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

Parma Chakravartti and Sudipto Mundle

Working Papers from eSocialSciences

Abstract: Building on the early work of Mitchell and Burns (1938,1946), the automatic leading indicator (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 dynamic 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%.

Keywords: Growth Rate; Forecasting; Automatic Leading Indicator; Dynamic Factor Model; Agriculture; Industry; Services; GDP; Demonetization; Mature; Economies; Macroeconomic; Autoregression; Structural; Techniques. (search for similar items in EconPapers)
Date: 2017-05
Note: Institutional Papers
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Working Paper: An Automatic Leading Indicator Based Growth Forecast For 2016-17 and The Outlook Beyond (2017)
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