Incentives For Agents Research Articles

Recent Trends in Information Elicitation

This note provides a survey for the Economics and Computation community of some recent trends in the field of information elicitation. At its core, the field concerns the design of incentives for strategic agents to provide accurate and truthful information. Such incentives are formalized as proper scoring rules , and turn out to be the same object as loss functions in machine-learning settings, providing many connections. More broadly, the field concerns the design of mechanisms to obtain information from groups of agents and aggregate it or use it for decision making. Recently, work on information elicitation has expanded and been connected to online no-regret learning, mechanism design, fair division, and more.

Relative performance evaluation in spillover networks

In a multi-agent contracting problem, agents are linked in performance through two channels, effort spillover, governed by spillover network, and risk correlation, governed by risk structure. Assigning compensation weights on peers' performances can not only filter out common risks but also alter agent's incentives. We study how the network and risk structure jointly determine the optimal linear contract. First, the relative compensation sensitivity is determined by ratio of the dot product, between spillover vector and pure hedge portfolio, to unhedgeable risk. We then propose an index named informativeness along the spillover direction and argue that this index measures how precisely the principal can infer the agent's effort. By showing that both the implemented effort and induced welfare are increasing in the informativeness index, we argue that this index captures how central each agent is in this economy. Finally, results regarding relative sensitivities still hold under optimal contract with bounded compensation.

Enhancing Unit-linked Insurance Consumer Loyalty: The Role of Service Quality, Information Asymmetry, and Agent Marketing Strategies

Unit-linked insurance (PAYDI), Indonesia's top-selling life insurance product, has driven industrial growth in the last two decades through effective agent marketing. However, its complexity, blending protection, and investment have drawn criticism for consumers’ detriment and increasing complaints about insurance agent practices. This study aimed to achieve critical objectives by examining consumer perceptions of agent-provided service quality and distinguishing between active and lapsed policyholders as a measure of loyalty. It also seeks to construct a model that delineates the impact of service quality on consumer satisfaction and loyalty with information asymmetry as a moderating variable. This study used a cross-sectional research design, and gathered data through electronic questionnaires distributed to PAYDI insurance consumers. Purposive sampling was used to select participants, resulting in 159 respondents meeting the study’s criteria. Data analysis was conducted using Partial Least Squares Structural Equation Modelling (PLS-SEM). These findings underscore the critical influence of agent reliability and empathy on consumer satisfaction with information asymmetry emerging as a key moderator between satisfaction and loyalty. These results imply that reinforcing agent training in reliability, empathy, and efforts to minimize information asymmetry significantly enhances consumer satisfaction and loyalty in the insurance sector. This research suggests that companies should develop a Key Performance Indicator (KPI) and incentives for agents to enhance both customer acquisition and post-purchase services, ensure transparent information sharing, and set measurable satisfaction targets such as the Net Promoter Score (NPS). Future studies should focus on operational diversity and alternative proxies of firms.

Data and incentives

“Big data” gives markets access to previously unmeasured characteristics of individual agents. Policymakers must decide whether and how to regulate the use of this data. We study how new data affects incentives for agents to exert effort in settings such as the labor market, where an agent's quality is initially unknown but is forecast from an observable outcome. We show that measurement of a new covariate has a systematic effect on the average effort exerted by agents, with the direction of the effect determined by whether the covariate is informative about long‐run quality versus a shock to short‐run outcomes. For a class of covariates satisfying a statistical property that we call strong homoskedasticity, this effect is uniform across agents. More generally, new measurements can impact agents unequally, and we show that these distributional effects have a first‐order impact on social welfare.

Strategic default in financial networks

This paper investigates a model of default in financial networks where the decision by one agent on whether or not to default impacts the incentives of other agents to escape default. Agents' payoffs are determined by the clearing mechanism introduced in the seminal contribution of Eisenberg and Noe (2001). We first show the existence of a Nash equilibrium of this default game. Furthermore, we develop an algorithm to find all Nash equilibria and guide regulatory intervention that relies on the financial network structure. The algorithm provides a ranking for the set of Nash equilibria for specific financial network structures, which can serve as a measure of systemic risk. Finally, we show that introducing a central clearing counterparty achieves the efficient equilibrium at no additional cost.

