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On the power of underdifferencing and over differencing tests against nearly nonstationary alternatives

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Detalhes bibliográficos
Resumo:The choice of the appropriate degree of integration is a very important question in ARIMA time series modeling. This choice is particularly difficult in the presence of either a nearly nonstationary autoregression or a fractionally integrated process. Via a Monte Carlo study we assess the size and power of MA, AR and spectral estimation tests in the presence of fractionally integrated, nearly nonstationary, and nearly noninvertible processes.
Autores principais:Crato, Nuno
Outros Autores:Lima, Pedro de
Assunto:ARIMA ARFIMA AR MA Unit Roots
Ano:1997
País:Portugal
Tipo de documento:artigo
Tipo de acesso:acesso aberto
Instituição associada:Universidade de Lisboa
Idioma:inglês
Origem:Repositório da Universidade de Lisboa
Descrição
Resumo:The choice of the appropriate degree of integration is a very important question in ARIMA time series modeling. This choice is particularly difficult in the presence of either a nearly nonstationary autoregression or a fractionally integrated process. Via a Monte Carlo study we assess the size and power of MA, AR and spectral estimation tests in the presence of fractionally integrated, nearly nonstationary, and nearly noninvertible processes.