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estimation methods from the treatment evaluation literature we separate the direct effect of textbooks from their peer effect …
estimation methods from the treatment evaluation literature we separate the direct effect of textbooks from their peer effect …
estimation methods from the treatment evaluation literature we separate the direct effect of textbooks from their peer effect …
estimation methods from the treatment evaluation literature we separate the direct effect of textbooks from their peer effect …
In a treatment effect model with unconfoundedness, treatment assignments are not only independent of potential outcomes given the covariates, but also given the propensity score alone. Despite this powerful dimension reduction property, adjusting for the propensity score is known to lead to an...
In nonparametric instrumental variables estimation, the mapping that identifies the function of interest, g say, is discontinuous and must be regularised (that is, modified) to make consistent estimation possible. The amount of modification is contolled by a regularisation parameter. The optimal...
In a treatment effect model with unconfoundedness, treatment assignments are not only independent of potential outcomes given the covariates, but also given the propensity score alone. Despite this powerful dimension reduction property, adjusting for the propensity score is known to lead to an...
This paper presents econometric methods for measuring the average output effect of reallocating an indivisible input across production units. A distinctive feature of reallocations is that, by definition, they involve no augmentation of resources and, as such, leave the marginal distribution of...
Existing indices of residential segregation are based on a partition of the city in neighborhoods: given a spatial distribution of racial groups, the index measures different segregation levels for different partitions. I propose a spatial approach, which estimates segregation at the individual...
In nonparametric instrumental variables estimation, the mapping that identifies the function of interest, g, is discontinuous and must be regularized to permit consistent estimation. The optimal regularization parameter depends on population characteristics that are unknown in applications. This...