OCCUPATIONAL SEX SEGREGATION AND ECONOMIC INEQUALITY UNDER SOCIALISM:

An increase in scholarly attention to income differences between sex-typed occupations has generated a burgeoning literature. Typically-female occupations require preemployment education, not prolonged on-the-job training; receive less renumeration for work autonomy than male-typed occupations; and are concentrated in economically disadvantaged industrial sectors. However, these issues have received only preliminary consideration regarding noncapitalist societies and research has lacked an integrative, analytical focus. This study compares the earnings effects of education, type of work, and industrial sector between female- and male-dominated occupations in socialist Yugoslavia. As expected, average earnings are significantly higher in male than in female occupations. The results from the earnings regressions reveal a higher explained variance and larger economic returns to education among female- dominated occupations, especially in the managerial and professional strata. A decomposition of the earnings difference between sex-typed occupations suggests a variation in the source of inequality across skill strata. In the discussion, a comparison of capitalism and socialism reveals that while some aspects of the earnings attainment process may be unique to socialism, others are not.     

Simulating Properties of the Likelihood Ratio Test for a Unit Root in an Explosive Second-Order Autoregression

This paper provides a means of accurately simulating explosive autoregressive processes and uses this method to analyze the distribution of the likelihood ratio test statistic for an explosive second-order autoregressive process of a unit root. While the standard Dickey-Fuller distribution is known to apply in this case, simulations of statistics in the explosive region are beset by the magnitude of the numbers involved, which cause numerical inaccuracies. This has previously constituted a bar on supporting asymptotic results by means of simulation, and analyzing the finite sample properties of tests in the explosive region.     

Bayesian Multivariate Spatial Interpolation with Data Missing by Design

In a network of s _g sites, responses like levels of airborne pollutant concentrations may be monitored over time. The sites need not all measure the same set of response items and unmeasured items are considered as data missing by design . We propose a hierarchical Bayesian approach to interpolate the levels of, say, k responses at s _u other locations called ungauged sites and also the unmeasured levels of the k responses at the gauged sites. Our method involves two steps. First, when all hyperparameters are assumed to be known, a predictive distribution is derived. In turn, an interpolator, its variance and a simultaneous interpolation region are obtained. In step two, we propose the use of an empirical Bayesian approach to estimate the hyperparameters through an EM algorithm. We base our theory on a linear Gaussian model and the relationship between a multivariate normal and matrix T -distribution. Our theory allows us to pool data from several existing networks that measure different subsets of response items for interpolation.     

PROBLEMS WITH BINOMIAL TWO-SIDED TESTS AND THE ASSOCIATED CONFIDENCE INTERVALS

Confidence intervals for parameters of distributions with discrete sample spaces will be less conservative (i.e. have smaller coverage probabilities that are closer to the nominal level) when defined by inverting a test that does not require equal probability in each tail. However, the P‐value obtained from such tests can exhibit undesirable properties, which in turn result in undesirable properties in the associated confidence intervals. We illustrate these difficulties using P‐values for binomial proportions and the difference between binomial proportions.     

On Tiku's robust procedure — a Bayesian insight

Tiku's robust procedure for testing mean and variance from nonnormal universe is examined from the Bayesian viewpoint. The posterior distribution of the scale parameter is derived and then approximated by a Laguerre polynomial expansion while the posterior distribution of the location parameter is approximated by a linear combination of t-distributions. For the example with Darwin's data, the approximations appear to be extremely good.     

Helping parents to manage infant crying and sleeping: a review of the evidence and its implications for services

Infant crying and night waking are common concerns for parents, costly problems for health services and may trigger infant abuse or lead to serious child disturbances. Parents are given contradictory advice on how to manage infant crying and sleeping, indicating the need for evidence‐based guidance. This review of recent research draws distinctions between infant crying and sleeping problems, between the problem identified by parents and the infant behaviour underlying the problem, between different types of crying behaviour and their causes, and between the types of cases which present at different ages. It proposes that the two main approaches to parenting advocated by baby‐care experts, ‘infant‐demand’ and ‘structured’ parenting, have different benefits, and costs. Comparative studies have found that infant‐demand parenting is associated with low amounts of fussing and crying in the first three months of age, but with night waking which continues beyond three months. Randomised controlled trials have provided evidence that structured parenting leads to more overall fussing and crying during the first three months, but reduced night waking and crying after that. The findings are translated into recommendations for preventing and treating infant crying and sleeping problems, for policy debate, and for further research. Copyright © 2007 John Wiley & Sons, Ltd.