Stochastic discount factor (SDF) processes in dynamic economies admit a permanent-transitory decomposition in which the permanent component characterizes pricing over long investment horizons. This paper introduces an empirical framework to analyze the permanent-transitory decomposition of SDF processes. Specifically, we show how to estimate nonparametrically the solution to the Perron-Frobenius eigenfunction problem of Hansen and Scheinkman (2009). Our empirical framework allows researchers to (i) recover the time series of the estimated permanent and transitory components and (ii) estimate the yield and the change of measure which characterize pricing over long investment horizons. We also introduce nonparametric estimators of the continuation value function in a class of models with recursive preferences by reinterpreting the value function recursion as a nonlinear Perron-Frobenius problem. We establish consistency and convergence rates of the eigenfunction estimators and asymptotic normality of the eigenvalue estimator and estimators of related functionals. As an application, we study an economy where the representative agent is endowed with recursive preferences, allowing for general (nonlinear) consumption and earnings growth dynamics.

This paper develops characterizations of identified sets of structures and structural features for complete and incomplete models involving continuous or discrete variables.Multiple values of unobserved variables can be associated with particular combinations of observed variables.This can arise when there are multiple sources of heterogeneity, censored or discrete endogenous variables, or inequality restrictions on functions of observed and unobserved variables.The models generalize the class of incomplete instrumental variable (IV) models in which unobserved variables are singlevalued functions of observed variables.Thus the models are referred to as generalized IV (GIV) models, but there are important cases in which instrumental variable restrictions play no significant role.Building on a definition of observational equivalence for incomplete models the development uses results from random set theory that guarantee that the characterizations deliver sharp bounds, thereby dispensing with the need for case-by-case proofs of sharpness.The use of random sets defined on the space of unobserved variables allows identification analysis under mean and quantile independence restrictions on the distributions of unobserved variables conditional on exogenous variables as well as under a full independence restriction.The results are used to develop sharp bounds on the distribution of valuations in an incomplete model of English auctions, improving on the pointwise bounds available until now.Application of many of the results of the paper requires no familiarity with random set theory.

This paper proposes a perfectly competitive model of a market with adverse selection. Prices are determined by zero-profit conditions, and the set of traded contracts is determined by free entry. Crucially for applications, contract characteristics are endogenously determined, consumers may have multiple dimensions of private information, and an equilibrium always exists. Equilibrium corresponds to the limit of a differentiated products Bertrand game. We apply the model to establish theoretical results on the equilibrium effects of mandates. Mandates can increase efficiency but have unintended consequences. With adverse selection, an insurance mandate reduces the price of low-coverage policies, which necessarily has indirect effects such as increasing adverse selection on the intensive margin and causing some consumers to purchase less coverage.

Owing to the worldwide shortage of deceased‐donor organs for transplantation, living donations have become a significant source of transplant organs. However, not all willing donors can donate to their intended recipients because of medical incompatibilities. These incompatibilities can be overcome by an exchange of donors between patients. For kidneys, such exchanges have become widespread in the last decade with the introduction of optimization and market design techniques to kidney exchange. A small but growing number of liver exchanges have also been conducted. Over the last two decades, a number of transplantation procedures emerged where organs from two living donors are transplanted to a single patient. Prominent examples include dual‐graft liver transplantation, lobar lung transplantation, and simultaneous liver‐kidney transplantation. Exchange, however, has been neither practiced nor introduced in this context. We introduce dual‐donor organ exchange as a novel transplantation modality, and through simulations show that living‐donor transplants can be significantly increased through such exchanges. We also provide a simple theoretical model for dual‐donor organ exchange and introduce optimal exchange mechanisms under various logistical constraints.

