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英文文献：Statistical vs. Economic Significance in Economics and Econometrics: Further comments on McCloskey & Ziliak-经济学和计量经济学中的统计与经济意义:关于McCloskey和Ziliak的进一步评论
英文文献作者：Tom Engsted
英文文献摘要：
I comment on the controversy between McCloskey & Ziliak and Hoover & Siegler on statistical versus economic significance, in the March 2008 issue of the Journal of Economic Methodology. I argue that while McCloskey & Ziliak are right in emphasizing ’real error’, i.e. non-sampling error that cannot be eliminated through specification testing, they fail to acknowledge those areas in economics, e.g. rational expectations macroeconomics and asset pricing, where researchers clearly distinguish between statistical and economic significance and where statistical testing plays a relatively minor role in model evaluation. In these areas models are treated as inherently misspecified and, consequently, are evaluated empirically by other methods than statistical tests. I also criticise McCloskey & Ziliak for their strong focus on the size of parameter estimates while neglecting the important question of how to obtain reliable estimates, and I argue that significance tests are useful tools in those cases where a statistical model serves as input in the quantification of an economic model. Finally, I provide a specific example from economics - asset return predictability - where the distinction between statistical and economic significance is well appreciated, but which also shows how statistical tests have contributed to our substantive economic understanding.
在《经济方法论杂志》(Journal of economic Methodology) 2008年3月刊上，我就麦克罗斯基和齐里亚克(McCloskey & Ziliak)与胡佛和西格勒(Hoover & Siegler)在统计意义与经济意义上的争论发表了评论。我认为尽管麦克洛斯基& Ziliak就在强调“真正的错误”,即non-sampling错误,不能消除通过规范测试,他们不承认这些地区在经济,如宏观经济学理性预期和资产定价,研究者明确区分统计和经济意义和统计测试模型评价中起着相对次要的作用。在这些领域，模型被视为固有的不明确，因此，只能通过统计检验以外的其他方法进行经验评估。我也批评麦克洛斯基& Ziliak强烈关注的参数估计的大小而忽略了重要的问题如何获得可靠的估计,和我认为意义测试是有用的工具在这些情况下,一个统计模型作为输入量化的经济模式。最后，我提供了一个经济学中的具体例子——资产回报可预测性——在这个例子中，统计意义和经济意义之间的区别得到了很好的理解，但它也显示了统计检验如何有助于我们对经济的实质性理解。
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