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理性预期的相容性：刻画与检验AI 解读

In this paper, we build a new test of rational expectations based on the marginal distributions of realizations and subjective beliefs. This test is widely applicable, including in the common situation where realizations and beliefs are observed in two different data sets that cannot be matched. We show that whether one can rationalize rational expectations is equivalent to the distribution of realizations being a mean‐preserving spread of the distribution of beliefs. The…

Using data from Duke University undergraduates, we make three main contributions to the literature. First, we show that data on earnings beliefs and probabilities of choosing particular occupations are highly informative of future earnings and occupations. Second, we show how beliefs data can be used to recover ex ante treatment effects and their relationship with individual choices. We find large differences in expected earnings across occupations and provide evidence of…

样本选择模型的极端分位数回归与黑人—白人工资差距AI 解读

We consider the estimation of a semiparametric sample selection model without instrument or large support regressor. Identification relies on the independence between the covariates and selection, for arbitrarily large values of the outcome. We propose a simple estimator based on extremal quantile regression and establish its asymptotic normality by extending previous results on extremal quantile regressions to allow for selection. Finally, we apply our method to estimate…

扩展 Roy 模型的推断及其在法国教育选择中的应用AI 解读

This paper considers the identification and estimation of an extension of Roy’s model (1951) of sectoral choice, which includes a non-pecuniary component in the selection equation and allows for uncertainty on potential earnings. We focus on the identification of the non-pecuniary component, which is key to disentangling the relative importance of monetary incentives versus preferences in the context of sorting across sectors. By making the most of the structure of the…

重新审视样本选择模型的无穷远识别AI 解读

It is often believed that without instruments, endogenous sample selection models are identified only if a covariate with a large support is available (see, e.g., Chamberlain, 1986, Journal of Econometrics 32, 189–218; Lewbel, 2007, Journal of Econometrics 141, 777–806) . We propose a new identification strategy mainly based on the condition that the selection variable becomes independent of the covariates for large values of the outcome. No large support on the covariates…