Causality between inflation and inflation uncertainty in South Africa: Evidence from a Markov-switching vector autoregressive model

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• 作者：Adnen Ben Nasr^a ; ^{adnen.bennasr@isg.rnu.tn" class="auth_mail" title="E-mail the corresponding author} ; Mehmet Balcilar^b ; ^c ; ^{mehmet@mbalcilar.net" class="auth_mail" title="E-mail the corresponding author} ; Ahdi N. Ajmi^d ; ^{ajmi.ahdi.noomen@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; Goodness C. Aye^d ; ^{goodness.aye@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; Rangan Gupta^c ; ^{rangan.gupta@up.ac.za" class="auth_mail" title="E-mail the corresponding author} ; Reneé ; van Eyden^d ; ^{renee.vaneyden@up.ac.za" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Inflation ; Inflation uncertainty ; Seasonality ; Long memory ; Time-varying causality ; Markov switching model
• 刊名：Emerging Markets Review
• 出版年：2015
• 出版时间：September 2015
• 年：2015
• 卷：24
• 期：Complete
• 页码：46-68
• 全文大小：954 K

文摘

This study investigates the asymmetric and time-varying causalities 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 the 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 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 favor 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.