Retrospective questions: data quality,task difficulty,and the use of a checklist

Data from a national panel study with waves in 1987 and 1991 (N=1257), present evidence of the low accuracy of responses to retrospective questions, concerning both attitudes and behaviour. Applying a split ballot design, it is investigated whether using a checklist improves the response accuracy for a retrospective question about one single event: how respondents (N=363) did obtain the job they had four years ago. Furthermore interaction effects of ‘task difficulty’ are examined. The response accuracy indeed increases by using a checklist; however, this increase is not statistically significant. The expected increase of the checklist effect with higher ‘task difficulty’ appears for longer recall intervals, but not for more frequent changes of jobs. It turned out that for male respondents all the predicted effects are indeed clearly present. But for female respondents the checklist appeared to have no effect, irrespective of the task difficulty. A tentative explanation for this unexpected gender effect is suggested by pointing at indications that the male and female respondents differed in the way they obtained their job.     

Inference of the Russian drug community from one of the largest social networks in the Russian Federation

The criminal nature of narcotics complicates the direct assessment of a drug community, while having a good understanding of the type of people drawn or currently using drugs is vital for finding effective intervening strategies. Especially for the Russian Federation this is of immediate concern given the dramatic increase it has seen in drug abuse since the fall of the Soviet Union in the early nineties. Using unique data from the Russian social network ‘LiveJournal’ with over 39 million registered users worldwide, we were able for the first time to identify the on-line drug community by context sensitive text mining of the users’ blogs using a dictionary of known drug-related official and ‘slang’ terminology. By comparing the interests of the users that most actively spread information on narcotics over the network with the interests of the individuals outside the on-line drug community, we found that the ‘average’ drug user in the Russian Federation is generally mostly interested in topics such as Russian rock, non-traditional medicine, UFOs, Buddhism, yoga and the occult. We identify three distinct scale-free sub-networks of users which can be uniquely classified as being either ‘infectious’, ‘susceptible’ or ‘immune’.     

On Emissions Trading and Market Structure: Cap-and-Trade versus Intensity Standards

This paper examines the interdependence between imperfect competition and emissions trading. We particularly analyze the long run equilibrium in a two-sector (‘clean’ and ‘dirty’) model with Cournot competition among firms who face a fixed cost of production. The clean sector is defined as the sector with the highest long run cost margin on emissions. We compare the welfare implications of a cap-and-trade scheme with an emissions trading scheme based on relative intensity standards. It is shown that a firm’s long run equilibrium output in the clean or dirty sector does not depend on the emissions trading format, but only depends on the fixed cost of producing in the respective sector. Intensity standards can result in clean firms selling allowances to dirty firms, or dirty firms selling to clean firms. The former outcome yields higher welfare. It is demonstrated that cap-and-trade outperforms the intensity-based trading scheme in terms of long run welfare with free entry and exit. With intensity standards the size of the clean sector is too large.     

Equally important criteria and demanding aggregation

Within the class of weighted averages of ordered measurements on criteria of ‘equal importance’, we discuss aggregators that help assess to what extent ‘most’ criteria are satisfied, or a ‘good performance across the board’ is attained. All aggregators discussed are compromises between the simple mean and the very demanding minimum score. The weights of the aggregators are described in terms of the convex polytopes as induced by the characteristics of the aggregators, such as concavity. We take the barycentres of the polytopes as representative weights.     

Measuring Socio-Economic GENDER Inequality: Toward an Alternative to the UNDP Gender-Related Development Index

This paper assesses the United Nations Development Program’s (UNDP) Gender-Related Development Index (GDI). Although the GDI has increased attention on gender equality in human development, it suffers from several limitations. A major problem is that it conflates relative gender equality with absolute levels of human development and thus gives no information on comparative gender inequality among countries. Using the same indicators as the GDI, the paper constructs a Relative Status of Women (RSW) index, which demonstrates how using a measure of gender equality that abstracts from levels of development results in very different country rankings. However, the RSW is not an ideal measure of gender inequality. The GDI indicators are not the most appropriate ones for measuring gender inequality and hence both the RSW and the GDI have limited validity. The paper concludes by offering a conceptual framework that provides the basis for an alternative measure of gender inequality.     

Abstracts

Quality & Quantity -     

Ridge regression and its degrees of freedom

For ridge regression the degrees of freedom are commonly calculated by the trace of the matrix that transforms the vector of observations on the dependent variable into the ridge regression estimate of its expected value. For a fixed ridge parameter this is unobjectionable. When the ridge parameter is optimized on the same data, by minimization of the generalized cross validation criterion or Mallows \(\hbox {C}_{L}\) , additional degrees of freedom are used however. We give formulae that take this into account. This allows of a proper assessment of ridge regression in competitions for the best predictor.