Privacy regulations and economic efficiency: a dynamic perspective.

There are important public debates on how-or even whether-to regulate information about previous transactions in different markets. Examples are the regulation of cookies in online markets, secrecy laws in financial markets, and transparency directives in government purchases. In these debates, considerations of economic efficiency and fairness are central. Do more lenient information policies increase market efficiency? Do internet users benefit from cookies? Does more secrecy increase trade volume in financial markets? Does transparency on previous agreements deteriorate the bargaining power of public agencies? This essay sheds light on the answers to these questions using insights from economic theory. We do so by analyzing a simple, stylized setting where the incentives of different agents in the market will be clear. Our focus is on the dynamic effects of information regulations, as a trader's incentive to reveal or conceal information is driven by its future use by other traders. We use our setting to assess the implications of information regulations on behavior, trade efficiency, or social welfare.

Dynamic Contracting with Intermediation: Operational, Governance, and Financial Engineering

ABSTRACTPrivate equity funds intermediate investment and affect portfolio firm performance by actively engaging in operational, governance, and financial engineering. We study this type of intermediation in a dynamic agency model in which an active intermediary raises funds from outside investors and invests in a firm run by an agent. Optimal contracting addresses moral hazard at the intermediary and firm levels. The intermediary's incentives to affect firm performance are strongest after poor performance, while the agent's incentives are strongest after good performance. We also show how financial engineering, that is, financial contracting with outside investors, interacts with operational and governance engineering.

SocialMapf: Optimal and Efficient Multi-Agent Path Finding With Strategic Agents for Social Navigation

We propose an extension to the MAPF formulation, called <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SocialMapf</small> , to account for private incentives of agents in constrained environments such as doorways, narrow hallways, and corridor intersections. <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SocialMapf</small> is able to, for instance, accurately reason about the urgent incentive of an agent rushing to the hospital over another agent's less urgent incentive of going to a grocery store; MAPF ignores such agent-specific incentives. Our proposed formulation addresses the open problem of optimal and efficient path planning for agents with private incentives. To solve <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SocialMapf</small> , we propose a new class of algorithms that use mechanism design during conflict resolution to simultaneously optimize agents' private local utilities and the global system objective. We perform an extensive array of experiments that show that optimal search-based MAPF techniques lead to collisions and increased time-to-goal in <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SocialMapf</small> compared to our proposed method using mechanism design. Furthermore, we empirically demonstrate that mechanism design results in models that maximizes agent utility and minimizes the overall time-to-goal of the entire system. We further showcase the capabilities of mechanism design-based planning by successfully deploying it in environments with static obstacles. To conclude, we briefly list several research directions using the <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SocialMapf</small> formulation, such as exploring motion planning in the continuous domain for agents with private incentives.

Fiscal policy and economic growth in the short and long run: a literature review

The purpose of this paper is to establish the main channels of fiscal policy impact on economic growth and to identify problems or missing aspects in the analysis. The paper summarizes the impact of fiscal policy on economic growth in the long-run and short-run on the basis of extensive (82 sources) literature analysis. The paper analyzes the results of theoretical and empirical studies. The paper pays attention to the comparison of empirical results for poor and rich countries, as the optimal fiscal policy may differ significantly from country to country. On the theoretical side, the paper mainly focuses on endogenous growth models, but also touches on overlapping generations and Solow models. Special attention is paid to the estimation of fiscal multipliers. Through a broad view, the paper touches upon the main instruments of fiscal policy and their impact on economic growth both in the short run and in the long run. The author's contribution is in overview of a wide body of literature on fiscal policy, which helps to identify the main problems in analyzing the impact of fiscal policy. Fiscal policy can have short- and long-term effects on economic growth through changing the incentives of economic agents, through reducing transaction costs between them, and through influencing expectations. However, the main body of empirical literature examines the impact of fiscal policy on economic growth in developed countries. This poses a challenge for fiscal policy in developing countries, as recommendations derived from the experience of developed countries are often suboptimal for developing countries. The article also points out the significant problems associated with empirical analysis of the performance of fiscal policy even in developed countries.

