Upward and downward bias when measuring inequality of opportunity
Upward and downward bias when measuring inequality of opportunity
复制标题
衡量机会不平等时的向上和向下偏差
DOI：
10.2139/ssrn.2839232
复制
发表时间：
2016
影响因子：
0.9
通讯作者：
L. Serlenga
中科院分区：
文献类型：
--
作者：
P. Brunori;Vito Peragine;L. Serlenga
由于对影响个人结果的环境的部分可观察性造成的向下偏差，传统上提出了对机会不平等水平的估计作为下限。我们表明，由于抽样方差，这种估计也可能受到向上偏差的影响。后一种失真的程度取决于所使用的经验策略和观察到的样本。我们认为，尽管在经验贡献中被忽视，但向上的偏差可能是显著的，并且挑战了机会估计不平等作为下界的解释。我们提出了一个简单的标准来选择平衡两个偏差来源的最佳规范。我们的方法基于交叉验证，可以很容易地用调查数据实现。为了证明这种方法可以提高机会不平等测量的可靠性，我们提供了一个基于31个欧洲国家收入数据的实证说明。我们的证据表明，机会不平等的估计对模型选择很敏感。不同的规范导致机会不平等的绝对水平存在显著差异，并导致一些国家的重新排名，这证实了在衡量机会不平等时，需要一个客观标准来选择最佳的计量经济模型。
Estimates of the level of inequality of opportunity have traditionally been proposed as lower bounds due to the downward bias resulting from the partial observability of circumstances that affect individual outcome. We show that such estimates may also suffer from upward bias as a consequence of sampling variance. The magnitude of the latter distortion depends on both the empirical strategy used and the observed sample. We suggest that, although neglected in empirical contributions, the upward bias may be significant and challenge the interpretation of inequality of opportunity estimates as lower bounds. We propose a simple criterion to select the best specification that balances the two sources of bias. Our method is based on cross-validation and can easily be implemented with survey data. To show how this method can improve the reliability of inequality of opportunity measurement, we provide an empirical illustration based on income data from 31 European countries. Our evidence shows that estimates of inequality of opportunity are sensitive to model selection. Alternative specifications lead to significant differences in the absolute level of inequality of opportunity and to the re-ranking of a number of countries, which confirms the need for an objective criterion to select the best econometric model when measuring inequality of opportunity.
机会不平等的上限：德国和美国的理论和证据
影响因子：
0.9
作者：
NiehuesJ;Peichl
通讯作者：
Peichl