Incomplete Information Model Research Articles

Testing Models of Social Learning on Networks: Evidence From Two Experiments

We theoretically and empirically study an incomplete information model of social learning. Agents initially guess the binary state of the world after observing a private signal. In subsequent rounds, agents observe their network neighbors' previous guesses before guessing again. Agents are drawn from a mixture of learning types—Bayesian, who face incomplete information about others' types, and DeGroot, who average their neighbors' previous period guesses and follow the majority. We study (1) learning features of both types of agents in our incomplete information model; (2) what network structures lead to failures of asymptotic learning; (3) whether realistic networks exhibit such structures. We conducted lab experiments with 665 subjects in Indian villages and 350 students from ITAM in Mexico. We perform a reduced‐form analysis and then structurally estimate the mixing parameter, finding the share of Bayesian agents to be 10% and 50% in the Indian‐villager and Mexican‐student samples, respectively.

Learning from Monetary and Fiscal Policy

We present a dynamic incomplete information model where monetary and fiscal policy instruments serve as endogenous signals for the private sector. We highlight a novel information channel of policy interactions, and show the general equilibrium (GE) information feedback between policies largely shapes the economy's response to policy shocks. We document a non-monotone signaling effect of policies with respect to the policy rule parameters. Our analysis shows the GE information feedback is quantitatively significant, and the model provides a unified explanation of the various policy impacts on inflation, the dynamics of survey expectations, and the missing inflation after the Great Recession.

Price Competition and Consumer Search

We propose an incomplete-information model of price dispersion in which firms set different prices conditional on their privately-observed, heterogeneous production costs. We establish two types of equilibria, random equilibrium and searching equilibrium, based on whether consumers who are uninformed about prices purchase from a randomly-selected first firm or actively engage in sequential search in equilibrium. We find that random equilibrium is more likely to emerge when a large number of firms intensely compete in the market. Using a novel clickstream data from a large U.K. online retailer, we provide supporting empirical evidence.

Task Offloading in Vehicular Mobile Edge Computing: A Matching-Theoretic Framework

Mobile edge computing (MEC) is an emerging technology that leverages computing, storage, and network resources deployed in the proximity of users to offload terminals from computationintensive and delay-sensitive tasks. In this article, a vehicular MEC system is studied where edges, such as MEC servers deployed at roadside units (RSUs), and vehicles with excessive computing resources are able to provide offloading opportunities to other vehicles having limited computation capabilities. We first review the latest MEC research. Then, we focus on the task of offloading in an incomplete information environment and model the interactions between tasks and edges as a matching game. Our main objective is to minimize the average delay while taking into account vehicle mobility and energy consumption constraints. We elaborate on two typical application scenarios, namely, interference-free orthogonal multipleaccess (OMA) networks and interference nonorthogonal multiple-access (NOMA) networks, and develop two separate heuristic algorithms to solve the delay minimization problem. Simulation results demonstrate the efficiency of the proposed algorithms.

Core-selecting auctions with incomplete information

Core-selecting auctions were proposed as alternatives to the Vickrey–Clarke–Groves (VCG) mechanism for environments with complementarities. In this paper, we consider a simple incomplete-information model that allows correlations among bidders’ values. We perform a full equilibrium analysis of three core-selecting auction formats as applied to the “local-local-global” model. We show that seller revenues and efficiency from core-selecting auctions can improve as correlations among bidders’ values increase, producing outcomes that are closer to the true core than are the VCG outcomes. Thus, there may be a theoretical justification for policymakers to utilize core-selecting auctions rather than the VCG mechanism in certain environments.

Information Spillover in a Bayesian Repeated Game

This paper considers an infinitely repeated three-player Bayesian game with lack of information on two sides, in which an informed player plays two zero-sum games simultaneously at each stage against two uninformed players. This is a generalization of Aumann, Maschler and Stearns (1995) two-player zero-sum one-sided incomplete information model. Under a correlated prior, the informed player faces the problem of how to optimally disclose information among two uninformed players in order to maximize his long term average payoffs. The objective is to understand the adverse effects of “information spillover” from one game to the other in the equilibrium payoff set of the informed player. We provide conditions under which the informed player can fully overcome such adverse effects, and show that in some cases the adverse effects are unsurmountable and severe.

Heuristics as conceptual lens for understanding and studying the usage of bibliometrics in research evaluation

While bibliometrics are widely used for research evaluation purposes, a common theoretical framework for conceptually understanding, empirically studying, and effectively teaching its usage is lacking. In this paper, we outline such a framework: the fast-and-frugal heuristics research program, proposed originally in the context of the cognitive and decision sciences, lends itself particularly well for understanding and investigating the usage of bibliometrics in research evaluations. Such evaluations represent judgments under uncertainty in which typically not all possible options, their consequences, and those consequences’ probabilities of occurring may be known. In these situations of incomplete information, candidate descriptive and prescriptive models of human behavior are heuristics. Heuristics are simple strategies that, by exploiting the structure of environments, can aid people to make smart decisions. Relying on heuristics does not mean trading off accuracy against effort: while reducing complexity, heuristics can yield better decisions than more information-greedy procedures in many decision environments. The prescriptive power of heuristics is documented in a cross-disciplinary literature, cutting across medicine, crime, business, sports, and other domains. We outline the fast-and-frugal heuristics research program, provide examples of past empirical work on heuristics outside the field of bibliometrics, explain why heuristics may be especially suitable for studying the usage of bibliometrics, and propose a corresponding conceptual framework.

