Short description/annotation
Blending theory with practice, this book helps readers choose techniques suited both to their data and to their economic model, and illustrates the skills required to put these techniques into practice.
Back cover copy
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 illustratse 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 practise 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.
Table of contents:
CONTENTS
PREFACE
ACKNOWLEDGEMENTS
INTRODUCTION
PART I: DATA DESCRIPTION
1. DATA AND SURVEY DESIGN
1.1 THE HEALTH AND LIFESTYLE SURVEY (HALS)
1.2 THE BRITISH HOUSEHOLD PANEL SURVEY (BHPS)
1.3 THE EUROPEAN COMMUNITY HOUSEHOLD PANEL (ECHP)
1.4 THE CANADIAN NATIONAL POPULATION HEALTH SURVEY (NPHS)
1.5 THE WHO MULTI-COUNTRY STUDY (WHO-MCS)
1.6 OVERVIEW
2. DESCRIBING THE DYNAMICS OF HEALTH
2.1 INTRODUCTION
2.2 GRAPHICAL ANALYSIS
2.3 TABULATING THE DATA
3. INEQUALITY IN HEALTH UTILITY AND SELF-ASSESSED HEALTH
3.1 INTRODUCTION
3.2 DISTRIBUTIONAL ANALYSIS
3.3 REGRESSION ANALYSIS OF HUI: ORDINARY LEAST SQUARES (OLS)
3.4 REGRESSION ANALYSIS OF SAH: ORDERED PROBIT MODEL
3.5 COMBINED ANALYSIS OF HUI AND SAH: INTERVAL REGRESSION
3.6 OVERVIEW
PART II: CATEGORICAL DATA
4. BIAS IN SELF-REPORTED DATA
4.1 INTRODUCTION
4.2 VIGNETTES
4.3 STANDARD ORDERED PROBIT MODEL
4.4 USING VIGNETTES TO CONTROL FOR HETEROGENEOUS REPORTING
5. HEALTH AND LIFESTYLES
5.1 INTRODUCTION
5.2 HALS DATA AND SAMPLE
5.3 DESCRIPTIVE ANALYSIS
5.4 ESTIMATION STRATEGY AND RESULTS
5.5 DISCUSSION
PART III: SURVIVAL DATA
6. SMOKING AND MORTALITY
6.1 INTRODUCTION
6.2 BASIC CONCEPTS OF SURVIVAL ANALYSIS
6.3 THE HALS DATA
6.4 SURVIVAL DATA IN HALS
6.5 DESCRIPTIVE STATISTICS
6.6 DURATION MODELS
7. HEALTH AND RETIREMENT
7.1 INTRODUCTION
7.2 PREPARING AND SUMMARIZING THE DATA
7.3 THE ENDOGENEITY OF HEALTH
7.4 EMPIRICAL APPROACH TO DURATION MODELLING
7.5 STOCK SAMPLING AND DISCRETE-TIME HAZARD ANALYSIS
7.6 OVERVIEW
PART IV: PANEL DATA
8. HEALTH AND WAGES
8.1 INTRODUCTION
8.2 BHPS SAMPLE AND VARIABLES
8.3 EMPIRICAL MODEL AND ESTIMATION
8.4 DISCUSSION
9. MODELLING THE DYNAMICS OF HEALTH
9.1 INTRODUCTION
9.2 STATIC MODELS
9.3 DYNAMIC MODELS
10. NON-RESPONSE AND ATTRITION BIAS
10.1 INTRODUCTION
10.2 TESTING FOR NON-RESPONSE BIAS
10.3 ESTIMATION
11. MODELS FOR HEALTH CARE USE
11.1 INTRODUCTION
11.2 THE POISSON MODEL
11.3 THE NEGATIVE BINOMIAL MODEL
11.4 ZERO INFLATED MODELS
11.5 HURDLE MODELS
11.6 FINITE MIXTURE/LATENT CLASS MODELS
11.7 LATENT CLASS HURDLE MODEL
BIBLIOGRAPHY
INDEX
Blending theory with practice, this book helps readers choose techniques suited both to their data and to their economic model, and illustrates the skills required to put these techniques into practice.
