Job turnover, wage rates, and marital stability: How are they related?

This study examines the interplay between job stability, wage rates, and marital stability. We use a Dynamic Selection Control model in which young men make sequential choices about work and family and estimate the model using an approach that takes account of self-selection, simultaneity and unobserved heterogeneity. The results quantify how job stability affects wage rates, how both affect marital status, and how marital status affects earnings and job stability. The study reveals robust evidence that job changes lower wages and the likelihood of getting married and remaining married. At the same time, marriage raises wage rates and job stability. To project the sequential effects linking job change, marital status, and earnings, we simulate the impacts of shocks that raise preferences for marriage and that increase education. Feedback effects cause the simulated wage gains from marriage to cumulate over time, indicating that long-run marriage wage premiums exceed conventional short-run estimates.     

The Family Dynamics of School Phobics

Summary A casework based method of assessment was devised to examinethe family dynamics of school phobic children. There was significantdifferences found between the family interaction of male andfemale school phobic children. The relationships were dichotomizedalong gender lines, that were broadly oedipal in nature. Thesefindings and methodological problems were discussed     

Dynamic reliability models with conditional proportional hazards

A dynamic approach to the stochastic modelling of reliability systems is further explored. This modelling approach is particularly appropriate for load-sharing, software reliability, and multivariate failure-time models, where component failure characteristics are affected by their degree of use, amount of load, or extent of stresses experienced. This approach incorporates the intuitive notion that when a set of components in a coherent system fail at a certain time, there is a jump from one structure function to another which governs the residual lifetimes of the remaining functioning components, and since the component lifetimes are intrinsically affected by the structure function which they constitute, then at such a failure time there should also be a jump in the stochastic structure of the lifetimes of the remaining components. For such dynamically-modelled systems, the stochastic characteristics of their jump times are studied. These properties of the jump times allow us to obtain the properties of the lifetime of the system. In particular, for a Markov dynamic model, specific expressions for the exact distribution functions of the jump times are obtained for a general coherent system, a parallel system, and a series-parallel system. We derive a new family of distribution functions which describes the distributions of the jump times for a dynamically-modelled system.     

Bimodality based on the generalized skew-normal distribution

This paper focuses on the development of a new extension of the generalized skew-normal distribution introduced in Gómez et al. [Generalized skew-normal models: properties and inference. Statistics. 2006;40(6):495–505]. To produce the generalization a new parameter is introduced, the signal of which has the flexibility of yielding unimodal as well as bimodal distributions. We study its properties, derive a stochastic representation and state some expressions that facilitate moments derivation. Maximum likelihood is implemented via the EM algorithm which is based on the stochastic representation derived. We show that the Fisher information matrix is singular and discuss ways of getting round this problem. An illustration using real data reveals that the model can capture well special data features such as bimodality and asymmetry.     

Detection of outliers in simple circular regression models using the mean circular error statistic

The investigation on the identification of outliers in linear regression models can be extended to those for circular regression case. In this paper, we propose a new numerical statistic called mean circular error to identify possible outliers in circular regression models by using a row deletion approach. Through intensive simulation studies, the cut-off points of the statistic are obtained and its power of performance investigated. It is found that the performance improves as the concentration parameter of circular residuals becomes larger or the sample size becomes smaller. As an illustration, the statistic is applied to a wind direction data set.     

Maximum likelihood estimation in a Weibull regression model with type-1 censoring: a Monte Carlo study

Results of the Monte Carlo study of the performance of a maximum likelihood estimation in a Weibull parametric regression model with two explanatory variables are presented. One simulation run contained 1000 samples censored on the average by the amount of 0-30%. Each simulatedsample was generated in a form of two-factor two-level balanced experiment. The confidence intervals were computed using the large-sample normal approximation via the matrix of observed information. For small sample sizes the estimates of the scale parameter b of the loglifetime were significantly negatively biased, which resulted in a poor quality of confidence intervals for b and the low-level quantiles. All estimators improved their quality when the nominal value of b decreased. A moderate amount of censoring improved the quality of point and confidence estimation. The reparametrization b 7 produced rather accurate confidence intervals. Exact confidence intervals for b in case of non-censoring were obtained using the pivotal quantity b/b.     

The "quality " of early care and education settings: definitional and measurement issues

There is a widespread belief that high-quality early care and education can improve children's school readiness. However, debate continues about the essential elements of a high-quality experience, about whether quality means the same things across different types of care settings, about how to measure quality, and about the level of quality that might make a meaningful difference in outcomes for children. Are the aspects of the child care environment that researchers measure the ones that are most strongly related to children's development? This article argues that the ways in which researchers currently measure early care environments are flawed and that the conclusions drawn about the relationship between these measures and outcomes for children are frequently incorrect or overstated. The article addresses four questions: How is the quality of the child care environment commonly defined and measured? Do the most commonly used measures capture the child's experience? Do they work well across all settings? Are researchers drawing the correct conclusions from studies that relate the child care environment to child outcomes? Finally, the article discusses some possible directions for future research.     

SOME ECONOMIC CONSEQUENCES OF ANTICIPATING TECHNICAL ADVANCE

Using a simple model of a long run profit maximizing firm, we investigated the consequences of foreseeing future technical advance upon the adoption of new technology, scrapping of old, and for price and output of the firm's product. To simplify the analysis and highlight the conclusions, we assumed all technologies embodied in equipment and all equipment infinitely durable. It was shown that the often-used formulas for the unit cost of using capital over a finite (rkj/(l — a^T)) or infinite (rkj) life are appropriate only if the equipment does not become outmoded during its economic life and if there are no demand shifts in that time interval. Otherwise, the current cost of using capital (ex ante) must reflect future lesser or greater earning power of that capital due to outmodedness or demand shifts. Anticipation of technical advance tends to delay scrapping of old equipment and retard installation of new, with current output smaller and price higher than if technology is stagnant. Selection among currently competing technologies is also affected by the course future technical advance is expected to follow. The economic lifetime of capital equipment is independent of the elasticity of demand for the firm's output. On the other hand anticipation of demand expansion tends to partially or wholly offset the effect of anticipating future technical advance, while expected demand decline tends to reinforce it. Uncertainty about when improved technology will appear tends to retard adoption of current best practice technology, to retard scrapping of outmoded technology, restrict output and elevate price, in comparison with pptimal policy when the time of availability is believed known. The optimal policy is unaffected when it is the magnitude of the improvement rather than its timing which is unknown.