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Pharmaceutical industry is one of the sunrise industries in the Indian manufacturing sector. It has flourished in the recent past. This chapter makes a comparative analysis of the productivity growth of Indian pharmaceutical industry using production function approach and adopting two distinct measures of labour input and also explains whether the growth and productivity is eco-friendly or not. Annual Survey of Industries (ASI) data is considered as data base and the time period 1980–1981 to 2016–2017 is considered which is sub-divided into four periods (1980–1981 to 1989–1990; 1990–1991 to 1999–2000; 2000–2001 to 2009–2010; and rest of the period). The pattern of result for both the measures are more or less in the same direction. A remarkable growth in total factor productivity (TFP) is observed after the initiation of new economic policy for both the method used. So far as the environmental issues are concerned, this industry seems to have been polluting the environment, as per unit use of energy is increasing over time.

While rapid increase in demand for foods but limited availability of croplands has forced to adopt input-intensive farming practices to increase yield, there are serious long-term ecological implications including degradation of biodiversity. It is increasingly recognised that ensuring agricultural sustainability under the changing climatic conditions requires a change in the production system along with necessary policies and institutional arrangements. In this context, this chapter examines if climate-smart agriculture (CSA) can facilitate adaptation and mitigation practices by improving resource utilisation efficiency in India. Such an attempt has special significance as the existing studies have very limited discussions on three main aspects, viz., resource productivity, adaptation practices and mitigation strategies in a comprehensive manner. Based on insights from the existing studies, this chapter points out that CSA can potentially make significant contribution to enhancing resource productivity, adaptation practices, mitigation strategies and food security, especially among the land-constrained farmers who are highly prone to environmental shocks. In this connection, staggered trench irrigation structure has facilitated rainwater harvesting, local irrigation and livelihood generation in West Bengal. However, it is necessary to revisit the existing approaches to promotion of CSA and dissemination of information on the design of local adaptation strategies. This chapter also proposes a change in the food system from climate-sensitive to CSA through integration of technologies, institutions and policies.

The chapter examines the sources of total factor productivity growth (TFPG) of the 2-digit manufacturing industries as well as total manufacturing industry of Gujarat during the period from 1981–82 to 2010–11, using a stochastic frontier approach. The empirical finding clearly states that although factor accumulations as well as resource allocations in most of the 2-digit manufacturing industries of the state have been improved during the postreform period, technological progress (TP) and technical efficiency change (TEC) of the same have deteriorated in most industries of the state during that period. As a result TFPG in the major manufacturing industries as well as total manufacturing industry of the state have declined because the combined effect of their improvement in scale effect (SC) and allocation efficiency effect (AEC) could not offset the declining effect of both the TP and TEC of the same during that period. In this context, the government should take some policy initiatives to improve productive efficiency of the organized manufacturing industries in Gujarat. Once efficiency increases, it enhances competitiveness, thereby increasing productivity growth and its different sources of organized manufacturing industries of the state.

The study estimates total factor productivity growth (TFPG) and its components of the 4-digit manufacturing industries of chemical and chemical products in India from 1998–1999 to 2017–2018, pre-economic crises period (from 1998–1999 to 2007–2008) and post-economic crises period (from 2008–2009 to 2017–2018) using frontier approaches, that is, data envelope analysis DEA and stochastic frontier approach (SFA). The components of TFPG are technological progress (TP), technical efficiency change (TEC) and economic scale change (SC). It is found that the growth rates of total factor productivity (TFP) in most of the 4-digit industries of chemical and chemical products in India increased during the post-economic crises period (from 2008–2009 to 2017–2018) and the increase in TFPG of them during that period is mainly accounted for by the increase in TP of the same during that period. The TEC of almost all the industries remains the same, however, declined during the post-economic crises (from 2008–2009 to 2017–2018) and SC of them remains very low or even negative during the aforementioned study periods.

In view of discussion of two crises, Asian Financial crisis, 1997 and global meltdown, 2008 spreading over more than two decades, the objective of this article is to present econometrically whether productivity growth across countries can be a remedial measure toward tackling global recession pervaded during recent two or three decades worldwide and also to shed light on the aspect of whether productivity can truly act as a driver of growth of selected six economies like Korea Republic, Japan, India, China, USA, UK, and world economy as a whole. The panel data for the six selected countries for the period 1990–2018 were constructed keeping eyes on the 1997 Asian financial crisis and then the 2008–09 global economic crisis and a random effects model was applied after Hausman test. The empirical findings disclosed that the impacts on the growth of economies (represented by growth of GDP) from the growth rates of the manufacturing sector, labor productivity of manufacturing sector, and labor quantity are positive and statistically significant; while the effects of growth of the capital deepening and labor composition on economic growth of those sampled countries are statistically significant but negative. Some key factors that are likely to affect future productivity performance are centered on some issues like facilitating global learning spillovers; allowing productive firms to thrive; and making the most of human capital that should be taken care of.

Using the Environmental Kuznets Curve (EKC) hypothesis as a theoretical framework and applying Estimated Generalised Least Square (EGLS) approach, this chapter examines the impact of energy consumption, economic growth, industrialisation and corruption on carbon dioxide emissions as well as finds out the causal relationship among them using panel data of 10 Asian economies over the period 1980–2019. Our empirical findings from EGLS model suggest that there exists an ongoing rising relationship between CO₂ emissions and economic growth both in the short-run and long-run which is opposing to what is claimed by the EKC hypothesis. Moreover, per capita CO₂ emissions rise positively with respect to increase in energy consumption, urbanisation, gradual industrialisation and growth in urban population in the long-run. Moreover, countries with adoption of more corruptive practices are found to have causing more environmental degradation through excessive emission of carbon dioxide in the long-run. The study also indicates the existence of unidirectional causalities running from carbon dioxide emission to energy consumption, from industrialisation and urban population growth to per capita CO₂ emissions, from industrialisation to GDP growth per capita and bidirectional causality between financial development and economic growth via GDP growth per capita. Therefore, these unidirectional causalities entail that CO₂ emission reduction or abatement measures can be applied without having any unpleasant effect on the real industrialisation, energy consumption and urbanisation in selected Asian countries.

In this study, the authors have tried to estimate and examine the relationship between energy intensity (EI), capacity utilisation (CU) and total factor productivity (TFP) of Indian Iron and steel industry for the time period 1980–1981 to 2016–2017. The estimation of TFP and its growth is based on three inputs capital (K), labour (L) and energy (E) using transcendental logarithmic cost function. Besides, capital and labour factor inputs, the estimation of CU also take into account the input, energy. It also considers the variable, price of energy and uses a variable cost (VC) function. This study also takes into account the concept of adjusting total factor productivity growth (TFPG) by CU. From our result, this study observes that CU increased over time. Again, Iron and Steel industry has become energy intensive (increasing EI) over the time period taken up for the study. On the other hand, TFPG has declined in the liberalised era. The preliminary idea that we get from our result is that TFPG is negatively related to the extent of pollution generated by energy intensive nature of the Indian Iron and Steel industry, which is in line with reality. To come out of this situation, we may prescribe the use of green technology and green energy sources for this industry.