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Estimation of Variances using the Generalized Variance Function: Labor and Population Indicators in the Colombian Household Survey 2022
Estimación de varianzas utilizando la función generalizada de varianza: indicadores laborales y de población en la encuesta de hogares de Colombia 2022
DOI:
https://doi.org/10.15446/rce.v48n2.117060Keywords:
Generalized variance function, Complex surveys, Variance estimation, Sampling error household survey (en)Función generalizada de varianza, Encuestas complejas, Estimación de la varianza, Error de muestreo, Encuesta de hogares. (es)
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This study addresses the challenge of estimating variances in household surveys, particularly when sampling design variables are absent in publicly available microdata. By implementing the Generalized Variance Function (GVF), Colombia's Household Survey for 2022 serves as a case study. GVF models were developed and validated using the standard errors published by the National Administrative Department of Statistics (DANE) of Colombia. These models demonstrated high accuracy and robustness for estimates across various levels of disaggregation and periodicities. Additionally, their validation with 2023 data confirmed their predictive capacity and applicability in similar contexts, underscoring their effectiveness as tools for evaluating the quality of estimates in complex surveys.
Este estudio aborda el desafío de estimar la varianza en encuestas de hogares, causado por la ausencia de variables del diseño muestral en los microdatos públicos. A través de la implementación de la Función Generalizada de Varianza (FGV), se utiliza como caso de estudio la Encuesta de Hogares de Colombia para 2022. Los modelos de FGV se desarrollaron y validaron con base en los errores estándar publicados por el Departamento Administrativo Nacional de Estadística (DANE) de Colombia. Estos modelos demostraron alta precisión y robustez en estimaciones a diferentes niveles de desagregación y periodicidades. Asimismo, su validación con datos de 2023 confirmó su capacidad predictiva y aplicabilidad en contextos similares, destacando su eficacia como herramienta para evaluar la calidad de las estimaciones en encuestas complejas.
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