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VERSION:2.0
PRODID:-//AMSE//Event Calendar//FR
CALSCALE:GREGORIAN
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UID:event-8910@www.amse-aixmarseille.fr
DTSTAMP:20260430T013413Z
CREATED:20260430T013413Z
LAST-MODIFIED:20260430T013413Z
STATUS:CONFIRMED
SEQUENCE:0
SUMMARY:big data and econometrics seminar - Anne Ruiz-Gazen
DTSTART:20220426T120000Z
DTEND:20220426T133000Z
DESCRIPTION:Combining survey sample data and big data is an important curre
 nt challenge in finite population inference. While survey sample data are o
 btained through a probability sampling design\, big data consist usually of
  non-probability samples. Many well-known unbiased or approximately unbiase
 d estimation methods exist for estimating finite population parameters from
  a probability sample. Inference from a non-probability sample is\, however
 \, often subject to selection bias. Recently\, a data integration approach 
 has been proposed by Kim and Tam (2021) and incorporates a probability samp
 le to handle the selection bias of non-probability samples. In the first pa
 rt of the presentation\, we propose to revisit their approach and study in 
 detail the gain in terms of efficiency of some estimators when combining pr
 obability and non-probability samples. In the second part of the presentati
 on\, we focus on the case where the target variable is not observable in th
 e big data source\, while the auxiliary information\, present in this sourc
 e\, is not measured in the probability sample. In such a situation\, new es
 timators can be defined by following a prediction approach. These estimator
 s are either design-based\, model-based\, or cosmetic. Their properties in 
 terms of bias and efficiency are studied using theoretical and simulation r
 esults. The interest of the new estimators is illustrated in the context of
  the French postal service\, where the objective is to estimate the monthly
  postal traffic by combining a survey of the mailmen rounds with the databa
 se containing the automatically processed postal mail.\\n\\nContact: Michel
  Lubrano : michel.lubrano[at]univ-amu.frPierre Michel : pierre.michel[at]u
 niv-amu.fr\n\nPlus d'informations: https://www.amse-aixmarseille.fr/fr/even
 ements/anne-ruiz-gazen
LOCATION:Îlot Bernard du Bois - Salle 21\, AMU - AMSE\, 5-9 boulevard Maur
 ice Bourdet\, 13001 Marseille
URL;VALUE=URI:https://www.amse-aixmarseille.fr/fr/evenements/anne-ruiz-gazen
CONTACT:Michel Lubrano : michel.lubrano[at]univ-amu.frPierre Michel :&nbsp\
 ;pierre.michel[at]univ-amu.fr
TRANSP:OPAQUE
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