A two-step indirect inference approach to estimate the long-run risk asset pricing model
- The long-run consumption risk model provides a theoretically appealing explanation for prominent asset pricing puzzles, but its intricate structure presents a challenge for econometric analysis. This paper proposes a two-step indirect inference approach that disentangles the estimation of the model's macro-economic dynamics and the investor's preference parameters. A Monte Carlo study explores the feasibility and efficiency of the estimation strategy. We apply the method to recent U.S.\data and provide a critical re-assessment of the long-run risk model's ability to reconcile the real economy and financial markets. This two-step indirect inference approach is potentially useful for the econometric analysis of other prominent consumption-based asset pricing models that are equally difficult to estimate.
Author: | Joachim Grammig, Eva-Maria Küchlin |
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URN: | urn:nbn:de:hebis:30:3-438725 |
DOI: | https://doi.org/10.2139/ssrn.2820506 |
Document Type: | Report |
Language: | English |
Year of Completion: | 2017 |
Year of first Publication: | 2017 |
Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
Release Date: | 2017/10/17 |
Tag: | asset pricing; indirect inference estimation; long-run risk |
Issue: | May 27, 2017 |
Page Number: | 73 |
First Page: | 0 |
Last Page: | 72 |
HeBIS-PPN: | 419722815 |
Dewey Decimal Classification: | 3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft |
Sammlungen: | Universitätspublikationen |
Licence (German): | ![]() |