Project prospection: investing and learning

Detalhes bibliográficos
Autor(a) principal: Figueiredo Neto, José Edilson
Data de Publicação: 2023
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Institucional do FGV (FGV Repositório Digital)
Texto Completo: https://hdl.handle.net/10438/34411
Resumo: Consideramos um modelo no qual uma firma realiza investimentos em um projeto de inovação, objetivando sua conclusão. O término de tal projeto depende de uma ruptura que ocorre a depender de sua factibilidade (“bom”) ou infactibilidade (“ruim”), nunca ocorrendo em caso de um projeto não factível. Enquanto essa ruptura não é atingida, a firma atualiza suas crenças a respeito da qualidade do projeto de maneira pessimista e reconsidera suas decisões de investimento. Nosso principal objetivo é avaliar o efeito do aprendizado em suas decisões. Apesar de aumentos no investimento acarretarem atualizações mais rápidas de crença, as percepções acerca da qualidade do projeto são prejudicadas, o que pode levar a redução no fluxo de investimentos no futuro. Como resultado, concluímos que uma política mais parcimoniosa é ótima, isto é, atualizações bayesianas reduzem o investimento em projetos desse tipo.
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spelling Figueiredo Neto, José EdilsonEscolas::EPGECosta, Carlos Eugênio Ellery Lustosa da Faro, José HelenoGorno, Leandro2023-10-24T17:25:44Z2023-10-24T17:25:44Z2023-03-31https://hdl.handle.net/10438/34411Consideramos um modelo no qual uma firma realiza investimentos em um projeto de inovação, objetivando sua conclusão. O término de tal projeto depende de uma ruptura que ocorre a depender de sua factibilidade (“bom”) ou infactibilidade (“ruim”), nunca ocorrendo em caso de um projeto não factível. Enquanto essa ruptura não é atingida, a firma atualiza suas crenças a respeito da qualidade do projeto de maneira pessimista e reconsidera suas decisões de investimento. Nosso principal objetivo é avaliar o efeito do aprendizado em suas decisões. Apesar de aumentos no investimento acarretarem atualizações mais rápidas de crença, as percepções acerca da qualidade do projeto são prejudicadas, o que pode levar a redução no fluxo de investimentos no futuro. Como resultado, concluímos que uma política mais parcimoniosa é ótima, isto é, atualizações bayesianas reduzem o investimento em projetos desse tipo.We consider the problem of a firm continuously investing in a innovation project. The conclusion of the project relies on the occurrence of a breakthrough, which may never happen depending whether the idea is feasible (“good”) or unfeasible (“bad”). While such breakthrough is not achieved, the company updates its beliefs about the project quality and adjusts the amount of resources allocated to the project’s development. Our main goal is to evaluate the effect of learning in the investment decision. Although increasing investment leads to a quicker update in beliefs, it also damages the perception about the project quality, which may end up reducing future funding. As a result, we find that a more conservative policy is optimal, that is, in the present model, learning induces a lower investment rate in such projects.engBayesian learningProject conclusionR&DNon-homogeneous Poisson processInvestimentosTeoria bayesiana de decisão estatísticaProcesso de PoissonPesquisa e desenvolvimentoProject prospection: investing and learninginfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas (FGV)instacron:FGVTEXTDissertação_final_organized_organized (2).pdf.txtDissertação_final_organized_organized (2).pdf.txtExtracted texttext/plain49077https://repositorio.fgv.br/bitstreams/1d4c8350-4ec1-4d0c-9a5c-c6163c68083e/download54b5a5729afffe2ba4c17e9a0ba10be0MD53PDF.txtPDF.txtExtracted 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dc.title.por.fl_str_mv Project prospection: investing and learning
title Project prospection: investing and learning
spellingShingle Project prospection: investing and learning
Figueiredo Neto, José Edilson
Bayesian learning
Project conclusion
R&D
Non-homogeneous Poisson process
Investimentos
Teoria bayesiana de decisão estatística
Processo de Poisson
Pesquisa e desenvolvimento
title_short Project prospection: investing and learning
title_full Project prospection: investing and learning
title_fullStr Project prospection: investing and learning
title_full_unstemmed Project prospection: investing and learning
title_sort Project prospection: investing and learning
author Figueiredo Neto, José Edilson
author_facet Figueiredo Neto, José Edilson
author_role author
dc.contributor.unidadefgv.por.fl_str_mv Escolas::EPGE
dc.contributor.member.none.fl_str_mv Costa, Carlos Eugênio Ellery Lustosa da
Faro, José Heleno
dc.contributor.author.fl_str_mv Figueiredo Neto, José Edilson
dc.contributor.advisor1.fl_str_mv Gorno, Leandro
contributor_str_mv Gorno, Leandro
dc.subject.eng.fl_str_mv Bayesian learning
Project conclusion
R&D
Non-homogeneous Poisson process
topic Bayesian learning
Project conclusion
R&D
Non-homogeneous Poisson process
Investimentos
Teoria bayesiana de decisão estatística
Processo de Poisson
Pesquisa e desenvolvimento
dc.subject.bibliodata.por.fl_str_mv Investimentos
Teoria bayesiana de decisão estatística
Processo de Poisson
Pesquisa e desenvolvimento
description Consideramos um modelo no qual uma firma realiza investimentos em um projeto de inovação, objetivando sua conclusão. O término de tal projeto depende de uma ruptura que ocorre a depender de sua factibilidade (“bom”) ou infactibilidade (“ruim”), nunca ocorrendo em caso de um projeto não factível. Enquanto essa ruptura não é atingida, a firma atualiza suas crenças a respeito da qualidade do projeto de maneira pessimista e reconsidera suas decisões de investimento. Nosso principal objetivo é avaliar o efeito do aprendizado em suas decisões. Apesar de aumentos no investimento acarretarem atualizações mais rápidas de crença, as percepções acerca da qualidade do projeto são prejudicadas, o que pode levar a redução no fluxo de investimentos no futuro. Como resultado, concluímos que uma política mais parcimoniosa é ótima, isto é, atualizações bayesianas reduzem o investimento em projetos desse tipo.
publishDate 2023
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dc.date.available.fl_str_mv 2023-10-24T17:25:44Z
dc.date.issued.fl_str_mv 2023-03-31
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