Attrition, Selection Bias and Censored Regressions
Attrition, Selection Bias and Censored Regressions
复制标题
自然损耗、选择偏差和审查回归
DOI：
10.1007/978-3-540-75892-1_12
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发表时间：
2008
期刊：
影响因子：
--
通讯作者：
Marno Verbeek
中科院分区：
文献类型：
--
作者：
Bo E. Honoré;F. Vella;Marno Verbeek
在微观计量经济学的应用中，经常会出现与磨损、审查和非随机样本选择有关的问题。例如，在实证工作中，很常见的情况是，部分观察到感兴趣的变量，或者只有在满足某些其他数据要求时才观察到。这些形式的审查和选择性经常导致估计中的问题，如果忽视它们可能会导致不可靠的推断。例如，考虑一下可能出现的问题，如果一个人有兴趣根据面板数据集的检查从劳动力供应方程估计参数，并且他的目标是为整个人口而不仅仅是工人样本做出推断。出现的第一个困难是，通常只有工作的个人才会遵守工作时间。以这种方式，工时计量通常被审查为零，这给估计带来了困难，因为直接的最小二乘法，无论是对整个样本还是只对工人的子样本，都不是普遍适用的。其次，许多与利益相关的解释变量，如工资，也受到审查，因为它们只针对工人。此外，在这些情况下，这些变量中的许多也可能是劳动力供应的内生变量，这也可能造成估计的复杂性。尽管小组数据经常被视为克服与内生性有关的问题的一种方式，因为在同一单位上有重复观察可以利用各种数据转换来消除内生性的原因，但在许多情况下，使用小组数据会使问题复杂化。例如,
In micro-econometric applications issues related to attrition, censoring and nonrandom sample selection frequently arise. For example, it is quite common in empirical work that the variables of interest are partially observed or only observed when some other data requirement is satisfied. These forms of censoring and selectivity frequently cause problems in estimation and can lead to unreliable inference if they are ignored. Consider, for example, the problems which may arise if one is interested in estimating the parameters from a labor supply equation based on the examination of a panel data set and where one’s objective is to make inferences for the whole population rather than only the sample of workers. The first difficulty that arises is that hours are generally only observed for individuals that work. In this way the hours measure is generally censored at zero and this causes difficulties for estimation as straightforward least squares methods, either over the entire sample or only the subsample of workers, are not generally applicable. Second, many of the explanatory variables of interest, such as wages, are also censored in that they are only observed for workers. Moreover, in these instances many of these variables may also be endogenous to labor supply and this may also create complications in estimation. While panel data are frequently seen as a way to overcome issues related to endogeneity as the availability of repeated observations on the same unit can allow the use of various data transformations to eliminate the cause of the endogeneity, in many instances the use of panel data can complicate matters. For example,
影响因子：
6.1
作者：
ROBINSON, PM
通讯作者：
ROBINSON, PM