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High frequency online inflation and term structure of interest rates: Evidence from China

Author

Listed:
  • Zhang, Tao
  • Tang, Ke
  • Liu, Taoxiong
  • Jiang, Tingfeng

Abstract

In the digital era, the information value of online prices, characterized by weak price stickiness and high sensitivity to economic shocks, deserves more attention. This paper integrates the high-frequency online inflation rate into the dynamic Nelson-Siegel (DNS) model to explore its relationship with the term structure of interest rates. The empirical results show that the weekly online inflation significantly predicts the yield curve, especially the slope factor, whereas the monthly official inflation cannot predict the yield curve and is instead predicted by the yield curve factors. The mechanism analysis reveals that, due to low price stickiness, online inflation is more sensitive to short-term economic fluctuations and better reflects money market liquidity, thereby having significant predictive power for short-term interest rates and the slope factor. Specifically, online inflation for non-durable goods and on weekdays shows stronger predictive power for the slope factor. The heterogeneity in price stickiness across these categories explains the varying impacts on the yield curve.

Suggested Citation

  • Zhang, Tao & Tang, Ke & Liu, Taoxiong & Jiang, Tingfeng, 2025. "High frequency online inflation and term structure of interest rates: Evidence from China," Journal of Empirical Finance, Elsevier, vol. 83(C).
    • Handle: RePEc:eee:empfin:v:83:y:2025:i:c:s0927539825000489
    DOI: 10.1016/j.jempfin.2025.101626
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    Keywords

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    JEL classification:

    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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