IDEAS home Printed from https://ideas.repec.org/p/npf/wpaper/08-54.html
   My bibliography  Save this paper

Early warnings of inflation in India

Author

Listed:
  • Bhattacharya, Rudrani

    (National Institute of Public Finance and Policy)

  • Patnaik, Ila

    (National Institute of Public Finance and Policy)

  • Shah, Ajay

    (National Institute of Public Finance and Policy)

Abstract

In India, year-on-year percentage changes of price indexes are widely used as the measure of inflation. In terms of monthly data, each observation of a one-year change in inflation is the sum of twelve one month changes. This suggests that better information about inflationary pressures can be obtained using point-on-point monthly changes. This requires seasonal adjustment. We apply standard seasonal adjustment procedures in order to obtain a point-on-point seasonally adjusted monthly time-series of inflation in India. In three interesting high inflation episodes { 1994-95, 2007 and 2008 - we find that this data yields a faster and better understanding of inflationary pressures.

Suggested Citation

  • Bhattacharya, Rudrani & Patnaik, Ila & Shah, Ajay, 2008. "Early warnings of inflation in India," Working Papers 08/54, National Institute of Public Finance and Policy.
  • Handle: RePEc:npf:wpaper:08/54
    Note: Working Paper 54, 2008
    as

    Download full text from publisher

    File URL: http://www.nipfp.org.in/working_paper/wp_2008_54.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Harvey, Andrew & Koopman, Siem Jan & Riani, Marco, 1997. "The Modeling and Seasonal Adjustment of Weekly Observations," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 354-368, July.
    2. Pierce, David A & Grupe, Michael R & Cleveland, William P, 1984. "Seasonal Adjustment of the Weekly Monetary Aggregates: A Model-based Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(3), pages 260-270, July.
    3. Bell, William R & Hillmer, Steven C, 1984. "Issues Involved with the Seasonal Adjustment of Time Series: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 343-349, October.
    4. Bell, William R & Hillmer, Steven C, 1984. "Issues Involved with the Seasonal Adjustment of Economic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 291-320, October.
    5. Raghuram G. Rajan, 2008. "Draft Report of the Committee on financial Sector Reforms," Working Papers id:1463, eSocialSciences.
    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. Nadhanael G V & Sitikantha Pattanaik, 2010. "Measurement of Inflation in India: Issues and Associated Challenges for the Conduct of Monetary Policy," Working Papers id:2822, eSocialSciences.
    2. Ila Patnaik & Ajay Shah, 2009. "The difficulties of the Chinese and Indian exchange rate regimes," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 6(1), pages 157-173, June.
    3. Bhattacharya, Rudrani & Pandey, Radhika & Patnaik, Ila & Shah, Ajay, 2016. "Seasonal adjustment of Indian macroeconomic time-series," Working Papers 16/160, National Institute of Public Finance and Policy.
    4. Bhattacharya, Rudrani & Patnaik,Ila, 2014. "Monetary policy analysis in an inflation targeting framework in emerging economies: The case of India," Working Papers 14/131, National Institute of Public Finance and Policy.
    5. Ila Patnaik & Ajay Shah, 2012. "Asia Confronts the Impossible Trinity," Chapters, in: Masahiro Kawai & Peter J. Morgan & Shinji Takagi (ed.), Monetary and Currency Policy Management in Asia, chapter 7, Edward Elgar Publishing.
    6. Paunic, Alida, 2009. "I did it my way," MPRA Paper 17547, University Library of Munich, Germany.

