Estimating risk aversion from ascending and sealed-bid auctions: the case of timber auction data

Estimating bidders’ risk aversion in auctions is a challeging problem because of identification issues. This paper takes advantage of bidding data from two auction designs to identify nonparametrically the bidders’ utility function within a private value framework. In particular, ascending auction data allow us to recover the latent distribution of private values, while first-price sealed-bid auction data allow us to recover the bidders’ utility function. This leads to a nonparametric estimator. An application to the US Forest Service timber auctions is proposed. Estimated utility functions display concavity, which can be partly captured by constant relative risk aversion.Risk Aversion; Nonparametric Identi.cation; Nonparametric and Semipara-metric Estimation; Timber Auctions

Nonidentification of Insurance Models with Probability of Accidents

In contrast to Aryal, Perrigne and Vuong (2009), this note shows that in an insurance model with multidimensional screening when only information on whether the insuree has been involved in some accident is available, the joint distribution of risk and risk aversion is not identified.

Identification of Insurance Models with Multidimensional Screening

We study the identification of an insurance model with multidimensional screening, where insurees are characterized by risk and risk aversion. The model is solved using the concept of certainty equivalence under constant absolute risk aversion and an unspecified joint distribution of risk and risk aversion. The paper then analyzes how data availability constraints identification under four data scenarios from the ideal situation to a more realistic one. The observed number of accidents for each insuree plays a key role to identify the model. In a first part, we consider the case of a continuum of coverages offered to each insuree whether the damage distribution is fully observed or truncated. Truncation arises from that an insuree files a claim only when the accident involves a damage above the deductible. Despite bunching due to multidimensional screening, we show that the joint distribution of risk and risk aversion is identified. In a second part, we consider the case of a finite number of coverages offered to each insuree. When the full damage distribution is observed, we show that despite additional pooling due to the finite number of contracts, the joint distribution of risk and risk aversion is identified under a full support assumption and a conditional independence assumption involving the car characteristics. When the damage distribution is truncated, the joint distribution is identified up to the probability that the damage is above the deductible. In a third part, we derive the restrictions imposed by the model on observables for the fourth scenario. We also propose several identification strategies for the damage probability at the deductible. These identification results are further exploited in a companion paper developing an estimation method with an application to insurance data

Estimating risk aversion from ascending and sealed-bid auctions: the case of timber auction data

Estimating bidders’ risk aversion in auctions is a challeging problem because of identification issues. This paper takes advantage of bidding data from two auction designs to identify nonparametrically the bidders’ utility function within a private value framework. In particular, ascending auction data allow us to recover the latent distribution of private values, while first-price sealed-bid auction data allow us to recover the bidders’ utility function. This leads to a nonparametric estimator. An application to the US Forest Service timber auctions is proposed. Estimated utility functions display concavity, which can be partly captured by constant relative risk aversion

Estimating risk aversion from ascending and sealed-bid auctions: the case of timber auction data

Estimating bidders’ risk aversion in auctions is a challeging problem because of identification issues. This paper takes advantage of bidding data from two auction designs to identify nonparametrically the bidders’ utility function within a private value framework. In particular, ascending auction data allow us to recover the latent distribution of private values, while first-price sealed-bid auction data allow us to recover the bidders’ utility function. This leads to a nonparametric estimator. An application to the US Forest Service timber auctions is proposed. Estimated utility functions display concavity, which can be partly captured by constant relative risk aversion

Semiparametric Estimation of First-Price Auctions with Risk-Averse Bidders

This paper proposes a semiparametric estimation procedure of the first-price auction model with risk averse bidders within the independent private value paradigm. We show that the model is nonidentified in general from observed bids. We then exploit heterogeneity across auctioned objects to establish semiparametric identification under a conditional quantile restriction and parameterization of the bidders’ von Neuman Morgenstern utility function. Next we propose a semiparametric method for estimating the corresponding auction model. This method involves several steps and allows to recover the parameters of the utility function as well as the bidders’ private values and their density. We show that our semiparametric estimator of the utility function parameters converges at the optimal rate, which is slower than the parametric one. An illustration of the method on U.S. Forest Service timber sales is presented and a test of bidders’ risk neutrality is performed

Analyse empirique de l'économie industrielle (Berlin, 16-17 décembre 1994)

Perrigne Isabelle. Analyse empirique de l'économie industrielle (Berlin, 16-17 décembre 1994). In: Cahiers d'Economie et sociologie rurales, N°36, 3e trimestre 1995. pp. 145-148

Frontière de production et données de panel : application aux exploitations céréalières

Production frontier and panel data : application to grain farmers. This paper deals with the issue of estimating a stochastic production frontier and of measuring technical efficiency from a complete panel of grain farmer from 1982 to 1986. A survey of classical panel data econometric methods (Within and GLS) and their applications underline the limits of their use with respect to the empirical results and the characteristics of our data set. Moreover, the Hausman test shows a correlation between inputs and the error term which represents inefficiency, which invalidates GLS estimation. The use of a new method proposed by Ivaldi, Perrigne and Simioni (1994) based on a co-variance structural analysis allows to reveal correlations between regressors and the individual effect as well as to estimate an individual time-varying technical efficiency. Empirical evidences show a negative correlation between materials and efficiency and a declining trend for efficiency between 1982 and 1986.Ce papier propose d'estimer une frontière de production stochastique et de mesurer l'efficacité technique à partir d'un échantillon de panel cylindré d'exploitations céréalières de 1982 à 1986 en utilisant diverses méthodes. Une présentation des méthodes usuelles de données de panel (Within et GLS) et leurs applications mettent en lumière les limites de celles-ci quant aux résultats obtenus et aux spécificités de l'échantillon. De plus, le test d'Hausman montre l'existence d'une possible corrélation entre les inputs utilisés et le terme d'erreur représentant l'inefficacité, ce qui rend caduque l'estimation GLS. L'utilisation d'une méthode récente proposée par Ivaldi, Perrigne et Simioni (1994), basée sur une modélisation en termes d'analyse structurelle des covariances permet de révéler les corrélations entre les régresseurs et l'effet individuel. Cette modélisation permet aussi d'estimer l'efficacité technique de chaque individu comme une fonction du temps. Les résultats empiriques montrent d'une part, l'existence d'une corrélation néga-tive entre les consommations intermédiaires et l'efficacité et d'autre part, une décroissance des niveaux d'efficacité entre 1982 et 1986.Perrigne Isabelle. Frontière de production et données de panel : application aux exploitations céréalières. In: Cahiers d'Economie et sociologie rurales, N°36, 3e trimestre 1995. pp. 79-94