CONDITIONAL EXPECTATION FORMULAE FOR COPULAS

Not only are copula functions joint distribution functions in their own right, they also provide a link between multivariate distributions and their lower‐dimensional marginal distributions. Copulas have a structure that allows us to characterize all possible multivariate distributions, and therefore they have the potential to be a very useful statistical tool. Although copulas can be traced back to 1959, there is still much scope for new results, as most of the early work was theoretical rather than practical. We focus on simple practical tools based on conditional expectation, because such tools are not widely available. When dealing with data sets in which the dependence throughout the sample is variable, we suggest that copula‐based regression curves may be more accurate predictors of specific outcomes than linear models. We derive simple conditional expectation formulae in terms of copulas and apply them to a combination of simulated and real data.     

Intermittent child employment and its implications for estimates of child labour

Using longitudinal data from urban Brazil, the authors track the employment patterns of thousands of children aged 10-16 during four months of their lives in the 1980s and 1990s. The proportion of children who work at some point during a four-month period is substantially higher than the fraction observed working in any single month. The authors calculate an intermittency multiplier to summarize the difference between employment rates in one reference week vs. four reference weeks over a four-month period. They conclude that intermittent employment is a crucial characteristic of child labour which must be recognized to capture levels of child employment adequately and identify child workers.     

The association of smoking with drinking pattern may provide opportunities to reduce smoking among students

There is evidence that smoking and alcohol consumption are paired behaviours among university students, but we know little about how New Zealand students engage in these behaviours. We estimated prevalence of daily and occasional smoking among university students, and associations of smoking with drinking patterns, demographics and smokefree policies of the university. This research was conducted with 2822 university students, aged 17–25, from five New Zealand universities who participated in an online health survey in 2013. Fourteen percent reported they currently smoke occasionally, and 3% reported smoking on a daily basis. Increasing age, living situation, drinking more often, and drinking more alcohol during drinking occasions were all associated with greater levels of smoking. Understanding patterns of smoking in relation to alcohol consumption may help efforts to further reduce smoking prevalence. Specifically, policy makers should consider approaches that de-couple tobacco and alcohol consumption, such as expanding the smokefree perimeter of bars and disallowing the sale of tobacco at premises licensed to sell alcohol.     

People and Pixels 20 years later: the current data landscape and research trends blending population and environmental data

Population and Environment - In 1998, the National Research Council published People and Pixels: Linking Remote Sensing and Social Science. The volume focused on emerging research linking changes...