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Quarterly Forecasting Model for India’s Economic Growth: Bayesian Vector Autoregression Approach

Author

Listed:
  • Sen Gupta, Abhijit

    (Asian Development Bank)

  • Iyer, Tara

    (Asian Development Bank)

Abstract

This study develops a framework to forecast India’s gross domestic product growth on a quarterly frequency from 2004 to 2018. The models, which are based on real and monetary sector descriptions of the Indian economy, are estimated using Bayesian vector autoregression (BVAR) techniques. The real sector groups of variables include domestic aggregate demand indicators and foreign variables, while the monetary sector groups specify the underlying inflationary process in terms of the consumer price index (CPI) versus the wholesale price index given India’s recent monetary policy regime switch to CPI inflation targeting. The predictive ability of over 3,000 BVAR models is assessed through a set of forecast evaluation statistics and compared with the forecasting accuracy of alternate econometric models including unrestricted and structural VARs. Key findings include that capital flows to India and CPI inflation have high informational content for India’s GDP growth. The results of this study provide suggestive evidence that quarterly BVAR models of Indian growth have high predictive ability.

Suggested Citation

  • Sen Gupta, Abhijit & Iyer, Tara, 2019. "Quarterly Forecasting Model for India’s Economic Growth: Bayesian Vector Autoregression Approach," ADB Economics Working Paper Series 573, Asian Development Bank.
    • Handle: RePEc:ris:adbewp:0573
    as

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    File URL: https://www.adb.org/sites/default/files/publication/490601/ewp-573-forecasting-model-economic-growth-india.pdf
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    References listed on IDEAS

    as
    1. Duncan, Roberto & Martínez-García, Enrique, 2019. "New perspectives on forecasting inflation in emerging market economies: An empirical assessment," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1008-1031.
    2. repec:zbw:bofitp:2014_022 is not listed on IDEAS
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    Cited by:

    1. Iyer , Tara & Sen Gupta, Abhijit, 2019. "Nowcasting Economic Growth in India: The Role of Rainfall," ADB Economics Working Paper Series 593, Asian Development Bank.
    2. Barker, Jamie & Herrala, Risto, 2021. "Assessing the mid-term growth outlook for the Indian economy," BOFIT Policy Briefs 8/2021, Bank of Finland Institute for Emerging Economies (BOFIT).

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    More about this item

    Keywords

    Bayesian vector autoregressions; GDP growth; India; time series forecasting;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • 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
    • F43 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Economic Growth of Open Economies

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