Recent work estimating production functions has often used methodologies proposed in two literatures: (1) “proxy variable” estimation techniques (Olley, S. and Pakes, A., 1996, Econometrica, 64, pp. 1263–1295), and (2) “dynamic panel” estimation techniques. I illustrate how timing and information set assumptions are key to both, and how these assumptions can be strengthened (or weakened) almost continuously. I examinehow, in some common production datasets, strengthening or weakening these assumptions affects the precision of estimates—comparing these impacts to those achieved by imposing alternative assumptions sometimes utilized in these literatures. This illustrates efficiency tradeoffs between different possible assumptions, at least in the production function context.

中文翻译：

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时序假设和效率：生产函数背景下的经验证据

最近估计生产函数的工作经常使用两篇文献中提出的方法：（1）“代理变量”估计技术（Olley, S. 和 Pakes, A., 1996, Econometrica , 64, pp. 1263–1295）和（ 2 ）“动态面板”估计技术。我说明了时间和信息集假设如何对两者都至关重要，以及这些假设如何几乎连续地得到加强（或削弱）。我研究了在一些常见的生产数据集中，加强或削弱这些假设如何影响估计的精度——将这些影响与通过强加有时在这些文献中使用的替代假设所实现的影响进行比较。这说明了不同可能假设之间的效率权衡，至少在生产函数背景下。