Reconsidering union wage effects: Surveying new evidence on an old topic

I examine evidence on private sector union wage gaps in the United States. The consensus opinion among labor economists of an average union premium of roughly 15 percent is called into question. Two forms of measurement error bias downward standard wage gap estimates. Match bias results from Census earnings imputation procedures that do not include union status as a match criterion. Downward bias is roughly equal to the proportion of workers with imputed earnings, currently about 30 percent. Misclassification of union status causes additional attenuation in union gap measures. This bias has worsened as private sector density has declined, since an increasing proportion of workers designated as union are instead nonunion workers. Corrections for misclassification and match bias lead to estimated union gaps substantially higher than standard estimates, but with less of a downward trend since the mid 1980s. Private sector union gaps corrected for these biases are estimated from the CPS for 1973–2001. The uncorrected estimate for 2001 is .13 log points. Correction for match bias increases the gap to .18 log points; further correction for misclassification bias, based on an assumed 2 percent error rate, increases the gap to .24. Reexamination of the skill-upgrading hypothesis leads to the conclusion that higher union gap estimates are plausible. The conventional wisdom of a 15 percent union wage premium warrants reexamination.     

Health Policy and the Politics of Evidence

National decisions on the drugs, treatments and medical devices that should be funded through public expenditure are a fundamental element of health policy. But despite a political emphasis upon evidence‐based policy, the results of rigorous clinical trials and statistical modelling techniques rarely speak for themselves. So, does the pre‐eminence traditionally accorded to quantitative data in the medical field underpin policy decisions on a consistent basis? Or are more subtle, less transparent characteristics of context and interaction evident in the shaping of attendant decisions? This article considers these questions by drawing on a study of decision‐making in the National Institute for Health and Clinical Excellence (NICE)—an organization established by the British government in 1999 to decide whether selected health technologies should be made available throughout the National Health Service in England and Wales. In broad terms, the findings point to the primacy of arguments based on quantitatively oriented, experimentally derived data but also to a discursive hegemony of clinicians and health economists in mediating, including or debarring more qualitative, experientially based evidence. A more complex, dynamic understanding of policy governance in the field of health technology appraisal—founded on a discursive appropriation of the idea of the “common good”—goes some way to explaining the persistence of this hegemony despite an avowedly inclusive, plural approach to decision‐making.     

The Aesthetics of Aircraft Safety Cards: Spatial Negotiations and Affective Mobilities in Diagrammatic Instructions

Instructional diagrams encountered during transit, such as the aircraft safety card, employ a range of visual elements that direct us how to move and what actions we need to undertake. However, instructions are not always easy to decipher and comprehension rates suggest that there is potential for misinterpretation. The complexity of instructions and mismatching of visual techniques give rise to an aesthetics of transit that coordinates spatial experiences and movements. Using examples from aircraft safety cards and artworks based on this format, this paper analyses how ‘transit aesthetics’ can give rise to affective experiences of spatial and mobile relationships.     

Distance sampling methodology

We consider the method of distance sampling described by Buckland, Anderson, Burnham and Laake in 1993. We explore the properties of the methodology in simple cases chosen to allow direct and accessible comparisons of distance sampling in the design- and model-based frameworks. In particular, we obtain expressions for the bias and variance of the distance sampling estimator of object density and for the expected value of the recommended analytic variance estimator within each framework. These results enable us to clarify aspects of the performance of the methodology which may be of interest to users and potential users of distance sampling.     

Multivariate distributions defined in terms of contours

The paper deals with the problem of using contours as the basis for defining probability distributions. First, the most general probability densities with given contours are obtained and the particular cases of circular and elliptical contours are dealt with. It is shown that the so-called elliptically contoured distributions do not include all possible cases. Next, the case of contours defined by polar coordinates is analyzed including its simulation and parameter estimation. Finally, the case of cumulative distribution functions with given contours is discussed. Several examples are used for illustrative purposes.