Master's Dissertation
DOI
https://doi.org/10.11606/D.11.2004.tde-25032004-141721
Document
Author
Full name
Juliana Garcia Cespedes
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
Piracicaba, 2003
Supervisor
Committee
Leandro, Roseli Aparecida (President)
Achcar, Jorge Alberto
Demetrio, Clarice Garcia Borges
Title in Portuguese
Eficiência de produção: um enfoque Bayesiano.
Keywords in Portuguese
eficiência econômica
inferência bayesiana
Abstract in Portuguese
O uso de fronteira de produ¸c ao estoc´ astica com m´ ultiplos produtos
tem despertado um interesse especial em ´areas da economia que defrontam-se com o
problema de quantificar a eficiencia t´ecnica de firmas. Na estat´ýstica cl´ assica, quando
se defronta com firmas que possuem v´arios produtos, as fun¸c oes custo ou demanda
s ao mais utilizadas para calcular essa eficiencia, mas isso requer uma quantidade
maior de informa¸c oes sobre os dados, al´em das quantidades de insumos e produtos,
tamb´em s ao necess´ arios seus pre¸cos e custos. Quando existem apenas informa¸c oes
sobre os insumos (x) e os produtos (y) h´a a necessidade de se trabalhar com a fun¸c ao
de produ¸c ao e a inexistencia de estat´ýsticas suficientes para alguns par ametros tornam
a an´alise d´ýficil. A abordagem Bayesiana pode se tornar uma ferramenta muito ´ util
para esse caso, pois ´e poss´ývel obter uma amostra da distribui¸ c ao de probabilidade dos
par ametros do modelo, possibilitando a obten¸c ao de resumos de interesse. Para obter as amostras dessas distribui¸ c oes m´etodos Monte Carlo com cadeias de Markov, tais
como, amostrador de Gibbs, Metropolis-Hastings e "Slice sampling" s ao utilizados.
Title in English
Production efficiency: a bayesian approach.
Keywords in English
bayesian inference
economic efficiency
Abstract in English
The use of stochastic production frontier with multiple-outputs has
been waking up a special interest in areas of the economy that are confronted with
the problem of quantifying the technical efficiency of firms. In the classic statistics,
when it is confronted with firms that possess several outputs, cost or profit functions
are more used to calculate that efficiency, but that requests an amount larger of
information about data set, besides the amounts of inputs and outputs, are also
necessary your prices and costs. When just exist information on inputs (x) and
outputs (y) there is need to work with the production function and the lack of
enough statistics for some parameters turn the difficult analysis. Bayesian approach
can become a useful tool for that case, because is possible to obtain a sample of
the distribution of probability of the parameters of the model, making possible the
obtaining of summaries of interest. To obtain samples of those distributions methods Markov chains Monte Carlo, that is, Gibbs sampling, Metropolis-Hastings and Slice
sampling are used.
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Publishing Date
2004-03-29