Reinvigorating GVA Nowcasting in the Post-pandemic Period: A Case Study for India

Authors

Kaustubh NA, Reserve Bank of India, IndiaFollow
Soumya Suvra Bhadury, Reserve Bank of India, IndiaFollow
Saurabh Ghosh, Reserve Bank of India, IndiaFollow

Document Type

Call for Paper

Abstract

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.

Recommended Citation

NA, Kaustubh; Bhadury, Soumya Suvra; and Ghosh, Saurabh (2024) "Reinvigorating GVA Nowcasting in the Post-pandemic Period: A Case Study for India," Bulletin of Monetary Economics and Banking: Vol. 27: No. 0, Article 7.
DOI: https://doi.org/10.59091/2460-9196.2160
Available at: https://bulletin.bmeb-bi.org/bmeb/vol27/iss0/7

First Page

95

Last Page

130

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Country

India

Affiliation

Reserve Bank of India