REINVIGORATING GVA NOWCASTING IN THE POST-PANDEMIC PERIOD: A CASE STUDY FOR INDIA

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, such as India. Our findings advocate a bottom-up approach that tracks sectors separately rather than a headline number. Our results suggest that including digital-activity index and supply-side disruption index in the post-pandemic period could improve nowcast performance. Expectation-Maximization 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.