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Forecasting using a large number of predictors : is bayesian regression a valid alternative to principal components? / Christine De Mol, Domenico Giannone, Lucrezia Reichlin.

Por:

De Mol, Christine

Colaborador(es):

Tipo de material: Texto

TextoSeries Discussion paper (Deutsche Bundesbank). Series 1: economic studies ; ; no. 32/2006Detalles de publicación: Frankfurt am Main : Deutsche Bundesbank, 2006Descripción: 36 pISBN:

3865582079

Tema(s):

Clasificación CDD:

21 330.015195

Recursos en línea:

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Resumen: This paper considers Bayesian regression with normal and doubleexponential priors as forecasting methods based on large panels of time series. We show that, empirically, these forecasts are highly correlated with principal component forecasts and that they perform equally well for a wide range of prior choices. Moreover, we study the asymptotic properties of the Bayesian regression under Gaussian prior under the assumption that data are quasi collinear to establish a criterion for setting parameters in a large cross-section.

Existencias
Tipo de ítem	Biblioteca actual	Signatura topográfica	Estado	Fecha de vencimiento	Código de barras
Documento	Biblioteca Manuel Belgrano	F 330.015195 D 21081 (Navegar estantería(Abre debajo))	Disponible		21081 F

Bibliografía: p. 17-19.

This paper considers Bayesian regression with normal and doubleexponential priors as forecasting methods based on large panels of time series. We show that, empirically, these forecasts are highly correlated with principal component forecasts and that they perform equally well for a wide range of prior choices. Moreover, we study the asymptotic properties of the Bayesian regression under Gaussian prior under the assumption that data are quasi collinear to establish a criterion for setting parameters in a large cross-section.

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BIBLIOTECA MANUEL BELGRANO - Facultad de Ciencias Económicas - UNC

Forecasting using a large number of predictors : is bayesian regression a valid alternative to principal components? / Christine De Mol, Domenico Giannone, Lucrezia Reichlin.