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随机议价模型识别的新结果AI 解读

We present new identification results for stochastic sequential bargaining models when the data only reports the time of agreement and the evolution of observable states. With no information on the stochastic surplus available for allocation or how it is allocated under agreement, we recover the latent surplus process, the distribution of unobservable states, and the equilibrium outcome in counterfactual contexts. The method we propose, which is constructive and original,…

意识形态型选民的偏好分布识别与估计AI 解读

This article studies the non-parametric identification and estimation of voters’ preferences when voters are ideological. We establish that voter preference distributions and other parameters of interest can be identified from aggregate electoral data. We also show that these objects can be consistently estimated and illustrate our analysis by performing an actual estimation using data from the 1999 European Parliament elections.