...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of regulatory economics >Improving the econometric precision of regulatory models
【24h】

Improving the econometric precision of regulatory models

机译：提高监管模型的计量经济精度

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Regulatory regimes often attempt to introduce quasi-competitive pressures by undertaking comparative efficiency assessments between the regulated companies and setting company-specific cost reduction targets based on those comparisons. The UK water industry is one example of such a regime-indeed, it has emphasized the importance of maintaining the number of independent companies in order to preserve the robustness of the modeling. For example, in 2007, the Competition Commission considered whether the merger between Mid Kent Water and South East Water might prejudice the ability of the regulator (Ofwat) to make comparisons across water companies for the purposes of assessing performance and setting price controls. In this paper, we examine this issue and provide specific recommendations to regulators. Our cross-sectional results show that the impact of this merger is not significant. We demonstrate that joint estimation of all the sub-models using the 'seemingly unrelated regression' (SUR) procedure in a cross-section and/or panel data framework can dramatically improve the accuracy of the modeling. Moreover, the merger does not affect the confidence intervals significantly under such approaches, which still remain far superior to those under Ofwat's cross-sectional approach. Based on these results, we recommend that Ofwat and other regulators adopt SUR and/or panel data analysis and thereby reduce their reliance on having sufficient numbers of independent companies.
机译：监管制度通常试图通过在受监管公司之间进行比较效率评估并根据这些比较设定特定于公司的成本削减目标来引入准竞争压力。英国水业就是这种制度的一个例子，它强调了保持独立公司数量的重要性，以保持模型的稳健性。例如，在2007年，竞争委员会考虑了Mid Kent Water和South East Water之间的合并是否可能损害监管机构（Ofwat）为评估绩效和制定价格控制目的而对自来水公司进行比较的能力。在本文中，我们将研究此问题，并向监管机构提供具体建议。我们的横断面结果表明，此次合并的影响并不重大。我们证明了在横截面和/或面板数据框架中使用“看似无关的回归”（SUR）过程对所有子模型进行联合估计可以显着提高建模的准确性。而且，在这种方法下，合并不会显着影响置信区间，但仍远优于Ofwat的横截面方法。根据这些结果，我们建议Ofwat和其他监管机构采用SUR和/或面板数据分析，从而减少其对拥有足够数量的独立公司的依赖。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号