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摘要翻译：
动态离散选择模型(DDCMs)在结构估计文献中占有重要地位。由于结构误差在本质上是连续的和无界的，研究者们经常使用期望值函数。对期望值函数的求解思想，使求解更加实际，估计更加可行。然而，正如我们在本文中所表明的，期望值函数与一个替代方案：集成（事前）值函数相比是不切实际的。我们简要地描述了前者的无效性，并在状态空间的基数和决策数不同的实际问题上给出了基准。虽然这两种方法在理论上解决了相同的问题，但基准支持了集成价值函数在实践中更可取的主张。
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英文标题：
《Solving Dynamic Discrete Choice Models: Integrated or Expected Value
Function?》
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作者：
Patrick Kofod Mogensen
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最新提交年份：
2018
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分类信息：
一级分类：Economics 经济学
二级分类：Econometrics 计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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英文摘要：
Dynamic Discrete Choice Models (DDCMs) are important in the structural estimation literature. Since the structural errors are practically always continuous and unbounded in nature, researchers often use the expected value function. The idea to solve for the expected value function made solution more practical and estimation feasible. However, as we show in this paper, the expected value function is impractical compared to an alternative: the integrated (ex ante) value function. We provide brief descriptions of the inefficacy of the former, and benchmarks on actual problems with varying cardinality of the state space and number of decisions. Though the two approaches solve the same problem in theory, the benchmarks support the claim that the integrated value function is preferred in practice.
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PDF链接：
https://arxiv.org/pdf/1801.03978
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