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首页> 外文期刊>Communications in Statistics. B, Simulation and Computation >Em Algorithm Estimation Of Simultaneousequation Model With Limited Variables: an Example Of Cigarette Consumption
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Em Algorithm Estimation Of Simultaneousequation Model With Limited Variables: an Example Of Cigarette Consumption

机译:有限变量同时方程模型的Em算法估计:以卷烟消费为例

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The two-part model and Heckman's sample selection model are often used in economic studies which involve analyzing the demand for limited variables. This study proposed a simultaneous equation model (SEM) and used the expectation-maximization algorithm to obtain the maximum likelihood estimate. We then constructed a simulation to compare the performance of estimates of price elasticity using SEM with those estimates from the two-part model and the sample selection model. The simulation shows that the estimates of price elasticity by SEM are more precise than those by the sample selection model and the two-part model when the model includes limited independent variables. Finally, we analyzed a real example of cigarette consumption as an application. We found an increase in cigarette price associated with a decrease in both the propensity to consume cigarettes and the amount actually consumed.
机译:分为两部分的模型和Heckman的样本选择模型经常用于经济研究中,涉及分析对有限变量的需求。这项研究提出了一个联立方程模型(SEM),并使用期望最大化算法来获得最大似然估计。然后,我们构建了一个仿真,以比较使用SEM进行的价格弹性估算与两部分模型和样本选择模型估算的性能。仿真表明,当模型包含有限的独立变量时,通过SEM进行的价格弹性估计要比样本选择模型和两部分模型更为精确。最后,我们分析了一个实际的香烟消费实例作为应用。我们发现,卷烟价格的上涨与卷烟消费倾向和实际消费量的下降有关。

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