. Applications include: (i) matched sampling on the univariate propensity score, which is a generalization of discriminant matching, (ii) multivariate adjustment by subclassification on the propensity score where the same subclasses are used to estimate treatment effects for all outcome variables and in all

Empirical findings for a panel of around 100 countries from 1960 to 1990 strongly support the general notion of conditional convergence. For a given starting level of real per capita GDP, the growth rate is enhanced by higher initial schooling and life expectancy, lower fertility, lower government

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levels of the older workers exits, can bias the effect estimation on the entries of youngsters. In order to adjust for this, we apply propensity score methods as extended and generalized in a setting with a continuous treatment by Hirano and Imbens (2004). Our results show a positive and significant

(preliminary version) Mainly due to data unavailability, time with the mother is usually not included as an input in empirical papers trying to …nd the determinants of child’s achievement. We attempt to do so in this paper by using unique data that collects a child’s time-use diary, cognitive and non cognitive test scores. We implement the methodology developed recently on the treatment evaluation for continuous treatments. We …nd that more time with mothers leads both young and old children to perform better in cognitive tests, but the e¤ect for the former group is more pronounced. Once we divide our sample according to race we …nd that young black children tend to perform worse if they spend more than 5 hours with the mother in a day. This negative e¤ect is not present for white children, who tend to perform better if the time spent with mothers increases. Also white children bene…t from this e¤ect until later ages.

the generalized propensity score1

Generalized Propensity Score Evidence from the EU1

In this article we develop the theoretical properties of the propensity function, which is a generalization of the propensity score of Rosenbaum and Rubin. Methods based on the propensity score have long been used for causal inference in observational studies; they are easy to use and can