ELICITING A DIRECTED ACYCLIC GRAPH FOR A MULTIVARIATE TIME SERIES OF VEHICLE COUNTS IN A TRAFFIC NETWORK

The problem of modelling multivariate time series of vehicle counts in traffic networks is considered. It is proposed to use a model called the linear multiregression dynamic model (LMDM). The LMDM is a multivariate Bayesian dynamic model which uses any conditional independence and causal structure across the time series to break down the complex multivariate model into simpler univariate dynamic linear models. The conditional independence and causal structure in the time series can be represented by a directed acyclic graph (DAG). The DAG not only gives a useful pictorial representation of the multivariate structure, but it is also used to build the LMDM. Therefore, eliciting a DAG which gives a realistic representation of the series is a crucial part of the modelling process. A DAG is elicited for the multivariate time series of hourly vehicle counts at the junction of three major roads in the UK. A flow diagram is introduced to give a pictorial representation of the possible vehicle routes through the network. It is shown how this flow diagram, together with a map of the network, can suggest a DAG for the time series suitable for use with an LMDM.     

A cross-national look at married women's earnings dependency

Using the Luxembourg Income Study data we examine married women's dependency on their husbands' earnings in nine Western industrialized countries: Australia, Belgium, Canada, Finland, Germany, the Netherlands, Norway, Sweden, and the United States. When we examine the level and degree of dependency, and the labor force participation of married women across countries, the nine countries fall into the three clusters delineated in Esping-Andersen's welfare states typology. But when we examine the determinants of the dependency within each country, the clustering disappears. Wives' dependency increases with age, the presence of young children, and the number of children. It is reduced when wives' labor force participation and education are high relative to their husbands' and in families that rely more on unearned sources of income. The similarity of patterns across countries suggests that gender differences in the work-family nexus are deeply entrenched in all countries and continue even in the face of very active social policy to minize their effects. This is a revised version of a paper presented at the annual meeting of the American Sociological Association, August 1995, Washington DC. Her current research focuses on gender inequality and parents' time allocation between work and family. She conducts research on various aspects of family demography, including household and family characteristics, co-resident grandparent families, cohabitation, and child care. With Suzanne Bianchi, she is completing a research monograph on trends in the American family. Her research focuses on gender, work, and family issues.     

Forecasting Multivariate Road Traffic Flows Using Bayesian Dynamic Graphical Models,Splines and Other Traffic Variables

Traffic flow data are routinely collected for many networks worldwide. These invariably large data sets can be used as part of a traffic management system, for which good traffic flow forecasting models are crucial. The linear multiregression dynamic model (LMDM) has been shown to be promising for forecasting flows, accommodating multivariate flow time series, while being a computationally simple model to use. While statistical flow forecasting models usually base their forecasts on flow data alone, data for other traffic variables are also routinely collected. This paper shows how cubic splines can be used to incorporate extra variables into the LMDM in order to enhance flow forecasts. Cubic splines are also introduced into the LMDM to parsimoniously accommodate the daily cycle exhibited by traffic flows. The proposed methodology allows the LMDM to provide more accurate forecasts when forecasting flows in a real high‐dimensional traffic data set. The resulting extended LMDM can deal with some important traffic modelling issues not usually considered in flow forecasting models. Additionally, the model can be implemented in a real‐time environment, a crucial requirement for traffic management systems designed to support decisions and actions to alleviate congestion and keep traffic flowing.     

How does POSSLQ measure up? Historical estimates of cohabitation

We use March Current Population Survey (CPS) data from 1977 to 1997 to produce a new historical series of indirect cohabitation prevalence estimates. We compare our new estimates with those produced by the traditional method and evaluate the new estimates. We then compare the indirect estimates with the new direct estimates to investigate whether biases exist in the indirect estimates. Our findings indicate that the traditional indirect method of estimating cohabitation prevalence underestimates cohabitors in different subpopulations, especially among those with children. We also find that the new indirect measure produces relatively unbiased estimates of cohabitors' characteristics.     

Self-care: Why do parents leave their children unsupervised?

We used a preferences-and-constraints model to develop four hypotheses to explain why parents may choose self-care (an unsupervised arrangement) as the primary child care arrangement for their children over supervised alternatives and tested them in a multivariate framework using 1995 data from the Survey of Income and Program Participation. We found that the choice of self-care over supervised care alternatives is linked to the availability of parents' time to care for children, the child's level of responsibility and maturity, and the neighborhood context. However, we found no evidence that parents' ability to pay for child care is related to the choice of self-care. The results also suggest that parents use different decision-making processes, depending on their children's ages.     

Olympic medals as an indicator of social welfare

The relation between the amount of medals won at the Olympic games and various welfare indicators has been established for the games of Barcelona and Seoul using a Bayesian method of Poisson regression. It was found that medals won correlate strongly with income as well as with more general welfare indicators and that the elasticity with respect to the size of the population is surprisingly smaller than unity.     

Explaining Family Change and Variation: Challenges for Family Demographers

Twenty years ago, the National Institute of Child Health and Human Development (NICHD) issued a request for proposals that resulted in the National Survey of Families and Households (NSFH), a unique survey valuable to a wide range of family scholars. This paper describes the efforts of an interdisciplinary group of family demographers to build on the progress enabled by the NSFH and many other theoretical and methodological innovations. Our work, also supported by NICHD, will develop plans for research and data collection to address the central question of what causes family change and variation. We outline the group's initial assessments of orienting frameworks, key aspects of family life to study, and theoretical and methodological challenges for research on family change. Finally, we invite family scholars to follow our progress and to help develop this shared public good.     

FIAT EXCHANGE IN FINITE ECONOMIES

The state of the art of rendering fiat money valuable is either to impose a boundary condition or to make the boundary condition unimportant through an infinite sequence of markets so as to circumvent backward induction. We show fiat exchange may nevertheless arise in finite economies if agents have incomplete information about their relative position in the trade cycle or when the barter and autarky equilibria of the one-shot trading round support a monetary equilibrium with repeated trades.