| ID | 187819 |
| Title Proper | Informal economy at times of COVID-19 pandemic |
| Language | ENG |
| Author | Guo, Feng |
| Summary / Abstract (Note) | We provide a first view of vulnerable informal economy after the blows from COVID-19, using transaction-level business data of around 80 million offline micro businesses (OMBs) owners from the largest Fintech company in China and employing machine learning method for causal inference. We find that the OMBs activities in China experienced an immediate and dramatic drop of 50% during the trough. The businesses had rebounded to around 80% of where they should be seven weeks after the COVID-19 outbreak, but had remained at this level until the end of our time window. We find a larger disruption to the OMBs in urban areas, the female merchants and the merchants who were not grown up in the places where they conducted businesses. We discuss the implications for policy support to the most vulnerable, and highlight the importance to take full advantage of digital development to follow up the informal economy. |
| `In' analytical Note | China Economic Review Vol. 71; Feb 2022: p.101722 |
| Journal Source | China Economic Review 2022-01 71 |
| Key Words | Informal Economy ; Machine learning ; COVID-19 ; Offline Micro Businesses |