Working Paper: CEPR ID: DP15943
Authors: Kilian Huber
Abstract: Large-scale shocks directly affect some firms and households and indirectly impact others through general equilibrium spillovers. In this paper, I describe how researchers can directly estimate spillovers using quasi-experimental or experimental variation. I then argue that spillover estimates suffer from distinct sources of mechanical bias that standard empirical tools cannot resolve. These biases are particularly relevant in finance and macroeconomics where multiple spillover channels and nonlinear effects are common. I offer guidance on how to detect and overcome mechanical biases. An application and several examples highlight that the suggested methods are broadly relevant and can inform policy and multiplier calculations.
Keywords: General Equilibrium Effects; Spillovers; Estimation; Macroeconomic Shocks; Financial Shocks
JEL Codes: C2; E00; G21; G32; R11; L11
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| large-scale shocks (E32) | direct effects on some firms and households (H31) |
| large-scale shocks (E32) | indirect effects through general equilibrium spillovers (F69) |
| shock in one region (R11) | influence on employment and wages in neighboring regions (F66) |
| credit disruption at a bank (G21) | affects treated firms and other firms in the same region (R30) |
| spillover estimates (C21) | subject to mechanical biases (C83) |
| direct estimation of spillovers (C13) | calculation of policy and multiplier effects (C54) |