IDEAS home Printed from https://ideas.repec.org/p/iim/iimawp/14645.html
   My bibliography  Save this paper

Determinants of Disagreement: Learning from Indian Inflation Expectations Survey of Households

Author

Listed:
  • Singh, Gaurav Kumar
  • Bandyopadhyay, Tathagata

Abstract

This study explores the determinants of disagreement in households' belief on future inflation. Households commonly show strong information rigidity as a consequence of stickiness in their information update (Mankiw and Reis, 2002, 2006). This paper contributes to the understanding of the formation of disagreement of the Indian households by investigating the effects of - day to day purchasing experiences of the agents, the intensity of news about inflation in the media, and central bank transparency. We find the positive effects of their recent price experiences, media influence, and inflation targeting on lowering the disagreement. Female and Young people tend to exhibit stronger effects in comparison to their counterparts.

Suggested Citation

  • Singh, Gaurav Kumar & Bandyopadhyay, Tathagata, 2021. "Determinants of Disagreement: Learning from Indian Inflation Expectations Survey of Households," IIMA Working Papers WP 2021-01-01, Indian Institute of Management Ahmedabad, Research and Publication Department.
  • Handle: RePEc:iim:iimawp:14645
    as

    Download full text from publisher

    File URL: https://www.iima.ac.in/sites/default/files/rnpfiles/4009687172021-01-01.pdf
    File Function: English Version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Batchelor, Roy, 2007. "Bias in macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 23(2), pages 189-203.
    2. John C. Driscoll & Aart C. Kraay, 1998. "Consistent Covariance Matrix Estimation With Spatially Dependent Panel Data," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 549-560, November.
    3. Daniel Hoechle, 2007. "Robust standard errors for panel regressions with cross-sectional dependence," Stata Journal, StataCorp LP, vol. 7(3), pages 281-312, September.
    4. Author-Name: Alan S. Blinder & Alan B. Krueger, 2004. "What Does the Public Know about Economic Policy, and How Does It Know It?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 35(1), pages 327-397.
    5. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    6. Branch, William A., 2007. "Sticky information and model uncertainty in survey data on inflation expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 31(1), pages 245-276, January.
    7. Michael Ehrmann & Sylvester Eijffinger & Marcel Fratzscher, 2012. "The Role of Central Bank Transparency for Guiding Private Sector Forecasts," Scandinavian Journal of Economics, Wiley Blackwell, vol. 114(3), pages 1018-1052, September.
    8. Mr. Jaromir Benes & Kevin Clinton & Asish George & Joice John & Mr. Ondrej Kamenik & Mr. Douglas Laxton & Pratik Mitra & G.V. Nadhanael & Hou Wang & Fan Zhang, 2017. "Inflation-Forecast Targeting for India: An Outline of the Analytical Framework," IMF Working Papers 2017/032, International Monetary Fund.
    9. Michael Ehrmann & Sylvester Eijffinger & Marcel Fratzscher, 2012. "The Role of Central Bank Transparency for Guiding Private Sector Forecasts," Scandinavian Journal of Economics, Wiley Blackwell, vol. 114(3), pages 1018-1052, September.
    10. Kosuke Imai & In Song Kim, 2019. "When Should We Use Unit Fixed Effects Regression Models for Causal Inference with Longitudinal Data?," American Journal of Political Science, John Wiley & Sons, vol. 63(2), pages 467-490, April.
    Full references (including those not matched with items on IDEAS)

