Stochastic costly state verification and dynamic contracts

Popov, Latchezar

doi:10.1016/j.jedc.2015.12.006

Cited by 13 publications

(6 citation statements)

References 8 publications

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“…Popov () modeled verification of hidden information as reported by a worker. He keeps the problem nontrivial by assuming that the utility function is bounded from below and that the continuation utility is also bounded.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal unemployment insurance with monitoring

Setty

2019

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I model job-search monitoring in the optimal unemployment insurance framework, in which job-search effort is the worker's private information. In the model, monitoring provides costly information upon which the government conditions unemployment benefits. Using a simple one-period model with two effort levels, I show analytically that the monitoring precision increases and the utility spread decreases if and only if the inverse of the worker's utility in consumption has a convex derivative. The quantitative analysis that follows extends the model by allowing a continuous effort and separations from employment. That analysis highlights two conflicting economic forces affecting the optimal precision of monitoring with respect to the generosity of the welfare system: higher promised utility is associated not only with a higher cost of moral hazard, but also with lower effort and lower value of employment. The result is an inverse U-shaped precision profile with respect to promised utility.

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Section: Literature Reviewmentioning

confidence: 99%

Optimal unemployment insurance with monitoring

Setty

2019

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“…It follows that the promise keeping constraint (13) and the incentive compatibility (14) for ✓ L are satisfied by construction, and for ✏ sufficiently small ( 14) is still satisfied for ✓ H . The expected revenues will change to…”

Section: Discussionmentioning

confidence: 94%

“…Solving for the optimal long-term contract is equivalent to choosing how much to rely on dynamic incentives and how much to rely on current mon- (14) and the limited liability constraints on repayments and promised utilities, while taking as given the promised expected utility w of the borrower. The solution depends on w, because it is the promised expected utility w that determines the set of active constraints, the set of feasible repayments and ultimately benefits and costs of the two instruments.…”

Section: Discussionmentioning

confidence: 99%

“…In this class of models, Wang [19] transforms the dynamic problem into a sequence of static problems by considering deterministic monitoring probabilities and exponential utility, and in this case the set of monitoring states is time invariant: either a low income report is always verified or it is never verified. Differently, Popov [14] and Aiyagari and Alvarez [1], allow stochastic monitoring to obtain state dependent monitoring probabilities as a function, not necessarily monotonic, of the promised utility that the borrower is entitled to.…”

Section: Introductionmentioning

confidence: 99%

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Costly monitoring, dynamic incentives, and default

Antinolfi

Carli

2015

Journal of Economic Theory

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We study dynamic contracts between a lender and a borrower in the presence of costly state verification and hidden effort. The optimal contract minimizes social losses by mediating dynamic incentives and monitoring. Along the efficiency frontier, the threat of early termination is unavoidable for low levels of the borrower's promised utility; as the level increases, preventive monitoring is used to avoid future inefficient termination of the contractual relationship due to asymmetric information; for high level of promised utility, the threat of termination of the contractual relationship is no longer a useful tool to align dynamic incentives, preventive monitoring loses its role, and termination never occurs. Thus, the efficient contract optimizes the tradeoff between dymanic incentievs and static incentives. Following the interpretaion of the costly state verification literature, we can distinguish two levels of bankruptcy: one that leads to monitoring and the other that leads to liquidation.

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“…Remark 3 The absence of verification until a threshold duration is unlikely to be robust to other types of penalties. For instance, in Popov (2009) there is an exogenous lower bound on the worker's continuation utility and a worker who is caught cheating is pushed to this lower bound. So the penalty for a worker with high continuation utility is larger than that for a worker with low continuation utility.…”

Section: Stochastic Verificationmentioning

confidence: 99%

Unemployment Insurance Fraud and Optimal Monitoring

Fuller

Ravikumar

Zhang

2015

American Economic Journal: Macroeconomics

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An important incentive problem for the design of unemployment insurance is the fraudulent collection of unemployment benefits by workers who are gainfully employed. We show how to efficiently use a combination of tax/subsidy and monitoring to prevent such fraud. The optimal policy monitors the unemployed at fixed intervals. Employment tax is nonmonotonic: it increases between verifications but decreases after a verification. Unemployment benefits are relatively flat between verifications but decrease sharply after a verification. Our quantitative analysis suggests that the optimal monitoring cost is 60 percent of the cost in the current US system. (JEL D82, H24, J64, J65)

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Stochastic costly state verification and dynamic contracts

Cited by 13 publications

References 8 publications

Optimal unemployment insurance with monitoring

Optimal unemployment insurance with monitoring

Costly monitoring, dynamic incentives, and default

Unemployment Insurance Fraud and Optimal Monitoring

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