_____________________________________________________________________________________________________________________________________ ResumenEl estudio que se presenta tiene como objetivo central evaluar aquellos factores que llevan a un estudiante universitario a desertar no sólo al primer año sino también en los subsiguientes. A través de estimaciones de modelos de probabilidad logit, se encontró que los motivos que llevan a la deserción van cambiando a medida que se avanza en la carrera. Si bien existe un factor transversal, que corresponde al rendimiento académico universitario, en el primer año de carrera destacan otros factores, tales como, la región de procedencia, edad, y año de ingreso, mientras que al tercer año de carrera destacan el rendimiento académico y el financiamiento. A partir de estos resultados se pueden diseñar mejores políticas de retención estudiantil.Palabras clave: deserción; educación universitaria; rendimiento académico; financiamiento; tasas de retención. The Determinants of University Dropout. A Case of the Facultad de Ciencias Económicas y Administrativas de la Universidad Católica de la Santísima Concepción (Chile) AbstractThe objective of the study presented in this paper was to evaluate those factors leading a university student to leave her career, not just during the first year, but also during the following ones. By using a logit probability model, it was found that dropout's factors change during the career. Although there is a transversal factor that explains dropout, corresponding to academic performance, during the first year others factors appear, such as hometown, age, and year of entry, whereas by the third year of study the most important factors are academic performance and funding. These results can be used to design better student retention policies.
We estimate the technical efficiency gains of introducing individual quotas (IQs) in fisheries. Our estimates are based on two samples of vessels, considering a potential self-selection bias and controlling for quality changes in landings induced by the IQ system. The results suggest that the introduction of IQs has an important positive impact on fleet efficiency, and that properly measuring this impact requires controlling for the self-selection bias and quality changes induced by the regulatory shift.We are grateful to three anonymous referees of this journal for their helpful comments and suggestions. The usual disclaimer of responsibilities obviously applies. We gratefully acknowledge partial financial support for the revision stage of this paper provided by the Dirección de Investigación, Universidad de Concepción.
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