Browsing by Subject "Inverse probability weighting"

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    Analysis of group performance with categorical data when agents are heterogeneous: the evaluation of scholastic performance in the OECD through PISA
    (Elsevier, 2014-06) Villar, Antonio; Méndez Martínez, Ildefonso; Economía Aplicada
    This paper analyzes the evaluation of the relative performance of a set of groups when their outcomes are defined in terms of categorical data and the groups’ members are heterogeneous. This type of problem has been dealt with in Herrero and Villar (2013) for the case of a homogeneous population. Here we expand their model controlling for heterogeneity by means of inverse probability weighting techniques. We apply this extended model to the analysis of the scholastic performance of fifteen-year-old students in the OECD countries, using the data in the PISA. We evaluate the relative performance of the different countries out of the distribution of the students’ achievements across the different levels of competence, controlling by the students’ characteristics (explanatory variables regarding schooling and family environment). We find that differences in mathematical and reading abilities across OECD countries would lower by between 40% and 50% if the students’ characteristics would be those for the OECD average
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    Inverse probability weighted estimation of social tariffs: an illustration using the SF-6D value sets
    (Elsevier, 2011-12) Méndez Martínez, Ildefonso; Abellán Perpiñán, José María; Sánchez Martínez, Fernando I.; Martínez Pérez, Jorge E.; Economía Aplicada
    This paper presents a novel approach to model health state valuations using inverse probability weighting techniques. Our approach makes no assumption on the distribution of health state values, accommodates covariates in a flexible way, eschews parametric assumptions on the relationship between the outcome and the covariates, allows for an undetermined amount of heterogeneity in the estimates and it formally tests and corrects for sample selection biases. The proposed model is semi-parametrically estimated and it is illustrated with health state valuation data collected for Spain using the SF-6D descriptive system. Estimation results indicate that the standard regression model underestimates the utility loss that the Spanish general population assigns to departures from full health, particularly so for severe departures