The impact of discriminatory pricing based on customer risk: an empirical investigation using indirect lending through retail networks

PurposeThe purpose of this study is to understand the profit implications of analytics-driven centralized discriminatory pricing at the headquarter level compared with sales force price delegation in the purchase of an aftermarket good through an indirect retail channel with symmetric information.Design/methodology/approachUsing individual-level loan application and approval data from a North American financial institution and segment-level customer risk as the price discrimination criterion for the firm, the authors develop a three-stage model that accounts for the salesperson’s price decision within the limits of the latitude provided by the firm; the firm’s decision to approve or not approve a sales application; and the customer’s decision to accept or reject a sales offer conditional on the firm’s approval. Next, the authors compare the profitability of this sales force price delegation model to that of a segment-level centralized pricing model where agent incentives and consumer prices are simultaneously optimized using a quasi-Newton nonlinear optimization algorithm (i.e. Broyden–Fletcher–Goldfarb–Shanno algorithm).FindingsThe results suggest that implementation of analytics-driven centralized discriminatory pricing and optimal sales force incentives leads to double-digit lifts in firm profits. Moreover, the authors find that the high-risk customer segment is less price-sensitive and firms, upon leveraging this segment’s willingness to pay, not only improve their bottom-line but also allow these marginalized customers with traditionally low approval rates access to loans. This points out the important customer welfare implications of the findings.Originality/valueSubstantively, to the best of the authors’ knowledge, this paper is the first to empirically investigate the profitability of analytics-driven segment-level (i.e. discriminatory) centralized pricing compared with sales force price delegation in indirect retail channels (i.e. where agents are external to the firm and have access to competitor products), taking into account the decisions of the three key stakeholders of the process, namely, the consumer, the salesperson and the firm and simultaneously optimizing sales commission and centralized consumer price.

Aggregate and disaggregate performance measurements: Inter‐temporally correlated performance measures with limited commitment

AbstractThis study employs the LEN model in analyzing aggregations and disaggregate use of inter‐temporally correlated performance measures in two‐period agencies with limited commitment. The optimal disaggregate use where an agent's incentive is on basic measures suffers information loss to depend on agency particulars. Induced action is restricted by the subsequent period action, and limited commitment leads to fostering late optimal effort inducement. Performance measure aggregation yields inaccurate inter‐temporal information relative to the disaggregate use and leads to raising early optimal effort inducement. Both the total informativeness and the difference in informativeness of performance measures fortify early optimal effort inducement.

Agile contracting: Managing incentives under uncertain needs

We consider a novel principal–agent model that captures some salient features of an agile software development project. Specifically, the project is technically complex, can be modularized via a set of independent stories which are developed in sprints, and has requirements that can change over time due to exogenous changes in business needs, technologies, or market conditions. In addition, given the iterative nature of agile development, our model also captures and analyzes the interaction between two types of learning effects, namely, viability learning and cost learning, which until our paper have been examined only individually in the literature. Our paper makes the following contributions to the literature: (i) We characterize an optimal contract for the principal in closed‐form and generate managerial insights on how the agent's incentive to work changes, and consequently how the optimal contracting terms offered by the principal change, depending upon the business environment. We show that the interaction between the two learning effects and need‐risk plays an important and yet unexplored role in influencing the dynamics in the optimal contract. (ii) Using the optimal contract as the benchmark, we examine the performance of time‐and‐material contracts that are popularly used in agile projects. (iii) We obtain an optimal contract for precedence‐dependent stories in which one story must be completed before starting another story. Overall, our results provide both prescriptive and qualitative guidance to firms outsourcing agile software development projects.

