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How to deal with unobservable variables in economics

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Author Info
Krelle, Wilhelm
Abstract

The paper discusses different methods to deal with unobservable variables: Kalman-Filtering, principal components, factor analysis, LISREL, MIMIC, DYMIMIC, PLS with respect to parameter estimation and forecasting. We got very good results by an extension of Kalman-Filtering called AS (general stationary parameter model). LISREL proved to be superior to PLS in parameter estimation. Explicit introduction of the latent variables "mood" of the economic agents, the "political trend" and "social stability" improved the forecasting performance of an econometric model of the FRG.

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File URL: ftp://web.bgse.uni-bonn.de/pub/RePEc/bon/bonsfb/bonsfb414.pdf
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Publisher Info
Paper provided by University of Bonn, Germany in its series Discussion Paper Serie B with number 414.

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Length: pages
Date of creation: Aug 1997
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Handle: RePEc:bon:bonsfb:414

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Postal: Bonn Graduate School of Economics, University of Bonn, Adenauerallee 24 - 26, 53113 Bonn, Germany
Fax: +49 228 73 9221
Web page: http://www.bgse.uni-bonn.de/index.php?id=517

For technical questions regarding this item, or to correct its listing, contact: (Daniel Park).

Related research
Keywords: parameter estimation forecasting Germany Schneeweiß

Find related papers by JEL classification:
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing

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  1. Engle, Robert F. & Lilien, David M. & Watson, Mark, 1985. "A dymimic model of housing price determination," Journal of Econometrics, Elsevier, vol. 28(3), pages 307-326, June. [Downloadable!] (restricted)
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