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Rationality of inflation expectations: an interpretation of Google Trends data

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  • Motilal Bicchal
  • S. Raja Sethu Durai

Abstract

This study derives inflation expectations from the internet search query data of Google Trends and validates the rationality criteria for India. The empirical analysis is carried out with proper consideration of persistence characteristics of the data for the period from January 2006 to April 2018. The results indicate the derived inflation expectations fulfil the properties of rationality. The results have far-reaching policy implications for the better conduct of monetary policy in favour of using real-time internet search data as an indicator of inflation expectations.

Suggested Citation

  • Motilal Bicchal & S. Raja Sethu Durai, 2019. "Rationality of inflation expectations: an interpretation of Google Trends data," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 12(3), pages 229-239, September.
    • Handle: RePEc:taf:macfem:v:12:y:2019:i:3:p:229-239
    DOI: 10.1080/17520843.2019.1599980
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    Cited by:

    1. Bhattacharya, Rudrani & Kapoor, Mrigankshi, 2020. "Forecasting Consumer Price Index Inflation in India: Vector Error Correction Mechanism Vs. Dynamic Factor Model Approach for Non-Stationary Time Series," Working Papers 20/323, National Institute of Public Finance and Policy.
    2. Levent Bulut, 2018. "Google Trends and the forecasting performance of exchange rate models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(3), pages 303-315, April.
    3. Hakan Yilmazkuday, 2020. "Unequal unemployment effects of COVID-19 and monetary policy across U.S. States," Journal of Behavioral Economics for Policy, Society for the Advancement of Behavioral Economics (SABE), vol. 4(S3), pages 45-53, December.
    4. Goyal, Ashima & Parab, Prashant, 2021. "What influences aggregate inflation expectations of households in India?," Journal of Asian Economics, Elsevier, vol. 72(C).
    5. Petrova, Diana, 2022. "Assessment of inflation expectations based on internet data," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 66, pages 25-38.

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