| Summary/Abstract |
This study proposes an improved method for measuring green productivity growth in order to overcome the “discriminating power problem” and “technical regress” associated with the conventional data envelopment analysis (DEA) models. The rationale is to combine the concepts of super-efficiency and sequential DEA models to subsequently construct an improved production possibility set for the directional distance function (DDF). With this enhancement, the Malmquist–Luenberger productivity index (MLPI), which can be compared across sections and periods, is proposed. Therefore, the correct technical and efficiency change components can be obtained after decomposing the MLPI. This novel MLPI is employed to measure the green productivity growth of 36 Chinese industrial subsectors during the period 1998–2011, under the constraint of energy consumption and CO2 emissions. A comparison of the measures of the current study with the productivity growth indexes that have been previously used yielded the following results: (i) productivity growth rate is overestimated without considering CO2 emissions; (ii) the rates of technical and efficiency changes are under- and over-estimated respectively, and (iii) the rate of green productivity growth is also underestimated by the previous indexes. The main conclusions and its policy implications for China's green productivity growth through technology progress and structural adjustment are discussed in-depth.
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