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Cited by 259

The DOI matches its Crossref record; 152 of the 152 references it cites were found in a registry or an index.

Dynamic Models and Structural Estimation in Corporate Finance

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Strebulaev, Ilya A.·2011·Foundations and Trends® in Finance

Abstract

We review the last two decades of research in dynamic corporate finance, focusing on capital structure and the financing of investment. We first cover continuous time contingent claims models, starting with real options models, and working through static and dynamic capital structure models. We then move on to corporate financing models based on discrete-time dynamic investment problems. We cover the basic model with no financing, as well as more elaborate models that include features such as costly external finance, cash holding, and both safe and risky debt. For all the models, we offer a minimalist, simplified presentation with a great deal of intuition. Throughout, we show how these models can answer questions concerning the effects of financial constraints on investment, the level of corporate leverage, the speed of adjustment of leverage to its target, and market timing, among others. Finally, we review and explain structural estimation of corporate finance models.

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Metadata

Authors
Strebulaev, I. A.
Venue
Foundations and Trends® in Finance
Publisher
Emerald
Published
2011
Volume
6
Issue
1-2
Pages
1-163
ISSN
  • 1567-2395 (ISSN-L)
  • 1567-2409
OpenAlex
W3125404141
Cited by
259
References
152
FWCI
66.19
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Dynamic Models and Structural Estimation in Corporate Finance. https://app.cochat.ai/papers/10.1561/0500000035
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Strebulaev, I. A. (2011). Dynamic Models and Structural Estimation in Corporate Finance. Foundations and Trends® in Finance. https://doi.org/10.1561/0500000035

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.