and flexibility beyond conventional likelihood paradigms. This scenario is appraised here with some illustrative examples, and with some interesting problems of inference on stochastic ordering (dominance) in parametric as well as beyond parametric setups.     

On the asymptotic behaviour of location-scale invariant Bickel–Rosenblatt tests

Location-scale invariant Bickel–Rosenblatt goodness-of-fit tests (IBR tests) are considered in this paper to test the hypothesis that f, the common density function of the observed independent d-dimensional random vectors, belongs to a null location-scale family of density functions. The asymptotic behaviour of the test procedures for fixed and non-fixed bandwidths is studied by using an unifying approach. We establish the limiting null distribution of the test statistics, the consistency of the associated tests and we derive its asymptotic power against sequences of local alternatives. These results show the asymptotic superiority, for fixed and local alternatives, of IBR tests with fixed bandwidth over IBR tests with non-fixed bandwidth.     

A note on the connection between uniformity and generalized minimum aberration

Discrete discrepancy has been utilized as a uniformity measure for comparing and evaluating factorial designs. In this paper, for asymmetrical factorials, we give some linkages between uniformity measured by the discrete discrepancy and other criteria, such as generalized minimum aberration (Xu and Wu, 2001) and minimum projection variance (Ai and Zhang, 2004). These close linkages show a significant justification for the discrete discrepancy used to measure uniformity of factorial designs, and provide an additional rationale for using uniform designs. This research was partially supported by the NNSF of China (No. 10441001), the Key Project of Chinese Ministry of Education (No. 105119) and the Project-sponsored by SRF for ROCS (SEM) (No. [2004]176).     

Estimation of the distribution function with calibration methods

The paper proposes a new calibration estimator for the distribution function of the study variable. This estimator is a distribution function unlike others estimators that use auxiliary information. Comparisons are made with existing estimators in two simulation studies.     

Likelihood-based inference for a class of multivariate diffusions with unobserved paths

This paper presents a Markov chain Monte Carlo algorithm for a class of multivariate diffusion models with unobserved paths. This class is of high practical interest as it includes most diffusion driven stochastic volatility models. The algorithm is based on a data augmentation scheme where the paths are treated as missing data. However, unless these paths are transformed so that the dominating measure is independent of any parameters, the algorithm becomes reducible. The methodology developed in Roberts and Stramer [2001a. On inference for partial observed nonlinear diffusion models using the metropolis-hastings algorithm. Biometrika 88(3); 603–621] circumvents the problem for scalar diffusions. We extend this framework to the class of models of this paper by introducing an appropriate reparametrisation of the likelihood that can be used to construct an irreducible data augmentation scheme. Practical implementation issues are considered and the methodology is applied to simulated data from the Heston model.     

遭遇解放——论《东风·西风》（上篇）的女性叙事

《东风·西风》是赛珍珠创作的第一部长篇小说，是以一个年轻中国女子独白的形式讲述的故事，反映了“五四”新文化运动前后中国社会传统与现代的交锋、新旧势力的冲突，强调了现代化的力量是如何改变了中国传统的家庭结构和妇女的命运。从社会学和叙事学两种视角深入分析上篇的女性叙事，可以看出，中国妇女在现代化进程中所遭遇的解放必须面对传统文化早已内化的压抑和西方化的自我镜像的挑战，还有男性他者的强权。赛珍珠让沉默的中国女性发出了声音，这也使得《东风·西风》成为一部备受忽视但却颇有价值的作品和文献。