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New submissions

[ total of 10 entries: 1-10 ]
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New submissions for Thu, 21 May 20

[1]  arXiv:2005.09717 [pdf, other]
Title: Treatment recommendation with distributional targets
Comments: Treatment allocation, best treatment identification, statistical decision theory, pure exploration, nonparametric multi-armed bandits
Subjects: Econometrics (econ.EM); Statistics Theory (math.ST); Machine Learning (stat.ML)

We study the problem of a decision maker who must provide the best possible treatment recommendation based on an experiment. The desirability of the outcome distribution resulting from the policy recommendation is measured through a functional capturing the distributional characteristic that the decision maker is interested in optimizing. This could be its inherent inequality, welfare, level of poverty or its distance to a desired outcome distribution. If the functional of interest is not quasi-convex or if there are constraints, the policy maker must also consider mixtures of the available treatments. This vastly expands the set of recommendations that must be considered compared to the classic treatment problem in which one targets the mean. We characterize the difficulty of the problem by obtaining maximal expected regret lower bounds. Furthermore, we propose two regret-optimal policies. The first policy is static and thus applicable irrespectively of the the subjects arriving sequentially or not in the course of the experimental phase. The second policy can utilize that subjects arrive sequentially by successively eliminating inferior treatments and thus spends the sampling effort where it is most needed.

[2]  arXiv:2005.09839 [pdf, ps, other]
Title: Communication and Cooperation in Markets
Subjects: Theoretical Economics (econ.TH)

Many markets rely on traders truthfully communicating who has cheated in the past and ostracizing those traders from future trade. This paper investigates when truthful communication is incentive compatible. We find that if each side has a myopic incentive to deviate, then communication incentives are satisfied only when the volume of trade is low. By contrast, if only one side has a myopic incentive to deviate, then communication incentives do not constrain the volume of supportable trade. Accordingly, there are strong gains from structuring trade so that one side either moves first or has its cooperation guaranteed by external enforcement.

[3]  arXiv:2005.09951 [pdf, ps, other]
Title: Uniform Rates for Kernel Estimators of Weakly Dependent Data
Subjects: Econometrics (econ.EM)

This paper provides new uniform rate results for kernel estimators of absolutely regular stationary processes that are uniform in the bandwidth and in infinite-dimensional classes of dependent variables and regressors. Our results are useful for establishing asymptotic theory for two-step semiparametric estimators in time series models. We apply our results to obtain nonparametric estimates and their rates for Expected Shortfall processes.

Cross-lists for Thu, 21 May 20

[4]  arXiv:2005.09836 (cross-list from cs.GT) [pdf, other]
Title: Computations and Complexities of Tarski's Fixed Points and Supermodular Games
Subjects: Computer Science and Game Theory (cs.GT); Computational Complexity (cs.CC); Theoretical Economics (econ.TH)

We consider two models of computation for Tarski's order preserving function f related to fixed points in a complete lattice: the oracle function model and the polynomial function model. In both models, we find the first polynomial time algorithm for finding a Tarski's fixed point. In addition, we provide a matching oracle bound for determining the uniqueness in the oracle function model and prove it is Co-NP hard in the polynomial function model. The existence of the pure Nash equilibrium in supermodular games is proved by Tarski's fixed point theorem. Exploring the difference between supermodular games and Tarski's fixed point, we also develop the computational results for finding one pure Nash equilibrium and determining the uniqueness of the equilibrium in supermodular games.

[5]  arXiv:2005.09974 (cross-list from q-fin.RM) [pdf, other]
Title: Stochastic modeling of assets and liabilities with mortality risk
Subjects: Risk Management (q-fin.RM); Econometrics (econ.EM); Optimization and Control (math.OC)

This paper describes a general approach for stochastic modeling of assets returns and liability cash-flows of a typical pensions insurer. On the asset side, we model the investment returns on equities and various classes of fixed-income instruments including short- and long-maturity fixed-rate bonds as well as index-linked and corporate bonds. On the liability side, the risks are driven by future mortality developments as well as price and wage inflation. All the risk factors are modeled as a multivariate stochastic process that captures the dynamics and the dependencies across different risk factors. The model is easy to interpret and to calibrate to both historical data and to forecasts or expert views concerning the future. The simple structure of the model allows for efficient computations. The construction of a million scenarios takes only a few minutes on a personal computer. The approach is illustrated with an asset-liability analysis of a defined benefit pension fund.

[6]  arXiv:2005.09980 (cross-list from cs.AI) [pdf]
Title: Creative Artificial Intelligence -- Algorithms vs. humans in an incentivized writing competition
Subjects: Artificial Intelligence (cs.AI); Computation and Language (cs.CL); General Economics (econ.GN)

The release of openly available, robust text generation algorithms has spurred much public attention and debate, due to algorithm's purported ability to generate human-like text across various domains. Yet, empirical evidence using incentivized tasks to assess human behavioral reactions to such algorithms is lacking. We conducted two experiments assessing behavioral reactions to the state-of-the-art Natural Language Generation algorithm GPT-2 (Ntotal = 830). Using the identical starting lines of human poems, GPT-2 produced samples of multiple algorithmically-generated poems. From these samples, either a random poem was chosen (Human-out-of-the-loop) or the best one was selected (Human-in-the-loop) and in turn matched with a human written poem. Taking part in a new incentivized version of the Turing Test, participants failed to reliably detect the algorithmically-generated poems in the human-in-the-loop treatment, yet succeeded in the Human-out-of-the-loop treatment. Further, the results reveal a general aversion towards algorithmic poetry, independent on whether participants were informed about the algorithmic origin of the poem (Transparency) or not (Opacity). We discuss what these results convey about the performance of NLG algorithms to produce human-like text and propose methodologies to study such learning algorithms in experimental settings.

[7]  arXiv:2005.10038 (cross-list from cs.GT) [pdf, ps, other]
Title: Coopetition Against an Amazon
Subjects: Computer Science and Game Theory (cs.GT); Theoretical Economics (econ.TH)

This paper studies cooperative data-sharing between competitors vying to predict a consumer's tastes. We design optimal data-sharing schemes both for when they compete only with each other, and for when they additionally compete with an Amazon---a company with more, better data. In both cases we show that participants benefit from such coopetition. We then apply the insights from our optimal schemes to more general settings.

Replacements for Thu, 21 May 20

[8]  arXiv:1808.02233 (replaced) [pdf]
Title: Robust Pricing with Refunds
Subjects: Computer Science and Game Theory (cs.GT); Theoretical Economics (econ.TH)
[9]  arXiv:1810.01576 (replaced) [pdf, other]
Title: Interpreting OLS Estimands When Treatment Effects Are Heterogeneous: Smaller Groups Get Larger Weights
Subjects: Econometrics (econ.EM); Applications (stat.AP); Methodology (stat.ME)
[10]  arXiv:2004.01411 (replaced) [pdf]
Title: Targeting predictors in random forest regression
Subjects: Econometrics (econ.EM)
[ total of 10 entries: 1-10 ]
[ showing up to 2000 entries per page: fewer | more ]