Maximum likelihood estimation of the dynamic shock-error model

DOI10.1016/0304-4076(89)90045-6zbMath0692.62093OpenAlexW2072967894MaRDI QIDQ583814

Damayanti Ghosh

Publication date: 1989

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

Full work available at URL: https://doi.org/10.1016/0304-4076(89)90045-6

zbMATH Keywords

consistencyasymptotic normalitytime domainmaximum likelihood estimatesKalman filteringstate-space representationconsistent estimate of the information matrixdynamic shock-error model

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (4)

Identification of ARX and ARARX models in the presence of input and output noises ⋮ Estimation of quantized linear errors-in-variables models ⋮ The strong consistency of quasi-maximum likelihood estimators for \(p\)-order random coefficient autoregressive (RCA) models ⋮ Dynamic modeling of mean-reverting spreads for statistical arbitrage

Cites Work

• Alternative algorithms for the estimation of dynamic factor, mimic and varying coefficient regression models
• On the convergence properties of the EM algorithm
• Some identification and estimation results for regression models with stochastically varying coefficients
• Identification in dynamic shock-error models
• Efficient estimation of models with composite disturbance terms
• Stochastic processes and filtering theory
• The EM Approach to the Multiple Indicators and Multiple Causes Model Via the Estimation of the Latent Variable
• Evaluation of likelihood functions for Gaussian signals
• Martingale Central Limit Theorems
• Linear Statistical Inference and its Applications
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