© 2007 – Routledge
352 pages | 24 B/W Illus.
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. This book provides a practical guide to the skills required to put these techniques into practice.
This book illustrates practical applications of these methods using data on health from, among others, the British Health and Lifestyle Survey (HALS), the British Household Panel Survey (BHPS), the European Community Household Panel (ECHP) and the WHO Multi-Country Survey (WHO-MCS). Assuming a familiarity with the basic syntax and structure of Stata, this book presents and explains the statistical output using empirical case studies rather than general theory.
Never before has a health economics text brought theory and practice together and this book will be of great benefit to applied economists, as well as advanced undergraduate and post graduate students in health economics and applied econometrics.
'Jones et al. provide an excellent introduction to the methods used by health economists for the statistical analysis of survey data … Notwithstanding the health focus, the book will be a useful handbook for advanced undergraduates, graduate students, and researchers in many fields in addition to health.' - Stephen P. Jenkins, The Stata Journal
'I would strongly recommend using Applied Health Economics on advanced undergraduate and postgraduate courses in health economics.' - Martin Karlsson, Institute of Ageing, University of Oxford
Introduction Part 1: Data Description 1. Data and Survey Design 2. Describing the Dynamics of Health 3. Inequality in Health Utility and Self-assessed Health Part 2: Categorical Data 4. Bias in Self-reported Data 5. Health and Lifestyles Part 3: Survival Data 6. Smoking and Mortality 7. Health and Retirement Part 4: Panel Data 8. Health and Wages 9. Modelling the Dynamics of Health 10. Non-Response and Attrition Bias 11. Models for Health Care Use