Does Aggregating Forecasts by CPI Component Improve Inflation Forecast Accuracy in South Africa?
Does Aggregating Forecasts by CPI Component Improve Inflation Forecast Accuracy in South Africa?
复制标题
按 CPI 组成部分汇总预测是否可以提高南非通胀预测的准确性？
DOI：
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
J. Muellbauer
中科院分区：
文献类型：
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作者：
J. Aron;J. Muellbauer
通货膨胀是一种远非同质的现象，这一事实在建立消费者价格通胀模型时往往被忽视。这项研究是新兴市场国家的首项此类研究，通过汇总各分项价格指数的加权预测，与预测总消费者价格指数本身相比，研究了通胀预测准确性的提高。丰富的多元均衡校正模型采用一般和部门的信息为10个子组成部分，考虑到结构性断裂和制度变迁。模型选择是在1979年至2003年，与伪样本预测，四个季度前，产生到2007年。汇总各子组成部分的加权预测确实优于综合CPI预测，而且与使用基准朴素模型的预测相比，也有很大的收益。分析还有助于更好地了解部门性通货膨胀压力。这种预测方法在定期调整消费物价指数权重的情况下应更为稳健。
Inflation is a far from homogeneous phenomenon, a fact often neglected in modelling consumer price inflation. This study, the first of its kind for an emerging market country, investigates gains to inflation forecast accuracy by aggregating weighted forecasts of the sub-component price indices, versus forecasting the aggregate consumer price index itself. Rich multivariate equilibrium correction models employ general and sectoral information for ten sub-components, taking account of structural breaks and institutional changes. Model selection is over 1979-2003, with pseudo out-of-sample forecasts, four-quarters-ahead, generated to 2007. Aggregating the weighted forecasts of the sub-components does outperform the aggregate CPI forecasts, and also offers substantial gains over forecasting using benchmark naive models. The analysis also contributes an improved understanding of sectoral inflationary pressures. This forecasting method should be more robust to the regular reweighting of the CPI index.
南非消费者价格指数组成部分的随机估计框架
影响因子：
1.3
作者：
Aron J
通讯作者：
Aron J