Nowcasting Indian GDP in Real Time Using Factor Bridge Model and Factor VAR

Abstract

Gross domestic product (GDP) is one of the key economic variables observed to assess the country’s overall economy. India is the third largest economy in the world but lagging in quality and timeliness of GDP reporting.1 The USA, UK, Euro zone and most of the developed countries have been providing better quality and timely information on GDP. Nowcasting is defined as estimation of very recent past, the immediate present and the very recent future (Giannone, Reichlin, & Small, 2008). Much of the work on GDP nowcasting uses pseudo real time data, whereas our research work has used a real time dataset for both the dependent and independent variables for nowcasting Indian GDP in real time. However, the real time datasets have issues of data revisions and biases, which have been handled in this article using a factor modelling approach with bridge model and vector auto regression model. We also explore the impact of within quarter new information flow and this will provide an opportunity to improve the nowcasting accuracy by using the most recent information.

Post-COVID recovery and long-run forecasting of Indian GDP with Factor-augmented Error Correction Model (FECM)

“…A key finding is that rainfall has high predictive content for economic growth. Yadav (2021) nowcasted the Indian GDP in real-time using the factor bridge and factor VAR model. This study is the first research work that used a real-time dataset for both the dependent and independent variables for nowcasting Indian GDP.…”