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

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DC Field	Value	Language
dc.contributor.author	ADB; Iyer, Tara; Sen Gupta, Abhijit	-
dc.date.accessioned	2021-10-05T15:04:55Z	-
dc.date.available	2021-10-05T15:04:55Z	-
dc.date.issued	2019-03	-
dc.identifier.isbn	N/A	-
dc.identifier.isbn	N/A	-
dc.identifier.issn	2313-6537	-
dc.identifier.issn	2313-6545	-
dc.identifier.uri	https://www.adb.org/publications/quarterly-forecasting-model-economic-growth-india	-
dc.identifier.uri	https://elibrary.tucl.edu.np/handle/123456789/5663	-
dc.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.	-
dc.format.extent	46	-
dc.subject.other	Economic data	-
dc.subject.other	Economic research	-
dc.subject.other	Economics	-
dc.title	Quarterly Forecasting Model for India's Economic Growth: Bayesian Vector Autoregression Approach	-
local.publication.country	India	-
Appears in Collections:	ADB Collections

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