Productivity, Energy Intensity and Output: A Unit Level Analysis of the Indian Manufacturing Sector

Sahu, Santosh Kumar; Sharma, Himani

doi:10.1007/s40953-016-0034-7

Cited by 29 publications

(25 citation statements)

References 12 publications

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“…As our results confirm a positive relationship between energy intensity and output, we conclude that Indian industries are not in line with the argument of decoupling growth. A similar result was obtained in Sahu and Sharma (2016) for the manufacturing firms at unit level. Rather the results of Model 2 confirm a non-linear inverted U shape relationship between energy intensity and output, representing a case of productivity dilemma.…”

Section: Empirical Evidence At Disaggregate and Aggregate Levelssupporting

confidence: 84%

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Energy Intensity, Productivity and Pollution Loads: Empirical Evidence from Manufacturing Sector of India

Bagchi

Sahu

2020

Studies in Microeconomics

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We explain the relationship between energy intensity and productivity for the organized manufacturing sector of India. Using data from the secondary sources, we explain the relationships at aggregate, state and industry levels. The novelty of this paper lies in bringing in pollution loads in explaining inter-industry variations in energy intensity. Results of this study indicate that the organized manufacturing sector of India has gained energy efficiency and productivity. We found heterogeneity among Indian states in productivity growth and energy intensity. The results indicate that small states performed well whereas large states fall in the productivity paradox. The productivity dilemma hypothesis is validated at industry level analysis however, results are inconsistent to validate the decoupling growth hypothesis. Pollution loads as classified by Government of India, plays a vital role in explaining energy intensity variations across industries, which calls for better policies aiming at pollutive industries specifically to achieve sustainable growth for the manufacturing sector of the Indian economy.

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Section: Empirical Evidence At Disaggregate and Aggregate Levelssupporting

confidence: 84%

“…For example, Sahu and Sharma (2016) use Levinsohn and Petrin (2003) method in estimating TFP and relate with energy intensity at firm level, for the manufacturing firms in India. They report that most of the manufacturing firms exhibit positive growth in TFP and confirm a productivity dilemma 1 in case of the manufacturing firms in India.…”

Section: Introductionmentioning

confidence: 99%

Energy Intensity, Productivity and Pollution Loads: Empirical Evidence from Manufacturing Sector of India

Bagchi

Sahu

2020

Studies in Microeconomics

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“…Examples of such application to firm level data include Topalova and Khandelwal (2011), De and Nagaraj (2014), Goldar and Banga (2017), Satpathy et al (2017), and Goldar et al (2018, 2019). The Levinsohn–Petrin methodology for measuring TFP has been applied to plant-level panel dataset prepared from unit-level data of ASI in Sivadasan (2006, 2009), Gupta and Veeramani (2015) and Sahu and Sharma (2016). De and Nagaraj (2014) have used the Levinsohn–Pertin methodology based TFP estimates as the main one for their analysis, and have also made an alternate estimate based on the methodology suggested by Wooldridge (2009).…”

Section: Model Data and Variables And Regression Resultsmentioning

confidence: 99%

Services input and productivity in Indian manufacturing plants

Goldar

2019

IGDR

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Purpose The purpose of this paper is to analyse econometrically determinants of total factor productivity (TFP) in Indian manufacturing plants with a focus on the influence of services input on productivity. Design/methodology/approach Plant-level data drawn from Annual Survey of Industries for the years 1998-1999 to 2012-2013 are used for the estimation of TFP at plant-level by applying the Levinsohn–Petrin methodology. Econometric models are estimated to explain variations in plant-level TFP. The explanatory variables used are services input intensity (split into manufacturing services purchased and other services), the share of information communication technology (ICT) assets in total fixed capital stock, the share of contract workers in total workers and the share of imported materials out of total materials used, with plant size taken as a control variable. Model estimation is done by applying the fixed effects model. Findings Econometric results indicate that services input and ICT intensity have a significant positive effect on productivity of manufacturing plants in India. Use of imported materials raises productivity, whereas the use of contract workers in place of regular workers tends to lower productivity. The impact of imported materials on TFP of manufacturing plants seems to be relatively bigger for labour-intensive, low technology industries. Originality/value Care has been taken for TFP measurement. Analysis of the impact of services input on TFP has been undertaken for Indian manufacturing using plant-level data for the first time.

