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Estimation of Dynamic Econometric Models with Errors in Variables de Jaime Terceiro Lomba

Estimation of Dynamic Econometric Models with Errors in Variables: Lecture Notes in Economics and Mathematical Systems, cartea 339

Autor Jaime Terceiro Lomba
en Limba Engleză Paperback – 4 apr 1990
A new procedure for the maximum-likelihood estimation of dynamic econometric models with errors in both endogenous and exogenous variables is presented in this monograph. A complete analytical development of the expressions used in problems of estimation and verification of models in state-space form is presented. The results are useful in relation not only to the problem of errors in variables but also to any other possible econometric application of state-space formulations.
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Specificații

ISBN-13: 9783540523581
ISBN-10: 3540523588
Pagini: 132
Ilustrații: VIII, 121 p. 1 illus.
Dimensiuni: 170 x 244 x 7 mm
Greutate: 0.22 kg
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Lecture Notes in Economics and Mathematical Systems

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

1. Introduction.- 2. Formulation of Econometric Models in State-Space.- 2.1. Structural Form, Reduced Form and State-Space Form.- 2.2. Additional Remarks.- 3. Formulation of Econometric Models with Measurement Errors.- 3.1. Model of the Exogenous Variables.- 3.2. State-Space Formulation.- 4. Estimation of Econometric Models with Measurement Errors.- 4.1. Evaluation of the Likelihood Function.- 4.2. Maximization of the Likelihood Function.- 4.3. Initial Conditions.- 4.4. Gradient Methods and Identification.- 4.5. Asymptotic Properties.- 4.6. Numerical Considerations.- 4.7. Model Verification.- 5. Extensions of the Analysis.- 5.1. Missing Observations and Contemporaneous Aggregation.- 5.2. Temporal Aggregation.- 5.3. Correlated Measurement Errors.- 6. Numerical Results.- 7. Conclusions.- Appendices.- A. Kalman Filter and Chandrasekhar Equations.- A.1. Kalman Filter.- A.2. Chandrasekhar Equations.- B. Calculation of the Gradient.- C. Calculation of the Hessian.- D. Calculation of the Information Matrix.- E. Estimation of the Initial Conditions.- F. Solution of the Lyapunov and Riccati Equations.- F.1. Lyapunov Equation.- F.2. Riccati Equation.- G. Fixed-Interval Smoothing Algorithm.- References.- Author Index.