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
