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Association between inflation rates and inflation uncertainty in quantile regression

Alimi, R. Santos (2017): Association between inflation rates and inflation uncertainty in quantile regression.

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Abstract

Inflation and its associated uncertainty impose costs on real economic output in every economy. In developing economies, this welfare cost is higher than those obtainable in developed countries because inflation rate is still higher than desired, mostly double-digit in Africa. In contrast to conventional conditional mean approaches, this study employed quantile regressions and cross-sectional data from 44 African countries for the period 1986 to 2015 to examine the relationship between the level of inflation and inflation uncertainty. This study considers two measures of inflation – Inflation rate and mean inflation, and three different measures of inflation uncertainty – standard deviation, relative variation and median deviation of the inflation rate. The study found evidence of positive and significant association between inflation and its uncertainty across quantiles. It also found that higher inflation brings about more inflation variability, thereby supporting the Friedman-Ball hypothesis and on the other hand high inflation uncertainty prompts rises in inflation, confirming the Cukierman-Meltzer hypothesis. The study therefore recommend that policy makers should target low average inflation rates in order to reduce the negative consequences of inflation uncertainty, which in turn can improve economic performance in Africa.

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