Learning the Structure and Parameters of Large-Population Graphical Games from Behavioral Data

We consider learning, from strictly behavioral data, the structure and parameters of linear influence games (LIGs), a class of parametric graphical games introduced by Irfan and Ortiz (2014). LIGs facilitate causal strategic inference (CSI): Making inferences from causal interventions on stable behavior in strategic settings. Applications include the identification of the most influential individuals in large (social) networks. Such tasks can also support policy-making analysis. Motivated by the computational work on LIGs, we cast the learning problem as maximum-likelihood estimation (MLE) of a generative model defined by pure-strategy Nash equilibria (PSNE). Our simple formulation uncovers the fundamental interplay between goodness-of-fit and model complexity: good models capture equilibrium behavior within the data while controlling the true number of equilibria, including those unobserved. We provide a generalization bound establishing the sample complexity for MLE in our framework. We propose several algorithms including convex loss minimization (CLM) and sigmoidal approximations. We prove that the number of exact PSNE in LIGs is small, with high probability; thus, CLM is sound. We illustrate our approach on synthetic data and real-world U.S. congressional voting records. We briefly discuss our learning framework's generality and potential applicability to general graphical games.Comment: Journal of Machine Learning Research. (accepted, pending publication.) Last conference version: submitted March 30, 2012 to UAI 2012. First conference version: entitled, Learning Influence Games, initially submitted on June 1, 2010 to NIPS 201

Confessions of an Internet Monopolist: Demand Estimation for a Versioned Information Good

We investigate profit-maximizing versioning plans for an information goods monopolist. The analysis employs data obtained from a web-based field experiment in which potential buyers were offered information goods in varied price-quality configurations. Maximum simulated likelihood (MSL) methods are used to estimate parameters describing the distribution of utility function parameters across potential buyers of the good. The resulting estimates are used to examine the impact of versioning on seller profits and market efficiency.Versioning, price discrimination, field experiment, maximum simulated likelihood

Evidence for surprise minimization over value maximization in choice behavior

Classical economic models are predicated on the idea that the ultimate aim of choice is to maximize utility or reward. In contrast, an alternative perspective highlights the fact that adaptive behavior requires agents' to model their environment and minimize surprise about the states they frequent. We propose that choice behavior can be more accurately accounted for by surprise minimization compared to reward or utility maximization alone. Minimizing surprise makes a prediction at variance with expected utility models; namely, that in addition to attaining valuable states, agents attempt to maximize the entropy over outcomes and thus 'keep their options open'. We tested this prediction using a simple binary choice paradigm and show that human decision-making is better explained by surprise minimization compared to utility maximization. Furthermore, we replicated this entropy-seeking behavior in a control task with no explicit utilities. These findings highlight a limitation of purely economic motivations in explaining choice behavior and instead emphasize the importance of belief-based motivations

Determinants and Welfare Impacts of Export Crop Cultivation - Empirical Evidence from Ghana

This paper investigates the determinants of farm households‟ participation in export cropping and the impact of export cropping on household welfare, using cross-sectional data obtained from the Ghanaian living standards survey 2005-6. Given the problem of selectivity bias that arise when households self-select into export cropping, we employ the full information maximum likelihood approach to analyze the participation decision, and generalized propensity matching approach to examine the welfare impacts of participation. The empirical results indicate that farmers facing lower transport costs and having better access to credit facilities are more likely to participate in export cropping. Estimates of the welfare impacts of export cropping generally reveal a positive relationship between engagement in export cropping and farm household welfare. However, a consideration of the impact of extent of export cropping shows a non-linear relationship with household welfare indicators, with per capita expenditures rising and poverty declining only at higher levels of export specialization.Export crops, Farm households, Household welfare, Poverty, Generalized propensity score, Crop Production/Industries, International Relations/Trade,

A Study of the Austrian Labour Makret Dynamics Using a Model of Search Equilibrium

In this work we provide a theoretical overview of a search equilibrium model with continuous productivity dispersion and perform its estimation for the Austrian data. We describe empirically the dynamics of market equilibrium outcomes. Special emphasis is made on the analysis of changes in labour mobility and dependence of expected job durations on offered wages. We investigate the influence of excessive labour mobility on the equilibrium profits of firms. Facing a problem of top-coded wage data, we suggest an appropriate adjustment of the existing estimation methodology. Finally, we extend the econometric model for the observed heterogeneity of agents

Stochastic Expected Utility and Prospect Theory in a Horse Race: A Finite Mixture Approach

This study compares the performance of Prospect Theory versus Stochastic Expected Utility Theory at fitting data on decision making under risk. Both theories incorporate well-known deviations from Expected Utility Maximization such as the Allais paradox or the fourfold pattern of risk attitudes. Stochastic Expected Utility Theory parsimoniously extends the standard microeconomic model, whereas Prospect Theory, the benchmark for aggregate choice so far, is based on psychological findings. First, the two theories' fit to representative choice is assessed for two experimental data sets, one Swiss and one Chinese. In a second step, finite mixture regressions reveal a consistent mix of two different behavioral types suggesting that researchers may take individual heterogeneity into account in order to avoid aggregation bias.stochastic expected etility theory, prospect theory, finite mixture models

Scalable Robust Kidney Exchange

In barter exchanges, participants directly trade their endowed goods in a constrained economic setting without money. Transactions in barter exchanges are often facilitated via a central clearinghouse that must match participants even in the face of uncertainty---over participants, existence and quality of potential trades, and so on. Leveraging robust combinatorial optimization techniques, we address uncertainty in kidney exchange, a real-world barter market where patients swap (in)compatible paired donors. We provide two scalable robust methods to handle two distinct types of uncertainty in kidney exchange---over the quality and the existence of a potential match. The latter case directly addresses a weakness in all stochastic-optimization-based methods to the kidney exchange clearing problem, which all necessarily require explicit estimates of the probability of a transaction existing---a still-unsolved problem in this nascent market. We also propose a novel, scalable kidney exchange formulation that eliminates the need for an exponential-time constraint generation process in competing formulations, maintains provable optimality, and serves as a subsolver for our robust approach. For each type of uncertainty we demonstrate the benefits of robustness on real data from a large, fielded kidney exchange in the United States. We conclude by drawing parallels between robustness and notions of fairness in the kidney exchange setting.Comment: Presented at AAAI1