This paper develops a theory of randomization tests under an approximate symmetry as-sumption. Randomization tests provide a general means of constructing tests that control size in finite samples whenever the distribution of the observed data exhibits symmetry under the null hypothesis. Here, by exhibits symmetry we mean that the distribution remains invariant under a group of transformations. In this paper, we provide conditions under which the same construction can be used to construct tests that asymptotically control the probability of a false rejection whenever the distribution of the observed data exhibits approximate symmetry in the sense that the limiting distribution of a function of the data exhibits symmetry under the null hypothesis. An important application of this idea is in settings where the data may be grouped into a fixed number of “clusters ” with a large number of observations within each cluster. In such settings, we show that the distribution of the observed data satisfies our ap-proximate symmetry requirement under weak assumptions. In particular, our results allow for the clusters to be heterogeneous and also have dependence not only within each cluster, but also across clusters. This approach enjoys several advantages over other approaches in these settings. Among other things, it leads to a test that is asymptotically similar, which, as shown in a simulation study, translates into improved power at many alternatives. Finally, we use our results to revisit the analysis of Angrist and Lavy (2009), who examine the impact of a cash award on exam performance for low-achievement students in Israel.

The gCube System - AquaMaps Species View Portlet<br> --------------------------------------------------<br> <br> Species view explorer portlet for AquaMaps suite<br> <br> <br> This software is part of the gCube Framework (https://www.gcube-system.org/): an<br> open-source software toolkit used for building and operating Hybrid Data<br> Infrastructures enabling the dynamic deployment of Virtual Research Environments<br> by favouring the realisation of reuse oriented policies.<br> <br> The projects leading to this software have received funding from a series of <br> European Union programmes including: <br> * the Sixth Framework Programme for Research and Technological Development - <br> DILIGENT (grant no. 004260); <br> * the Seventh Framework Programme for research, technological development and <br> demonstration - D4Science (grant no. 212488), D4Science-II (grant no. <br> 239019),ENVRI (grant no. 283465), EUBrazilOpenBio (grant no. 288754), iMarine <br> (grant no. 283644); <br> * the H2020 research and innovation programme - BlueBRIDGE (grant no. 675680), <br> EGIEngage (grant no. 654142), ENVRIplus (grant no. 654182), Parthenos (grant <br> no. 654119), SoBigData (grant no. 654024);<br> <br> <br> Version<br> --------------------------------------------------<br> <br> 1.3.3-4.0.0-130288 (2016-11-27)<br> <br> Please see the file named "changelog.xml" in this directory for the release notes.<br> <br> <br> <br> Authors<br> --------------------------------------------------<br> <br> * Fabio Sinibaldi (fabio.sinibaldi-AT-isti.cnr.it) Istituto di Scienza e Tecnologie dell'Informazione "A. Faedo" - CNR, Pisa (Italy). <br> <br> Maintainers<br> -----------<br> <br> * Fabio Sinibaldi (fabio.sinibaldi-AT-isti.cnr.it) Istituto di Scienza e Tecnologie dell'Informazione "A. Faedo" - CNR, Pisa (Italy). <br> <br> <br> <br> Download information<br> --------------------------------------------------<br> <br> Source code is available from SVN: <br> http://svn.research-infrastructures.eu/public/d4science/gcube/trunk/portlets/user/aquamapsspeciesview<br> <br> Binaries can be downloaded from the gCube website: <br> https://www.gcube-system.org/<br> <br> Installation<br> --------------------------------------------------<br> <br> Installation documentation is available on-line in the gCube Wiki:<br> https://wiki.gcube-system.org/gcube/index.php/AquaMaps_Suite<br> <br> Documentation <br> --------------------------------------------------<br> <br> Documentation is available on-line in the gCube Wiki:<br> https://wiki.gcube-system.org/gcube/index.php/AquaMaps_Suite<br> https://wiki.gcube-system.org/gcube/index.php/AquaMaps_Suite<br> <br> <br> Support <br> --------------------------------------------------<br> <br> Bugs and support requests can be reported in the gCube issue tracking tool:<br> https://support.d4science.org/projects/gcube/<br> <br> <br> Licensing<br> --------------------------------------------------<br> <br> This software is licensed under the terms you may find in the file named "LICENSE" in this directory.<br>

We provide general conditions under which principal-agent problems admit mechanisms that are optimal for the principal. Our result covers as special cases those in which the agent has no private information – i.e., pure moral hazard – as well as those in which the agent’s only action is a participation decision – i.e., pure adverse selection. We allow multi-dimensional actions and signals, as well as both …nancial and non-financial rewards. Beyond measurability, we require no a priori restrictions on the space of mechanisms. Consequently, our optimal mechanisms are optimal among all measurable mechanisms. A key to obtaining our result is to permit randomized mechanisms. We also provide conditions under which randomization is unnecessary.