Imperfect Monitoring Research Articles

Zero-risk weights and capital misallocation

Financial institutions, especially in Europe, hold a disproportionate amount of domestic sovereign debt. We examine the extent to which this home bias leads to capital misallocation in a real business cycle model with imperfect information and fiscal stress. We assume banks can hold sovereign debt according to a zero-risk weight policy and contrast this scenario to one in which banks weight the sovereign debt according to default probabilities. Banks are assumed to miscalculate the probability of a disaster state due to moral hazard and imperfect monitoring. This distortion pushes the economy away from the first-best allocation. We show that the zero risk weight policy exacerbates these distortions while a non-zero risk-weight improves allocations. The welfare costs associated with zero-risk weight policies are large. Households are willing to give up 3.2 percent of their consumption to move to the first-best allocation, whereas in the economy with non-zero risk-weights households are willing to give up only 1.2 percent of their consumption to move to the first-best allocation.

Many-Body Dynamics in Monitored Atomic Gases without Postselection Barrier.

We study the properties of a monitored ensemble of atoms driven by a laser field and in the presence of collective decay. The properties of the quantum trajectories describing the atomic cloud drastically depend on the monitoring protocol and are distinct from those of the average density matrix. By varying the strength of the external drive, a measurement-induced phase transition occurs separating two phases with entanglement entropy scaling subextensively with the system size. Incidentally, the critical point coincides with the superradiance transition of the trajectory-averaged dynamics. Our setup is implementable in current light-matter interaction devices, and most notably, the monitored dynamics is free from the postselection measurement problem, even in the case of imperfect monitoring.

Leveraging Digital Technology to Improve Monitoring and Planning in Public Sector Supply Chains: Evidence From India’s Food Security Program

Governments across the developing world are adopting digital technologies to improve the performance of public sector supply chains. However, empirical evidence regarding the impact of these technologies on performance is mixed. In this paper, we evaluate the impact of using biometric authentication (BA) devices on the performance of India’s food security program. The program aims to deliver subsidized food grains to nearly 160 million low-income households through approximately 500,000 fair price shops (FPSs). Nearly half of those grains do not reach the beneficiaries and are diverted to the open market for private benefit. We estimate the impact of installing BA devices on reducing diversion in more than 3,300 FPSs in the Indian state of Karnataka between 2013 and 2015 using a difference-in-differences approach. We find that BA devices reduce up to 4% of the current diversion at the last mile. We argue that this relatively low impact is due to the presence of a workaround mechanism which results in imperfect monitoring and validate the decrease in diversion mechanism by estimating the differential impact of BA devices. We complement the empirical analysis with a simulation exercise to estimate the additional value that can be unlocked by using the BA devices. We find that the value of better replenishment planning using sales and inventory information captured by BA devices can be significant. The value of better planning can be as high as six times the value of reduction in diversion, depending on the preintervention levels of demand from genuine beneficiaries and diversion at the FPSs.

Contracts, Wage Differentials and Involuntary Unemployment

I study a simple model of labour markets with imperfect monitoring and efficiency wages that provide work incentives. Involuntary unemployment is an outcome, but it is just one particular instance of many inter-firm wage differentials that pervade the equilibrium. The goal of this paper is to study the relationship between firm size, work standards, wages paid, contractual utility for workers, and capital intensity in production. Under certain conditions: (a) larger firms pay higher wages and demand higher individual effort levels; (b) despite these opposing effects, larger firms offer a higher net contractual utility and (c) larger firms are more capital intensive, even when production functions are homothetic in capital and labour. JEL Classifications: D33, J31, J41

Contest and resource allocation: An experimental analysis of entitlement and self-selection effects

Leaders who decide the allocation of resources are often chosen through contests. Due to imperfect monitoring, they often decide to allocate resources to themselves at the expense of others. This paper investigates how being selected in a contest affects such allocation through two channels: entitlement and self-selection effects. In our experiment, two players compete for the right to allocate resources between themself and a third, uninvolved player. We identify the entitlement effect by comparing the choices of participants who participated in the contest with those who were chosen randomly. Self-selection effect is identified by comparing the choices of winners and losers between treatments via a difference-in-difference approach. We find a significant effect of entitlement; people participating in the contest transfer fewer resources to the third player compared to those who did not participate. Further, we find no evidence that the people with specific distributional preferences self-select into the leaders’ role. Our findings suggest that the primary reason leaders allocate resources to themselves is their involvement in the contest rather than being a result of self-selection.

