A global Malmquist productivity index

Pastor, Jesús T.; Lovell, C. A. Knox

doi:10.1016/j.econlet.2005.02.013

Cited by 590 publications

(320 citation statements)

References 6 publications

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“…As shown in Figure 1, the P G envelopes all contemporaneous benchmark technologies by establishing a single reference PPS. Pastor and Lovell [45] first proposed the GMPI, and traditional TFP growth can be measured by computing the change of GMPI. Moreover, GMPI can be decomposed into technical efficiency change (GMECH) and technical progress change (GMTCH): Due to the GMPI not incorporating the undesirable outputs, it is necessary to define a global DDF based on the global benchmark technology:…”

Section: Ddf and Gml Productivity Indexmentioning

confidence: 99%

Green Total Factor Productivity Growth and Its Determinants in China’s Industrial Economy

et al. 2018

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This paper employs directional distance function (DDF) and the global Malmquist-Luenberger (GML) productivity index to measure the green total factor productivity (GTFP) growth of China's 36 industrial sectors from 2000 to 2014. Based on this, this paper ascertains the determinants of GTFP from the perspectives of institution, technology, and structure, and the determinant factors that affect GTFP are empirically tested by a dynamic panel data (DPD) model. The research shows that, considering energy consumption and environmental undesirable outputs, the industrial GTFP goes backwards by 0.02% per year on average, and the contributions of GTFP to output growth are far from the target value of 50% in all industrial sectors, which indicates that the growth of industrial economy sacrifices resources and environment to a certain degree. In terms of the determinant factors of GTFP, environmental regulation does improve the GTFP, while environmental regulation is difficult to promote GTFP by the route of technological innovation. Compared with technology importation, the driving effect of independent research and development on GTFP is obvious, especially promoting the GTFP of moderately and lightly polluting industries, while the driving effect in heavily polluting industries is poor. Endowment structure and property right structure play a positive role in improving GTFP, but the impacts of capital structure and energy structure on GTFP are poor.

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Section: Ddf and Gml Productivity Indexmentioning

confidence: 99%

Green Total Factor Productivity Growth and Its Determinants in China’s Industrial Economy

et al. 2018

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“…This approach presents some problems, such as possible infeasibility in DEA models and lack of circularity. To overcome this, Pastor & Lovell (2005) propose the Global Malmquist index:…”

Section: Methodsmentioning

confidence: 99%

“…Thus Malmquist productivity indices, either traditional (Färe et al, 1994) or global (Pastor & Lovell, 2005) can be split into PEC, SEC and TC.…”

Section: Methodsmentioning

confidence: 99%

“…The main novelty of this work was the use and comparison of different techniques for measuring and decomposing TFP: contemporaneous Malmquist (Färe et al, 1994), Global Malmquist (Pastor & Lovell, 2005) and Färe-Primont indices (O'Donnell, 2011). In addition, to gain robustness several distance functions were employed: well-known Data Envelopment Analysis (DEA) efficiency measures (Charnes et al, 1978;Banker et al, 1984), slacks-based (SBM) nonradial (Tone, 2001) and free disposal hull (FDH) measures of efficiency (Deprins et al, 1984).…”

Section: Introductionmentioning

confidence: 99%

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Global Malmquist indices of productivity change in Egyptian wheat production

Elasraag

Alarcón

2017

Span. j. agric. res.

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This study aims to measure the total factor productivity of the main governorates of wheat production in Egypt during the time period 1990-2012 and decompose it into technical change, efficiency change and scale change. We used Global Malmquist TFP index as a non-parametric approach. The results indicated that the contribution of technical change component is more important than the efficiency change component. In fact technical change rose, 25.7%, while efficiency change presented a little decline, 3.7%. The decomposition of efficiency change indicated that the main problem of wheat production in Egypt was scale efficiency that worsened by 5.5%.

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“…Following [25,26], we further define the global benchmark technology for the industrial sub-sector i as:…”

Section: Introductionmentioning

confidence: 99%

Exploring Change in China’s Carbon Intensity: A Decomposition Approach

Lin

Xie

2017

Sustainability

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This paper aims to explore the change of CO 2 intensity in China at both national and provincial levels. To serve this purpose, we introduce a decomposition model which integrates the merits of index decomposition analysis and production-theoretical decomposition analysis. Based on the decomposition, we also estimate the potential reduction of CO 2 intensity for China and its provinces. Using a panel data set including China's 30 provinces during the period of 2006-2012, the empirical analysis is conducted and meaningful results are obtained. First, the potential energy intensity change was the dominant driving factor for the decrease of CO 2 intensity, which contributed to a total reduction of 19.8%. Second, the energy efficiency change and the CO 2 emission factor change also play positive roles in the CO 2 intensity reduction for most provinces. Third, provinces in the western area generally showed a relatively large potential reduction in CO 2 intensity, while those in the eastern area only demonstrated a small reduction.

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A global Malmquist productivity index

Cited by 590 publications

References 6 publications

Green Total Factor Productivity Growth and Its Determinants in China’s Industrial Economy

Green Total Factor Productivity Growth and Its Determinants in China’s Industrial Economy

Global Malmquist indices of productivity change in Egyptian wheat production

Exploring Change in China’s Carbon Intensity: A Decomposition Approach

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