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Development a measurement method of dynamic TFP using DEA and index number appoach

开发使用 DEA 和指数方法的动态 TFP 测量方法

基本信息

批准号：
14530030
负责人：
NEMOTO Jiro
金额：
$ 1.09万
依托单位：
Nagoya University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2002
资助国家：
日本
起止时间：
2002 至 2003
项目状态：
已结题

项目摘要

The purpose of this research is to extend the traditional method of measuring total factor productivity in two ways. Firstly, removing an assumption of fully efficient production, I develop a new method of productivity which enables us to evaluate the impacts of technical efficiency on productivity. For this purpose, a decomposition analysis of the Hicks-Moorsteen productivity index is proposed to factorize productivity change in technical change, efficiency change, scale change and the mix effects of inputs and outputs. A computational difficulty in measuring the Hicks-Moorsteen productivity index is to require both of input and output distance functions. I provide a consistent procedure for obtaining parameters of both functions. Also, a new convenient measure of the returns to scale is presented. The whole analysis is applied to productivity growth in 17 OECD countries, which proves its empirical usefulness. Secondly, the data envelopment analysis is extended to measure dynamic productivity and dynamic efficiency by introducing quasi-fixed inputs that incurs adjustment costs. Since this formulation is closely related to the standard theory of investment, it serves a basis for estimating the Euler equations and the marginal Tobin's q. This dynamic data envelopment analysis is applied to real data pertaining to Japanese electricity transmission and distribution. The results reveal that allocative inefficiencies frequently detected by traditional methods in transmission and distribution electric utilities are almost, due to lack of dynamic efficiency.

本研究的目的是从两个方面扩展传统的全要素生产率测算方法。首先，去掉完全有效生产的假设，我开发了一种新的生产率方法，使我们能够评估技术效率对生产率的影响。为此，提出了希克斯-穆尔斯汀生产率指数的分解分析，将生产率变化分解为技术变化、效率变化、规模变化和投入产出的混合效应。衡量希克斯-穆尔斯汀生产率指数的一个计算困难是既需要输入距离函数，也需要输出距离函数。我为获取这两个函数的参数提供了一致的过程。此外，还提出了一种新的衡量规模收益的简便方法。整个分析被应用于17个OECD国家的生产率增长，这证明了其经验有效性。其次，通过引入产生调整成本的准固定投入，将数据包络分析扩展到动态生产率和动态效率的度量。由于这一公式与投资的标准理论密切相关，因此它是估计欧拉方程和边际托宾Q的基础。这种动态数据包络分析被应用于与日本输配电有关的真实数据。结果表明，在输配电网中，由于缺乏动态效率，传统方法经常检测到的配置低效现象几乎都是存在的。