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Tracking India Growth in Real Time

Author

Listed:
  • Bhattacharya, Rudrani

    (National Institute of Public Finance and Policy)

  • Pandey, Radhika

    (National Institute of Public Finance and Policy)

  • Veronese, Giovanni

    (Bank of Italy)

Abstract

Tracking growth in the Indian economy would be best performed using a measure like GDP. Unfortunately official estimates of this indicator are released with quarterly frequency and with considerable delay. This paper compares different approaches to the short term forecasting (nowcasting) of real GDP growth in India and evaluates methods to optimally gauge the current state of the economy. Univariate quarterly models are compared with bridge models that exploit the available monthly indicators containing information on current quarter developments. In the forecasting exercise we perform a pseudo real-time simulation: by properly taking into account the actual publication lags of the series, we replicate the information set available to the policymaker at each point of time. We find that bridge models perform satisfactorily in predicting current quarter GDP growth. This result follows from the actual estimation technique used to construct the official quarterly national accounts, still largely dependent on a narrow information set. Our analysis also suggests mixed evidences about the additional predictive power of Indian survey data with respect to the hard data already used in the national accounts.

Suggested Citation

  • Bhattacharya, Rudrani & Pandey, Radhika & Veronese, Giovanni, 2011. "Tracking India Growth in Real Time," Working Papers 11/90, National Institute of Public Finance and Policy.
  • Handle: RePEc:npf:wpaper:11/90
    Note: Working Paper 90, 2011
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    References listed on IDEAS

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    13. Philipp Maier, 2011. "Mixed Frequency Forecasts for Chinese GDP," Staff Working Papers 11-11, Bank of Canada.
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    Cited by:

    1. 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.
    2. 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.
    3. Dahlhaus, Tatjana & Guénette, Justin-Damien & Vasishtha, Garima, 2017. "Nowcasting BRIC+M in real time," International Journal of Forecasting, Elsevier, vol. 33(4), pages 915-935.
    4. Daniela Bragoli & Jack Fosten, 2018. "Nowcasting Indian GDP," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(2), pages 259-282, April.
    5. Herwadkar, Snehal S. & Ghosh, Saurabh, 2020. "Is PMI a good leading indicator of industrial production?: Evidence from India," MPRA Paper 97924, University Library of Munich, Germany.

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    More about this item

    Keywords

    Nowcasting ; Bridge model ; Factor model ; Emerging markets ; India;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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