A timely and reliable prediction of economic activities is crucial in policymaking, especially in the current COVID-19 pandemic situation, which requires real-time decisions. However, making frequent predictions is challenging due to the substantial delays in releasing aggregate economic data. This study aims to nowcast Indonesia’s economic activities during the COVID-19 pandemic using the novel high-frequency Facebook Mobility Index as a predictor. Employing mixed-frequency, mixed-data sampling, and benchmark least-squares models, we expanded the mobility index and used it to track the growth dynamics of the gross regional domestic product of provinces in Java and Bali and performed a bottom-up approach to estimate the aggregated economic growth of the provinces altogether. Our results suggested that the daily Facebook Mobility Index was a considerably reliable predictor for projecting economic activities on time. All models almost consistently produced reliable directional predictions. Notably, we found the mixed data sampling-autoregressive model to be slightly superior to the other models in terms of overall precision and directional predictive accuracy across observations.

This research was conducted as a part of the project ‘ERIA Research on COVID-19’ at the Economic Research Institute for ASEAN and East Asia (ERIA).

Tracking the Ups and Downs in Indonesia’s Economic Activity During COVID-19 Using Mobility Index: Evidence from Provinces in Java and Bali