Measuring plant level energy efficiency and technical change in the U.S. metal-based durable manufacturing sector using stochastic frontier analysis

Boyd, Gale; Lee, Jonathan M.

doi:10.1016/j.eneco.2019.03.021

Cited by 41 publications

(18 citation statements)

References 55 publications

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“…Two approaches are most frequently applied: the distance function approach and the production function approach. The distance function approach allows us to analyze the technical efficiency in a production procedure that involves multiple outputs; recent applications in energy economics include Boyd and Lee (2019) and Liu et al (2019), among others. The production function approach, on the other hand, facilitates the calculation of a set of indicators for technological change.…”

Section: Literature Reviewmentioning

confidence: 99%

Directed technological change, energy and more: a modern story

2020

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Reliance of modern economic activities on the use of energy, most of which still comes from non-renewable sources, provokes concerns regarding the most efficient utilization of energy inputs in production. While most theory expects directed technological change to be biased towards the non-renewable input, there is rare macro-level evidence that technological change is actually biased towards energy rather than other main inputs. To fill this gap, we apply stochastic frontier analysis to country data regarding output produced with capital, labor and energy, and estimate a set of indicators for technological change. Findings show that technological change is biased the most towards energy in general. In particular, although different groups of countries exhibit various patterns, there is strong evidence that technological change favors energy more than labor. This is in line with the theoretical expectation that technological change ought to be biased towards the non-renewable input rather than the renewable ones.

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Section: Literature Reviewmentioning

confidence: 99%

Directed technological change, energy and more: a modern story

2020

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“…where X −E = (L, K, NEM). Again, assuming that both positive and negative shocks v can influence energy requirement and positing that energy is not used 100% efficiently used, we can rewrite (6) as…”

Section: Modelsmentioning

confidence: 99%

“…The existence of the "energy-paradox" may indicate that the industry remains inefficient. Indeed, [6] find that the mean plant-level efficiency in the United States over the time-period 1987-2012 ranges from 33% to 86% for plants in various manufacturing industries.…”

Section: Introductionmentioning

confidence: 99%

“…Further, following [11], we decompose overall inefficiency into persistent or structural and transient inefficiencies. This has an advantage over for example [3] or [6] since we can identify if efficiency can be improved with relatively small effort, or structural approach is required. We find a significant drop in energy use efficiency in the 1970s, which has probably been caused by the oil crisis.…”

Section: Introductionmentioning

confidence: 99%

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Energy Intensity and Long- and Short-Term Efficiency in US Manufacturing Industry

Badunenko

Kumbhakar

2020

Energies

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We analyze energy use efficiency of manufacturing industries in US manufacturing over five decades from 1960 to 2011. We apply a 4-component stochastic frontier model, which allows disentangling efficiency into a short- and long-term efficiency as well as accounting for industry heterogeneity. The data come from NBER-CES Manufacturing Industry Database. We find that relative to decade-specific frontiers, the overall efficiency of manufacturing industries, which is a product of transient and persistent efficiencies has deteriorated greatly in the 1970s and rebounded only in the 2000s. The industries are very efficient in the short-term and this has not changed over five decades. The high level of overall inefficiency is almost completely due to the structural inefficiency which can be explained by what is referred to as the “energy paradox”. Finally, higher energy-intensive industries perform worse in terms of energy use efficiency than their low energy-intensity counterparts.

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“…Up to now, abundant literature has sought various approaches to open the "black box" of the TFP growth; the stochastic frontier analysis (SFA) is one of the main approaches in the application of estimating TFP growth. SFA was originally proposed by Aigner et al and Meeusen and van den Broeck [37,38], and has been broadly applied by many researchers into study [39][40][41][42][43][44][45][46][47][48][49][50][51][52][53][54] due to the following fundamental advantages. Firstly, it can explain more accurately the theoretical definition of a production function which estimates the maximum output attainable from a given set of inputs, and secondly, the technical efficiency of the sample may be estimated by comparing the observed output with the predicted (or attainable) output [44,46,[55][56][57].…”

Section: Introductionmentioning

confidence: 99%

Carbon Sequestration Total Factor Productivity Growth and Decomposition: A Case of the Yangtze River Economic Belt of China

Guang-ming

Jin-lian

et al. 2019

Sustainability

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To find out whether carbon sequestration is both effective at mitigating climate change and promoting economic growth, in this paper, by adopting a stochastic frontier panel model with translog production function, carbon sequestration is incorporated into endogenous variables to establish estimation model of carbon sequestration total factor productivity (CSTFP) and examine CSTFP growth and its drivers decomposition of the Yangtze River Economic Belt (YREB) of China in three estimations. The result shows that, (1) compared to traditional TFP growth, CSTFP growth in YREB is improved by 26.74 percentages (from −26.55% to 0.20%), contributed by three positive drivers of technical efficiency change (28.59%), technological progress change (18.55%), and scale efficiency change (3.99%); (2) different CSTFP growth exists in three watershed segments of YREB, which firstly is the upper reaches (0.62%), then the lower reaches (0.11%) and the middle reaches (−0.14%). Improved CSTFP growth owes to carbon sequestration’s harmonious symbiosis where natural ecosystems and human activities are naturally blended while insufficient synergies are bottleneck for promotion of CSTFP growth in YREB. Related policy suggestions are provided in the end. The proposed analysis framework is efficient to disclose CSTFP growth in YREB, and can also be applied to similar analysis on CSTFP in regions and extended to multi-country/region analysis.

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Measuring plant level energy efficiency and technical change in the U.S. metal-based durable manufacturing sector using stochastic frontier analysis

Cited by 41 publications

References 55 publications

Directed technological change, energy and more: a modern story

Directed technological change, energy and more: a modern story

Energy Intensity and Long- and Short-Term Efficiency in US Manufacturing Industry

Carbon Sequestration Total Factor Productivity Growth and Decomposition: A Case of the Yangtze River Economic Belt of China

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