ANALYSIS OF THE TOURISM SECTOR DEVELOPMENT STRATEGY DURING THE COVID 19 PANDEMIC IN THE CITY OF SABANG

Anticipating the spread of COVID-19, a number of tourist sites in various provinces in Indonesia are temporarily closed including in the province of Aceh. Aceh Province is a tourist destination that has cultural diversity and natural beauty to invite tourists to visit and witness it. The decline in the number of tourist visits in Indonesia certainly has a significant effect on the number of tourist visits in Aceh Province. The development of the tourism sector in the city of Sabang requires the right direction and strategy so that benefits for the regional economy remain profitable even in the midst of Covid 19. In the long term the sustainability of the tourism sector will depend on maintaining a balance between the interests of the economic aspect. This study aims to analyze the estimated value of the sector's economic losses. tourism, tourism sector development strategies and Sabang City government policies related to Tourism Areas during the COVID19 pandemic in Sabang City. This research is survey research with a qualitative approach, using SWOT. The sample in this study amounted to 62 respondents. The results of this study indicate that the value of the economic loss in the tourism sector in Sabang City is estimated at IDR 3,950,000,000 or only 41% of revenue before the COVID-19 pandemic. So the decline in tourism sector revenue due to COVID-19 was 59%. This loss is the value of lost revenue from tourism business actors including hotel managers and restaurant managers in the Sabang Island Tourism Area. The right strategy to be implemented in the development of the Sabang tourism sector is a diversification strategy (quadrant II). Alternative strategies that can be implemented are optimizing the use of social media as a means of promotion, collaborating with elements of the government, increasing access to financing for tourism business actors, increasing incentives for tourism business actors, airlines, travel agents, and promotions in the form of ticket discounts, providing incentives for group incentive trips/famtrips and promotions through influence Acceleration of infrastructure development in priority tourist destinations; Tourism promotions, exhibitions and events are gradually starting to be activated. One of the policies of the Sabang City Government regarding tourism sector policies is contained in Sabang Mayor Regulation Number 30 of 2020 concerning the application of discipline and health protocols as an effort to prevent and control the spread of the Covid virus which is quite effective in reducing the number of tourist visits to Sabang Island both at tourist attractions, hotels , and restaurants. Based on the results of this study, the authors suggest that the Sabang City Government can provide assistance to tourism business actors not only in the form of relief in paying taxes, but also in the form of direct financial assistance. The management of the tourism business is tightening and emphasizing the health protocol for visiting tourists in order to reduce the spread of the COVID-19 pandemic. Especially tourists coming from outside should be checked for the completeness of the letter not infected with the COVID-19 pandemic and the COVID-19 vaccine card. Requiring vaccinations for tourists so that tourism activities can continue during the COVID-19 pandemic with a lower possibility of COVID-19 infection.

The price of Anarchy as a classifier for mechanism design in a Pareto-Bayesian-Nash context

The complex interaction of fixed incentives for multiple agents can lead to inefficient results. The Price of Anarchy (PoA) is a concept employed in economics and game theory to quantify how, in the worst-case scenario, a system's efficiency diminishes due to the selfish behavior of its actors. It evaluates the outcomes obtained by perfect coordination to that obtained by self-interested players in a Nash equilibrium.This paper investigates the PoA in mechanism design for Pareto-Bayesian-Markov (PBN) games in which the players privately know their information. Our approach is restricted to the development of algorithmic mechanisms. We consider an ergodic finite Markov chain in which players' transitions are independent and decisions are made across a finite number of periods. As a key outcome, we completely characterize the Pareto frontier and calculate an efficient, ex-post incentive-compatible technique. We employ Tikhonov's regularization technique, for assuring that the original problem's solution converges to a unique solution. The ratio equilibria of the PoA is found employing a projection-gradient method, which is our main result. We compute the PoA using an auxiliary variable and present the formulas for retrieving the variables of interest. We show that our theoretical conclusions ensure convergence and we provide a numerical example to demonstrate the method's utility.

