An Automatic Leading Indicator Based Growth Forecast For 2016-17 and The Outlook Beyond
Parma Chakravartti () and
Sudipto Mundle
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Parma Chakravartti: National Institute of Public Finance and Policy
Working Papers from 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
Keywords: Growth Rate; Forecasting; Automatic Leading Indicator; Dynamic Factor Model; Agriculture; Industry; Services; GDP; Demonetization (search for similar items in EconPapers)
JEL-codes: C32 C5 O4 (search for similar items in EconPapers)
Date: 2017-03
New Economics Papers: this item is included in nep-for and nep-mac
Note: Working Paper 193, 2017
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Citations: View citations in EconPapers (3)
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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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