An Imperfect Monitoring Game-Theoretic Approach for Crowdsourcing Reliable Wireless Data

An Imperfect Monitoring Game-Theoretic Approach for Crowdsourcing Reliable Wireless Data

Cooperation through collective punishment and participation

AbstractWe experimentally explore the role of institutions imposing collective sanctions in sustaining cooperation. In our experiment, players only observe noisy signals about individual contributions in finitely repeated public goods game with imperfect monitoring, while total output is perfectly observed as it is often the case in collective action problems in society. We consider sanctioning mechanism that allows agents to commit to collective punishment in case the level of cooperation among members of society falls short of a target. We find that cooperation is higher with collective punishment compared to both no punishment or punishment targeting individuals. Importantly, our results indicate that it is the combination of making a commitment to be punished and the collective nature of punishment which induces cooperation. Our findings show that punishing a group collectively for misbehavior of some of its members induces cooperation when individuals participate in setting up the sanctioning institution. The study contributes to the literature on institutional legitimacy and how to ensure good government performance when dealing with collective action problems, and, by considering commitment, improves enforcement methods criticized for their detrimental effects on some societal groups.

Assessing the performance of voluntary environmental agreements under high monitoring costs: Evidence from the Brazilian Amazon

Voluntary environmental arrangements generally coexist with State-based and private rules, creating a property rights system that legitimizes certain behaviors. In a world of positive transaction costs, legitimacy ensues from imperfect monitoring activities, opening room for opportunism. In this paper, we discuss how the existence of multiple rules in a scenario of high monitoring costs affects the performance of an environmental policy. We discuss the case of deferred prosecution agreements (TAC, acronym in Portuguese), which are voluntary arrangements designed with the goal of incentivizing slaughterhouses to monitor the environmental practices of ranchers in the Brazilian Amazon. More specifically, we study how the signature of a TAC agreement affects deforestation rates in the Brazilian Amazônia Legal region at the municipality level. This paper adopts a difference-in-differences approach to analyze a sample of Brazilian municipalities between 2006 and 2017. Our results, which remain robust across alternative estimators and subsamples, show that the signature of a TAC agreement increases deforestation rates by 0.2 standard deviations. We argue that the signature of a TAC agreement, by creating an imperfect proxy for “good behavior” that enables both compliant and non-compliant organizations to access credit, may incentivize deforestation in the Brazilian Amazon.

Optimal monitoring and attack detection of networks modeled by Bayesian attack graphs

Early attack detection is essential to ensure the security of complex networks, especially those in critical infrastructures. This is particularly crucial in networks with multi-stage attacks, where multiple nodes are connected to external sources, through which attacks could enter and quickly spread to other network elements. Bayesian attack graphs (BAGs) are powerful models for security risk assessment and mitigation in complex networks, which provide the probabilistic model of attackers’ behavior and attack progression in the network. Most attack detection techniques developed for BAGs rely on the assumption that network compromises will be detected through routine monitoring, which is unrealistic given the ever-growing complexity of threats. This paper derives the optimal minimum mean square error (MMSE) attack detection and monitoring policy for the most general form of BAGs. By exploiting the structure of BAGs and their partial and imperfect monitoring capacity, the proposed detection policy achieves the MMSE optimality possible only for linear-Gaussian state space models using Kalman filtering. An adaptive resource monitoring policy is also introduced for monitoring nodes if the expected predictive error exceeds a user-defined value. Exact and efficient matrix-form computations of the proposed policies are provided, and their high performance is demonstrated in terms of the accuracy of attack detection and the most efficient use of available resources using synthetic Bayesian attack graphs with different topologies.

