THE STEADY-STATE ASSUMPTION AND THE ESTIMATION OF DISTRIBUTIONAL AND RELATED MODELS*

THE STEADY-STATE ASSUMPTION AND THE ESTIMATION OF DISTRIBUTIONAL AND RELATED MODELS*
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稳态假设和分布及相关模型的估计*

DOI：
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发表时间：
1984
期刊：
影响因子：
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通讯作者：
S. Jenkins
S. Jenkins
中科院分区：
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文献类型：
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作者：
A. Atkinson;S. Jenkins

文献摘要

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相似文献

人们对收入分配、社会经济成就和相关变量的世代演变的线性结构方程模型(包括路径分析)的估计相当感兴趣。在数据不足的情况下，模型的估计通常是通过做出减少数据需求的假设来进行的。具体地说，(通常是含蓄地)假定所研究的变量的分布处于稳定状态。在这篇文章中，我们检验了这一假设的作用，并论证了在其使用中需要谨慎。
There is considerable interest in the estimation of linear structural equation models (including path analysis) of the evolution across generations of the distribution of income, of socioeconomic achievement, and of related variables. Given insufficient data, the estimation of the models has commonly proceeded by making assumptions which reduce the data requirements. In particular, it has been assumed (often implicitly) that the distribution of the variables being studied is in steady-state. In this paper we examine the role of this assumption and argue the need for care in its use.