2017 Best Paper Awards
Quantitative Economics and Theoretical Economics Best Paper Awards
The Econometric Society congratulates the 2017 winners of the "Best Paper Prize" for its two journals Quantitative Economics and Theoretical Economics. These awards highlight the best paper published in each of the journals in the areas of quantitative economics and economic theory. The journals' Editors and Co-Editors select a list of nominees, from which the Associate Editors elect the winning paper.
We are pleased to announce the following papers have been awarded the 2017 "Best Paper Prize":
William Diamond and Nikhil Agarwal, “Latent indices in assortative matching models,” Quantitative Economics, Volume 8, Issue 3, 685–728.
Abstract
A large class of two‐sided matching models that include both transferable and non‐transferable utility result in positive assortative matching along a latent index. Data from matching markets, however, may not exhibit perfect assortativity due to the presence of unobserved characteristics. This paper studies the identification and estimation of such models. We show that the distribution of the latent index is not identified when data from one‐to‐one matches are observed. Remarkably, the model is nonparametrically identified using data in a single large market when each agent on one side has at least two matched partners. The additional empirical content in many‐to‐one matches is demonstrated using simulations and stylized examples. We then derive asymptotic properties of a minimum distance estimator as the size of the market increases, allowing estimation using dependent data from a single large matching market. The nature of the dependence requires modification of existing empirical process techniques to obtain a limit theorem.
Péter Eső and Balázs Szentes, “Dynamic contracting: An irrelevance theorem,” Theoretical Economics, Volume 12, Issue 1, 109-139.
Abstract
This paper generalizes a conceptual insight in dynamic contracting with quasilinear payoffs: the principal does not need to pay any information rents for extracting the agent's `new' private information obtained after signing the contract. This is shown in a general model in which the agent's type stochastically evolves over time, and her payoff (which is linear in transfers) depends on the entire history of private and any contractible information, contractible decisions and her hidden actions. The contract is offered by the principal in the presence of initial informational asymmetry. The model can be transformed into an equivalent one where the agent's subsequent information is independent in each period (type orthogonalization). We show that for any fixed decision-action rule implemented by a mechanism, the agent's rents (as well as the principal's maximal revenue) are the same as if the principal could observe and contract on the agent's orthogonalised types after the initial period. We also show that any monotonic decision-action rule can be implemented in a Markovian environment satisfying certain regularity conditions, and provide a simple `recipe' for solving such dynamic contracting problems.
