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Reinvigorating Gva Nowcasting In The Post-Pandemic Period: A Case Study For India, Kaustubh Na, Soumya Suvra Bhadury, Saurabh Ghosh
Reinvigorating Gva Nowcasting In The Post-Pandemic Period: A Case Study For India, Kaustubh Na, Soumya Suvra Bhadury, Saurabh Ghosh
Bulletin of Monetary Economics and Banking
We reinvigorate nowcasting models considering structural changes caused by the COVID-19 pandemic. It emphasizes the need to understand the heterogeneous impact of shocks on agriculture, industry, and services sectors in an emerging market economy (e.g., India). Our findings advocate a bottom-up approach that tracks sectors separately rather than a headline number. Our results suggest including digital-activity index and supply-side disruption index in the post-pandemic period could improve nowcast performance. Expectation-Maximization (E-M) algorithm is used to combine data series based on their availability. Among bridging methods, the averaging method is preferred due to its simplicity and flexibility.