Sabiia Seb
PortuguêsEspañolEnglish
Embrapa
        Busca avançada

Botão Atualizar


Botão Atualizar

Ordenar por: RelevânciaAutorTítuloAnoImprime registros no formato resumido
Registros recuperados: 1
Primeira ... 1 ... Última
Imagem não selecionada

Imprime registro no formato completo
Bayesian Learning and the Regulation of Greenhouse Gas Emissions AgEcon
Karp, Larry S.; Zhang, Jiangfeng.
We study the importance of anticipated learning - about both environmental damages and abatement costs - in determining the level and the method of controlling greenhouse gas emissions. We also compare active learning, passive learning, and parameter uncertainty without learning. Current beliefs about damages and abatement costs have an important effect on the optimal level of emissions, However, the optimal level of emissions is not sensitive either to the possibility of learning about damages. or to the type of learning (active or passive), Taxes dominate quotas, but by a small margin.
Tipo: Working or Discussion Paper Palavras-chave: Climate change; Uncertainty; Bayesian learning; Asymmetric information; Choice of instruments; Dynamic optimization; Environmental Economics and Policy; Research Methods/ Statistical Methods; Cll; C6l; D8; H2l; Q28.
Ano: 2001 URL: http://purl.umn.edu/6214
Registros recuperados: 1
Primeira ... 1 ... Última
 

Empresa Brasileira de Pesquisa Agropecuária - Embrapa
Todos os direitos reservados, conforme Lei n° 9.610
Política de Privacidade
Área restrita

Embrapa
Parque Estação Biológica - PqEB s/n°
Brasília, DF - Brasil - CEP 70770-901
Fone: (61) 3448-4433 - Fax: (61) 3448-4890 / 3448-4891 SAC: https://www.embrapa.br/fale-conosco

Valid HTML 4.01 Transitional