30 Years of Synthetic Data
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Abstract (arXiv)
The idea to generate synthetic data as a tool for broadening access to sensitive microdata has been proposed for the first time three decades ago. While first applications of the idea emerged around the turn of the century, the approach really gained momentum over the last ten years, stimulated at least in parts by some recent developments in computer science. We consider the upcoming 30th jubilee of Rubin's seminal paper on synthetic data (Rubin, 1993) as an opportunity to look back at the historical developments, but also to offer a review of the diverse approaches and methodological underpinnings proposed over the years. We will also discuss the various strategies that have been suggested to measure the utility and remaining risk of disclosure of the generated data.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Apr 2023.
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Citing papers per year: 2023: 2; 2024: 0; 2025: 4; 2026: 1.
7 papers.
- 2025LLM Generated Persona is a Promise with a Catchcited by 77
- 2025A Consensus Privacy Metrics Framework for Synthetic Datacited by 8
- 2023The Real Deal Behind the Artificial Appeal: Inferential Utility of Tabular Synthetic Datacited by 5
- 2025Emulating Public Opinion: A Proof-of-Concept of AI-Generated Synthetic Survey Responses for the Chilean Casecited by 1
- 2026Harnessing Synthetic Data from Generative AI for Statistical Inferencecited by 1
- 2023Statistical properties and privacy guarantees of an original distance-based fully synthetic data generation methodcited by 0
- 2025Synthetic data for ratemaking: imputation-based methods vs adversarial networks and autoencoderscited by 0
- 2026Harnessing Synthetic Data from Generative AI for Statistical Inference5 Mar 2026
- 2025Emulating Public Opinion: A Proof-of-Concept of AI-Generated Synthetic Survey Responses for the Chilean Case11 Sep 2025
- 2025Synthetic data for ratemaking: imputation-based methods vs adversarial networks and autoencoders2 Sep 2025
- 2025LLM Generated Persona is a Promise with a Catch18 Mar 2025
- 2025A Consensus Privacy Metrics Framework for Synthetic Data6 Mar 2025
- 2023The Real Deal Behind the Artificial Appeal: Inferential Utility of Tabular Synthetic Data13 Dec 2023
- 2023Statistical properties and privacy guarantees of an original distance-based fully synthetic data generation method10 Oct 2023