scholarly journals LOCAL IDENTIFICATION IN EMPIRICAL GAMES OF INCOMPLETE INFORMATION

2010 ◽  
Vol 26 (6) ◽  
pp. 1638-1662 ◽  
Author(s):  
Jean-Pierre Florens ◽  
Erwann Sbaï

This paper studies identification for a broad class of empirical games in a general functional setting. Global identification results are known for some specific models, e.g., in some standard auction models. We use functional formulations to obtain general criteria for local identification. These criteria can be applied to both parametric and nonparametric models, and also to models with asymmetry among players and affiliated private information. A benchmark model is developed where the structural parameters of interest are the distribution of private information and an additional dissociated parameter, such as a parameter of risk aversion. Criteria are derived for some standard auction models, games with exogenous variables, games with randomized strategies, such as mixed strategies, and games with strategic functions that cannot be derived analytically.

2018 ◽  
Vol 10 (1) ◽  
pp. 278-314 ◽  
Author(s):  
Melis Kartal

New relationships are often plagued with uncertainty because one of the players has some private information about her “type.” The reputation literature has shown that equilibria that reveal this private information typically involve breach of trust and conflict. But are these inevitable for equilibrium learning? I analyze self-enforcing relationships where one party is privately informed about her time preferences. I show that there always exist honest reputation equilibria, which fully reveal information and support cooperation without breach or conflict. I compare these to dishonest reputation equilibria from several perspectives. My results are applicable to a broad class of repeated games. (JEL C73, D82, D83, D86, Z13)


2003 ◽  
Vol 11 (4) ◽  
pp. 316-344 ◽  
Author(s):  
Curtis S. Signorino

Social scientists are often confronted with theories in which one or more actors make choices over a discrete set of options. In this article, I generalize a broad class of statistical discrete choice models, with both well-known and new nonstrategic and strategic special cases. I demonstrate how to derive statistical models from theoretical discrete choice models and, in doing so, I address the statistical implications of three sources of uncertainty: agent error, private information about payoffs, and regressor error. For strategic and some nonstrategic choice models, the three types of uncertainty produce different statistical models. In these cases, misspecifying the type of uncertainty leads to biased and inconsistent estimates, and to incorrect inferences based on estimated probabilities.


2012 ◽  
Vol 2012 ◽  
pp. 1-10
Author(s):  
Romeo Rizzi ◽  
Luca Nardin

The Interactive Knapsacks Heuristic Optimization (IKHO) problem is a particular knapsacks model in which, given an array of knapsacks, every insertion in a knapsack affects also the other knapsacks, in terms of weight and profit. The IKHO model was introduced by Isto Aho to model instances of the load clipping problem. The IKHO problem is known to be APX-hard and, motivated by this negative fact, Aho exhibited a few classes of polynomial instances for the IKHO problem. These instances were obtained by limiting the ranges of two structural parameters, c and u, which describe the extent to which an insertion in a knapsack in uences the nearby knapsacks. We identify a new and broad class of instances allowing for a polynomial time algorithm. More precisely, we show that the restriction of IKHO to instances where is bounded by a constant can be solved in polynomial time, using dynamic programming.


2019 ◽  
Vol 26 (2) ◽  
pp. 477-487
Author(s):  
Bruno Chiarini ◽  
Elisabetta Marzano

Purpose Crime games cannot be simply read with mixed strategies. These strategies are inconclusive of how the players act rationally. This is undeniably true for the crime of tax evasion, where dishonest taxpayers are rational agents, motivated by the comparison of payoffs, when considering the risk of non-compliance. The purpose of this paper is to illustrate that in the presence of a small “private disturbance” of the players’ payoff, the Nash equilibrium in mixed strategies provides us with the necessary information on equilibria in pure strategies that will be played. Design/methodology/approach In tax-evasion games, an equilibrium must necessarily be interpreted in pure strategies, and the only way to do this is to insert some private information into the game and reinterpret it in a Bayesian scheme. We show that taxpayers’ private,subjective considerations on the effective implementation of the penalty and the revenue agency’s private information on the cost of monitoring and conviction can lead to Bayesian equilibria in pure strategies. The present paper takes issue with this Bayesian equilibrium and the implications for comparative-statics results. Findings In this context, tougher sentencing deters crime, although, as the Italian experience teaches, the necessary condition required is the certainty of punishment and the ability of the government to enforce it. The equilibrium strategies with incomplete information reveal whether it is convenient for the two agents to maintain their “private disturbance” as private information or, on the contrary, it is convenient to expect it to be “common knowledge.” Originality/value A distinct set of studies has adopted a game theoretic approach and shows that the standard economic approach to crime deterrence inspired by Gary Beker’s seminal paper might be flawed. See, among others, Saha and Poole (2000), Tsebelis (1989) and Andreozzi (2010). This paper shows that a greater severity of the penalty and a higher certainty of punishment (a lower possibility of appealing against sanctions and no discounts on due penalties) necessarily lead to a unique Bayesian equilibrium without evasion.


