The form of incentive contracts: agency with moral hazard, risk neutrality, and limited liability

ABSTRACT: Disclosure and monitoring policy are studied, where disclosure relates to information about the monitoring system. A moral hazard model is presented where employee monitoring occurs with some exogenous probability and the owner privately learns whether he will be monitoring before the employee chooses his productive action. Disclosure policy is an owner choice between revealing to the employee whether he will be monitoring before the action (Disclosure) or remaining silent (Secrecy). The results rely on the joint presence of risk aversion and limited liability. Risk aversion creates an efficiency/risk tradeoff where secrecy obtains risk-sharing benefits. Limited liability reduces these benefits, allowing preference for disclosure. Lower monitoring probabilities increase the risk premium required to obtain effort with secrecy. For small monitoring probabilities, disclosure is preferred even though less efficient production is achieved, because disclosure provides a greater risk-sharing benefit. For high monitoring probabilities, secrecy is preferred because it leads to greater efficiency despite a greater risk premium.

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Dynamic Moral Hazard, Risk-Shifting, and Optimal Capital Structure

SSRN Electronic Journal ◽

10.2139/ssrn.3066525 ◽

2017 ◽

Author(s):

Alejandro Rivera

Keyword(s):

Moral Hazard ◽

Capital Structure ◽

Risk Shifting ◽

Optimal Capital Structure ◽

Hazard Risk ◽

Optimal Capital

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Moral Hazard, Incentive Contracts, and Risk: Evidence from Procurement

The Review of Economic Studies ◽

10.1093/restud/rdu002 ◽

2014 ◽

Vol 81 (3) ◽

pp. 1201-1228 ◽

Cited By ~ 32

Author(s):

G. Lewis ◽

P. Bajari

Keyword(s):

Moral Hazard ◽

Incentive Contracts

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Sound Deposit Insurance Pricing Using a Machine Learning Approach

Risks ◽

10.3390/risks7020045 ◽

2019 ◽

Vol 7 (2) ◽

pp. 45 ◽

Cited By ~ 2

Author(s):

Hirbod Assa ◽

Mostafa Pouralizadeh ◽

Abdolrahim Badamchizadeh

Keyword(s):

Machine Learning ◽

Moral Hazard ◽

Deposit Insurance ◽

Implied Volatility ◽

Calibration Method ◽

Quadratic Model ◽

Learning Approach ◽

Conceptual Issue ◽

Hazard Risk ◽

Machine Learning Approach

While the main conceptual issue related to deposit insurances is the moral hazard risk, the main technical issue is inaccurate calibration of the implied volatility. This issue can raise the risk of generating an arbitrage. In this paper, first, we discuss that by imposing the no-moral-hazard risk, the removal of arbitrage is equivalent to removing the static arbitrage. Then, we propose a simple quadratic model to parameterize implied volatility and remove the static arbitrage. The process of removing the static risk is as follows: Using a machine learning approach with a regularized cost function, we update the parameters in such a way that butterfly arbitrage is ruled out and also implementing a calibration method, we make some conditions on the parameters of each time slice to rule out calendar spread arbitrage. Therefore, eliminating the effects of both butterfly and calendar spread arbitrage make the implied volatility surface free of static arbitrage.

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