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An Automatic Leading Indicator Based Growth Forecast For 2016-17 and The Outlook Beyond

Author

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  • Chakravartti, Parma

    (National Institute of Public Finance and Policy)

  • Mundle, Sudipto

    (National Institute of Public Finance and Policy)

Abstract

Building on the early work of Mitchell and Burns (1938,1946), the automatic leading indica-tor (ALI) approach has been developed over the last few decades by Geweke (1977), Sargent and Sims (1977), Stock and Watson (1988), Camba-Mendez et al. (1999) , Mongardini and Sedik (2003), Duo-Qin et al. (2006), Grenouilleau (2006) and others. It has come to be widely accepted as one of the most effective methods for macroeconomic forecasting. This paper uses the ALI approach to forecast aggregate and sectoral GDP growth for 2016-17. The approach uses a dy-namic factor model (DFM) in the form of state space representation to extract factors from a pool of variables and then the factors are incorporated into a VAR model to generate the forecast series. Three alternate models have been tried: demand side, supply side and combined model. The model with the lowest RMSE is selected for the forecast. Real GDP growth is forecast at 6.7% for 2016-17 without factoring in the impact of demonetisation. Incorporating that impact reduces the forecast to 6.1%.Length: 30

Suggested Citation

  • Chakravartti, Parma & Mundle, Sudipto, 2017. "An Automatic Leading Indicator Based Growth Forecast For 2016-17 and The Outlook Beyond," Working Papers 17/193, National Institute of Public Finance and Policy.
    • Handle: RePEc:npf:wpaper:17/193
    Note: Working Paper 193, 2017
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    References listed on IDEAS

    as
    1. Stock, James H & Watson, Mark W, 1988. "Variable Trends in Economic Time Series," Journal of Economic Perspectives, American Economic Association, vol. 2(3), pages 147-174, Summer.
    2. Sudipto Mundle, 2017. "Employment, Education and the State," The Indian Journal of Labour Economics, Springer;The Indian Society of Labour Economics (ISLE), vol. 60(1), pages 17-31, March.
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    8. Duo Qin & Marie Anne Cagas & Geoffrey Ducanes & Nedelyn Magtibay-Ramos & Pilipinas Quising, 2006. "Forecasting Inflation and GDP growth: Comparison of Automatic Leading Indicator (ALI) Method with Macro Econometric Structural Models (MESMs)," Working Papers 554, Queen Mary University of London, School of Economics and Finance.
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    1. Parsheera, Smriti & Shah, Ajay & Bose, Avirup, 2017. "Competition Issues in India's Online Economy," Working Papers 17/194, National Institute of Public Finance and Policy.
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    3. Regy, Prasanth V. & Roy, Shubho, 2017. "Understanding Judicial Delays in Debt Tribunals," Working Papers 17/195, National Institute of Public Finance and Policy.

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    More about this item

    Keywords

    Growth Rate ; Forecasting ; Automatic Leading Indicator ; Dynamic Factor Model ; Agriculture ; Industry ; Services ; GDP ; Demonetization;
    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
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity

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