Please use this identifier to cite or link to this item: https://elibrary.tucl.edu.np/handle/123456789/5663
Title: Quarterly Forecasting Model for India's Economic Growth: Bayesian Vector Autoregression Approach
Authors: ADB; Iyer, Tara; Sen Gupta, Abhijit
Issue Date: Mar-2019
Description: This study seeks to develop an appropriate econometric framework to forecast India’s gross domestic product (GDP) growth on a quarterly basis. The framework, based on Bayesian econometric methods, is found to have high predictive ability. Useful findings emerge on the particular variables that are responsible for explaining GDP growth in India. The best performing models take into account the influence of capital flows in driving growth over the past decade and trade linkages in influencing growth in the early 2000s. Overall, the results from this study provide suggestive evidence that Bayesian vector autoregression methods are highly effective in predicting GDP growth in India.
URI: https://www.adb.org/publications/quarterly-forecasting-model-economic-growth-india
https://elibrary.tucl.edu.np/handle/123456789/5663
ISBN: N/A
N/A
ISSN: 2313-6537
2313-6545
Country: India
Appears in Collections:ADB Collections

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.