Causality between Inflation and Inflation Uncertainty in South Africa: Evidence from a Markov-Switching Vector Autoregressive Model
Adnen Ben Nasr (),
Ahdi Noomen Ajmi,
Goodness Aye (),
Rangan Gupta () and
Renee van Eyden
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Goodness Aye: Department of Economics, University of Pretoria
No 201453, Working Papers from University of Pretoria, Department of Economics
This study investigates the asymmetric and time-varying causality between inflation and inflation uncertainty in South Africa within a conditional Gaussian Markov switching vector autoregressive (MS-VAR) model framework. The MS-VAR model is capable of determining both the sign and direction of causality. We account for the nonlinear, long memory and seasonal features of inflation series simultaneously by measuring inflation uncertainty as the conditional variance of inflation generated by recursive estimation of a Seasonal Fractionally Integrated Smooth Transition Autoregressive Asymmetric Power GARCH (SEA-FISTAR-APGARCH) model using monthly data for the period 1921:01 to 2012:12. The recursive, rather than a full-sample, estimation allows us to obtain a time-varying measure of uncertainty and better mimics the real-time scenario faced by economic agents and/or policy makers. The inferred probabilities from the four-state MS-VAR model show evidence of a time-varying relationship. The conditional (i.e. lead-lag) and regime-prediction Granger causality provide evidence in favour of Friedman’s hypothesis. This implies that past information on inflation can help improve the one-step-ahead prediction of inflation uncertainty but not vice versa. Our results have some important policy implications.
Keywords: Inflation; inflation uncertainty; seasonality; long memory; time-varying causality; Markov switching model (search for similar items in EconPapers)
JEL-codes: C12 C32 E31 (search for similar items in EconPapers)
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Journal Article: Causality between inflation and inflation uncertainty in South Africa: Evidence from a Markov-switching vector autoregressive model (2015)
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