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A Random Matrix Approach to Dynamic Factors in macroeconomic data

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  • Ma{l}gorzata Snarska

Abstract

We show how random matrix theory can be applied to develop new algorithms to extract dynamic factors from macroeconomic time series. In particular, we consider a limit where the number of random variables N and the number of consecutive time measurements T are large but the ratio N / T is fixed. In this regime the underlying random matrices are asymptotically equivalent to Free Random Variables (FRV).Application of these methods for macroeconomic indicators for Poland economy is also presented.

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  • Ma{l}gorzata Snarska, 2012. "A Random Matrix Approach to Dynamic Factors in macroeconomic data," Papers 1201.6544, arXiv.org.
  • Handle: RePEc:arx:papers:1201.6544
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    File URL: http://arxiv.org/pdf/1201.6544
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    Cited by:

    1. Jerzy Rydlewski & Małgorzata Snarska & Dominik Mielczarek & Daniel Kosiorowski, 2014. "Sparse Methods for Analysis of Sparse Multivariate Data From Big Economic Databases," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 15(1), pages 111-132, January.

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