Timing Assumptions and Efficiency: Empirical Evidence in a Production Function Context
探讨了生产函数估计中时序和信息集假设如何影响估计精度，通过对比不同假设下的效率权衡，帮助研究者理解假设选择对结果的影响。
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.