Learning from manipulable signals

We study a dynamic stopping game between a principal and an agent. The agent is privately informed about his type. The principal learns about the agent’s type from a noisy performance measure, which can be manipulated by the agent via a costly and hidden action. We fully characterize the unique Mark...

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Main Authors: EKMEKCI, Mehmet, GORNO, Leandrro, MAESTRI, Lucas, SUN, Jian, WEI, Dong
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Language:English
Published: Institutional Knowledge at Singapore Management University 2022
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Online Access:https://ink.library.smu.edu.sg/lkcsb_research/7105
https://ink.library.smu.edu.sg/context/lkcsb_research/article/8104/viewcontent/2007.08762.pdf
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spelling sg-smu-ink.lkcsb_research-81042022-12-20T07:14:19Z Learning from manipulable signals EKMEKCI, Mehmet GORNO, Leandrro MAESTRI, Lucas SUN, Jian WEI, Dong We study a dynamic stopping game between a principal and an agent. The agent is privately informed about his type. The principal learns about the agent’s type from a noisy performance measure, which can be manipulated by the agent via a costly and hidden action. We fully characterize the unique Markov equilibrium of this game. We find that terminations/ market crashes are often preceded by a spike in (expected) performance. Our model also predicts that, due to endogenous signal manipulation, too much transparency can inhibit learning. As the players get arbitrarily patient, the principal elicits no useful information from the observed signal. 2022-12-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/lkcsb_research/7105 info:doi/10.1257/aer.20211158 https://ink.library.smu.edu.sg/context/lkcsb_research/article/8104/viewcontent/2007.08762.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection Lee Kong Chian School Of Business eng Institutional Knowledge at Singapore Management University Asymmetric information learning signal manipulation venture capital Finance Finance and Financial Management
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Asymmetric information
learning
signal manipulation
venture capital
Finance
Finance and Financial Management
spellingShingle Asymmetric information
learning
signal manipulation
venture capital
Finance
Finance and Financial Management
EKMEKCI, Mehmet
GORNO, Leandrro
MAESTRI, Lucas
SUN, Jian
WEI, Dong
Learning from manipulable signals
description We study a dynamic stopping game between a principal and an agent. The agent is privately informed about his type. The principal learns about the agent’s type from a noisy performance measure, which can be manipulated by the agent via a costly and hidden action. We fully characterize the unique Markov equilibrium of this game. We find that terminations/ market crashes are often preceded by a spike in (expected) performance. Our model also predicts that, due to endogenous signal manipulation, too much transparency can inhibit learning. As the players get arbitrarily patient, the principal elicits no useful information from the observed signal.
format text
author EKMEKCI, Mehmet
GORNO, Leandrro
MAESTRI, Lucas
SUN, Jian
WEI, Dong
author_facet EKMEKCI, Mehmet
GORNO, Leandrro
MAESTRI, Lucas
SUN, Jian
WEI, Dong
author_sort EKMEKCI, Mehmet
title Learning from manipulable signals
title_short Learning from manipulable signals
title_full Learning from manipulable signals
title_fullStr Learning from manipulable signals
title_full_unstemmed Learning from manipulable signals
title_sort learning from manipulable signals
publisher Institutional Knowledge at Singapore Management University
publishDate 2022
url https://ink.library.smu.edu.sg/lkcsb_research/7105
https://ink.library.smu.edu.sg/context/lkcsb_research/article/8104/viewcontent/2007.08762.pdf
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