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Statistical framework for fully register based population counts.

Fabrizio Solari1, Antonella Bernardini1, Nicoletta Cibella1

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This summary is machine-generated.

Administrative data enables a shift from traditional censuses to register-based approaches. This study presents a statistical framework for register-based population size estimation, enhancing data quality through sampling surveys.

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Area of Science:

  • Statistics
  • Demography
  • Data Science

Background:

  • Growing availability of administrative data archives.
  • Transition from traditional censuses to combined or register-based censuses.
  • Need for robust statistical frameworks for new estimation processes.

Purpose of the Study:

  • To design a statistical framework for register-based population estimation.
  • To address statistical challenges in using administrative data for censuses.
  • To formalize population size estimation using administrative data.

Main Methods:

  • Defining a population frame for surveying and estimation.
  • Implementing sampling surveys for quality assessment.
  • Developing a formalization of population size estimation based on administrative data.
  • Applying the framework to the Italian estimation process.

Main Results:

  • A formalized statistical framework for register-based population estimation.
  • Demonstration of the framework's application using Italian data.
  • Identification of key statistical issues in register-based estimation.

Conclusions:

  • Register-based estimation is a viable alternative to traditional censuses.
  • Sampling surveys are crucial for quality assurance in register-based systems.
  • The proposed framework supports accurate population size estimation using administrative data.