Variance Estimation in a Random Coefficients Model

Schlicht, Ekkehart und Ludsteck, Johannes (März 2006): Variance Estimation in a Random Coefficients Model. Münchener Wirtschaftswissenschaftliche Beiträge (VWL) 2006-12

Abstract

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.

• Dokumententyp: Paper
• Keywords: time-varying coefficients, adaptive estimation, random walk, Kalman filter, state-space model
• Fakultät: Volkswirtschaft ; Volkswirtschaft > Munich Discussion Papers in Economics ; Volkswirtschaft > Munich Discussion Papers in Economics > Statistische Methoden ; Volkswirtschaft > Lehrstühle > Seminar für Theorie und Politik der Einkommensverteilung (aufgelöst)
• Themengebiete: 300 Sozialwissenschaften > 300 Sozialwissenschaft, Soziologie ; 300 Sozialwissenschaften > 330 Wirtschaft
• JEL Classification: C2, C22, C51, C52
• Sprache: Englisch