The Collateral Channel: How Real Estate Shocks Affect Corporate Investment
Open accessAbstract
What is the impact of real estate prices on corporate investment? In the presence of financing frictions, firms use pledgeable assets as collateral to finance new projects. Through this collateral channel, shocks to the value of real estate can have a large impact on aggregate investment. To compute the sensitivity of investment to collateral value, we use local variations in real estate prices as shocks to the collateral value of firms that own real estate. Over the 1993–2007 period, the representative US corporation invests $0.06 out of each $1 of collateral. (JEL D22, G31, R30)
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The stable groups assumption is presumably satisfied for the Chaney et al. (2012) regression because it is likely that between each pair of consecutive years, there are firms whose market value divided by their lagged PPE does not change.
“The stable groups assumption is presumably satisfied: it is likely that between each pair of consecutive years, there are firms whose market value divided by their lagged PPE does not change.”
From Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects (2020) · cites this paper as Chaney et al. (2012)
In the Chaney et al. (2012) regression Equation (1), the dependent variable is the value of investment in firm i and year t divided by the lagged book value of properties, plants, and equipments (PPE), and the explanatory variables are firm and time fixed effects and the market value of firm i in year t divided by its lagged PPE, and controls.
“In regression Equation (1), the dependent variable is the value of investment in firm i and year t divided by the lagged book value of properties, plants, and equipments (PPE), and the explanatory variables are firm and time fixed effects and the market value of firm i in year t divided by its lagged PPE, and some controls.”
From Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects (2020) · cites this paper as Chaney et al. (2012)
The Chaney et al. (2012) regression corresponds to Regression 1, with some controls.
“This regression corresponds to Regression 1, with some controls.”
From Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects (2020) · cites this paper as Chaney et al. (2012)
The Chaney et al. (2012) regression is a sharp design.
“This is a sharp design.”
From Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects (2020) · cites this paper as Chaney et al. (2012)
Cites
Credit Rationing in Markets with Imperfect Information
Stiglitz, J. E., & Weiss, A. (1981) · Columbia University · doi:10.7916/d8v12ft1 · Cited by 12,769 · see citing works
How Much Should We Trust Differences-in-Differences Estimates?
Bertrand, M., Duflo, E., & Mullainathan, S. (2004) · The Quarterly Journal of Economics · doi:10.1162/003355304772839588 · Cited by 10,641 · see citing works
Agency Costs, Net Worth, And Business Fluctuations
Bernanke, B., Gertler, M., Bernanke, B., & Gertler, M. (1988) · Unknown · doi:10.22004/ag.econ.292693 · Cited by 4,386 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects
de Chaisemartin, C., & D’Haultfœuille, X. (2020) · American Economic Review · doi:10.1257/aer.20181169 · Cited by 5,031 · see citing works
Finance, Growth, and Inequality
Levine, R. (2021) · IMF Working Papers · doi:10.5089/9781513583365.001 · Cited by 62 · see citing works
- Authors
- Chaney, T., Sraer, D., & Thesmar, D.
- Affiliations
- University of Chicago (US)
- Princeton University (US)
- Fondation HEC (FR)
- ORCID
- Thesmar, David
- Venue
- American Economic Review
- Publisher
- American Economic Association
- Published
- 2012-10-01
- Volume
- 102
- Issue
- 6
- Pages
- 2381-2409
- ISSN
- 0002-8282 (ISSN-L)
- OpenAlex
- W3125003292
- Cited by
- 977
- References
- 3
- Citations by year
- 2026: 82 · 2025: 94 · 2024: 92 · 2023: 91 · 2022: 92 · 2021: 92 · 2020: 78 · 2019: 61 · 2018: 67 · 2017: 57 · 2016: 45 · 2015: 43 · 2014: 37 · 2013: 28 · 2012: 9
- FWCI
- 144.46
- Type
- journal article
- Language
- en
- Open access
- green
- hec.hal.science
- Licence
- other-oa
- Locations
- American Economic Review (publishedVersion)
- HAL (submittedVersion, other-oa)
- RePEc: Research Papers in Economics (submittedVersion)
- SPIRE (Sciences Po) (submittedVersion, other-oa)
- Topics
- Social Sciences › Business, Management and Accounting › Accounting › Corporate Finance and Governance
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Housing Market and Economics
- Social Sciences › Economics, Econometrics and Finance › Finance › Capital Investment and Risk Analysis
- Keywords
- real estate prices, corporate investment, collateral channel, financial frictions, collateral value, corporate leverage, aggregate investment
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review