Estimating cointegrated systems using subspace algorithms

DOI10.1016/S0304-4076(02)00119-7zbMath1031.62069OpenAlexW2023592030MaRDI QIDQ1868966

Dietmar Bauer, Martin Wagner

Publication date: 9 April 2003

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0304-4076(02)00119-7

zbMATH Keywords

CointegrationSubspace algorithmsState space representation

Mathematics Subject Classification ID

Related Items (14)

Cointegration analysis with state space models ⋮ Unit roots and cointegration modelling through a family of flexible information criteria ⋮ Cointegrated continuous-time linear state-space and MCARMA models ⋮ A new proposal to solve the autocorrelation problem for monitoring processes in the cutlery industry ⋮ AUTOMATED DISCOVERY IN ECONOMETRICS ⋮ ESTIMATING LINEAR DYNAMICAL SYSTEMS USING SUBSPACE METHODS ⋮ Exact maximum likelihood estimation of partially nonstationary vector ARMA models ⋮ Using subspace algorithm cointegration analysis: simulation performance and application to the term structure ⋮ Business cycle analysis and VARMA models ⋮ Quasi-maximum likelihood estimation for cointegrated continuous-time linear state space models observed at low frequencies ⋮ Forecasting key macroeconomic variables from a large number of predictors: a state space approach ⋮ Comparing the CCA Subspace Method to Pseudo Maximum Likelihood Methods in the case of No Exogenous Inputs ⋮ On the Run Length of a State-Space Control Chart for Multivariate Autocorrelated Data ⋮ Forecasting linear dynamical systems using subspace methods

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