Predictive inference on finite populations segmented in planned and unplanned domains

Arbeitspapier

In this paper, we develop a new model-based method to inference on totals and averages of nite populations segmented in planned domains or strata. Within each stratum, we decompose the total as the sum of its sampled and unsampled parts, making inference on the unsampled part using Bayesian nonparametric methods. Additionally, we extend this method to make inference on totals of unplanned domains simultaneously modelling, within each stratum, the underlying uncertainty about the composition of the population and the totals across unplanned domains. Making inference on population averages is straightforward in both frameworks. To illustrate these methods, we develop a simulation exercise and evaluate the uncertainty surrounding the gender wage gap in Mexico.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: Working Papers ; No. 2014-04

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Bayesian Analysis: General ; Semiparametric and Nonparametric Methods: General ; Classification Discontinued 2008. See C83. ; Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access ; Data Collection and Data Estimation Methodology; Computer Programs: Other Computer Software ; Wage Level and Structure; Wage Differentials
• Thema: survey methods ; robustness ; species-sampling models

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Martínez-Ovando, Juan Carlos ; Olivares-Guzmán, Sergio I. ; Roldán-Rodríguez, Adriana
• Ereignis: Veröffentlichung
• (wer): Banco de México
• (wo): Ciudad de México
• (wann): 2014

Weitere Informationen

• Handle: http://hdl.handle.net/10419/100118
• Letzte Aktualisierung: 10.03.2025, 11:44 MEZ