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Nowcasting Indian GDP

Author

Listed:
  • Daniela Bragoli

    (Universita Cattolica)

  • Jack Fosten

    (University of East Anglia)

Abstract

We propose a nowcasting model for the Indian real GDP growth rate which uses the flow of relevant information to update predictions on a daily basis and can serve as a timely barometer to track the Indian development process. There are several challenges faced when nowcasting GDP in developing economies such as India. The first challenge is to proxy im- portant missing variables such as international trade in the service sector. Our novel solution augments a baseline model with series on US and Euro-area output which improves predictions, particularly during the 2008-2009 global crisis. The second challenge is the impact of sizeable revisions to the GDP data. We construct a new series for real-time Indian GDP using press releases from the Central Statistics Office (CSO), finding that data revisions have a non-trivial influence on our results. Therefore, caution should be taken when evaluating predictions using the preliminary GDP release.

Suggested Citation

  • Daniela Bragoli & Jack Fosten, 2016. "Nowcasting Indian GDP," University of East Anglia School of Economics Working Paper Series 2016-06, School of Economics, University of East Anglia, Norwich, UK..
  • Handle: RePEc:uea:ueaeco:2016_06
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    References listed on IDEAS

    as
    1. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
    2. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
    3. Daniela Bragoli & Luca Metelli & Michele Modugno, 2015. "The importance of updating: Evidence from a Brazilian nowcasting model," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2015(1), pages 5-22.
    4. Martin D. D. Evans, 2005. "Where Are We Now? Real-Time Estimates of the Macroeconomy," International Journal of Central Banking, International Journal of Central Banking, vol. 1(2), September.
    5. Boivin, Jean & Ng, Serena, 2006. "Are more data always better for factor analysis?," Journal of Econometrics, Elsevier, vol. 132(1), pages 169-194, May.
    6. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    7. Bernanke, Ben S. & Boivin, Jean, 2003. "Monetary policy in a data-rich environment," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 525-546, April.
    8. repec:eee:intfor:v:33:y:2017:i:4:p:915-935 is not listed on IDEAS
    9. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2005. "Nowcasting GDP and Inflation: The Real Time Informational Content of Macroeconomic Data Releases," CEPR Discussion Papers 5178, C.E.P.R. Discussion Papers.
    10. Alberto Caruso, 2015. "Nowcasting Mexican GDP," Working Papers ECARES ECARES 2015-40, ULB -- Universite Libre de Bruxelles.
    11. 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.
    12. Bhattacharya, Rudrani & Pandey, Radhika & Veronese, Giovanni, 2011. "Tracking India Growth in Real Time," Working Papers 11/90, National Institute of Public Finance and Policy.
    13. Marta Bańbura & Michele Modugno, 2014. "Maximum Likelihood Estimation Of Factor Models On Datasets With Arbitrary Pattern Of Missing Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(1), pages 133-160, January.
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    1. repec:eee:intfor:v:33:y:2017:i:4:p:915-935 is not listed on IDEAS
    2. repec:eee:ecmode:v:69:y:2018:i:c:p:160-168 is not listed on IDEAS
    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. Pérez, Fernando, 2018. "Nowcasting Peruvian GDP using Leading Indicators and Bayesian Variable Selection," Working Papers 2018-010, Banco Central de Reserva del Perú.

    More about this item

    Keywords

    nowcasting; emerging markets; data revisions; dynamic factor model; economic growth;

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • 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
    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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