license:mit size_categories:10K<n<100K format:csv modality:tabular library:datasets library:pandas library:mlcroissant library:polars doi:10.57967/hf/3701 region:us
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license: mit
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**Synthesized Economic Agents Dataset**

The authors would like to extend their gratitude to the University of National and World Economy and the project NID NI 23/2023/V for funding this research, and for the prime administrative assistance in general.

In the era of big data, there is a notable scarcity of datasets containing inherently sensitive information. Such datasets include those falling under regulations like GDPR, the Banking Secrecy Act, European data protection legislation, and others. The current research explores the possibility of filling this gap by generating a multidimensional dataset integrating personal characteristics, demographic features, personal preferences, and more, applicable for conducting research in banking, financial markets, and other economic and financial domains. The nature of the data, its complexity, and legal frameworks necessitate alternative approaches to acquire, simulate, and synthesize the required quantity and quality of information.

The aim is to accumulate a wide range of diverse personal characteristics to help build a comprehensive profile of a statistically significant number of individuals. Financially active individuals and their behavior in the financial-economic context are identified. The dataset thus compiled could be applied in a broad range of economic and social studies.

