An application to general maximum entropy to utility

Bibliographic Details
Main Author: Ferreira, Paulo
Publication Date: 2013
Other Authors: Dionísio, Andreia
Format: Article
Language: por
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10174/8947
Summary: Methodologies related to information theory have been increasingly used in studies in economics and management. In this paper, we use generalised maximum entropy as an alternative to ordinary least squares in the estimation of utility functions. Generalised maximum entropy has some advantages: it does not need such restrictive assumptions and could be used with both well and ill-posed problems, for example, when we have small samples, which is the case when estimating utility functions. Using linear, logarithmic and power utility functions, we estimate those functions and confidence intervals and perform hypothesis tests. Results point to the greater accuracy of generalised maximum entropy, showing its efficiency in estimation.
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spelling An application to general maximum entropy to utilityGMElinear functionpower functionlogarithmic functionMethodologies related to information theory have been increasingly used in studies in economics and management. In this paper, we use generalised maximum entropy as an alternative to ordinary least squares in the estimation of utility functions. Generalised maximum entropy has some advantages: it does not need such restrictive assumptions and could be used with both well and ill-posed problems, for example, when we have small samples, which is the case when estimating utility functions. Using linear, logarithmic and power utility functions, we estimate those functions and confidence intervals and perform hypothesis tests. Results point to the greater accuracy of generalised maximum entropy, showing its efficiency in estimation.Inderscience Enterprise LTD2013-10-30T11:50:09Z2013-10-302013-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/8947http://hdl.handle.net/10174/8947porFerreira, P; Dionísio, A. (2013). An application to general maximum entropy to utility, International Journal of Applied Decision Sciences, 6 (3), 228-244.Departamento de Gestãopjsf@uevora.ptandreia@uevora.pt637Ferreira, PauloDionísio, Andreiainfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-01-03T18:50:30Zoai:dspace.uevora.pt:10174/8947Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T11:59:19.427548Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv An application to general maximum entropy to utility
title An application to general maximum entropy to utility
spellingShingle An application to general maximum entropy to utility
Ferreira, Paulo
GME
linear function
power function
logarithmic function
title_short An application to general maximum entropy to utility
title_full An application to general maximum entropy to utility
title_fullStr An application to general maximum entropy to utility
title_full_unstemmed An application to general maximum entropy to utility
title_sort An application to general maximum entropy to utility
author Ferreira, Paulo
author_facet Ferreira, Paulo
Dionísio, Andreia
author_role author
author2 Dionísio, Andreia
author2_role author
dc.contributor.author.fl_str_mv Ferreira, Paulo
Dionísio, Andreia
dc.subject.por.fl_str_mv GME
linear function
power function
logarithmic function
topic GME
linear function
power function
logarithmic function
description Methodologies related to information theory have been increasingly used in studies in economics and management. In this paper, we use generalised maximum entropy as an alternative to ordinary least squares in the estimation of utility functions. Generalised maximum entropy has some advantages: it does not need such restrictive assumptions and could be used with both well and ill-posed problems, for example, when we have small samples, which is the case when estimating utility functions. Using linear, logarithmic and power utility functions, we estimate those functions and confidence intervals and perform hypothesis tests. Results point to the greater accuracy of generalised maximum entropy, showing its efficiency in estimation.
publishDate 2013
dc.date.none.fl_str_mv 2013-10-30T11:50:09Z
2013-10-30
2013-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10174/8947
http://hdl.handle.net/10174/8947
url http://hdl.handle.net/10174/8947
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv Ferreira, P; Dionísio, A. (2013). An application to general maximum entropy to utility, International Journal of Applied Decision Sciences, 6 (3), 228-244.
Departamento de Gestão
pjsf@uevora.pt
andreia@uevora.pt
637
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Inderscience Enterprise LTD
publisher.none.fl_str_mv Inderscience Enterprise LTD
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
_version_ 1833592407315185664

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