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Estimação da Eficiência Técnica do SUS nos Estados Brasileiros na Presença de Variáveis Contextuais

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  • Benegas, Maurício
  • da Silva, Francisco Gildemir

Abstract

O propósito deste trabalho é estimar a eficiência técnica do SUS utilizando dados de 2006, referentes às UF´s no Brasil. Utiliza-se o modelo DEA com inclusão de variáveis contextuais para analisar o impacto que certas características locais podem ter sobre a eficiência na oferta de saúde. Adicionalmente, é utilizado um método de seleção de variáveis a fim de melhorar o poder discricionário do modelo. Os resultados mostram que o modelo reduzido melhora o poder discriminatório sem haver perda significativa de informação, e que, população é a única variável contextual que efetivamente promove um ambiente favorável na oferta de saúde pública.

Suggested Citation

  • Benegas, Maurício & da Silva, Francisco Gildemir, 2014. "Estimação da Eficiência Técnica do SUS nos Estados Brasileiros na Presença de Variáveis Contextuais," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 68(2), June.
  • Handle: RePEc:fgv:epgrbe:v:68:y:2014:i:2:a:3058
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    References listed on IDEAS

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    1. Adler, Nicole & Golany, Boaz, 2001. "Evaluation of deregulated airline networks using data envelopment analysis combined with principal component analysis with an application to Western Europe," European Journal of Operational Research, Elsevier, vol. 132(2), pages 260-273, July.
    2. N Adler & B Golany, 2002. "Including principal component weights to improve discrimination in data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(9), pages 985-991, September.
    3. Jenkins, Larry & Anderson, Murray, 2003. "A multivariate statistical approach to reducing the number of variables in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 147(1), pages 51-61, May.
    4. Dyson, R. G. & Allen, R. & Camanho, A. S. & Podinovski, V. V. & Sarrico, C. S. & Shale, E. A., 2001. "Pitfalls and protocols in DEA," European Journal of Operational Research, Elsevier, vol. 132(2), pages 245-259, July.
    5. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2006. "Introduction to Data Envelopment Analysis and Its Uses," Springer Books, Springer, number 978-0-387-29122-2, September.
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