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Master's Dissertation
DOI
https://doi.org/10.11606/D.12.2008.tde-08102008-100017
Document
Author
Full name
Paloma Vaissman Uribe
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2008
Supervisor
Committee
Alves, Denisard Cneio de Oliveira (President)
Avelino, Ricardo Rezende Gomes
Belluzzo Junior, Walter
Title in Portuguese
Utilização de modelos de contagem na estimação da demanda por consultas médicas
Keywords in Portuguese
Econometria
Economia da saúde
Sistema unificado de saúde
Abstract in Portuguese
Este trabalho tem por objetivo identificar e quantificar o efeito dos determinantes para a demanda de consultas médicas no Brasil. Utilizando a base de dados do suplemento sobre saúde da PNAD de 2003, foram estimados modelos de contagem e comparados segundo critérios estatísticos. O modelo escolhido foi o Hurdle Binomial Negativo, que guarda relação com a teoria do agente principal aplicada à Economia da Saúde. Na especificação foram consideradas variáveis socioeconômicas como renda, gênero, idade, escolaridade, raça e região, e variáveis de saúde, como informação sobre morbidades, auto-avaliação da saúde, tipo de provimento (público ou privado) e cobertura de seguro-saúde. Além disso, estimou-se um preço sombra para o setor público de forma a incorporar a variável preço dos serviços de saúde na estimação. De forma geral, concluiu-se que existem iniqüidades no acesso à saúde da população favorecendo os indivíduos de renda elevada.
Title in English
Count data models: an application to the demand for health care
Keywords in English
Econometrics
Health Economics
Health System
Abstract in English
The present work intends to identify and to measure the effect of some drivers for the healthcare demand. Using the database of the health supplement of the national household survey of the year 2003, several count data models were compared. According to some statistical criteria, the Hurdle Negative Binomial model was considered the best and was founded to be related to the agency theory applied to Health Economics. The specification was composed by social and economic variables such as income, gender, age, education, race and region and by health related variables, like morbidity, self assessed health, health system and insurance status. Moreover, it was estimated a shadow price for public sector in order to incorporate the price of health services in the healthcare frequency model. In general, it was founded iniquities in the access to the healthcare services.
 
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paloma_uribe_final2.pdf (546.10 Kbytes)
Publishing Date
2008-10-10
 
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