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While promoting manufacturing growth is imperative to boost economic growth, potential adverse consequences on natural resources and ecology have created sustainability-related concerns and challenges. In India, with the reform processes deepening further and the business environment becoming more market-oriented over the years, the adoption of appropriate measures for sustainable manufacturing growth under such conditions would require a deeper investigation of the underlying dynamics, particularly to address the impacts of external shocks. This is especially true when external shocks alter market dynamics and, hence, input is used significantly in the manufacturing sector. Given this backdrop, the present paper examines how the major external shocks to the Indian economy during in the post-reform era have altered the resource use patterns in selected manufacturing industries. The paper uses secondary data collected from the KLEMS database of the Reserve Bank of India for the period from 1980–81 to 2019–20 and applies descriptive statistics and econometric techniques to address the research objective. It is found that energy intensity, vertical integration, capital intensity, and rate of growth of total factor productivity decreased over the decades, whereas labour productivity experienced an increasing trend in most industries. However, the trends are mixed in the case of material intensity. Further, the regression results indicate significant effects of external shocks on resource use, factor productivity, and structural changes. There are also industry-specific differences in the nature and extent of such changes. Hence, a deeper investigation of the underlying factors and impacts at a disaggregate industry level is necessary to draw more robust insights. [ABSTRACT FROM AUTHOR]

This study estimates the contribution of gendered social norms in explaining the gender gap in productivity of unorganised manufacturing firms. Restrictions on mobility and burden of household work mean that female firm-owners primarily operate from their household premises. Using data from unorganised firms operating in the manufacturing sector in India, this paper finds gender gap in firm productivity. The Blinder-Oaxaca decomposition at mean show that despite controlling for size of the firm, assets and other conventional factors, the location of a female proprietary firm within the household premises of the owner explains 19% of the observed gender gap in productivity. The RIF decomposition results show that at the different quartiles, this contribution varies from 19 to 36% of the composition effect. The evidence suggests that the persistence of the gender gap in firm productivity is associated with the persistence of gendered social norms. Plain English Summary: Almost 95% of female owned firms in the unorganised manufacturing sector in India operate from within the household premises, due to prevalent gendered social norms. These norms put the responsibility of unpaid household work solely on women and impose mobility restrictions. This paper examines whether restrictive social norms contribute towards the gender gap in firm productivity. I find that that the location of these firms within the household restricts them from expanding, as well as contribute to prevalent the gender gap in productivity and incomes generated from proprietary firms operating in the unorganised manufacturing sector. Newer policies supporting women's mobility and paid work that supplement conventional policies to improve entrepreneurship are required. However, as social norms involve coordinated actions and fear of sanction in case of noncompliance, these policies would work effectively if they are targeted towards both genders and entire neighbourhoods. [ABSTRACT FROM AUTHOR]

The study examines the effects of electricity consumption from different sectors such as agricultural, commercial, domestic, industrial (HV), industrial (LV-MV) and miscellaneous sectors on economic growth over the period of 1981–2019 in the case of India. We used SVAR framework and concluded that the consumption of electricity from agriculture sector has a negative impact on economic growth, whereas the industrial (HV and MV-LV) and commercial electricity consumption has positive impact on economic growth. Similarly, electricity consumption by the domestic sector has less positive effect on economic growth. Further, we computed the total factor productivity growth (TFP) by using the DEA method and showed the effects of sector-wise electricity consumption on TFP as the robustness of our analysis. We obtain similar kind of results. From the policy perceptive, the study suggests that the government must speed up the construction of a power grid to improve the availability of electricity for achieving higher rate of economic growth. [ABSTRACT FROM AUTHOR]

