Nonparametric Measurement of Productivity Growth and Technical Change
Subhash C. Ray
What the paper says
The three main components of productivity change are technical change, change in technical efficiency, and returns to scale effects. Solow measured productivity change at the macroeconomic level as the difference between the growth rates of output and input which, under constant returns to scale and in the absence of any technical inefficiency, is a measure of technical change. The focus in this monograph is on the individual firm and both technical inefficiency and variable returns to scale are accommodated. In neoclassical production economics, productivity change can be measured alternatively from the production, cost, profit, or distance functions. In continuous time analysis, one measures the rates of productivity and technical change. In discrete time, one measures indexes of productivity and technical change over time. This work describes the Tornqvist, Fisher, and Malmquist productivity indexes along with the Luenberger productivity indicator and a Geometric Young index and how they relate to one another. The relevant nonparametric DEA models for measuring the different productivity indexes are formulated for nonparametric analysis of productivity, technical change, and change in efficiency.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.00 × 0.4 = 0.00 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.