Arbeitspapier

Variance estimation in a random coefficients model

This papers describes an estimator for a standard state-space model with coefficients generated by a random walk that is statistically superior to the Kalman filter as applied to this particular class of models. Two closely related estimators for the variances are introduced: A maximum likelihood estimator and a moments estimator that builds on the idea that some moments are equalized to their expectations. These estimators perform quite similar in many cases. In some cases, however, the moments estimator is preferable both to the proposed likelihood estimator and the Kalman filter, as implemented in the program package Eviews.

Language
Englisch

Bibliographic citation
Series: IZA Discussion Papers ; No. 2031

Classification
Wirtschaft
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Model Construction and Estimation
Model Evaluation, Validation, and Selection
Subject
time-varying coefficients
adaptive estimation
Kalman filter
state-space

Event
Geistige Schöpfung
(who)
Schlicht, Ekkehart
Ludsteck, Johannes
Event
Veröffentlichung
(who)
Institute for the Study of Labor (IZA)
(where)
Bonn
(when)
2006

Handle
Last update
10.03.2025, 11:44 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Schlicht, Ekkehart
  • Ludsteck, Johannes
  • Institute for the Study of Labor (IZA)

Time of origin

  • 2006

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