Quantifying Reduced-Form Evidence on Collateral Constraints

Sylvain Catherine (1) , Thomas Chaney (2, 3, 4) , Zongbo Huang (5, 6) , David Sraer (7, 4, 8) , David Thesmar (9, 8, 4)

1 University of Pennsylvania
2 USC - University of Southern California
3 ECON - Département d'économie (Sciences Po)
4 CEPR - Center for Economic Policy Research
5 The Chinese University of Hong Kong [Hong Kong]
6 Shenzhen University [Shenzhen]
7 UC Berkeley - University of California [Berkeley]
8 NBER - National Bureau of Economic Research [New York]
9 MIT - Massachusetts Institute of Technology

This paper quantifies the aggregate effects of financing constraints. We start from a standard dynamic investment model with collateral constraints. In contrast to the existing quantitative literature, our estimation does not target the mean leverage ratio to identify the scope of financing frictions. Instead, we use a reduced-form coefficient from the recent corporate finance literature that connects exogenous debt capacity shocks to corporate investment. Relative to a frictionless benchmark, collateral constraints induce losses of 7.1% for output and 1.4% for total factor productivity (TFP) (misallocation). We show these estimated losses tend to be more robust to misspecification than estimates obtained by targeting leverage.

Domains: Economics and Finance

Sylvain Catherine, Thomas Chaney, Zongbo Huang, David Sraer, David Thesmar. Quantifying Reduced-Form Evidence on Collateral Constraints. Journal of Finance, 2022, 77 (4), pp.2143-2181. ⟨10.1111/jofi.13158⟩. ⟨hal-03869851⟩