The impossibility of strategy-proof clustering

Clustering methods group individuals or objects based on information about their similarity or proximity. When the raw information to generate clusters cannot be easily observed or verified, the cluster designer must rely on information reported by individuals behind the observations. When these individuals receive utility from a public decision taken with aggregated data within each own's cluster and have single-peaked preferences, we prove that there do not exist clustering methods such that truth-revealing behavior is always a dominant strategyclustering methods

A Social Choice Trade-off Between Alternative Fairness Concepts: Solidarity versus Flexibility

In this paper, we define simple measures of two properties that social choice functions may embody in different degrees in public goods environments. First, a measure of solidarity is proposed such that Thomson's (1990) replacement monotonicity property is a particular case in which the full amount of solidarity is required. Secondly, we introduce a measure of the degree of flexibility of a social choice function and prove that a trade-off in Campbell and Kelly's (1993) sense exists between both properties. More solidarity can only be achieved in exchange of less flexibility of the decision rule. When we restrict ourselves to the family of voting schemes called generalized Condorcet winner solutions, introduced by Moulin (1980), we find the exact trade-off and we can easily find the degrees of fulfillment of both properties, which amount to some generalization of the idea of ''qualified majority''.Single-peaked preferences, solidarity, welfare domination under preference replacement

The Impossibility of Strategy-Proof Clustering.

Clustering methods group individuals or objects based on information about their similarity or proximity. When the raw information to generate the clusters cannot be easily observed or verified, the clusters designer must rely on information reported on individuals behind the observations. When individuals receive utility from a public decision taken with aggregated data within each own's cluster and have single-peaked preferences, we prove that there do not exist cluster methods such that truth-revealing behavior is always a dominant strategy.clustering methods, strategy-proofness, single-peaked preferences, public decision.

Strategy-Proof Estimators for Simple Regression

In this paper we propose a whole class of estimators (“clockwise repeated median estimators” or CRM) for the simple regression model that are immune to manipulation by the agents generating the data. Although strategic considerations affecting the stability of the estimated parameters in regression models have already been studied (the Lucas critique), few efforts have been made to design estimators that are incentive compatible. We find that some well-known robust estimators proposed in the literature like the resistant line method are included in our family. Finally, we also undertake a Monte Carlo study to compare the distribution of some estimators that are robust to data manipulation with the OLS estimators under some specific data manipulation process.strategy-proofness, single-peaked preferences, robust regression, data contamination.

THEORY AND MISBEHAVIOR OF FIRST-PRICE AUCTIONS: THE IMPORTANCE OF INFORMATION FEEDBACK IN EXPERIMENTAL MARKETS

This article reports the results of a market experiment designed to test the predictions of the constant relative risk aversion model and to study the importance of information feedback in repeated first-price sealed-bid auctions. The data reveal that introduction of price information feedback implies a significant change of individual behavior. Without price information feedback, the data support the risk neutral Nash equilibrium prediction; with price information feedback, on the other hand, subjects overbid the risk neutral Nash equilibrium significantly. The constant relative risk aversion model is rejected since it predicts overbidding for both feedback conditions.Experimental Economics, First-price Sealed-bid Auctions, Independent Private Value Model, Bidding Theory, Risk Aversion

Forecasting the density of asset returns

In this paper we introduce a transformation of the Edgeworth-Sargan series expansion of the Gaussian distribution, that we call Positive Edgeworth-Sargan (PES). The main advantage of this new density is that it is well defined for all values in the parameter space, as well as it integrates up to one. We include an illustrative empirical application to compare its performance with other distributions, including the Gaussian and the Student's t, to forecast the full density of daily exchange-rate returns by using graphical procedures. Our results show that the proposed function outperforms the other two models for density forecasting, then providing more reliable value-at-risk forecasts.Density forecasting, Edgeworth-Sargan distribution, probability integral transformations, P-value plots, VaR

Within-Team Competition in the Minimum Effort Coordination Game

We report the results of an experiment on a continuous version of the minimum effort coordination game. The introduction of within-team competition significantly increases effort levels relative to a baseline with no competition and increases coordination relative to a secure treatment where the payoff-dominant equilibrium strategy weakly dominates all other actions. Nonetheless, within-team competition does not prevent subjects to polarize both in the efficient and the inefficient equilibria.Coordination Games, Team Incentives, Minimum Effort Game

Selfish-biased conditional cooperation: On the decline of contributions in repeated public goods experiments

The recent literature suggests that people have social preferences with a self-serving bias. Our data analysis reveals that the stylized fact of declining cooperation in repeated public goods experiments results from this bias and adaptation.experimental economics, information feedback, public goods, voluntary contributions, conditional cooperation

Multivariate moments expansion density : application of the dynamic equicorrelation model

En este estudio, proponemos un nuevo tipo de distribución semi-noparamétrica (SNP) para describir la densidad de los rendimientos de las carteras de activos. Esta distribución, denominada «expansión de momentos multivariante» (MME), admite cualquier distribución (multivariante) no-Gausiana como base de la expansión, ya que está directamente especificada en términos de los momentos de dicha distribución. En el caso de la expansión de una distribución normal, la MME es una reformulación de la distribución Gram-Charlier multivariante (MGC), pero, cuando se utilizan transformaciones de positividad para obtener densidades bien definidas, la MME es más sencilla y manejable que la MGC. Como aplicación empírica, extendemos el modelo de equicorrelación dinámica condicional (DECO) a un contexto SNP utilizando la MME. El modelo resultante presenta una formulación sencilla que admite la estimación consistente en dos etapas e incorpora DECO, así como las características no-Gausianas de la distribución de los rendimientos de cartera. La capacidad predictiva del modelo MME-DECO para una cartera de 10 activos demuestra que puede ser una herramienta útil para la gestión y el control del riesgo de carteraIn this study, we propose a new semi-nonparametric (SNP) density model for describing the density of portfolio returns. This distribution, which we refer to as the multivariate moments expansion (MME), admits any non-Gaussian (multivariate) distribution as its basis because it is specified directly in terms of the basis densitys moments. To obtain the expansion of the Gaussian density, the MME is a reformulation of the multivariate Gram-Charlier (MGC), but the MME is much simpler and tractable than the MGC when positive transformations are used to produce well-defined densities. As an empirical application, we extend the dynamic conditional equicorrelation (DECO) model to an SNP framework using the MME. The resulting model is parameterized in a feasible manner to admit two-stage consistent estimation, and it represents the DECO as well as the salient non-Gaussian features of portfolio return distributions. The in- and out-of-sample performance of a MME-DECO model of a portfolio of 10 assets demonstrates that it can be a useful tool for risk management purpose

Multivariate Gram-Charlier Densities

This paper introduces a new family of multivariate distributions based on Gram-Charlier and Edgeworth expansions. This family encompasses many of the univariate seminonparametric densities proposed in the financial econometrics as marginal distributions of the different formulations. Within this family, we focus on the specifications that guarantee positivity so obtaining a well-defined multivariate density. We compare different "positive" multivariate distributions of the family with the multivariate Edgeworth-Sargan, Normal and Student’s t in an in- and out-sample framework for financial returns data. Our results show that the proposed specifications provide a quite reasonably good performance being so of interest for applications involving the modelling and forecasting of heavy-tailed distributions.Multivariate distributions; Gram-Charlier and Edgeworth-Sargan densities; MGARCH models; financial data