Quantitative Risk Management: Concepts, Techniques, and Tools
Quantitative Risk Management: Concepts, Techniques, and Tools
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DOI：
10.1198/jasa.2006.s156
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发表时间：
2006-12
影响因子：
3.7
通讯作者：
C. Anderson‐Cook
中科院分区：
文献类型：
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作者：
C. Anderson‐Cook
作者广泛使用蒙特卡洛模拟。蒙特卡罗模拟用于帮助学生理解抽样分布的重要概念以及其他概念，例如线性模型的违规和潜在偏差。通过使用作者的 Excel 工作簿，学生几乎可以毫不费力地执行蒙特卡罗模拟。温贝托和巴雷托撰写了一本有价值且独特的计量经济学入门教科书。我最初对 Excel 和蒙特卡罗模拟能否连贯地集成持怀疑态度，但作者执行得很好。这本书有很多优点，包括易读性、有可能吸引一些本来可能不感兴趣的学生，以及学生完成后对抽样分布和线性回归有深入了解的可能性。另一方面，也存在一些消极方面。虽然狭隘的关注点在某些方面是有利的，但它妨碍了某些主题的全面发展。例如，没有提及方差分析方法。因此，任何考虑本文的教师都应检查目录，以确保涵盖所有相关主题（或准备在必要时提供其他来源）。此外，由于本文仅使用 Excel，因此进入就业市场或申请研究生院的学生不能声称掌握了统计知识——一项潜在的市场技能。不管这些批评如何，积极的一面大于消极的一面，教师应该在本科计量经济学课程中考虑这本进步的教科书。
authors use Monte Carlo simulation extensively. Monte Carlo simulations are used to help students understand the important concept of sampling distributions as well as other concepts, such as violations and potential biases to linear models. By using the authors’ Excel workbooks, students are able to perform Monte Carlo simulations almost effortlessly. Humberto and Barreto have written a worthwhile and unique textbook on introductory econometrics. I was initially skeptical that Excel and Monte Carlo simulation could be integrated coherently, but the authors execute it well. This book has many positives, including accessibility, potential to engage some students who otherwise might not be interested, and likelihood of students finishing with a strong understanding of sampling distributions and linear regression. On the other hand, a few negative aspects exist. Whereas a narrow focus is advantageous in some ways, it precludes comprehensive development of some topics. For instance, no mention is made of analysis of variance methods. Consequently, any instructor considering this text should check the table of contents to ensure that all relevant topics are covered (or be prepared to provide other sources where necessary). In addition, because the text uses Excel exclusively, students entering the job market or applying for graduate school cannot claim knowledge of a statistical package—a potentially marketable skill. Regardless of these criticisms, the positives outweigh the negatives, and instructors should consider this progressive textbook for their undergraduate econometrics course.