    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. Gaurav Kumar Singh & Tathagata Bandyopadhyay, 2024. "Determinants of disagreement: Learning from inflation expectations survey of households," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 326-343, March.
    2. Ayhan, Fatih & Elal, Onuray, 2023. "The IMPACTS of technological change on employment: Evidence from OECD countries with panel data analysis," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    3. Paul Hubert, 2014. "FOMC Forecasts as a Focal Point for Private Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(7), pages 1381-1420, October.
    4. Dilla, Diana, 2017. "Staatsverschuldung und Verschuldungsmentalität [Public Debt and Debt Mentality]," MPRA Paper 79432, University Library of Munich, Germany.
    5. Kai Daniel Schmid & Michael Schmidt, 2012. "EMU and the Renaissance of Sovereign Credit Risk Perception," IAW Discussion Papers 87, Institut für Angewandte Wirtschaftsforschung (IAW).
    6. G. C. Montes & L. V. Oliveira & A. Curi & R. T. F. Nicolay, 2016. "Effects of transparency, monetary policy signalling and clarity of central bank communication on disagreement about inflation expectations," Applied Economics, Taylor & Francis Journals, vol. 48(7), pages 590-607, February.
    7. Ming Zhong & Jingjing Yu & Syed Anees Haider Zaidi, 2024. "Investigating the Impact of Financial Inclusion on Energy Consumption: Does Corruption Matter?," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(2), pages 8797-8814, June.
    8. Frenkel, Michael & Rülke, Jan-Christoph & Zimmermann, Lilli, 2013. "Do private sector forecasters chase after IMF or OECD forecasts?," Journal of Macroeconomics, Elsevier, vol. 37(C), pages 217-229.
    9. Michael J. Lamla & Thomas Maag, 2012. "The Role of Media for Inflation Forecast Disagreement of Households and Professional Forecasters," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(7), pages 1325-1350, October.
    10. Monica Jain & Christopher S. Sutherland, 2020. "How Do Central Bank Projections and Forward Guidance Influence Private-Sector Forecasts?," International Journal of Central Banking, International Journal of Central Banking, vol. 16(5), pages 179-218, October.
    11. Hoechle, Daniel & Schmid, Markus & Zimmermann, Heinz, 2017. "Does Unobservable Heterogeneity Matter for Portfolio-Based Asset Pricing Tests?," Working Papers on Finance 1717, University of St. Gallen, School of Finance, revised Mar 2020.
    12. Fratianni, Michele & Marchionne, Francesco, 2013. "The fading stock market response to announcements of bank bailouts," Journal of Financial Stability, Elsevier, vol. 9(1), pages 69-89.
    13. Juan Camilo Anzoátegui-Zapata & Juan Camilo Galvis-Ciro, 2020. "Disagreements in Consumer Inflation Expectations: Empirical Evidence for a Latin American Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 16(2), pages 99-122, November.
    14. Faruk Balli & Syed Basher & Rosmy Jean Louis, 2012. "Channels of risk-sharing among Canadian provinces: 1961–2006," Empirical Economics, Springer, vol. 43(2), pages 763-787, October.
    15. André, Christophe & Christou, Christina & Gupta, Rangan, 2024. "Revisiting international house price convergence using house price level data," Economic Systems, Elsevier, vol. 48(2).
    16. Tsani, Stella, 2013. "Natural resources, governance and institutional quality: The role of resource funds," Resources Policy, Elsevier, vol. 38(2), pages 181-195.
    17. Ehrmann, Michael & Gaballo, Gaetano & Hoffmann, Peter & Strasser, Georg, 2019. "Can more public information raise uncertainty? The international evidence on forward guidance," Journal of Monetary Economics, Elsevier, vol. 108(C), pages 93-112.
    18. Atif Khan Jadoon & Sania Akhtar & Ambreen Sarwar & Syeda Azra Batool & Sarvjeet Kaur Chatrath & Saima Liaqat, 2021. "Is Economic Growth And Industrial Growth The Reason For Environmental Degradation In Saarc Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 11(6), pages 418-426.
    19. Ehrmann, Michael, 2021. "Point targets, tolerance bands or target ranges? Inflation target types and the anchoring of inflation expectations," Journal of International Economics, Elsevier, vol. 132(C).
    20. Ouoba, Youmanli, 2016. "Natural resources: Funds and economic performance of resource-rich countries," Resources Policy, Elsevier, vol. 50(C), pages 108-116.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:iim:iimawp:14645. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/eciimin.html .

    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.