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“…To overcome the problem of biased estimation, scholars like Klenow et al (2011), Kathuria et al (2013) and Majumdar and Mukherjee (2014) have applied the Levinsohn and Petrin (2003) methodology (hereafter LP), to estimate the TFP accurately. Energy efficiency (the reciprocal of energy intensity) trends and impact of TFP on the energy intensity are analyzed by many scholars like Doms and Dunne (1995), Subrahmanya (2006), Papadogonas et al (2007), Narayanan (2011), Golder (2011), Ladu and Meleddu (2014), Hu et al (2016) and Sahu and Sharma (2016). These studies have shown positive impact of TFP on energy efficiency.…”

Section: Literature Reviewmentioning

confidence: 99%

Does total factor productivity affect the energy efficiency

Haider

Bhat

2020

IJESM

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Purpose Because of growing energy consumption and increasing absolute CO2 emissions, the recent calibrations about the environmental sustainability across the globe have mandated to achieve the minimal energy consumption through employing energy-efficient technology. This study aims to estimate linkage between simple measure of energy efficiency indicator that is reciprocal of energy intensity and total factor productivity (TFP) in case of Indian paper industry for 21 major states. In addition, the study incorporates the other control variables like labour productivity, capital utilization and structure of paper industry to scrutinize their likely impact on energy efficiency performance of the industry. Design/methodology/approach To derive the plausible estimates of TFP, the study applies the much celebrated Levinsohn and Petrin (2003) methodology. Using the regional level data for the period 2001-2013, the study employs instrumental variable-generalized method of moments (GMM-IV) technique to examine the nature of relationship among the variables involved in the analysis. Findings An elementary examination of energy intensity shows that not all states are equally energy intensive. States like Goa, Rajasthan, Jharkhand and Tamil Nadu are less energy intensive, whereas Uttar Pradesh, Kerala, Chhattisgarh, Assam and Punjab are most energy-intensive states on the basis of their state averages over the whole study period. The results estimated through GMM-IV show that increasing level of TFP is associated with lower level of energy per unit of output. Along this better skills and capacity utilization are also found to have positive impact on energy efficiency performance of industry. However, the potential heterogeneity within the structure of industry itself is found responsible for its higher energy intensity. Practical implications States should ensure and undertake substantial investment projects in the research and development of energy-efficient technology and that targeted allocations could be reinforced for more fruitful results. Factors aiming at improving the labour productivity should be given extra emphasis together with capital deepening and widening, needed for energy conservation and environmental sustainability. Given the dependence of structure of paper industry on the multitude of factors like regional inequality, economic growth, industrial structure and the resource endowment together with the issues of fragmented sizes, poor infrastructure and availability and affordability of raw materials etc., states should actively promote the coordination and cooperation among themselves to reap the benefits of technological advancements through technological spill overs. In addition, owing to their respective state autonomies, state governments should set their own energy saving targets by taking into account the respective potentials and opportunities for the different industries. Despite the requirement of energy-efficient innovations, however, the cons of technological advancements and the legal frameworks on the employment structure and distributional status should be taken care of before their adoption and execution. Originality/value To the best of our knowledge, this is the first study that empirically examines the linkage between energy efficiency and TFP in case of Indian paper industry. The application of improved methods like Levinsohn and Petrin (2003) to derive the TFP measure and the use of GMM-IV to account for potential econometric problems like that of endogeneity will again add to the novelty of study.

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Productivity, Energy Intensity and Output: A Unit Level Analysis of the Indian Manufacturing Sector

Cited by 29 publications

References 12 publications

Energy Intensity, Productivity and Pollution Loads: Empirical Evidence from Manufacturing Sector of India

Energy Intensity, Productivity and Pollution Loads: Empirical Evidence from Manufacturing Sector of India

Services input and productivity in Indian manufacturing plants

Does total factor productivity affect the energy efficiency

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