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.