We investigate the use of the inclusive value based approach for estimating dynamic discrete choice models of demand with aggregate data. The inclusive value sufficiency (IVS) approach approximates a multi-dimensional state space with a single “sufficient statistic” in order to mitigate the curse of dimensionality and tractability estimate model primitives. Although in widespread use, the conditions under which IVS is appropriate have not been examined. Theoretically, we show that the estimator is biased and inconsistent. We then use Monte Carlo simulations (of a simple model of dynamic durable goods adoption) to demonstrate the degree of bias associated with the inclusive value approximation estimator under an array of parameterizations and data generating processes. In our examination, we show that the estimator performs better when the discount factor is smaller and/or when the price sensitivity of the consumer is larger. Examining how the bias impacts economic quantities of interest, we find that the IVS method under estimates the true long-run own-price elasticities and over estimates the change in profits as prices change. Theses findings highlight the importance of correctly specifying how consumers form expectations. As a result, researchers should consider how to empirically support their assumption for the underlying consumer belief structure.

中文翻译：

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用汇总数据估计动态离散选择模型：包含值近似的属性

我们调查使用基于包容性的方法来估计具有汇总数据的需求动态离散选择模型。包容性值充足性（IVS）方法使用单个“足够的统计量”近似多维状态空间，以减轻维数和易处理性估计模型基元的诅咒。尽管广泛使用，但尚未检查适合使用IVS的条件。从理论上讲，我们证明了估计量是有偏的和不一致的。然后，我们使用蒙特卡洛模拟（采用动态耐用品的简单模型）来说明在一系列参数化和数据生成过程下，与包容性值近似估计量相关的偏差程度。在我们的考试中 我们表明，当折扣系数较小和/或消费者的价格敏感性较大时，估计器的效果会更好。通过考察偏差如何影响利息经济量，我们发现IVS方法估计的是真正的长期自身价格弹性，而高估了价格变化带来的利润变化。这些发现强调了正确指定消费者如何形成期望的重要性。因此，研究人员应考虑如何从经验上支持其对潜在消费者信仰结构的假设。我们发现，IVS方法在估计真实的长期自身价格弹性的同时，过高地估计了价格变化带来的利润变化。这些发现强调了正确指定消费者如何形成期望的重要性。因此，研究人员应考虑如何从经验上支持其对潜在消费者信仰结构的假设。我们发现，IVS方法在估计真实的长期自身价格弹性的同时，过高地估计了价格变化带来的利润变化。这些发现强调了正确指定消费者如何形成期望的重要性。因此，研究人员应考虑如何从经验上支持其对潜在消费者信仰结构的假设。