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The Index of the Financial Safety (IFS) of South Africa and Bayesian Estimates for IFS Vector-Autoregressive Model

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  • Matkovskyy, Roman

Abstract

This paper proposes an approach to explore the strength of the financial system of a country against the possibility of financial perturbations appearing based on the construction of the Index of Financial Safety (IFS) of a country. The Markov Chain Monte Carlo (MCMC) and Gibbs sampler technique is used to estimate a Bayesian Vector Autoregressive Model of the IFS of South Africa for the period 1990Q1-2011Q1 and to forecast its value over the period 2011Q2-2017Q1. It is shown that the IFS could capture the disturbances in the financial system and the BVAR models with the non-informative and Minnesota priors could predict the future dynamics of IFS with sufficient accuracy.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 42173.

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Date of creation: Apr 2012
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Handle: RePEc:pra:mprapa:42173

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Keywords: Financial safety; index of financial safety (IFS); Bayesian Vector Autoregressive (BVAR) model; MCMC; Gibbs sampler; South Africa;

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Cited by:
  1. Matkovskyy, Roman, 2013. "To the Problem of Financial Safety Estimation: the Index of Financial Safety of Turkey," MPRA Paper 47673, University Library of Munich, Germany.
  2. Matkovskyy, Roman, 2012. "Forecasting the Index of Financial Safety (IFS) of South Africa using neural networks," MPRA Paper 42153, University Library of Munich, Germany.

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