Optimal assignment mechanisms with imperfect verification

Objects of different quality are to be allocated to agents. Agents can receive at most one object, and there are not enough high‐quality objects for every agent. The value to the social planner from allocating objects to any given agent depends on that agent's private information. The social planner is unable to use transfers to give incentives for agents to convey their private information. Instead, she is able to imperfectly verify their reports through signals that are positively affiliated with each agent's type. We characterize mechanisms that maximize the social planner's expected payoff. In the optimal mechanism, each agent chooses one of various tracks, which are characterized by two thresholds. If the agent's signal exceeds the upper threshold of the chosen track, the agent receives a high‐quality object, if it is between the two thresholds, he receives a low‐quality object, and if it is below the lower threshold, he receives no object.

The New Institutional Economics Approach to Economic Development: A Discussion of Social, Political, Legal, and Economic Institutions

The last 50 years of development economics have seen hopes for global development raised high and dashed time and again. While there has been positive, sometimes even impressive, growth in many countries, in most of the world experience has not matched expectations. The accumulation of physical capital and human capital, liberalisation and privatisation have all been proposed as the elixirs of growth. While all these arguments have some merit, by themselves they are incomplete solutions to the problem of development. The disappointing performance of the post-Communist transition, the slow growth of the 1970s and 80s in Africa and Latin America, and the Asian financial crisis of the 1990s were all rooted in poor governance. Good governance involves aligning the incentives of agents with the interests of principals in both economic and political spheres. This paper describes some insights from New Institutional Economics on how best to design these incentives.

Conflicts of interest and agent heterogeneity in buyer brokerage

AbstractThis article investigates the incentives of agents working with buyers (buying agents) under the fixed percentage commission system and the implications on housing market outcomes. Our model shows that the absence of a binding contract creates a risk of losing clients for buying agents, which helps mitigate the conflict of interest between buying agents and their clients. Both the buying agent's prediction accuracy regarding their client's reservation prices and the level of tolerance given by the buyer to the buying agent affect the binding force. Results from simulations and empirical analyses using house transactions in Canada support our model predictions.

Efficient public good provision by lotteries with nonlinear pricing

In this paper, we introduce nonlinear pricing of lottery tickets to the mechanism of Morgan (2000), in which a lottery is used to finance the public good. In a model with n symmetric agents, we find that incorporating this instrument fully achieves the efficient provision of public good when each agent’s initial wealth is sufficiently high. In a model with two asymmetric agents, there exists a nonlinear lottery mechanism that induces efficient public good provision provided that agents are not too heterogenous. Intuitively, the proposed nonlinear pricing rule leads to a decreasing marginal cost for ticket purchase, which provides stronger incentives for agents to make contributions, compared with Morgan (2000).

Pandemic Crisis, Power and the Role of the State

ABSTRACT We build on the experience of the COVID-19 crisis to investigate how a State owned and a private company, such as the national health system, are managed when a crisis may occur. We develop our analysis considering an incomplete contract model. We concentrate our attention on the incentives for economic agents assuming that the State expropriates property rights in the crisis event. The choice between public and private health system depends on three key elements: expropriation degree of the State/power of the private sector, damage of cost reduction innovations, probability of a crisis event. If the probability of the crisis is high, the damage is significant and the contracting power of the manager is strong then public ownership may be optimal because cost innovations are more aligned to the first best solution than in case of a private ownership.

Frequent monitoring in dynamic contracts

I consider a dynamic principal-agent model in which the agent does not observe the quality of his output and the principal chooses how much to monitor the agent. Monitoring improves production outcomes but can reduce the agent's incentive to work if it uncovers bad performance and leads to punishing the agent. The optimal monitoring intensity is path dependent: an agent who performed poorly in the past is monitored less going forward to reduce the risk of early termination. Conversely, an agent who performed well is monitored more as his accumulated promised compensation provides a buffer against bad monitoring outcomes and reduces the associated penalties by deferring the pay-for-performance risk to states of the world in which termination costs are low.