IDEAS home Printed from https://ideas.repec.org/a/eee/intfor/v35y2019i3p980-993.html
   My bibliography  Save this article

Inflation expectations in India: Learning from household tendency surveys

Author

Listed:
  • Das, Abhiman
  • Lahiri, Kajal
  • Zhao, Yongchen

Abstract

We use a large household survey that is being conducted by the Reserve Bank of India since 2005 to estimate the dynamics of aggregate inflation expectations over a volatile inflation regime. A simple average of the quantitative responses produces biased estimates of the official inflation data. We therefore estimate expectations by quantifying the reported directional responses. We perform quantification by using the hierarchical ordered probit model, in addition to the balance statistic. We find that the quantified expectations from qualitative forecasts track the actual inflation rate better than the averages of the quantitative forecasts, highlighting the filtering role of qualitative tendency surveys. We also report estimates of the disagreement among households. The proposed approach is particularly suitable in emerging economies, where inflation tends to be high and volatile.

Suggested Citation

  • Das, Abhiman & Lahiri, Kajal & Zhao, Yongchen, 2019. "Inflation expectations in India: Learning from household tendency surveys," International Journal of Forecasting, Elsevier, vol. 35(3), pages 980-993.
  • Handle: RePEc:eee:intfor:v:35:y:2019:i:3:p:980-993
    DOI: 10.1016/j.ijforecast.2019.03.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0169207019300561
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Dasgupta, Susmita & Lahiri, Kajal, 1992. "A Comparative Study of Alternative Methods of Quantifying Qualitative Survey Responses Using NAPM Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 391-400, October.
    2. Vermeulen, Philip, 2014. "An evaluation of business survey indices for short-term forecasting: Balance method versus Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 30(4), pages 882-897.
    3. Lui, Silvia & Mitchell, James & Weale, Martin, 2011. "The utility of expectational data: Firm-level evidence using matched qualitative-quantitative UK surveys," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1128-1146, October.
    4. R?diger Bachmann & Steffen Elstner & Eric R. Sims, 2013. "Uncertainty and Economic Activity: Evidence from Business Survey Data," American Economic Journal: Macroeconomics, American Economic Association, vol. 5(2), pages 217-249, April.
    5. Lahiri, Kajal & Monokroussos, George, 2013. "Nowcasting US GDP: The role of ISM business surveys," International Journal of Forecasting, Elsevier, vol. 29(4), pages 644-658.
    6. Lahiri, Kajal & Zhao, Yongchen, 2015. "Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 31(1), pages 51-62.
    7. Ash, J. C. K. & Smyth, D. J. & Heravi, S. M., 1998. "Are OECD forecasts rational and useful?: a directional analysis," International Journal of Forecasting, Elsevier, vol. 14(3), pages 381-391, September.
    8. Breitung, Jörg & Schmeling, Maik, 2013. "Quantifying survey expectations: What’s wrong with the probability approach?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 142-154.
    9. Kishor, N. Kundan, 2011. "Data revisions in India: Implications for monetary policy," Journal of Asian Economics, Elsevier, vol. 22(2), pages 164-173, April.
    10. Easaw, Joshy & Golinelli, Roberto & Malgarini, Marco, 2013. "What determines households inflation expectations? Theory and evidence from a household survey," European Economic Review, Elsevier, vol. 61(C), pages 1-13.
    11. Taniya Ghosh & Sohini Sahu & Siddhartha Chattopadhyay, 2017. "Households' Inflation Expectations in India: Role of Economic Policy Uncertainty and Global Financial Uncertainty Spill-over," Working Papers id:11890, eSocialSciences.
    12. Kajal Lahiri & Yongchen Zhao, 2016. "Determinants of Consumer Sentiment Over Business Cycles: Evidence from the US Surveys of Consumers," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(2), pages 187-215, December.
    13. Krkoska, Libor & Teksoz, Utku, 2007. "Accuracy of GDP growth forecasts for transition countries: Ten years of forecasting assessed," International Journal of Forecasting, Elsevier, vol. 23(1), pages 29-45.
    14. Michela Nardo, 2003. "The Quantification of Qualitative Survey Data : A Critical Assessment," Journal of Economic Surveys, Wiley Blackwell, vol. 17(5), pages 645-668, December.
    15. Rina Rosenblatt-Wisch & Rolf Scheufele, 2015. "Quantification and characteristics of household inflation expectations in Switzerland," Applied Economics, Taylor & Francis Journals, vol. 47(26), pages 2699-2716, June.
    16. Richard Curtin, 2007. "Consumer Sentiment Surveys: Worldwide Review and Assessment," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2007(1), pages 7-42.
    17. Alberto Cavallo & Guillermo Cruces & Ricardo Perez-Truglia, 2016. "Learning from Potentially-Biased Statistics: Household Inflation Perceptions and Expectations in Argentina," NBER Working Papers 22103, National Bureau of Economic Research, Inc.
    18. Laurence Ball & Anusha Chari & Prachi Mishra, 2016. "Understanding Inflation in India," NBER Working Papers 22948, National Bureau of Economic Research, Inc.
    19. repec:eee:intfor:v:33:y:2017:i:4:p:878-893 is not listed on IDEAS
    20. Fishe, Raymond P. H. & Lahiri, Kajal, 1981. "On the estimation of inflationary expectations from qualitative responses," Journal of Econometrics, Elsevier, vol. 16(1), pages 89-102, May.
    21. Kaufmann, Daniel & Scheufele, Rolf, 2017. "Business tendency surveys and macroeconomic fluctuations," International Journal of Forecasting, Elsevier, vol. 33(4), pages 878-893.
    22. Yuichiro Ito & Sohei Kaihatsu, 2016. "Effects of Inflation and Wage Expectations on Consumer Spending: Evidence from Micro Data," Bank of Japan Working Paper Series 16-E-7, Bank of Japan.
    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. Ashima Goyal & Prashant Parab, 2019. "Modeling heterogeneity and rationality of inflation expectations across Indian households," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2019-02, Indira Gandhi Institute of Development Research, Mumbai, India.

    More about this item

    Keywords

    Hierarchical ordered probit model; Quantification; Tendency survey; Disagreement; Indian inflation;

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

    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:eee:intfor:v:35:y:2019:i:3:p:980-993. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/ijforecast .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.