Sinking ships: Liquidity constraints and return predictability in recessions

Using the context of the dry-bulk shipping industry, I document that future returns on real assets are strongly predictable and negatively related to current asset prices, earnings, and investment during recessions. However, there is no such relationship outside recessions. This evidence points to significant liquidity constraints faced by firms during downturns, resulting in cash-in-the-market pricing of capital and rising expected returns for buyers. It is puzzling, however, why firms would not exploit opportunities to buy assets cheaply in recessions, e.g. by pre-arranging credit lines. I build and estimate a model of a competitive industry with credit frictions that can quantitatively account for return predictability during downturns, even though firms can use state-contingent contracts to preserve liquidity for when they need it most. Firms’ relative impatience limits their risk management, meaning that even well-capitalized firms can become constrained following adverse shocks. This results in significant asymmetric amplification of shocks in equilibrium. • Returns on real assets are strongly predictable in recessions, but not other times. • This points to significant liquidity constraints faced by firms during downturns. • A model with financial frictions can quantitatively account for these findings. • Asymmetric amplification arises even when firms can hedge aggregate risk.

Authors

Institutions

Publication Details

Journal
Journal of Monetary Economics
Published
2025-01-23
DOI
https://doi.org/10.1016/j.jmoneco.2025.103746
Citations
1
Primary Topic
Financial Markets and Investment Strategies
Type
article
Field-Weighted Citation Impact
2.21
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Sinking ships: Liquidity constraints and return predictability in recessions

Artur Doshchyn
1 citations
Journal of Monetary Economics
Financial Markets and Investment Strategies
2.21
article

Sinking ships: Liquidity constraints and return predictability in recessions

Artur Doshchyn
article en
1 citations

Abstract

Using the context of the dry-bulk shipping industry, I document that future returns on real assets are strongly predictable and negatively related to current asset prices, earnings, and investment during recessions. However, there is no such relationship outside recessions. This evidence points to significant liquidity constraints faced by firms during downturns, resulting in cash-in-the-market pricing of capital and rising expected returns for buyers. It is puzzling, however, why firms would not exploit opportunities to buy assets cheaply in recessions, e.g. by pre-arranging credit lines. I build and estimate a model of a competitive industry with credit frictions that can quantitatively account for return predictability during downturns, even though firms can use state-contingent contracts to preserve liquidity for when they need it most. Firms’ relative impatience limits their risk management, meaning that even well-capitalized firms can become constrained following adverse shocks. This results in significant asymmetric amplification of shocks in equilibrium. • Returns on real assets are strongly predictable in recessions, but not other times. • This points to significant liquidity constraints faced by firms during downturns. • A model with financial frictions can quantitatively account for these findings. • Asymmetric amplification arises even when firms can hedge aggregate risk.

Journal of Monetary EconomicsVol. 151
University of Bristol (GB)
Climate action
Openalex Percentile: Top 18%
Financial Markets and Investment Strategies
2.21
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.