Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
IDEAS home Printed from https://ideas.repec.org/a/ris/apltrx/0444.html
   My bibliography  Save this article

Assessment of inflation expectations based on internet data

Author

Listed:
  • Petrova, Diana

    (RANEPA; Moscow, Russian Federation)

Abstract

This article provides assessments of inflation expectations of Russian internet users based on the posts of the social media Vkontakte and Google Trends search queries during 2014–2021. We collect posts from news communities and search queries to measure inflation expectations using inflation-related regular expressions. Inflation expectations based on internet data are highly correlated with actual inflation and reflect household concerns about price increases during 2014–2021. Granger causality tests have shown both measures of internet user inflation expectations can be potential predictors of actual inflation. An econometric analysis of the New Keynesian Phillips Curve is carried out using VAR from February 2015 to December 2021. The results suggest that an increase in inflation expectations is consistent with an increase in actual inflation and a tightening of monetary policy.

Suggested Citation

  • 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.
    • Handle: RePEc:ris:apltrx:0444
    as

    Download full text from publisher

    File URL: http://pe.cemi.rssi.ru/pe_2022_66_025-038.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Larsen, Vegard H. & Thorsrud, Leif Anders & Zhulanova, Julia, 2021. "News-driven inflation expectations and information rigidities," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 507-520.
    2. J. Daniel Aromí & Martín Llada, 2020. "Forecasting inflation with twitter," Asociación Argentina de Economía Política: Working Papers 4308, Asociación Argentina de Economía Política.
    3. Sophocles Mavroeidis & Mikkel Plagborg-Møller & James H. Stock, 2014. "Empirical Evidence on Inflation Expectations in the New Keynesian Phillips Curve," Journal of Economic Literature, American Economic Association, vol. 52(1), pages 124-188, March.
    4. Angelico, Cristina & Marcucci, Juri & Miccoli, Marcello & Quarta, Filippo, 2022. "Can we measure inflation expectations using Twitter?," Journal of Econometrics, Elsevier, vol. 228(2), pages 259-277.
    5. Galí, Jordi & Gertler, Mark, 1999. "Inflation Dynamics: A Structural Economic Analysis," CEPR Discussion Papers 2246, C.E.P.R. Discussion Papers.
    6. Lamla, Michael J. & Lein, Sarah M., 2014. "The role of media for consumers’ inflation expectation formation," Journal of Economic Behavior & Organization, Elsevier, vol. 106(C), pages 62-77.
    7. Lei, Chengyao & Lu, Zhe & Zhang, Chengsi, 2015. "News on inflation and the epidemiology of inflation expectations in China," Economic Systems, Elsevier, vol. 39(4), pages 644-653.
    8. Olivier Coibion & Yuriy Gorodnichenko & Rupal Kamdar, 2018. "The Formation of Expectations, Inflation, and the Phillips Curve," Journal of Economic Literature, American Economic Association, vol. 56(4), pages 1447-1491, December.
    9. Gali, Jordi & Gertler, Mark, 1999. "Inflation dynamics: A structural econometric analysis," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 195-222, October.
    10. I. Goloshchapova & M. Andreev., 2017. "Measuring inflation expectations of the Russian population with the help of machine learning," VOPROSY ECONOMIKI, N.P. Redaktsiya zhurnala "Voprosy Economiki", vol. 6.
    11. 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.
    12. Saakshi Jha & Sohini Sahu, 2020. "Forecasting inflation for India with the Phillips Curve: Evidence from internet search data," Economics Bulletin, AccessEcon, vol. 40(3), pages 2372-2379.
    13. Efrem Castelnuovo & Paolo Surico, 2010. "Monetary Policy, Inflation Expectations and The Price Puzzle," Economic Journal, Royal Economic Society, vol. 120(549), pages 1262-1283, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Vasilii Chsherbakov & Ilia Karpov, 2024. "Regional inflation analysis using social network data," Papers 2403.00774, arXiv.org, revised Mar 2024.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Petar Soric & Enric Monte & Salvador Torra & Oscar Claveria, 2022. ""Density forecasts of inflation using Gaussian process regression models"," IREA Working Papers 202210, University of Barcelona, Research Institute of Applied Economics, revised Jul 2022.