Analysis of Signal Game for Supply Chain Finance (SCF) of MSEs and Banks Based on Incomplete Information Model

The signal gaming model based on incomplete information is used to analyze the decisions of commercial banks and medium-sized and small enterprises (SMEs) in supply chain finance business. It is found that the returns of banks are closely relied on the probability of good SMEs join which is proportional to θ (the probability of “good” SMEs in the market) and p (the probability of “good” SMEs chosen to join the supply chain finance) in supply chain finance business, and the default cost is an important constrain for determining the strategies adopted by the SMEs and the banks. To achieve higher returns, SMEs and banks should make effects to create a better supply chain finance business environment to achieve the separation equilibrium.

Agency Equilibrium

Agency may be exercised by different entities (e.g., individuals, firms, households). A given individual can form part of multiple agents (e.g., he may belong to a firm and a household). The set of agents that act in a given situation might not be common knowledge. We adapt the standard model of incomplete information to model such situations.

Repercussions of Endogenous Fast Rising Top Inequality

This paper develops a fully-solvable equilibrium matching model of incomplete information with early skill acquisition to provide general theoretical insights into fast rising top income inequality observed in the United States. First, fast rising top income inequality is endogenously accommodated: In response to a change in each factor contributing to rising inequality, the equilibrium percentage changes in skill investment, income, and firm earnings are monotonically increasing in individual type, switching from negative to positive at respective cuto types. Second, rising fractal top income inequality is associated with a downward shift in the Lorenz curve even when the whole income distribution is not Pareto. Third, rising income inequality has serious repercussions on welfare and eciency. A change in each factor contributing to rising inequality makes individuals of type below a corresponding cuto type worse o but individuals of type above better o. However, only changes in firm-related factors necessarily improve ecienc

Reliability Logic Model for Incomplete Information in Sensor Monitoring Databases

Reliability Logic Model for Incomplete Information in Sensor Monitoring Databases

Information structure and statistical information in discrete response models

Strategic interaction parameters characterize the impact of actions of one economic agent on the payo of another economic agent. In this paper we study how the information available to economic agents regarding other economic agents can inuence the ability of an econometrician to recover strategic information parameters from the observed actions. We consider two extreme cases: the complete information case where the information sets of participating economic agents coincide, and the incomplete information case where each agent has a privately observable type. We nd that in models with incomplete information the statistical (Fisher) information for the interaction parameters is zero, implying that estimation and inference become nonstandard. In contrast, in the incomplete information models with any non-zero variance of player types, the statistical information is positive, implying the existence of regular estimators for these parameters converging at the parametric rate. This nding is illustrated in two cases: treatment eect models (expressed as a triangular system of equations), and the static game models. In both types of models the observed discrete outcomes are driven by continuously distributed errors with an unknown distribution (unobserved heterogeneity). We nd that the key factor driving the result in these models is

Robust games: theory and application to a Cournot duopoly model

In this paper, the robust game model proposed by Aghassi and Bertsimas (Math Program Ser B 107:231–273, 2006) for matrix games is extended to games with a broader class of payoff functions. This is a distribution-free model of incomplete information for finite games where players adopt a robust-optimization approach to contend with payoff uncertainty. They are called robust players and seek the maximum guaranteed payoff given the strategy of the others. Consistently with this decision criterion, a set of strategies is an equilibrium, robust-optimization equilibrium, if each player’s strategy is a best response to the other player’s strategies, under the worst-case scenarios. The aim of the paper is twofold. In the first part, we provide robust-optimization equilibrium’s existence result for a quite general class of games and we prove that it exists a suitable value $$\epsilon $$ such that robust-optimization equilibria are a subset of $$\epsilon $$ -Nash equilibria of the nominal version, i.e., without uncertainty, of the robust game. This provides a theoretical motivation for the robust approach, as it provides new insight and a rational agent motivation for $$\epsilon $$ -Nash equilibrium. In the last part, we propose an application of the theory to a classical Cournot duopoly model which shows significant differences between the robust game and its nominal version.

