Pseudo Panel Data
Pseudo Panel Data
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伪面板数据
DOI：
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发表时间：
1993
期刊：
影响因子：
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通讯作者：
Marno Verbeek
中科院分区：
文献类型：
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作者：
Marno Verbeek
在前面的章节中，我们非常关注在各种模型中使用面板数据的估计和检验策略。[1]然而，在实际情况中，真实的面板数据集可能并不总是可用的，而重复的横截面是可用的。例如，在联合王国，没有关于消费者支出或劳动力供应的专门小组数据。不过，每年的家庭支出调查都有一个人口随机抽样。最近，几位作者强调了这样一个事实，即面板数据对于许多通常估计的模型的识别并不是必不可少的，并且通常可以从单个横截面或一系列横截面中识别出感兴趣的参数（有或没有一些额外的假设）（例如，参见Heckman和Robb [1985]，Deaton [1985]和Moffitt [1991]）。在本章中，我们将讨论从重复截面中识别和估计面板数据模型。特别是，将注意到固定的个体效应的线性模型和包含滞后内生变量的tomodels。
In the previous chapters much attention was paid to estimation and testing strategies using panel data in a variety of models.1 In practical situations, however, a true panel data set may not always be available, while repeated cross sections are. For example, in the United Kingdom, no panel data are available on consumer expenditures or labour supply. Nevertheless, a random sample of the population is available each year in the Family Expenditure Surveys (F.E.S.). Recently, several authors have stressed the fact that panel data are not indispensible for the identification of many commonly estimated models and that the parameters of interest can often be identified (with or without some additional assumptions) from a single cross section or a series of cross sections (see, for example, Heckman and Robb [1985], Deaton [1985] and Moffitt [1991]). In this chapter we shall discuss the identification and estimation of panel data models from repeated cross sections. In particular, attention will be paid to linear models with fixed individual effects and tomodels containing lagged endogenous variables.