遵守国际软法:采用软法可预见吗?

Michael D'Rosario, John Zeleznikow
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引用次数: 4

摘要

本文考虑了法律制度起源符合“国际软法”或非约束性文本中包含的规范性规定的重要性。该研究考虑了各国对首个巴塞尔协议实施程度的关键经济和治理指标。本研究采用了70个国家的一组数据,考虑了市场力量的作用以及对执行软法的双边和多边压力。很少有人知道与法律制度结构有关的变量作为减缓多边协定和国际软性法(如1988年协定)执行的因素所起的作用。本研究在现有文献研究的基础上,采用了一种新的估计方法,即多层感知器人工神经网络(MPANN)的神经网络建模技术。与早期的研究一致,本文确定了与民主制度和巴塞尔协议的实施相关的重大积极影响。然而,在传统估算技术的基础上,该研究确定了储蓄率和政府效率在决定执行方面的重要性。值得注意的是,该方法在确定实现时能够达到优越的拟合优度和预测精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Compliance with International Soft Law: Is the Adoption of Soft Law Predictable?
The present article considers the importance of legal system origin in compliance with ‘international soft law,' or normative provisions contained in non-binding texts. The study considers key economic and governance metrics on national acceptance an implementation of the first Basle accord. Employing a data set of 70 countries, the present study considers the role of market forces and bilateral and multi-lateral pressures on implementation of soft law. There is little known about the role of legal system structure-related variables as factors moderating the implementation of multi-lateral agreements and international soft law, such as the 1988 accord. The present study extends upon research within the extant literature by employing a novel estimation method, a neural network modelling technique, with multi-layer perceptron artificial neural network (MPANN). Consistent with earlier studies, the article identifies a significant and positive effect associated with democratic systems and the implementation of the Basle accord. However, extending upon traditional estimation techniques, the study identifies the significance of savings rates and government effectiveness in determining implementation. Notably, the method is able to achieve a superior goodness of fit and predictive accuracy in determining implementation.
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