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Decomposing inflation using microprice data Stickyprice inflation

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  • Franz Ruch
  • Neil Rankin
  • Stan du Plessis

Abstract

Some prices are stickier than others. In South Africa (SA), consumer prices on average change every five months; with the most frequent prices changing every month and the least frequent changing every 15 months. Firms that change prices less frequently generally need to take account of the likely path of future inflation when setting these prices if they want to maximise profits. Therefore, prices that are sticky contain more forward-looking information and can be exploited to uncover inflation expectations and underlying, or core, inflation. Using micro-price data this paper decomposes goods inflation into a flexible and sticky-price inflation measure for South Africa at a product level from 2008 to 2015. Flexible-price inflation is more volatile, less persistent, and contributes the most to volatility in overall goods inflation. Sticky-price inflation is more persistent, less volatile and correlates well with future goods inflation. The advantage of sticky-price inflation is that it grounds the concept of underlying inflation into the theoretical framework currently used by central banks to make policy decisions and what is considered optimal policy, making it an ideal core inflation candidate for the central bank. We provide an initial analysis of the appeal of sticky-price inflation comparing it to a number of other core inflation measures including the common exclusion-based measure currently used as well as extend versions of trimmed means and persistence-weighted measures.

Suggested Citation

  • Franz Ruch & Neil Rankin & Stan du Plessis, 2016. "Decomposing inflation using microprice data Stickyprice inflation," Working Papers 7354, South African Reserve Bank.
  • Handle: RePEc:rbz:wpaper:7354
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    File URL: http://www.resbank.co.za/content/dam/sarb/publications/working-papers/2016/7354/WP1607.pdf
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    Cited by:

    1. Byron Botha & Rulof Burger & Kevin Kotzé & Neil Rankin & Daan Steenkamp, 2023. "Big data forecasting of South African inflation," Empirical Economics, Springer, vol. 65(1), pages 149-188, July.

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