IDEAS home Printed from https://ideas.repec.org/a/spr/jqecon/v16y2018i1d10.1007_s40953-017-0116-1.html
   My bibliography  Save this article

Is PMI Useful in Quarterly GDP Growth Forecasts for India? An Exploratory Note

Author

Listed:
  • Sangeeta Das

    (Reserve Bank of India
    Reserve Bank of India)

  • Dipankor Coondoo

    (Indian Statistical Institute
    Institute of Development Studies)

Abstract

This paper examines the relationship between India’s quarterly overall GDP, manufacturing GDP and services GDP and the corresponding monthly data on overall manufacturing and services PMI for the period January 2006 to July 2014. The objective is to see if the two overall PMIs are related to the level and quarterly growth rate of overall GDP and its chosen components. Considering the quarterly time series nature of the data set, the HEGY equation of Hylleberg et al. (J Econom 44:215–238, 1990) extended by adding the PMI variables as exogenous regressors is used as the regression mode to relate a GDP level/growth rate variable to the two overall PMI variables. The results show that the three GDP level variables, but none of the GDP growth rate variables, have significant positive correlation with services PMI, but not with manufacturing PMI. Finally, the marginal effect of services PMI on manufacturing GDP level is found to be the largest, followed by that for overall GDP level and services GDP level.

Suggested Citation

  • Sangeeta Das & Dipankor Coondoo, 2018. "Is PMI Useful in Quarterly GDP Growth Forecasts for India? An Exploratory Note," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(1), pages 199-207, December.
    • Handle: RePEc:spr:jqecon:v:16:y:2018:i:1:d:10.1007_s40953-017-0116-1
    DOI: 10.1007/s40953-017-0116-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40953-017-0116-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s40953-017-0116-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    References listed on IDEAS

    as
    1. Lombardi, Marco J. & Maier, Philipp, 2011. "Forecasting economic growth in the euro area during the Great Moderation and the Great Recession," Working Paper Series 1379, European Central Bank.
    2. 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.
    3. Hylleberg, S. & Engle, R. F. & Granger, C. W. J. & Yoo, B. S., 1990. "Seasonal integration and cointegration," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 215-238.
    4. Bhattacharya, Rudrani & Pandey, Radhika & Veronese, Giovanni, 2011. "Tracking India Growth in Real Time," Working Papers 11/90, National Institute of Public Finance and Policy.
    5. James Rossiter, 2010. "Nowcasting the Global Economy," Discussion Papers 10-12, Bank of Canada.
    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. Radoslaw Sobko & Maria Klonowska-Matynia, 2021. "The Relationship between the Purchasing Managers’ Index (PMI) and Economic Growth: The Case for Poland," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 198-219.
    2. Ergun Ermisoglu & Yasin Akcelik & Arif Oduncu, 2013. "GDP Growth and Credit Data," Working Papers 1327, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    3. Stratford, Kate, 2013. "Nowcasting world GDP and trade using global indicators," Bank of England Quarterly Bulletin, Bank of England, vol. 53(3), pages 233-242.
    4. Liu, Ping & James Hueng, C., 2017. "Measuring real business condition in China," China Economic Review, Elsevier, vol. 46(C), pages 261-274.
    5. Gabe de Bondt, 2012. "Nowcasting: Trust the Purchasing Managers’ Index or wait for the flash GDP estimate?," EcoMod2012 3896, EcoMod.
    6. Deicy J. Cristiano & Manuel D. Hernández & José David Pulido, 2012. "Pronósticos de corto plazo en tiempo real para la actividad económica colombiana," Borradores de Economia 724, Banco de la Republica de Colombia.
    7. George Kapetanios & Fotis Papailias, 2018. "Big Data & Macroeconomic Nowcasting: Methodological Review," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-12, Economic Statistics Centre of Excellence (ESCoE).
    8. Gabe J. Bondt & Stefano Schiaffi, 2015. "Confidence Matters for Current Economic Growth: Empirical Evidence for the Euro Area and the United States," Social Science Quarterly, Southwestern Social Science Association, vol. 96(4), pages 1027-1040, December.
    9. Huseyin Cagri Akkoyun & Mahmut Gunay, 2013. "Milli Gelir Buyume Tahmini : IYA ve PMI Gostergelerinin Rolu," CBT Research Notes in Economics 1331, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    10. Lahiri, Kajal & Monokroussos, George & Zhao, Yongchen, 2013. "The yield spread puzzle and the information content of SPF forecasts," Economics Letters, Elsevier, vol. 118(1), pages 219-221.
    11. Garrod Brian & Almeida António & Machado Luiz, 2023. "Modelling of nonlinear asymmetric effects of changes in tourism on economic growth in an autonomous small-island economy," European Journal of Tourism, Hospitality and Recreation, Sciendo, vol. 13(2), pages 154-172, December.
    12. A. Phiri, 2019. "Asymmetries in the revenue–expenditure nexus: new evidence from South Africa," Empirical Economics, Springer, vol. 56(5), pages 1515-1547, May.
    13. Chambers, Marcus J. & Ercolani, Joanne S. & Taylor, A.M. Robert, 2014. "Testing for seasonal unit roots by frequency domain regression," Journal of Econometrics, Elsevier, vol. 178(P2), pages 243-258.
    14. Pulapre Balakrishnan & M Parameswaran, 2019. "Modeling the Dynamics of Inflation in India," Working Papers 16, Ashoka University, Department of Economics.
    15. Isaac Abunyuwah, 2020. "Modeling Market Integration and Asymmetric Price Transmission Dynamics of Yam Markets in Ghana," Journal of Economics and Behavioral Studies, AMH International, vol. 12(3), pages 23-31.
    16. Derek Bond & Michael J. Harrison & Edward J. O'Brien, 2005. "Testing for Long Memory and Nonlinear Time Series: A Demand for Money Study," Trinity Economics Papers tep20021, Trinity College Dublin, Department of Economics.
    17. Jimeno, Juan F. & Bentolila, Samuel, 1998. "Regional unemployment persistence (Spain, 1976-1994)," Labour Economics, Elsevier, vol. 5(1), pages 25-51, March.
    18. Bespalova, Olga, 2018. "Forecast Evaluation in Macroeconomics and International Finance. Ph.D. thesis, George Washington University, Washington, DC, USA," MPRA Paper 117706, University Library of Munich, Germany.
    19. Moosa, Imad A. & Choe, Chongwoo, 1998. "Is the Korean economy export-driven?," Economic Modelling, Elsevier, vol. 15(2), pages 237-255, April.
    20. Ozlem Goktas & Aycan Hepsag, 2011. "Do stock returns lead real economic activity? Evidence from seasonal cointegration analysis," Economics Bulletin, AccessEcon, vol. 31(3), pages 2117-2127.

    More about this item

    Keywords

    Purchasing Managers’ Index; GDP change; Forecasting;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

    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:spr:jqecon:v:16:y:2018:i:1:d:10.1007_s40953-017-0116-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.