Penalty lottery*

AbstractTo control sequential public bad productions under imperfect monitoring, this paper proposes a penalty lottery: a violator passes the responsibility of the fine to the next potential violator with some probability and pays all the accumulated fines with the complementary probability. The penalty lottery does not merely impose extreme fines because an absorbing state is practically unreachable. It self‐selects people more willing to produce public bads and endogenously imposes the larger expected fines on them. It has advantages over the day‐fine system in which the fine depends on the offender's daily income. Experimental evidence is consistent with the proposed theoretical predictions.

Attendance manipulation and efficiency in Chile’s school voucher system

To improve the quality of education, one can either directly reward performance or introduce school choice, private provision, and demand subsidies. The Chilean voucher scheme combines both approaches: an attendance-related subsidy favors school choice and creates incentives for schools to promote attendance throughout the year. With imperfect monitoring, however, institutions may respond by manipulating performance indicators. By analyzing audit data, we find evidence that a large fraction of Chilean schools – including public schools – over-report attendance, with a higher prevalence among for-profit and under-achieving institutions. Expenditure data suggest that manipulation among for-profit schools seems to follow rent extraction purposes rather than educational goals.

The Dark Side of Transparency: Mission Variety and Industry Equilibrium in Decentralised Public Good Provision

Abstract We study the implications of transparency policies on decentralised public good provision by the non-profit sector. We present a model where imperfect monitoring of the use of funds interacts with the competitive structure of the non-profit sector under alternative informational regimes. Increasing transparency regarding the use of funds may have ambiguous effects on total public good provision and on donors’ welfare. On the one hand, transparency encourages all non-profit firms to engage more actively in curbing fund diversion. On the other hand, it tilts the playing field against non-profits facing higher monitoring costs, pressing them to give up on their missions. This effect on the extensive margin implies that transparency policies lead to a reduction in the diversity of social missions addressed by the non-profit sector. We show that the negative impact of transparency on social mission variety and on donors’ welfare is highest for intermediate levels of asymmetry in monitoring costs.

Research on Monitoring, Early Warning and Prevention System of land Subsidence in Beijing-Tianjin-Hebei Region

The Beijing-Tianjin-Hebei region, one of the most serious areas of ground subsidence in China, has entered the stage of high-speed development of synergistic integration, and the establishment of a unified and efficient, automatic and intelligent, mature and advanced monitoring and warning prevention system is inevitable. After reviewing a large amount of literature, we analyze and summarize that the ground subsidence in this region was formed earlier, and although the monitoring, early warning and prevention work is gradually promoted, there are still problems such as imperfect monitoring network, in depth early warning research and unsound joint prevention and control mechanism. Only with the integration of multi-source monitoring technology, increasingly refined early warning technology and multi-pronged prevention and control technology can the ground subsidence monitoring and early warning prevention and control system in Beijing, Tianjin and Hebei make great progress and gradually advance towards intelligence, refinement and wisdom.

Artificial Intelligence: Can Seemingly Collusive Outcomes Be Avoided?

Strategic decisions are increasingly delegated to algorithms. We extend previous results of the algorithmic collusion literature to the context of dynamic optimization with imperfect monitoring by analyzing a setting where a limited number of agents use simple and independent machine-learning algorithms to buy and sell a storable good. No specific instruction is given to them, only that their objective is to maximize profits based solely on past market prices and payoffs. With an original application to battery operations, we observe that the algorithms learn quickly to reach seemingly collusive decisions, despite the absence of any formal communication between them. Building on the findings of the existing literature on algorithmic collusion, we show that seeming collusion could originate in imperfect exploration rather than excessive algorithmic sophistication. We then show that a regulator may succeed in disciplining the market to produce socially desirable outcomes by enforcing decentralized learning or with adequate intervention during the learning process. This paper was accepted by Gabriel Weintraub, revenue management and market analytics. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2022.4623 .

