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A Network Analysis of the United Kingdom’s Consumer Price Index

Author

Listed:
  • Georgios Antonios Sarantitis

    (Democritus University of Thrace)

  • Theophilos Papadimitriou

    (Democritus University of Thrace)

  • Periklis Gogas

    (Democritus University of Thrace)

Abstract

In this paper we model the United Kingdom’s Consumer Price Index as a complex network and we apply clustering and optimization techniques to study the network evolution through time. By doing this, we provide a dynamic, multi-level analysis of the mechanism that drives inflation in the U.K. We find that the CPI classes’ network exhibits an evolving topology through time which depends substantially on the prevailing economic conditions in the U.K. We identify non-overlapping communities of these CPI classes and we observe that they do not correspond to the actual categories they belong to; a finding that suggests that diverse forces are driving the inter-relations of the CPI classes which are stronger between categories rather than within them. Finally, we construct a reduced version of the U.K. CPI that fulfills the core inflation measure criteria and can possibly be used as an appropriate measure of the underlying inflation in the U.K. Since this new measure makes use of only 14 out of the 85 U.K. CPI classes, it can be used to complement the Bank of England’s arsenal of core inflation measures without the need for further resource allocation.

Suggested Citation

  • Georgios Antonios Sarantitis & Theophilos Papadimitriou & Periklis Gogas, 2018. "A Network Analysis of the United Kingdom’s Consumer Price Index," Computational Economics, Springer;Society for Computational Economics, vol. 51(2), pages 173-193, February.
    • Handle: RePEc:kap:compec:v:51:y:2018:i:2:d:10.1007_s10614-016-9625-9
    DOI: 10.1007/s10614-016-9625-9
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    References listed on IDEAS

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    6. Robalo Marques, Carlos & Duarte Neves, Pedro & Morais Sarmento, Luis, 2003. "Evaluating core inflation indicators," Economic Modelling, Elsevier, vol. 20(4), pages 765-775, July.
    7. Jamie Armour, 2006. "An Evaluation of Core Inflation Measures," Staff Working Papers 06-10, Bank of Canada.
    8. Daron Acemoglu & Vasco M. Carvalho & Asuman Ozdaglar & Alireza Tahbaz‐Salehi, 2012. "The Network Origins of Aggregate Fluctuations," Econometrica, Econometric Society, vol. 80(5), pages 1977-2016, September.
    9. Cogley, Timothy, 2002. "A Simple Adaptive Measure of Core Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(1), pages 94-113, February.
    10. Kapetanios, George, 2004. "A note on modelling core inflation for the UK using a new dynamic factor estimation method and a large disaggregated price index dataset," Economics Letters, Elsevier, vol. 85(1), pages 63-69, October.
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    Cited by:

    1. Michail Tsagris, 2021. "A New Scalable Bayesian Network Learning Algorithm with Applications to Economics," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 341-367, January.
    2. Sun, Qingru & Gao, Xiangyun & Wen, Shaobo & Chen, Zhihua & Hao, Xiaoqing, 2018. "The transmission of fluctuation among price indices based on Granger causality network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 36-49.
    3. Emiliano Alvarez & Juan Gabriel Brida & Pablo Mones, 2024. "On the Dynamics of Relative Prices and the Relationship with Inflation: An Empirical Approach," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 339-355, January.
    4. Qingru Sun & Xiangyun Gao & Ze Wang & Siyao Liu & Sui Guo & Yang Li, 2020. "Quantifying the risk of price fluctuations based on weighted Granger causality networks of consumer price indices: evidence from G7 countries," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(4), pages 821-844, October.

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    More about this item

    Keywords

    Network analysis; Threshold-minimum dominating set; Community detection; Core inflation; Consumer price index;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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