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

2003 Fiscal Year Final Research Report Summary

• Project/Area Number: 14530030
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Single-year Grants
• Section: 一般
• Research Field: Economic statistics
• Research Institution: Nagoya University
• Principal Investigator: NEMOTO Jiro Nagoya University, Graduate School of Economics, Associate professor, 大学院・経済学研究科, 助教授 (20180705)
• Project Period (FY): 2002 – 2003
• Keywords: total factor productivity / productivity analysis / efficiency analysis / dynamic productivity / dynamic efficiency

Research Abstract

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.