A Structural Econometric Analysis of Network Formation Games Through Subnetworks

Econometrica ◽  
2020 ◽  
Vol 88 (5) ◽  
pp. 1829-1858 ◽  
Author(s):  
Shuyang Sheng
Keyword(s):  
Multiple Equilibria ◽  
Network Formation ◽  
Equilibrium Selection ◽  
Partial Identification ◽  
Strategic Interactions ◽  
Large Networks ◽  
Network Formation Games ◽  
Identification Approach ◽  
Structural Econometric ◽  
Simultaneous Move

The objective of this paper is to identify and estimate network formation models using observed data on network structure. We characterize network formation as a simultaneous‐move game, where the utility from forming a link depends on the structure of the network, thereby generating strategic interactions between links. With the prevalence of multiple equilibria, the parameters are not necessarily point identified. We leave the equilibrium selection unrestricted and propose a partial identification approach. We derive bounds on the probability of observing a subnetwork, where a subnetwork is the restriction of a network to a subset of the individuals. Unlike the standard bounds as in Ciliberto and Tamer (2009), these subnetwork bounds are computationally tractable in large networks provided we consider small subnetworks. We provide Monte Carlo evidence that bounds from small subnetworks are informative in large networks.

scholarly journals Determinants of Equilibrium Selection in Network Formation: An Experiment

Games ◽  
2018 ◽  
Vol 9 (4) ◽  
pp. 89 ◽  
Author(s):  
Britta Hoyer ◽  
Stephanie Rosenkranz
Keyword(s):  
Perceived Risk ◽  
Multiple Equilibria ◽  
Network Formation ◽  
Equilibrium Selection ◽  
Theoretical Models ◽  
Factors Affecting ◽  
Formation Experiment ◽  
The Stability

Theoretical models on network formation focus mostly on the stability and efficiency of equilibria, but they cannot deliver an understanding of why specific equilibrium networks are selected or whether they are all actually reachable from any starting network. To study factors affecting equilibrium selection, we designed a network formation experiment with multiple equilibria, which can be categorized in terms of the demand on players’ farsightedness and robustness to errors. In a second scenario, we increase the need for farsighted behavior by players, as well as the perceived riskiness of equilibria by adding a stage in which the network is disrupted. This setting allows us to analyze the interplay between the need for farsightedness and perceived risk of errors and its effect on network formation and equilibrium selection.

scholarly journals Equilibrium computation in discrete network games

2020 ◽  
Vol 11 (4) ◽  
pp. 1325-1347 ◽  
Author(s):  
Michael P. Leung
Keyword(s):  
Network Formation ◽  
Pure Strategy ◽  
Dominant Strategy ◽  
Strategic Interactions ◽  
Network Formation Games ◽  
Data Generating Process ◽  
Finite Action ◽  
Game Theoretic ◽  
Bounded Below ◽  
Action Spaces

Counterfactual policy evaluation often requires computation of game‐theoretic equilibria. We provide new algorithms for computing pure‐strategy Nash equilibria of games on networks with finite action spaces. The algorithms exploit the fact that many agents may be endowed with types such that a particular action is a dominant strategy. These agents can be used to partition the network into smaller subgames whose equilibrium sets may be more feasible to compute. We provide bounds on the complexity of our algorithms for models obeying certain restrictions on the strength of strategic interactions. These restrictions are analogous to the assumption in the widely used linear‐in‐means model of social interactions that the magnitude of the endogenous peer effect is bounded below one. For these models, our algorithms have complexity O p ( n c ), where the randomness is with respect to the data‐generating process, n is the number of agents, and c depends on the strength of strategic interactions. We also provide algorithms for computing pairwise stable and directed Nash stable networks in network formation games.

A HYBRID GENETIC ALGORITHM FOR THE MAXIMUM LIKELIHOOD ESTIMATION OF MODELS WITH MULTIPLE EQUILIBRIA: A FIRST REPORT

2005 ◽  
Vol 01 (02) ◽  
pp. 295-303 ◽  
Author(s):  
VICTOR AGUIRREGABIRIA ◽  
PEDRO MIRA
Keyword(s):  
Genetic Algorithm ◽  
Maximum Likelihood ◽  
Multiple Equilibria ◽  
Structural Parameters ◽  
Hybrid Genetic Algorithm ◽  
Likelihood Estimation ◽  
Maximum Likelihood Estimates ◽  
Large Space ◽  
Pseudo Maximum Likelihood ◽  
Structural Econometric

This paper presents a hybrid genetic algorithm to obtain maximum likelihood estimates of parameters in structural econometric models with multiple equilibria. The algorithm combines a pseudo maximum likelihood (PML) procedure with a genetic algorithm (GA). The GA searches globally over the large space of possible combinations of multiple equilibria in the data. The PML procedure avoids the computation of all the equilibria associated with every trial value of the structural parameters.

scholarly journals Axiomatization and Measurement of Quasi-Hyperbolic Discounting *

2014 ◽  
Vol 129 (3) ◽  
pp. 1449-1499 ◽  
Author(s):  
José Luis Montiel Olea ◽  
Tomasz Strzalecki
Keyword(s):  
Hyperbolic Discounting ◽  
Partial Identification ◽  
Axiomatic Characterization ◽  
Discount Factors ◽  
Elasticity Of Intertemporal Substitution ◽  
Trade Offs ◽  
Subject Pool ◽  
Identification Approach ◽  
The Subject

Abstract This article provides an axiomatic characterization of quasi-hyperbolic discounting and a more general class of semi-hyperbolic preferences. We impose consistency restrictions directly on the intertemporal trade-offs by relying on what we call “annuity compensations.” Our axiomatization leads naturally to an experimental design that disentangles discounting from the elasticity of intertemporal substitution. In a pilot experiment we use the partial identification approach to estimate bounds for the distributions of discount factors in the subject pool. Consistent with previous studies, we find evidence for both present and future bias.

scholarly journals Bounding preference parameters under different assumptions about beliefs: a partial identification approach

2010 ◽  
Vol 13 (3) ◽  
pp. 334-345 ◽  
Author(s):  
Charles Bellemare ◽  
Luc Bissonnette ◽  
Sabine Kröger
Keyword(s):  
Partial Identification ◽  
Identification Approach

On network formation games with heterogeneous players and basic network creation games

2018 ◽  
Vol 717 ◽  
pp. 62-72
Author(s):  
Christos Kaklamanis ◽  
Panagiotis Kanellopoulos ◽  
Sophia Tsokana
Keyword(s):  
Network Formation ◽  
Heterogeneous Players ◽  
Network Formation Games ◽  
Basic Network ◽  
Network Creation Games

scholarly journals Network Formation Games Among Relay Stations in Next Generation Wireless Networks

2011 ◽  
Vol 59 (9) ◽  
pp. 2528-2542 ◽  
Author(s):  
Walid Saad ◽  
Zhu Han ◽  
Tamer Basar ◽  
Merouane Debbah ◽  
Are Hjorungnes
Keyword(s):  
Wireless Networks ◽  
Network Formation ◽  
Next Generation ◽  
Next Generation Wireless Networks ◽  
Network Formation Games ◽  
Relay Stations

Identi cation of Preferences in Network Formation Games

2014 ◽  
Author(s):  
Aureo de Paula ◽  
Seth Richards-Shubik ◽  
Elie T. Tamer
Keyword(s):  
Network Formation ◽  
Network Formation Games
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