Structural Empirical Analysis of Vacancy Referrals with Imperfect Monitoring and the Strategic Use of Sickness Absence

Structural Empirical Analysis of Vacancy Referrals with Imperfect Monitoring and the Strategic Use of Sickness Absence

Monitoring versus Discounting in Repeated Games

We study how discounting and monitoring jointly determine whether cooperation is possible in repeated games with imperfect (public or private) monitoring. Our main result provides a simple bound on the strength of players' incentives as a function of discounting, monitoring precision, and on‐path payoff variance. We show that the bound is tight in the low‐discounting/low‐monitoring double limit, by establishing a public‐monitoring folk theorem where the discount factor and the monitoring structure can vary simultaneously.

Reputation and liability in experience goods markets with imperfect monitoring

This paper investigates the interaction of reputation and product liabilities from a new perspective. We introduce a reputation model in an experience good market with imperfect monitoring, in which reputation incentives without product liability are not sufficient for inducing a desired outcome. Even a firm with high market reputation will cheat consumers, and the reputation will eventually collapse. We then introduce two product liabilities into the reputation model: strict liability and negligence rule . It is shown that under certain conditions, these two liabilities can both improve firms’ incentives and final outcomes. What is the best product liability depends on the costs of firms and courts as well as courts’ professional level. The paper also sheds light on which liability regime is optimal in this reputational setting. • We investigate the interaction of reputation and product liabilities from a new perspective. • We introduce a reputation model in an experience good market with imperfect monitoring, in which reputation incentives without product liability are not sufficient for inducing a desired outcome. • Under certain conditions, strict liability and negligence rule can both improve firms’ incentives and final outcomes. • What is the best product liability depends on the costs of firms and courts as well as courts’ professional level.

IRREVERSIBILITY AND MONITORING IN DYNAMIC GAMES: EXPERIMENTAL EVIDENCE

AbstractThis article provides experimental evidence on the impacts of irreversibility and imperfect monitoring on the efficiency and the equity of a repeated public goods game. We find that irreversibility and imperfect monitoring both lead to inefficient and unequal outcomes through different channels. Irreversibility lowers public goods contribution in earlier periods and makes the initial‐period contribution gap between two players long‐lasting. Imperfect monitoring hampers conditional cooperation and persistently reduces group contribution. A finite mixture estimation with conditional cooperators provides a coherent account of the treatment effects.

Honeypot Allocation for Cyber Deception Under Uncertainty

Cyber deception aims to misrepresent the state of the network to mislead the attackers, falsify their reconnaissance conclusions, and deflect them away from their goals. Honeypots serve as decoy devices inside networks that can capture adversaries for monitoring purposes. We propose a two-phase deception approach based on honeypot allocation. In the first phase, we develop a proactive deceptive honeypot allocation policy, the second phase proposes a reactive deception approach that dynamically allocates honeypots according to IDS updates. Considering a practical scenario, the defender partially monitors the adversary’s activities. To this end, we develop our deception approach using a combination of game-theoretic and reinforcement learning models. We cast the problem of reactive deception as a partially observable Markov decision process (POMDP) based on a game-theoretic dynamic model to accommodate the imperfect monitoring of the actions taken by the attacker. We solve this combined partially observable game model using Monte-Carlo tree search to overcome the game model complexity. We give a game-theoretic analysis to explain the attack-defense policies at equilibrium. Finally, we present numerical results to validate the effectiveness of the proposed deception approach.

Political Agency and Implementation Subsidies with Imperfect Monitoring

Abstract Voters are frequently ill-equipped to monitor politicians’ actions. Politicians are expected to implement projects, whose benefits sometimes partially accrue to interest groups (IGs) and not entirely to voters. IGs thus have an incentive to affect which projects politicians implement by providing implementation subsidies to lower the cost of policymaking that politicians incur. This article shows how these considerations interact in a two-period political agency model with moral hazard and adverse selection. I study how the involvement of IGs in the policymaking process can affect voters’ welfare and show why voters might rationally not perfectly monitor politicians in the presence of IGs that might capture projects’ benefits and affect policymaking.