法院的低效率:行业结构、能力和分配不当

IF 2.3 4区 经济学 Q3 BUSINESS Journal of Productivity Analysis Pub Date : 2024-07-25 DOI:10.1007/s11123-024-00731-5
Antonio Peyrache, Angelo Zago
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引用次数: 0

摘要

在本文中,我们引入了一个优化模型,用于量化法院案件量的资源能力利用率和处置时间之间的权衡。该优化模型考虑了在缩短处理时间时可能出现的需求增加的影响。我们利用该模型来衡量各种政策改革方案在法院和系统层面对审判时间的影响。为此,我们使用 2005-2012 年期间意大利法院的人口数量,将潜在的资源重新分配考虑在内。结果表明,如果我们讨论的所有政策方案都得以实施,民事案件的平均审理时间将缩短一半以上,从目前的 15.5 个月缩短至约 7 个月。实施最佳做法,最有效的一项政策相当于增加 25% 的法官人数(否则每年将花费约 1 亿欧元)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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The inefficiency of courts of justice: industry structure, capacity and misallocation

In this paper, we introduce an optimization model to quantify the trade-off between resource capacity utilization and disposition time for the caseload of courts of justice. The optimization model takes into account the impact of an increase in demand that may arise when disposition time is reduced. We employ the model to measure the impact of various policy reform scenarios on the length of trials, both at the court and system level. We do so by taking into account the potential reallocation of resources, using the population of Italian courts of justice over the 2005–2012 period. Our results show that if all policy scenarios we discuss were to be implemented, the average length of trials for civil cases would be more than halved, from the current 15.5 months to about 7 months. Implementing best practices, the single most effective policy would be equivalent to a 25% increase in the number of judges (which would otherwise cost around 100 million euros per year).

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来源期刊
CiteScore
3.10
自引率
6.20%
发文量
30
期刊介绍: The Journal of Productivity Analysis publishes theoretical and applied research that addresses issues involving the measurement, explanation, and improvement of productivity. The broad scope of the journal encompasses productivity-related developments spanning the disciplines of economics, the management sciences, operations research, and business and public administration. Topics covered in the journal include, but are not limited to, productivity theory, organizational design, index number theory, and related foundations of productivity analysis. The journal also publishes research on computational methods that are employed in productivity analysis, including econometric and mathematical programming techniques, and empirical research based on data at all levels of aggregation, ranging from aggregate macroeconomic data to disaggregate microeconomic data. The empirical research illustrates the application of theory and techniques to the measurement of productivity, and develops implications for the design of managerial strategies and public policy to enhance productivity. Officially cited as: J Prod Anal
期刊最新文献
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