Back cover copy
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 illustratse 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 practise 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.
Table of contents:
CONTENTS
PREFACE
ACKNOWLEDGEMENTS
INTRODUCTION
PART I: DATA DESCRIPTION
1. DATA AND SURVEY DESIGN
1.1 THE HEALTH AND LIFESTYLE SURVEY (HALS)
1.2 THE BRITISH HOUSEHOLD PANEL SURVEY (BHPS)
1.3 THE EUROPEAN COMMUNITY HOUSEHOLD PANEL (ECHP)
1.4 THE CANADIAN NATIONAL POPULATION HEALTH SURVEY (NPHS)
1.5 THE WHO MULTI-COUNTRY STUDY (WHO-MCS)
1.6 OVERVIEW
2. DESCRIBING THE DYNAMICS OF HEALTH
2.1 INTRODUCTION
2.2 GRAPHICAL ANALYSIS
2.3 TABULATING THE DATA
3. INEQUALITY IN HEALTH UTILITY AND SELF-ASSESSED HEALTH
3.1 INTRODUCTION
3.2 DISTRIBUTIONAL ANALYSIS
3.3 REGRESSION ANALYSIS OF HUI: ORDINARY LEAST SQUARES (OLS)
3.4 REGRESSION ANALYSIS OF SAH: ORDERED PROBIT MODEL
3.5 COMBINED ANALYSIS OF HUI AND SAH: INTERVAL REGRESSION
3.6 OVERVIEW
PART II: CATEGORICAL DATA
4. BIAS IN SELF-REPORTED DATA
4.1 INTRODUCTION
4.2 VIGNETTES
4.3 STANDARD ORDERED PROBIT MODEL
4.4 USING VIGNETTES TO CONTROL FOR HETEROGENEOUS REPORTING
5. HEALTH AND LIFESTYLES
5.1 INTRODUCTION
5.2 HALS DATA AND SAMPLE
5.3 DESCRIPTIVE ANALYSIS
5.4 ESTIMATION STRATEGY AND RESULTS
5.5 DISCUSSION
PART III: SURVIVAL DATA
6. SMOKING AND MORTALITY
6.1 INTRODUCTION
6.2 BASIC CONCEPTS OF SURVIVAL ANALYSIS
6.3 THE HALS DATA
6.4 SURVIVAL DATA IN HALS
6.5 DESCRIPTIVE STATISTICS
6.6 DURATION MODELS
7. HEALTH AND RETIREMENT
7.1 INTRODUCTION
7.2 PREPARING AND SUMMARIZING THE DATA
7.3 THE ENDOGENEITY OF HEALTH
7.4 EMPIRICAL APPROACH TO DURATION MODELLING
7.5 STOCK SAMPLING AND DISCRETE-TIME HAZARD ANALYSIS
7.6 OVERVIEW
PART IV: PANEL DATA
8. HEALTH AND WAGES
8.1 INTRODUCTION
8.2 BHPS SAMPLE AND VARIABLES
8.3 EMPIRICAL MODEL AND ESTIMATION
8.4 DISCUSSION
9. MODELLING THE DYNAMICS OF HEALTH
9.1 INTRODUCTION
9.2 STATIC MODELS
9.3 DYNAMIC MODELS
10. NON-RESPONSE AND ATTRITION BIAS
10.1 INTRODUCTION
10.2 TESTING FOR NON-RESPONSE BIAS
10.3 ESTIMATION
11. MODELS FOR HEALTH CARE USE
11.1 INTRODUCTION
11.2 THE POISSON MODEL
11.3 THE NEGATIVE BINOMIAL MODEL
11.4 ZERO INFLATED MODELS
11.5 HURDLE MODELS
11.6 FINITE MIXTURE/LATENT CLASS MODELS
11.7 LATENT CLASS HURDLE MODEL
BIBLIOGRAPHY
INDEX