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Copula-Based Synthetic Data Generation in Firm-Size Variables

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Abstract

Using the survival Clayton copula, we propose a method for generating synthetic data on such firm-size variables as operating revenues and the number of employees. Synthetic data must satisfy two stylized facts on firm-size statistics. First, firm-size distributions have power-law tails. Second, there should be a Gibrat’s law for the ratio of two different firm-size variables. With the survival Clayton copula, we introduce random variables whose marginal distributions are uniform on the interval from 0 to 1, and transform them to obey power-law distributions. The resulting variables satisfy the two stylized facts.

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Acknowledgements

We express deep gratitude to Dr. Ietomi, Dr. Ohnishi, Dr. Tanaka and Dr. Watanabe, all of whom inspired us to start this research.

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Authors and Affiliations

  1. Department of Economic Informatics, Kanazawa Gakuin University, Kanazawa, 920-1392, Japan

    Shouji Fujimoto & Atushi Ishikawa

  2. National Institute of Informatics, Tokyo, 101-8430, Japan

    Takayuki Mizuno

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  1. Shouji Fujimoto
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  2. Atushi Ishikawa
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  3. Takayuki Mizuno
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Correspondence to Shouji Fujimoto.

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Fujimoto, S., Ishikawa, A. & Mizuno, T. Copula-Based Synthetic Data Generation in Firm-Size Variables. Rev Socionetwork Strat 16, 479–492 (2022). https://doi.org/10.1007/s12626-022-00128-6

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