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Copula-Based Synthetic Data Generation in Firm-Size Variables

Shouji Fujimoto (), Atushi Ishikawa and Takayuki Mizuno
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Shouji Fujimoto: Kanazawa Gakuin University
Atushi Ishikawa: Kanazawa Gakuin University
Takayuki Mizuno: National Institute of Informatics

The Review of Socionetwork Strategies, 2022, vol. 16, issue 2, 479-492

Abstract: 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.

Keywords: Copula; Synthetic data; Firm size; Power law; Gibrat’s law; 62H10; 91B38; 91B64; 91B82 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s12626-022-00128-6

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