Information transmission during the trial: The role of punitive damages and legal costs

AbstractThis paper studies an incomplete information model in which a preventable accident occurred. The judge determining punitive damages observes the firm's (defendant) investment decisions, but is uninformed about the firm's experience adopting safety measures. Our model allows firms to file an appeal if the judge's verdict is incorrect, which the judge may accept or reject. We identify under which conditions a separating equilibrium exists where the firm's investment decisions signal its type to the judge, who responds with a correct verdict, thus avoiding future appeals. Our paper also finds conditions under which a pooling equilibrium exists whereby the firm's investment in precaution conceals its type from the judge, who can respond with an incorrect verdict thus giving rise to appeals. Furthermore, we show that the separating equilibrium is more likely to arise if the percentage of revenue that defendants are required to pay in punitive damages decreases, if the punitive‐to‐compensatory ratio increases, and if the legal cost of filing an appeal increases.

Bayes-Nash Equilibria in Generalized Second Price Auctions with Allocative Externalities

In this paper, we investigate an incomplete information model of generalized second price auctions with allocative externalities originating from the heterogeneous match rates of bidders. A novel feature of our model is that it generates endogenous click-through rates (CTRs). In this setting, we establish existence of symmetric efficient equilibria for common classes of primitives. This contrasts with the findings of Gomes and Sweeney (2014), who study a similar model but with fixed CTRs. Moreover, non-existence results require strong assumptions on the primitives of the model. We conclude that existence of equilibria in GSP with incomplete information is quite general.

Flip-Flopping, Primary Visibility, and the Selection of Candidates

We present an incomplete information model of two-stage elections in which candidates can choose different platforms in primaries and general elections. Voters do not directly observe the chosen platforms, but infer the candidates' ideologies from observing candidates' campaigns. The ability of voters to detect candidates' types depends on the visibility of the race. This model captures two patterns: the post-primary moderation effect, in which candidates pander to the party base during the primary and shift to the center in the general election; and the divisive-primary effect, which refers to the detrimental effect of hard-fought primaries on a party's general-election prospects. (JEL D11, D72, D83)

The Role of Dispersed Information in Pricing Default: Evidence from the Great Recession

The recent Global Games literature makes important predictions on how financial crises unfold. We test the empirical relevance of these theories by analyzing how dispersed information affects banks' default risk. We find evidence that precise information acts as a coordination device which reduces creditors' willingness to roll over debt to a bank, thus increasing both its default risk and its vulnerability to changes in expectations. We establish two new results. First, given an unfavorable median forecast, less dispersed beliefs greatly increase default risk; this is consistent with incomplete information models that rely on coordination risk while in contrast with a wide range of models that neglect this component. Second, less dispersion of beliefs amplifies the reaction of default risk to changes in market expectations; importantly, precise information raises banks' vulnerability by more than standard measures of banks' fragility. Taken together, our results suggest that enhanced transparency, by providing agents with more precise information, increases banks' vulnerability to changes in sentiment and raises the default risk of weaker banks. Finally, we address concerns of endogeneity of market expectations by introducing a novel set of instruments.

A non-cooperative game with incomplete information to improve patient hospital choice

In order to improve the accessibility of health care service, the hierarchical health care delivery system that includes the general hospital (GH) and the community health care center (CHC) has been gradually established in urban China. In this paper, we introduce a game theoretic framework that considers both the influence of static and dynamic factors on patients’ choices among health care facilities. We formulate a non-cooperative game with incomplete information and regard the equilibrium of this game as a best prediction of patients’ hospital choice results. We implement the proposed game theoretic framework by a case study. We provide quantitative analysis on the equilibrium to study how those factors affect patients’ hospital choices. Finally, to achieve the goal that alleviates the congestion of GH and balance the patient flow among GHs and CHCs, we implement two incentive policies in our model, along with analysing their effects on patients’ hospital choices. The non-cooperative game with incomplete information model functions as a quantitative tool to help the government decision-maker to improve the patient flow distribution in urban China.

Crime and conspicuous consumption

We study how property crime distorts consumption decisions. Using an incomplete information model, we argue that consuming conspicuous goods reveals information to criminals seeking bountiful victims and increases the likelihood of being victimized. Thus, property crime reduces the consumption of visible goods, even when these cannot be directly stolen but simply carry information about a potential victim's wealth. We exploit the large decline in property crime in the U.S. during the 90s to test this mechanism. Using data from the U.S. Consumer Expenditure Survey from 1986 to 2003, we find that households located in states experiencing sharper reductions in property crime increased significantly their consumption of visible goods, even when these goods are not generally stolen, both in absolute terms and relative to other consumption goods. Our findings hold when we instrument the decline in property crime during the 90s using a variety of strategies.

Learning and coordination with dispersed information

We analyse adaptive learning in a model of incomplete and dispersed information, with externalities and strategic interactions. We build on the framework proposed by Angeletos and Pavan (2007a) and extend it to a dynamic multi-period setting where agents need to learn to coordinate. We derive conditions under which adaptive learning obtains in such setting and show that, when actions are strategic substitutes, the information structure affects the speed of convergence: while more precise private information is beneficial, better public information has negative effects. We also show that adaptive learning dynamics converge to the Bayesian Nash equilibrium, which means that agents can learn to act strategically by relying only on observable (exogenous) information.