BINARY OUTCOMES AND ENDOGENOUS EXPLANATORY VARIABLES - TESTS AND SOLUTIONS WITH AN APPLICATION TO THE DEMAND FOR CONTRACEPTIVE USE IN TUNISIA
BINARY OUTCOMES AND ENDOGENOUS EXPLANATORY VARIABLES - TESTS AND SOLUTIONS WITH AN APPLICATION TO THE DEMAND FOR CONTRACEPTIVE USE IN TUNISIA
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DOI：
10.2307/2061900
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发表时间：
1995-02-01
期刊：
影响因子：
3.5
通讯作者：
MROZ, TA
中科院分区：
文献类型：
--
作者：
BOLLEN, KA;GUILKEY, DK;MROZ, TA
许多人口统计学研究考察离散结果，研究人员经常怀疑，一些解释变量可能受到决定所考察的离散结果的相同未观察到的因素的影响。在线性模型中，这种潜在内生性偏差的标准解是一个估计量，如两阶段最小二乘。这些方法已扩展到具有有限因变量的模型，但关于这些方法在人口研究中通常使用的数据集类型中的性能的资料很少。本文有助于填补这一空白。它描述了一个简单的分析框架，用于估计解释变量对离散结果的影响，它控制了解释变量的潜在内生性。它还讨论了检验的外生性和联合确定的结果和解释变量。它总结了对这些技术性能的蒙特卡罗研究的结果，并使用这些结果来建议研究人员在实践中应该如何处理这些问题。我们根据1988年突尼斯人口与健康调查的数据，将这些方法应用于检查生育意愿对避孕药具使用的影响。
Many demographic studies examine discrete outcomes, and researchers often suspect that some of the explanatory variables may be influenced by the same unobserved factors that determine the discrete outcome under examination. In linear models, the standard solution to this potential endogeneity bias is an estimator such as two-stage least squares. These methods have been extended to models with limited dependent variables, but there is little information on the performance of the methods in the types of data sets typically used in demographic research. This paper helps to fill this gap. It describes a simple analytic framework for estimating the effects of explanatory variables on discrete outcomes, which controls for the potential endogeneity of explanatory variables. It also discusses tests for exogeneity and joint determination of the outcomes and the explanatory variables. It summarizes the results of a Monte Carlo study of the performance of these techniques and uses these results to suggest how researchers should approach these problems in practice. We apply these methods to the examination of the impact of fertility intentions on contraceptive use, based on data from the 1988 Tunisia Demographic and Health Survey.