Título : | Interpretación del indice de pobrezade Amartya Sen | Tipo de documento: | texto impreso | Autores: | Narváez Tulcán, Luis Carlos., Autor | Editorial: | Bogotá: Universidad la Gran Colombia | Fecha de publicación: | 2008. | Número de páginas: | 79 p. | ISBN/ISSN/DL: | 958-9441-82-40 | Idioma : | Español (spa) | Materias: | Ciencias Sociales
| Palabras clave: | Pobreza - Mediciones Metodología. | Clasificación: | 362.5 / N178i | Nota de contenido: | Conceptualización y descripción teórica del índice de Amartya Kumar Sen , Cración del índice de pobreza , Interpretación del indicador de pobreza de Amartya Sen "Ps" , Formulación del indice de sen "Ps" , Derivación axiomática del indice de Sen. |
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) 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