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Nowcasting GDP Growth Using a Coincident Economic Indicator for India

Author

Listed:
  • Bhadury, Soumya
  • Ghosh, Saurabh
  • Kumar, Pankaj

Abstract

In India, the first official estimate of quarterly GDP is released approximately 7-8 weeks after the end of the reference quarter. To provide an early estimate of the current quarter GDP growth, we construct a Coincident Economic Indicator for India (CEII) using 6, 9 and 12 high-frequency indicators. These indicators represent various sectors, display high contemporaneous correlation with GDP, and track GDP turning points well. While CEII-6 includes domestic economic activity indicators, CEII-9 combines indicators on trade and services along with the indicators used in CEII-6. Finally, CEII-12 adds financial indicators to the indicators used in CEII-9. In addition to the conventional economic activity indicators, we include a financial block in CEII-12 to reflect the growing influence of the financial sector on economic activity. CEII is estimated using a dynamic factor model to extract a common trend underlying the highfrequency indicators. We use the underlying trend to gauge the state of the economy and to identify sectors contributing to economic fluctuations. Further, CEIIs are used to nowcast GDP growth, which closely tracks the actual GDP growth, both in-sample and out-of-sample.

Suggested Citation

  • Bhadury, Soumya & Ghosh, Saurabh & Kumar, Pankaj, 2019. "Nowcasting GDP Growth Using a Coincident Economic Indicator for India," MPRA Paper 96007, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:96007
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    References listed on IDEAS

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    Cited by:

    1. Rudrani Bhattacharya & Bornali Bhandari & Sudipto Mundle, 2023. "Nowcasting India’s Quarterly GDP Growth: A Factor-Augmented Time-Varying Coefficient Regression Model (FA-TVCRM)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(1), pages 213-234, March.

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    More about this item

    Keywords

    Nowcast; Gross Domestic Product; Economic Cycle; Dynamic Factor Model; Turning Point Analysis; Jagged Edge Data;
    All these keywords.

    JEL classification:

    • 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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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