Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.22617/WPS190056-2 |
Quarterly Forecasting Model for India's Economic Growth: Bayesian Vector Autoregression Approach | |
[unavailable] | |
2019-03-13 | |
出版年 | 2019 |
语种 | 英语 |
国家 | 国际 |
领域 | 气候变化 |
英文摘要 |
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. Contents
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URL | 查看原文 |
来源平台 | Asian Development Bank |
引用统计 | |
文献类型 | 科技报告 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/237098 |
专题 | 气候变化 |
推荐引用方式 GB/T 7714 | [unavailable]. Quarterly Forecasting Model for India's Economic Growth: Bayesian Vector Autoregression Approach,2019. |
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ewp-573-forecasting-(692KB) | 科技报告 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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