    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. García, Juan R. & Pacce, Matías & Rodrigo, Tomasa & Ruiz de Aguirre, Pep & Ulloa, Camilo A., 2021. "Measuring and forecasting retail trade in real time using card transactional data," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1235-1246.
    2. Diego Bodas & Juan Ramon Garcia & Juan Murillo & Matias Pacce & Tomasa Rodrigo & Juan de Dios Romero & Pep Ruiz & Camilo Ulloa & Heribert Valero, 2018. "Measuring Retail Trade Using Card Transactional Data," Working Papers 18/03, BBVA Bank, Economic Research Department.
    3. Wildi, Marc & McElroy, Tucker S., 2019. "The trilemma between accuracy, timeliness and smoothness in real-time signal extraction," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1072-1084.
    4. Yorghos Tripodis & Jeremy Penzer, 2009. "Modelling time series with season-dependent autocorrelation structure," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(7), pages 559-574.
    5. Barend Abeln & Jan P. A. M. Jacobs, 2023. "CAMPLET: Seasonal Adjustment Without Revisions," SpringerBriefs in Economics, in: Seasonal Adjustment Without Revisions, chapter 0, pages 7-29, Springer.
    6. M. Angeles Carnero & Siem Jan Koopman & Marius Ooms, 2003. "Periodic Heteroskedastic RegARFIMA Models for Daily Electricity Spot Prices," Tinbergen Institute Discussion Papers 03-071/4, Tinbergen Institute.
    7. Edward E. Leamer, 2011. "Workday, Holiday and Calendar Adjustment with 21st Century Data: Monthly Aggregates from Daily Diesel Fuel Purchases," NBER Working Papers 16897, National Bureau of Economic Research, Inc.
    8. Ghysels, E., 1993. "A Time Series Model with Periodic Stochastic Regime Switching," Cahiers de recherche 9314, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    9. Alberto Cabrero & Gonzalo Camba-Mendez & Astrid Hirsch & Fernando Nieto, 2009. "Modelling the daily banknotes in circulation in the context of the liquidity management of the European Central Bank," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(3), pages 194-217.
    10. Barnett, William A. & de Peretti, Philippe, 2009. "Admissible Clustering Of Aggregator Components: A Necessary And Sufficient Stochastic Seminonparametric Test For Weak Separability," Macroeconomic Dynamics, Cambridge University Press, vol. 13(S2), pages 317-334, September.
    11. Susi Gorbey & Doug James & Jacques Poot, 1999. "Population Forecasting with Endogenous Migration: An Application to Trans-Tasman Migration," International Regional Science Review, , vol. 22(1), pages 69-101, April.
    12. Maravall, Agustin, 2006. "An application of the TRAMO-SEATS automatic procedure; direct versus indirect adjustment," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2167-2190, May.
    13. Barend Abeln & Jan P. A. M. Jacobs, 2023. "COVID-19 and Seasonal Adjustment," SpringerBriefs in Economics, in: Seasonal Adjustment Without Revisions, chapter 0, pages 53-61, Springer.
    14. Rishab Guha & Serena Ng, 2019. "A Machine Learning Analysis of Seasonal and Cyclical Sales in Weekly Scanner Data," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 403-436, National Bureau of Economic Research, Inc.
    15. Silhan, Peter A., 2014. "Income smoothing from a Census X-12 perspective," Advances in accounting, Elsevier, vol. 30(1), pages 106-115.
    16. Maravall, Agustin & Planas, Christophe, 1999. "Estimation error and the specification of unobserved component models," Journal of Econometrics, Elsevier, vol. 92(2), pages 325-353, October.
    17. Tommaso Proietti, 2012. "Seasonality, Forecast Extensions And Business Cycle Uncertainty," Journal of Economic Surveys, Wiley Blackwell, vol. 26(4), pages 555-569, September.
    18. Mariam El Hamiani Khatat, 2018. "Monetary Policy and Models of Currency Demand," IMF Working Papers 2018/028, International Monetary Fund.
    19. Tommaso Proietti & Marco Riani, 2009. "Transformations and seasonal adjustment," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(1), pages 47-69, January.
    20. Barend Abeln & Jan P.A.M. Jacobs, 2015. "Seasonal adjustment with and without revisions: A comparison of X-13ARIMA-SEATS and CAMPLET," CIRANO Working Papers 2015s-35, CIRANO.

    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:npf:wpaper:08/54. 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: S.Siva Chidambaram (email available below). General contact details of provider: http://www.nipfp.org.in .

    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.