The paper explores the role of absorptive capacity in understanding the association between international knowledge spillovers and total factor productivity (TFP) growth in Indian manufacturing. Imports and FDI provide two major channels of knowledge spillovers while private research and development (R&D) and education-weighted human capital are used as proxies for domestic absorptive capacity. Applying pooled linear regression on 2-digit manufacturing sectors based on NIC 2008 (ISIC Rev. 4) for 2000–2016 in India, positive spillover effects of FDI and imports on TFP growth are confirmed. However, when looking at moderation effects, absorptive capacity is found to moderate the relationship between knowledge spillovers and domestic productivity negatively. When the manufacturing sectors are sub-grouped based on their technological intensities, interesting differences emerge. For the low-tech and medium–low-tech sectors, spillovers from FDI negatively affect TFP. In contrast, in the high-tech and medium–high-tech sectors, spillovers from imports as well as FDI have a dampening effect on productivity. With respect to interaction effects, absorptive capacity negatively moderates the relationship between FDI spillovers and TFP growth in the low-tech sectors. In the high-tech sectors, interestingly, human capital positively moderates import spillovers for productivity growth while no such moderation effect is found for R&D. Overall, results indicate that industries witnessing considerable FDI inflows and imports in recent years have not experienced direct productivity gains in the same proportion. This highlights the importance of absorptive capacity for productivity growth and the need for policy intervention at disaggregated sectoral level in India. [ABSTRACT FROM AUTHOR]

This study aims to explore the driving determinants on the export-related carbon intensity (ECI) of China, to better understand the impact of international trade on climate change governance and facilitate China's carbon intensity mitigation goals. First, China's ECI evolution and its gaps with the USA and India are measured during 2002–2014. Then, the main drivers of China's ECIvert study further discusses the influencing factors of ECI in the manufacturing industry using the environmental-extended STIRPAT model and GMM method. The results show that (1) China's overall ECI increases from 1.50 Kg/US$ in 2002 to 1.92 Kg/US$ in 2005 and then decreases to 1.27 Kg/US$ in 2014. The ECI of the manufacturing industry is significantly higher than that of the agriculture and service industry. China's ECI gap with the USA is greater than that with India, and both show a downward trend. (2) Carbon emission coefficient is the domain factor to reduce China's ECI during 2002–2014; the effects of the value-added coefficient, input–output structure, and final demand are limited. The input structure dominantly expands China's ECI gaps both with the USA and India, followed by the value-added coefficient. The carbon emission coefficient enlarges the ECI gap with the USA while reduces that with India. (3) Industrial productivity and value-added rate are negatively correlated with ECI in the manufacturing industry, while per capita capital stock plays the opposite role. The positive correlation between energy intensity and CIE becomes significant after distinguishing technology heterogeneity. In contrast to the non-tech-intensive manufacturing industry, the increase of backward GVCs participation of tech-intensive ones will reduce the ECI. The threshold effect of backward GVCs participation exists in the whole manufacturing industry. Targeted ECI reduction policy implications are suggested. [ABSTRACT FROM AUTHOR]

Environmental pollution caused by carbon emissions is an emerging issue to study among researchers. The nexus between environmental pollution and carbon emissions has motivated researchers to evaluate the impact of cleaner energy on carbon emissions. This study further contributes to the research by examining the above relationship by studying the asymmetric influence of nuclear energy (NE), industrial productivity (IP), and economic growth rate (GDP) on carbon emissions (CO2) in India from 1975 to 2018 using the asymmetric autoregressive distribution lag approach. The results of the bound test and the Wald test show that in the long run, there is an asymmetric relationship between CO2, NE, GDP, and IP, and in the short run, there is a symmetric relationship between CO2, GDP, and IP. The result implies that increased usage of nuclear energy over fossil fuels and improvement in industrial productivity, in the long run, reduces CO2 emission in India. Furthermore, the study concludes that the government should consider the asymmetric relationship between the variables and devise appropriate policies to increased nuclear energy and industrial productivity in India for environmental sustainability. [ABSTRACT FROM AUTHOR]

