Applied Health Economics

by Jones, Andrew M.; Rice, Nigel; Bago D'uva, Teresa; Balia, Silvia

• ISBN13: 9780203972304
• ISBN10: 0203972309
• Copyright: 2007-03-20
• Publisher: Taylor & Francis

Summary

"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 economies 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." "A distinctive feature of the text is the way that it brings together theory and practice. 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."--BOOK JACKET.

Author Biography

Silvia Balia is an Assistant Professor at the Department of Economic and Social Research, University of Cagliari. Teresa Bago d'Uva is an Assistant Professor at the Department of Economics, Erasmus University. Nigel Rice is Reader in Health Economics at the University of York. Andrew M. Jones is Professor of Economics and Director of the Graduate Programme in Health Economics at the University of York.

Table of Contents

Preface

Acknowledgements

Introduction

Data Description

Data and Survey Design

The Health and Lifestyle Survey (HALS)

The British Household Panel Survey (BHPS)

The European Community Household Panel (ECHP)

The Canadian National Population Health Survey (NPHS)

The Who Multi-Country Study (WHO-MCS)

Overview

Describing the Dynamics of Health

Introduction

Graphical Analysis

Tabulating the Data

Inequality in Health Utility and Self-Assessed Health

Introduction

Distributional Analysis

Regression Analysis of Hui: Ordinary Least Squares (OLS)

Regression Analysis of Sah: Ordered Probit Model

Combined Analysis of Hui and Sah: Interval Regression

Overview

Categorical Data

BIas in Self-Reported Data

Introduction

Vignettes

Standard Ordered Probit Model

Using Vignettes to Control For Heterogeneous Reporting

Health and Lifestyles

Introduction

Hals Data and Sample

Descriptive Analysis

Estimation Strategy and Results

Discussion

Survival Data

Smoking and Mortality

Introduction

Basic Concepts of Survival Analysis

The Hals Data

Survival Data in Hals

Descriptive Statistics

Duration Models

Health and Retirement

Introduction

Preparing and Summarizing the Data

The Endogeneity of Health

Empirical Approach to Duration Modelling

Stock Sampling and Discrete-Time Hazard Analysis

Overview

Panel Data

health and Wages

Introduction

BHPS Sample and Variables

Empirical Model and Estimation

Discussion

Modelling the Dynamics of Health

Introduction

Static Models

Dynamic Models

Non-Response and Attrition Bias

Introduction

Testing For Non-Response Bias

Estimation

Models For Health Care Use

Introduction

The Poisson Model

The Negative Binomial Model

Zero Inflated Models

Hurdle Models

Finite Mixture/Latent Class Models

Latent Class Hurdle Model

Bibliography

Index

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