Slipping anchor? Testing the vignettes approach to identification and correction of reporting heterogeneity

Anchoring vignettes are increasingly used to identify and correct heterogeneity in the reporting of health, work disability, life satisfaction, political efficacy, etc. with the aim of improving interpersonal comparability of subjective indicators of these constructs. The method relies on two assumptions: vignette equivalence – the vignette description is perceived by all to correspond to the same state; and, response consistency - individuals use the same response scales to rate the vignettes and their own situation. We propose tests of these assumptions. For vignette equivalence, we test a necessary condition of no systematic variation with observed characteristics in the perceived difference in states corresponding to any two vignettes. To test response consistency we rely on the assumption that objective indicators fully capture the covariation between the construct of interest and observed individual characteristics, and so offer an alternative way to identify response scales, which can then be compared with those identified from the vignettes. We also introduce a weaker test that is valid under a less stringent assumption. We apply these tests to cognitive functioning and mobility related health problems using data from the English Longitudinal Survey of Ageing. Response consistency is rejected for both health domains according to the first test, but the weaker test does not reject for cognitive functioning. The necessary condition for vignette equivalence is rejected for both health domains. These results cast some doubt on the validity of the vignettes approach, at least as applied to these health domains

Applied Health Economics

The first edition of Applied Health Economics did an expert job of showing how the availability of large scale data sets and the rapid advancement of advanced econometric techniques can help health economists and health professionals make sense of information better than ever before. This second edition has been revised and updated throughout and includes a new chapter on the description and modelling of individual health care costs, thus broadening the book's readership to those working on risk adjustment and health technology appraisal. The text also fully reflects the very latest advances in the health economics field and the key journal literature. Large-scale survey datasets, in particular complex survey designs such as panel data, provide a rich source of information for health economists. They offer the scope to control for individual heterogeneity and to model the dynamics of individual behaviour. However, the measures of outcome used in health economics are often qualitative or categorical. These create special problems for estimating econometric models. The dramatic growth in computing power over recent years has been accompanied by the development of methods that help to solve these problems. The purpose of this book is to provide a practical guide to the skills required to put these techniques into practice. Practical applications of the methods are illustrated using data on health from the British Health and Lifestyle Survey (HALS), the British Household Panel Survey (BHPS), the European Community Household Panel (ECHP), the US Medical Expenditure Panel Survey (MEPS) and Survey of Health, Ageing and Retirement in Europe (SHARE). There is a strong emphasis on applied work, illustrating the use of relevant computer software with code provided for Stata. Familiarity with the basic syntax and structure of Stata is assumed. The Stata code and extracts from the statistical output are embedded directly in the main text and explained at regular intervals. The book is built around empirical case studies, rather than general theory, and the emphasis is on learning by example. It presents a detailed dissection of methods and results of some recent research papers written by the authors and their colleagues. Relevant methods are presented alongside the Stata code that can be used to implement them and the empirical results are discussed at each stage. This text brings together the theory and application of health economics and econometrics, and will be a valuable reference for applied economists and students of health economics and applied econometrics