2012 ◽  
Vol 28 (4) ◽  
pp. 719-729 ◽  
Author(s):  
Ivana Komunjer

This paper derives sufficient conditions for global identification in nonlinear models characterized by a finite number of unconditional moment restrictions. The main contribution of this paper is to provide a set of assumptions that are alternative to those of Gale-Nikaidô-Fisher-Rothenberg, and which when satisfied guarantee that the moment conditions globally identify the parameters of interest.


2021 ◽  
Vol 16 (2) ◽  
pp. 449-475
Author(s):  
Harry Pei

I study a repeated game in which a patient player wants to win the trust of some myopic opponents, but can strictly benefit from betraying them. His benefit from betrayal is strictly positive and is his persistent private information. I characterize every type of patient player's highest equilibrium payoff and construct equilibria that attain this payoff. Since the patient player's Stackelberg action is mixed and motivating the lowest‐benefit type to play mixed actions is costly, every type's highest equilibrium payoff is strictly lower than his Stackelberg payoff. In every equilibrium where the patient player approximately attains his highest equilibrium payoff, no type of the patient player plays stationary strategies or completely mixed strategies.


1988 ◽  
Vol 20 (4) ◽  
pp. 535-546 ◽  
Author(s):  
P A Williams

The purpose in this paper is to develop and validate a model of the intraurban trip-making process for households. To this end, a simultaneous equations model, which represents a conceptual model of the process, is calibrated with intraurban-travel survey data. In addition, as the process is found to be hierarchical, a recursive model, which provides both consistent and unbiased estimates of the structural parameters of the model, is calibrated. Household activity, trip frequency, and travel time are each shown to be directly influenced by several exogenous socioeconomic and locational characteristics of the household. Furthermore, frequency of household trips and accrued travel time are shown to be consequences of levels of household activity and of those exogenous variables found to influence this activity.


2013 ◽  
Vol 47 ◽  
pp. 649-695 ◽  
Author(s):  
T. Leaute ◽  
B. Faltings

As large-scale theft of data from corporate servers is becoming increasingly common, it becomes interesting to examine alternatives to the paradigm of centralizing sensitive data into large databases. Instead, one could use cryptography and distributed computation so that sensitive data can be supplied and processed in encrypted form, and only the final result is made known. In this paper, we examine how such a paradigm can be used to implement constraint satisfaction, a technique that can solve a broad class of AI problems such as resource allocation, planning, scheduling, and diagnosis. Most previous work on privacy in constraint satisfaction only attempted to protect specific types of information, in particular the feasibility of particular combinations of decisions. We formalize and extend these restricted notions of privacy by introducing four types of private information, including the feasibility of decisions and the final decisions made, but also the identities of the participants and the topology of the problem. We present distributed algorithms that allow computing solutions to constraint satisfaction problems while maintaining these four types of privacy. We formally prove the privacy properties of these algorithms, and show experiments that compare their respective performance on benchmark problems.


2001 ◽  
Vol 17 (2) ◽  
pp. 451-470 ◽  
Author(s):  
Jeffrey M. Wooldridge

I provide a systematic treatment of the asymptotic properties of weighted M-estimators under standard stratified sampling. Simple, consistent asymptotic variance matrix estimators are proposed for a broad class of problems. When stratification is based on exogenous variables, I show that the usual, unweighted M-estimator is more efficient than the weighted estimator under a generalized conditional information matrix equality. Hausman tests for the exogeneity of the sampling scheme, including fully robust forms, are derived.


2016 ◽  
Vol 230 (4) ◽  
Author(s):  
Janis Timoshenko ◽  
Andris Anspoks ◽  
Aleksandr Kalinko ◽  
Alexei Kuzmin

AbstractEXAFS spectroscopy is an element-specific method that can provide perhaps the most extensive information on the local atomic structure and lattice dynamics for a broad class of materials. Conventional methods of EXAFS data treatment are often limited to the nearest coordination shells of the absorbing atom due to the difficulties in accurate accounting for the large number of correlated structural parameters that have to be included in the analysis. In this study we overcome this problem by applying novel simulation-based method: reverse Monte Carlo simulations, coupled with the evolutionary algorithm and with a powerful signal processing technique – wavelet transform. This complex approach was applied to the analysis of the W L


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