Gaurab Aryal

Identification of Insurance Models with Multidimensional Screening

This paper addresses the identification of insurance models with multidimensional screening where insurees have private information about their risk and risk aversion. The model includes a random damage and the possibility of several claims. Screening of insurees relies on their certainty equivalence. The paper then investigates how data availability on the number of offered coverages and reported claims affects the identification of the model primitives under four different scenarios. We show that the model structure is identified despite bunching due to multidimensional screening and/or a finite number of offered coverages. The observed number of claims plays a key role in the identification of the joint distribution of risk and risk aversion. In addition, the paper derives all the restrictions imposed by the model on observables. Our results are constructive with explicit equations for estimation and model testing.

Empirical Relevance of Ambiguity in First Price Auction Models

We study the identification and estimation of first-price auction models where bidders have ambiguity about the valuation distribution and their preferences are represented by maxmin expected utility. When entry is exogenous, the distribution and ambiguity structure are nonparametrically identified, separately from risk aversion (CRRA). We propose a flexible Bayesian method based on Bernstein polynomials. Monte Carlo experiments show that our method estimates parameters precisely, and chooses reserve prices with (nearly) optimal revenues, whether there is ambiguity or not. Furthermore, if the model is misspecified -- incorrectly assuming no ambiguity among bidders -- it may induce estimation bias with a substantial revenue loss.

A Note on Kuhn's Theorem with Ambiguity Averse Players

Kuhn’s Theorem shows that extensive games with perfect recall can equivalently be analyzed using mixed or behavioral strategies, as long as players are expected utility maximizers. This note constructs an example that illustrates the limits of Kuhn’s Theorem in an environment with ambiguity averse players who use a maxmin decision rule and full Bayesian updating.

A point decision for partially identified auction models

This article proposes a decision-theoretic method to choose a single reserve price for partially identified auction models, such as Haile and Tamer (2003), using data on transaction prices from English auctions. The article employs Gilboa and Schmeidler (1989) for inference that is robust with respect to the prior over unidentified parameters. It is optimal to interpret the transaction price as the highest value, and maximize the posterior mean of the seller’s revenue. The Monte Carlo study shows substantial gains relative to the revenues corresponding to a random point and the midpoint in the Haile and Tamer interval.

Is Collusion Proof Auction Expensive? Estimates from Highway Procurements

We propose a method to nonparametriclly estimate the revenue under a auction that is efficient and resilient to collusion [Chen and Micali, 2012]. Efficiency is achieved on account of a lower revenue and we propose a method to quantify this efficiency-revenue trade-off, i.e. the extra cost for which efficient allocation can be guaranteed even when bidders collude. We implement a local polynomial estimation method on sample of California highway procurements data and find that to achieve efficiency the cost of procurement must increase by at lest 10.8% and can go up to 48.8% depending on the size of bidding-ring.

An Empirical Analysis of Competitive Nonlinear Pricing

We estimate a model of competitive nonlinear pricing with multidimensional preference heterogeneity using individual level data on advertisements bought by local businesses (e.g., doctors, electricians) from two Yellow Page Directories in one U.S. city-market. Variation in individual choices and payments allow us to identify the joint density of preferences, marginal costs of publishing and common utility parameters. Our estimates suggest substantial welfare loss due to asymmetric information. Comparing duopoly outcomes with (counterfactual) monopoly outcomes, we find that with less competition (i) producer surplus increases substantially; (ii) more “low-type�? consumers are excluded; (iii) product variety increases, but benefits accrue only to the “high-type�? consumers; (iv) total consumer surplus decreases; (v) but its distribution, across consumers, does not change.

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.

Public Communication and Collusion in the Airline Industry

We investigate whether legacy U.S. airlines communicated via earnings calls to coordinate with other legacy airlines in offering fewer seats on competitive routes. To this end, we first use text analytics to build a novel dataset on communication among airlines about their capacity choices. Estimates from our preferred specification show that when all legacy airlines in a market discuss the concept of “capacity discipline,�? they reduce offered seats by 1.79%. We verify that this reduction materializes only when airlines communicate concurrently, and that it cannot be explained by other possibilities, including that airlines are simply announcing to investors their unilateral intentions to reduce capacity, and then following through on those announcements. Additional results from conditional-exogeneity tests and control function estimates confirm our interpretation.