Statistical Journal of the IAOS

Aims & Scope

This is the flagship journal of the International Association for Official Statistics and is expected to be widely circulated and subscribed to by individuals and institutions in all parts of the world.

The main aim of the Journal is to support the IAOS mission by publishing articles to promote the understanding and advancement of official statistics and to foster the development of effective and efficient official statistical services on a global basis.

Papers are expected to be of wide interest to readers.

Such papers may or may not contain strictly original material.

All papers are refereed.

The journal should encourage papers with a focus on the basic principles for official statistics covering areas such as the importance of applying the best scientific methods, the need for statistical independence, balancing the needs of users with the burden on respondents, the continuing challenges around confidentiality, and the growing need for consistency and coherence across statistical domains and over time and for international comparability.

As a guide, articles relating, but not exclusively, to the following broad topics will be of interest to the journal: Developments and challenges for both global and national statistical systems Statistical independence and legislation New directions for official statistics Delivering relevant and effective statistical services New and innovative ways of increasing uses and users of official statistics Quality of official statistics Engagement of producers Innovative use of ICT for official statistics Creative use of both new and existing statistical sources Organisation of statistical services Statistical infrastructure and tools Management of statistical and related meta data Innovative statistical products and services Training of statistical staff, users and producers Improving statistical literacy in the community.

View Aims & Scope

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Metrics & Ranking

SJR (SCImago Journal Rank)

Year	Value
2024	0.251

Quartile

Year	Value
2024	Q3

h-index

Year	Value
2024	24

Journal Rank

Year	Value
2024	18569

Journal Citation Indicator

Year	Value
2024	185

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Business, Management and Accounting, Decision Sciences and Economics, Econometrics and Finance, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Back to the basics: Identifying and addressing underlying challenges in achieving high quality and relevant health statistics for Indigenous populations in Canada

  Citation: 92

  Authors: Janet, Michelle

• Integrating refugees in the United States: The successes and challenges of resettlement in a Global Context

  Citation: 47

  Authors: Randy, Kathleen, Susan, Susannah, Greg, Michael, Margie

• An empirical examination of the relationship between nonresponse rate and nonresponse bias

  Citation: 45

  Authors: Graham

• The System of social statistical datasets of Statistics Netherlands: An integral approach to the production of register-based social statistics

  Citation: 44

  Authors: Bart F.M., Johan, Leo

• The opportunities, challenges and risks of big data for official statistics

  Citation: 42

  Authors: Rob

• The identification of the Indigenous population in Brazil’s official statistics, with an emphasis on demographic censuses

  Citation: 40

  Authors: Ricardo Ventura, Bruno Nogueira, Alessandra Traldi, Leandro Okamoto, Marta, Fernando, Rosa Sebastiana, Marta Maria

• Recognition and indigenizing official statistics: Reflections from Aotearoa New Zealand and Australia

  Citation: 35

  Authors: Tahu, Maggie

• Providing bespoke synthetic data for the UK Longitudinal Studies and other sensitive data with the synthpop package for R1

  Citation: 34

  Authors: Beata, Gillian M., Chris

• Web scraping techniques to collect data on consumer electronics and airfares for Italian HICP compilation

  Citation: 34

  Authors: Federico, Riccardo, Rosanna Lo, Stefano, Francesca

• Don't get duped: Fraud through duplication in public opinion surveys

  Citation: 33

  Authors: Noble, Michael

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