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Forecasting core inflation: the case of South Africa

机译：预测核心通货膨胀：南非的案例

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Underlying, or core, inflation is likely the most important variable for monetary policy. It is considered to be the optimal nominal anchor as it is stable, excludes relative price shocks, and reflects underlying trends in the behaviour of price-setters and demand conditions in the economy. Despite its importance, there is sparse literature on estimating and forecasting core inflation in South Africa, with the focus still on measuring it. This paper emphasizes predicting core inflation from time-varying parameter vector autoregressive models (TVP-VARs), factor-augmented VARs (FAVAR), and structural break models using quarterly data from 1981Q1 to 2013Q4. We use mean squared forecast errors (MSFE) and predictive likelihoods to evaluate the forecasts. In general, we find that (i) time-varying parameter models consistently outperform constant coefficient models (ii) small TVP-VARs outperform all other models; (iii) models with heteroscedastic errors do better than models with homoscedastic errors; and (iv) allowing for structural breaks does not improve the predictability of core inflation. Overall, our results imply that additional information on the growth rate of the economy and the interest rate is sufficient to forecast core inflation accurately, but the relationship between these three variables needs to be modelled in a time-varying fashion.
机译：底层或核心，通货膨胀可能是货币政策最重要的变量。它被认为是最佳的标称锚定，因为它稳定，不包括相对价格冲击，并反映了在经济中价格稳定者和需求条件的行为的基础趋势。尽管重要的是，在南非估算和预测核心通胀的估计和预测核心通胀有稀疏的文献，重点仍在测量它。本文强调，使用1981Q1至2013Q4的季度数据，从时变参数矢量自回归模型（TVP-VAR），因子增强的var（Favar），因子增强的var（Favar）和结构中断模型中的核心通胀预测。我们使用均衡预测错误（MSFE）和预测似然性来评估预测。一般来说，我们发现（i）时变参数模型始终优于恒定恒定系数模型（ii）小型TVP-vars优于所有其他型号; （iii）具有异源误差的模型比具有同性恋错误的模型更好; （iv）允许结构性断裂不会提高核心通胀的可预测性。总体而言，我们的结果意味着有关经济增长率和利率的额外信息足以准确地预测核心通胀，但这三个变量之间的关系需要以时变的方式进行建模。

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