In this paper, we employ the less frequently used Geometric Young index to measure productivity change. We reformulate the Geometric Distance Function of Portela and Thanassoulis (J Product Anal 25:25–41, 2006) by removing the restrictions on the individual input scaling factors and the output scaling factors to obtain the benchmark input–output bundle on the frontier. In this reformulated model, the Geometric Young index is exhaustively decomposed into the technical efficiency change and technical change factors even under variable returns to scale. Further, between any two periods, the measured rate of technical change is identical across all units. In our empirical analysis, we use state-level data from the Annual Survey of Industries for the period 2010–2011 through 2016–2017 to measure total factor productivity growth in Indian manufacturing and provide its decomposition for the major manufacturing states in India. At the All-India level, the annual average Geometric Young productivity index shows a modest growth over the sample period. This resulted from an improvement in technical efficiency reinforced by a very modest increase in the Technical Change Index. [ABSTRACT FROM AUTHOR]

This paper empirically examines the difference in productivity existing between the public and private sector of the mining industry in India. The literature on the effect of firm ownership on productive efficiency stands highly divided; hence, in this context, our study adds to the literature by attempting to study the effect of firm ownership on total factor productivity (TFP) in the four sectors of the Indian mining industry from 2000 to 2016. Here, we have sought to compare the productivity difference between the public and private mining firms in the four sectors, namely metallic, non-metallic, coal and petroleum. This paper uses the Levinson and Petrin (LP) method for estimating the TFP of each firm. The results indicate the superiority of private firms in three sectors—metallic, non-metallic, and coal—whereas the petroleum sector reports quite the opposite result. The results raise questions about the stability of the public sector firms over time. Overall, the paper suggests measures like provision of incentives, improvement in infrastructural facilities, upgradation of manpower and so on to improve the productivity performance of public sector firms. [ABSTRACT FROM AUTHOR]

In today's organizational environment, the need to accomplish more with less people constitutes a source of employee stress. Increasing worker utilization may improve productivity in the system in the short run but at the cost of welfare of workers. This will negatively affect the capability of an organization to innovate, which is harmful for it in the long run. Hence, it becomes essential to take care of the welfare of both the employees and the organization simultaneously. An innovative model has been developed for a manufacturing system in lean environment to examine the current 'welfare' state which is considered as a combination of a set of welfare parameters for both the employees and the organization. Subsequently, a set of flexibility parameters have been identified and their respective impacts on the current 'welfare' state observed. The model has been tested with the help of an Indian case study which revealed a positive impact of flexibility. [ABSTRACT FROM AUTHOR]

This article investigates the effects of corruption on the performance of the manufacturing sector at the state level in India. We employ conviction rates of corruption-related cases as an instrument for the extent of corruption, address the underreporting problem, and examine the impact of corruption on the gross value added per worker, total factor productivity, and capital-labor ratio of three-digit manufacturing industries in each state. Our estimation results show that corruption reduces gross value added per worker and total factor productivity. Furthermore, we show that the adverse effects of corruption are more salient in industries with smaller average firm size. [ABSTRACT FROM AUTHOR]

Are smaller firms more productive? Intuitively, while small firms have the advantage of more flexible management and lower response time to market changes, larger firms have the advantages of economies of scale, political clout and better access to government credits, contracts and licenses, particularly in developing countries. Using a panel dataset from a commercially available database of financial statements of manufacturing firms in India, we find that firms in the lowest quintile of the asset distribution that invest in research and have better liquidity are most productive. The Indian manufacturing sector, characterized by both large scale public and private firms as well as numerous smaller firms, provides an ideal setting. Our findings are robust to alternative definitions of size, alternative estimation methods and alternative estimates of total factor productivity. [ABSTRACT FROM AUTHOR]

The study investigates how market imperfections distort the impact of trade reform on productivity growth. As the trade expands it influences both product and factor prices and if the distortions arise due to these market imperfections are not eliminated, the usual estimate of total factor productivity growth, using the growth accounting method, would be misleading. Theoretically, it shows that the usual estimate tends to be overestimated in the export competing sector and underestimated in the import competing sector. A modified approach of Olley-Pakes and Levinsohn-Petrin methods involving three-digits industries over the fifteen major Indian states during the period 1998-2005 has been used to deal with the simultaneity issue of factor choice and market distortions for the better estimate. A positive and significant impact of openness on the productivity growth has been observed only when the market imperfections are eliminated. Moreover, the modified productivity growth, after controlling market imperfections, has turned out to be lower than that of the usual estimate in India. [ABSTRACT FROM AUTHOR]

