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跨异质地点的因果效应迁移估计AI 解读

We consider the problem of extrapolating treatment effects across heterogeneous populations (“sites”/“contexts”). We consider an idealized scenario in which the researcher observes cross-sectional data for a large number of units across several “experimental” sites in which an intervention has already been implemented to a new “target” site for which a baseline survey of unit-specific, pre-treatment outcomes and relevant attributes is available. Our approach treats the…

大量参与者下的策略性网络形成AI 解读

We derive asymptotic approximations for models of strategic network formation, where limits are taken as the number of nodes (agents) increases to infinity. Our framework assumes a random utility model where agents have heterogeneous tastes over links, and payoffs allow for anonymous and non-anonymous interaction effects, and the observed network is assumed to be pairwise stable. Our main results concern convergence of the link intensity from finite pairwise stable networks…

因果自助法AI 解读

The bootstrap, introduced by The Jackknife, the Bootstrap and Other Resampling Plans ((1982), SIAM), has become a very popular method for estimating variances and constructing confidence intervals. A key insight is that one can approximate the properties of estimators by using the empirical distribution function of the sample as an approximation for the true distribution function. This approach views the uncertainty in the estimator as coming exclusively from sampling…

双维及更高维聚类依赖下的自助法AI 解读

We propose a bootstrap procedure for data that may exhibit cluster‐dependence in two or more dimensions. The asymptotic distribution of the sample mean or other statistics may be non‐Gaussian if observations are dependent but uncorrelated within clusters. We show that there exists no procedure for estimating the limiting distribution of the sample mean under two‐way clustering that achieves uniform consistency. However, we propose bootstrap procedures that achieve adaptivity…

多参与者博弈的统计推断AI 解读

We develop an asymptotic theory for static discrete-action games with a large number of players, and propose a novel inference approach based on stochastic expansions around the limit of the finite-player game. Our analysis focuses on anonymous games in which payoffs are a function of the agent's own action and the empirical distribution of her opponents' play. We establish a law of large numbers and central limit theorem which can be used to establish consistency of point…

作为双边需求系统的大型匹配市场AI 解读

This paper studies two-sided matching markets with non-transferable utility when the number of market participants grows large. We consider a model in which each agent has a random preference ordering over individual potential matching partners, and agents' types are only partially observed by the econometrician. We show that in a large market, the inclusive value is a sufficient statistic for an agent's endogenous choice set with respect to the probability of being matched…

拍卖次序统计量估计方法的大样本性质AI 解读

For symmetric auctions, there is a close relationship between distributions of order statistics of bidders' valuations and observable bids that is often used to estimate or bound the valuation distribution, optimal reserve price, and other quantities of interest nonparametrically. However, we show that the functional mapping from distributions of order statistics to their parent distribution is, in general, not Lipschitz continuous and, therefore, introduces an irregularity…