Comparing the forecasting ability of financial conditions indices : the case of South Africa

Show simple item record Balcilar, Mehmet Gupta, Rangan Van Eyden, Renee Thompson, Kirsten L. Majumdar, Anandamayee 2018-04-24T12:54:14Z 2018-08
dc.description.abstract In this paper we test the forecasting ability of three estimated financial conditions indices (FCIs) with respect to key macroeconomic variables of output growth, inflation and interest rates. We do this by forecasting the aforementioned macroeconomic variables based on the information contained in the three alternative FCIs using a Bayesian VAR (BVAR), nonlinear logistic vector smooth transition autoregression (VSTAR) and nonparametric (NP) and semi-parametric (SP) regressions, and compare the results with the standard benchmarks of random-walk, univariate autoregressive and classical VAR models. The three FCIs are constructed using rolling-window principal component analysis (PCA), dynamic model averaging (DMA) in the context of a time-varying parameter factor-augmented vector autoregressive (TVP-FAVAR) model, and a time-varying parameter vector autoregressive (TVP-VAR) model with constant factor loadings. Our results suggest that the VSTAR model performs best in the case of forecasting output and inflation, while a SP specification proves to be the best for forecasting the interest rate. More importantly, statistical testing for significant differences in forecast errors across models corroborates the finding of superior predictive ability of the nonlinear models. en_ZA
dc.description.department Economics en_ZA
dc.description.embargo 2020-08-26
dc.description.librarian hj2018 en_ZA
dc.description.uri en_ZA
dc.identifier.citation Balcilar, M., Gupta, R., Van Eyden, R. et al. 2018, 'Comparing the forecasting ability of financial conditions indices: the case of South Africa', Quarterly Review of Economics and Finance, vol. 69, pp. 245-259. en_ZA
dc.identifier.issn 1062-9769
dc.identifier.other 10.1016/j.qref.2018.03.012
dc.language.iso en en_ZA
dc.publisher Elsevier en_ZA
dc.rights © 2018 Board of Trustees of the University of Illinois. Published by Elsevier Inc. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in Quarterly Review of Economics and Finance. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. A definitive version was subsequently published inQuarterly Review of Economics and Finance, vol. 69, pp. 245-259, 2018. doi : 10.1016/j.qref.2018.03.012. en_ZA
dc.subject Financial conditions indices (FCIs) en_ZA
dc.subject Bayesian VAR (BVAR) en_ZA
dc.subject Vector smooth transition autoregression (VSTAR) en_ZA
dc.subject Nonparametric (NP) regression en_ZA
dc.subject Semi-parametric (SP) regression en_ZA
dc.subject Principal component analysis (PCA) en_ZA
dc.subject Dynamic model averaging (DMA) en_ZA
dc.subject Nonlinear logistic smooth transition vector autoregressive model en_ZA
dc.title Comparing the forecasting ability of financial conditions indices : the case of South Africa en_ZA
dc.type Postprint Article en_ZA

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