The paper analyses the patterns of export productivity and trade specialization profiles in Brazil, China, India and South Africa, and in other economic groupings and regions. Various measures of trade specialization and a time varying export productivity indicator are estimated using highly disaggregated export data. The findings reveal that there are important differences in the export productivity and specialisation patterns across countries and regions. Export productivity-and export sophistication-are in line to that of wealthier and more advance economies. The results further confirm the importance of not just the volume of exports, but the type of specialisation patterns. [ABSTRACT FROM AUTHOR]

Stock market is an important segment of the financial system of any country as it plays an important role in channelizing savings from deficit sector to surplus sector. These stock markets have always been an area of serious concern for policy makers, economists and researchers. They are often defined as the barometer of any economy because they reflect the change and direction of pressure on the economy. The movement and volatility in stock markets often reflect the direction of any economy. The available literature suggests that since the inception of stock markets researchers are making attempts to establish relationship between change in macroeconomic factors and stock market returns. There are various models developed so far by scholars globally for establishing the relationship between stock returns and these factors such as - discounted cash flows model (DCFM), the capital asset pricing model (CAPM), and the arbitrage-pricing model (APM). But these existing models also suffer from many limitations based on the concept of market equilibrium and the existence of a perfect market. In many developing countries, there are market imperfections and other market characteristics, which make the existing models unsuitable for developing countries like India. From the literature review, the study has seen that asset-pricing theories do not specify the fundamental macroeconomic factors that affect securities prices. The purpose of this paper is to investigate the impact of change in macroeconomic factors on the Indian stock market. The findings of the study conclude that emerging economies like India in long term are more affected by domestic macroeconomic factors than global factors. The main domestic macroeconomic factors affecting the stock market in long run are industrial production; wholesale price index and interest rate. [ABSTRACT FROM AUTHOR]

In this paper, an attempt is being made to analyse the productivity performance of the unorganised manufacturing sector in India for 15 major states for the period 1994-95 to 2005-06, using the National Sample Survey (NSS) unit level data. Productivity is measured by using both partial (labour productivity) and total factor productivity (TFP) measures. The Cobb-Douglas production function is estimated by using the Levinsohn and Petrin method, which addresses the potential simultaneity bias in production function estimationsEstimations show that labour productivity witnessed a fluctuating trend in the unorganised sector as it grew at a rate of 7 per cent during the first period, viz. 1995-2001, but fell considerably during the second period, viz. 2001-2006, thereby registering a huge decline of 12.6 per cent. An across-the-board increase in the capital-labour ratio has been noticed over time in all the states but the growth slowed down during the second period. It has also been found that capital intensity acted as a major driver of labour productivity in the sector. Production function estimates demonstrate that capital rather than labour played a significant role in the production process for the sector. The TFP reported a steady decline in the sector similar to the trend in labour productivity. The declining labour and TFP, on the one hand, and the increasing capital intensity of the unorganised sector, on the other hand, are causes of worry and raise several important questions. [ABSTRACT FROM AUTHOR]

Combining two data sources on emissions with value-added and employment data, this paper constructs six data bases on sulfur dioxide (SO2) intensities that vary across countries, sectors and years. This allows us to perform a growth decomposition exercise where the change in world manufacturing emissions is decomposed into scale, composition and technique effects. The sample covers the period 1990–2000, and includes 62 countries that account for 76% of world-wide emissions. While manufacturing activity has increased by a rough 10% (scale effect), we estimate that emissions have fallen by about 10%, thanks to the adoption of cleaner production techniques (the technique effect) and a small shift towards cleaner industries (between-sector effect). As output and productivity gains have been biased towards large emerging countries like China and India, which are both clean in terms of emissions per unit labor and dirty in terms of emissions per dollar, the sign and magnitude of the between-country effect depends on the choice regarding the scaling factor ( − 2% for employment, + 25% for value-added, with a corresponding adjustment of the technique effect). The paper also shows that these estimates are robust to changes in aggregation across entities (regions or countries) and across industries, and that composition changes are correlated with changes in prices and trade intensities. [ABSTRACT FROM AUTHOR]

