Information, data dimension and factor structure
AbstractThis paper employs concepts from information theory to choosing the dimension of a data set. We calculate relative measures of information in the data in terms of eigenvalues and derive criteria to determine the `optimal' size of the data set, in particular whether an extra variable adds information. The methods can be used as a first step in the construction of a dynamic factor model or a leading index, as illustrated with a macroeconomic data set on The Netherlands.
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Bibliographic InfoPaper provided by Netherlands Central Bank, Research Department in its series DNB Working Papers with number 150.
Date of creation: Oct 2007
Date of revision:
information; data set dimension; dynamic factor models; leading index.;
Other versions of this item:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
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