    2. Bec, Frédérique & Kanda, Patrick, 2020. "Is inflation driven by survey-based, VAR-based or myopic expectations? An empirical assessment from US real-time data," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    3. Combes, Jean-Louis & Lesuisse, Pierre, 2022. "Inflation and unemployment, new insights during the EMU accession," International Economics, Elsevier, vol. 172(C), pages 124-142.
    4. Michael McLeay & Silvana Tenreyro, 2020. "Optimal Inflation and the Identification of the Phillips Curve," NBER Macroeconomics Annual, University of Chicago Press, vol. 34(1), pages 199-255.
    5. Pooja Kapoor & Sujata Kar, 2023. "A review of inflation expectations and perceptions research in the past four decades: a bibliometric analysis," International Economics and Economic Policy, Springer, vol. 20(2), pages 279-302, May.
    6. Barnichon, Regis & Mesters, Geert, 2021. "The Phillips multiplier," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 689-705.
    7. Thórarinn G. Pétursson, 2022. "Long‐term inflation expectations and inflation dynamics," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 158-174, January.
    8. Paul Hubert & Harun Mirza, 2019. "The role of forward‐ and backward‐looking information for inflation expectations formation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(8), pages 733-748, December.
    9. Lena Boneva & James Cloyne & Martin Weale & Tomasz Wieladek, 2020. "Firms' Price, Cost and Activity Expectations: Evidence from Micro Data," The Economic Journal, Royal Economic Society, vol. 130(627), pages 555-586.
    10. Vasilii Chsherbakov & Ilia Karpov, 2024. "Regional inflation analysis using social network data," Papers 2403.00774, arXiv.org, revised Mar 2024.
    11. Frédérique Bec & Patrick Kanda, 2019. "Is inflation driven by survey-based, VAR-based or myopic expectations?," Working Papers hal-02175836, HAL.
    12. Alexander Doser & Ricardo Nunes & Nikhil Rao & Viacheslav Sheremirov, 2023. "Inflation expectations and nonlinearities in the Phillips curve," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 453-471, June.
    13. Franz Xaver Zobl & Martin Ertl, 2021. "The Condemned Live Longer – New Evidence of the New Keynesian Phillips Curve in Central and Eastern Europe," Open Economies Review, Springer, vol. 32(4), pages 671-699, September.
    14. Chee-Hong Law & Kim Huat Goh, 2024. "A systematic literature review of the implications of media on inflation expectations," International Economics and Economic Policy, Springer, vol. 21(2), pages 311-340, May.
    15. Xu, Kun & Cheng, Jian-hua & Xu, Wenli, 2016. "通胀及通胀预期冲击的动态特征分析 [Study on Dynamics of Inflation and Inflation Expectation Shocks in China]," MPRA Paper 71977, University Library of Munich, Germany.
    16. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Working Papers 22-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    17. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org, revised Oct 2024.
    18. Boneva, Lena & Cloyne, James & Weale, Martin & Wieladek, Tomasz, 2018. "Firms' Expectations of New Orders, Employment, Costs and Prices: Evidence from Micro Data," CEPR Discussion Papers 12722, C.E.P.R. Discussion Papers.
    19. Aguiar-Conraria, Luís & Martins, Manuel M.F. & Soares, Maria Joana, 2023. "The Phillips curve at 65: Time for time and frequency," Journal of Economic Dynamics and Control, Elsevier, vol. 151(C).
    20. Marco Del Negro & Michele Lenza & Giorgio E. Primiceri & Andrea Tambalotti, 2020. "What's Up with the Phillips Curve?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 51(1 (Spring), pages 301-373.

    More about this item

    Keywords

    inflation expectations; internet data; Vkontakte; Google Trends; search queries; VAR;
    All these keywords.

    JEL classification:

    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ris:apltrx:0444. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Anatoly Peresetsky (email available below). General contact details of provider: http://appliedeconometrics.cemi.rssi.ru/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.