Comments on the article "From Hindu Growth to Productivity Surge: The Mystery of the Indian Growth Transition," by Dani Rodrik and Arvind Subramanian, published in the periodical "International Monetary Fund Staff Papers". Failure of the article's authors to provide a convincing analysis of the reasons behind the productivity growth of India during the 1980s; Argument against the article's basic claim that it is not the systemic reforms of the 1990s that changed the growth process of the country's economy but a mysterious shift in the 1980s.

This paper explores the causes of India's productivity surge around 1980, more than a decade before serious economic reforms were initiated. Trade liberalization, expansionary demand, a favorable external environment, and improved agricultural performance did not play a role. We find evidence that the trigger may have been an attitudinal shift by the government in the early 1980s that, unlike the reforms of the 1990s, was probusiness rather than promarket in character, favoring the interests of existing businesses rather than new entrants or consumers. A relatively small shift elicited a large productivity response, because India was far away from its income- possibility frontier Registered manufacturing, which had been built up in previous decades, played an important role in determining which states took advantage of the changed environment. [ABSTRACT FROM AUTHOR]

Evaluates the organizational characteristics of state-owned enterprises in India. Role of the government in establishing businesses aimed at providing capital goods to the masses; Estimates of industrial productivity; Details on the policy governing the privatization process of state-owned enterprises.

Frontier production functions are important for the prediction of technical efficiencies of individual firms in an industry. A stochastic frontier production function model for panel data is presented, for which the firm effects are an exponential function of time. The best predictor for the technical efficiency of an individual firm at a particular time period is presented for this time-varying model. An empirical example is presented using agricultural data for paddy farmers in a village in India. [ABSTRACT FROM AUTHOR]

Replies to comments made on the article "From Hindu Growth to Productivity Surge: The Mystery of the Indian Growth Transition," published in the periodical "International Monetary Fund Staff Papers". Argument against the commentator's claim that the reason behind the productivity growth of India during the 1980s was caused by fiscal expansion and hence is unsustainable; Authors' claim that they do not consider India's 1991 balance of payments crisis to constitute compelling evidence that the growth of the 1980s was unsustainable.

Pakistan and India are the two major producers of the cotton, the most demanding crop of the world which is known as white gold. However, for some recent years, it deems that Pakistan's share in the international textile market dwindles compared to India. Thereby, the study will investigate whether the productivity of the crop per hectare is the reason or area of the crop, in the countries which lead to a higher share of India in the international market. In addition, which country has a comparative advantage in terms of cotton yield kg per hectare, particularly due to technological advancement in India and Pakistan's agriculture sector? And this study also examines which country has exploited natural and technological inputs most. The time-series data from 1954 to 2017 have been used in this study, the results of the study are drawn using two-stage analysis. At first, we get total factor productivity (TFPCc) for both the countries using Tornqvist–Theil Index: total factor productivity input–output method. Then, the obtained variable has been employed as a regress and variable on farm and non-farm regressors. The ARDL: autoregressive distribution lag regression model has been applied on [area of cotton, fertilizer consumption kg/ha, high yield varieties (HYV) seeds, electricity consumption in agriculture sector, agriculture labor force, and irrigation by canal water and tube well water, besides tractors] to find the technological advancement impact on the TFPC of cotton. The results explore that overall improvement in farm inputs has a more stable impact on the productivity of cotton in Pakistan, whereas HYV seeds, mechanization, and area are the real reason for the growth in India. [ABSTRACT FROM AUTHOR]