Working Paper: NBER ID: w30689
Authors: Gaurav Khanna; Nicolas Morales; Nitya Pandalainayar
Abstract: We characterize what features make supply chains more resilient. Using new data on the universe of firm-to-firm transactions from an Indian state, we identify firms with larger supplier risk following the Covid-19 lockdowns. Using an event-study design we find firms with suppliers in strict-lockdown districts experienced 4.5pp higher separation rates (a 15% increase relative to baseline). We study which characteristics increase supply-chain resilience. Firms that buy more complex products, with fewer available suppliers, are less likely to break links. We explore how firms change post-shock supplier composition. Firms with higher supplier risk form new links with larger and better-connected suppliers.
Keywords: Supply Chain Resilience; COVID-19; Indian Firms; Supplier Risk
JEL Codes: F14; L14
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Supplier lockdown severity (L81) | Increased separation rates (J12) |
| Higher supplier risk (L14) | Lower entry rates (E43) |
| Higher supplier risk (L14) | Higher net separations (F12) |
| One standard deviation increase in supplier risk (C69) | Decrease in input purchases (E20) |
| One standard deviation increase in supplier risk (C69) | Decrease in output (E23) |
| Supplier characteristics (L15) | Net separation rates (J63) |
| Purchasing more complex products (L14) | Lower likelihood of breaking links (L15) |