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• During 1993–2018, market services grew at a faster rate than non-market services. • Applying Domar weights we observed that transport and storage was the highest contributor among market services industries, while public administration has made relatively higher contribution to aggregate non-market services TFP growth. • TFP growth in manufacturing has a significant positive effect on TFP growth of both market services and non-market services. • Market services TFP growth is positively impacted by a spillover effect of TFP growth in India's trade partners. The services have been the driver of India's overall growth since the onset of economic reforms in the 1990s. The value-added share of services increased from 41 percent in 1990 to 53 percent in 2018. On average, the sector grew at 7.5 percent annually during 1993–2018, contributing to about half of the aggregate economic growth. Using the India KLEMS data, we examine the trends in total factor productivity (TFP) in individual industries within services and their contribution to aggregate TFP growth in the sector during 1993–2018. We find that transport and storage was the highest contributor among various market services industries followed by financial services, while public administration made a relatively high contribution to aggregate non-market services TFP growth. Moreover, we investigate the factors driving TFP growth in the services sector, particularly the role of manufacturing TFP – looking into spillover effect from manufacturing to market services and non-market services. Our results suggest that TFP growth in manufacturing had a significant positive impact on TFP growth in the services sector. Also, we find evidence of significant productivity spillover effect to India's services sector from other countries, particularly the developed countries. [ABSTRACT FROM AUTHOR]

This paper investigates income convergence of Indian states in the post-reform period when markets played a greater role in resource allocation. We analyze stochastic convergence of relative per capita incomes of 19 states for the period 1994–2018 by employing a recently developed panel data approach controlling for structural breaks as smooth shifts. Smooth shifts are modelled using a more flexible Fourier approach that does not require identifying the number, date, and form of breaks. The empirical results, contrary to recent empirical findings, do not support evidence in favour of convergence in per capita income among Indian states. Poor infrastructure, lack of adequate financial development, and weak governance structure coupled with low total factor productivity growth seem to be responsible for the divergence of income. The findings suggest that development intervention in the post-reform period has neither been of the required order nor in the desired direction to help the lagging states to catch up with the leading ones. [ABSTRACT FROM AUTHOR]

Water and energy crisis, rising temperature and subsequent changes in climate result in calamitous loss of wheat productivity due to adverse effect on plant growth and development. Plateauing yield trends and declining total factor productivity compel for alternative water and energy-efficient conservation practices supporting sustainable wheat productivity in humid tropics. Present investigation tested the hypothesis stating that the alternate wheat establishment methods and inter-culture practices would economize energy and water requirement with enhanced productivity. Different wheat establishment methods viz., conventional tillage, reduced tillage, zero tillage and raised bed landforms of 40/20 and 60/20 cm and two inter-culture practices, i.e. conoweeding and alternate ridging on spring wheat were evaluated for two years at Pantnagar in Uttarakhand, India. Zero and reduced tillage depicted better economic viability with benefit cost ratio of 2.86 and 2.84, respectively, which was statistically at par with conventional tillage. Alternate ridging and raised bed (60/20 cm) recorded 13.3 and 41.7% saving of irrigation water, respectively. Highest energy use efficiency was observed in raised bed 60/20 cm with 22.4% less energy consumption compared to conventional method. Thus, adoption of conservation practices with improved inter-culture operations holds potential for sustainable, water and energy-efficient and profitable wheat productivity. [ABSTRACT FROM AUTHOR]

Productivity rise as a source of growth has high potential to uplift millions out of poverty. Mitigating the productivity gap can play vital role in helping developing countries to offset with developed countries. In this regard, present study attempts to scrutinize the relationship and significance of various determinants of total factor productivity (TFP) in India for the period 1990-1991 to 2019-2020. To this end, autoregressive distributed lag bounds testing approach has been utilized. The results pinpoint that trade openness and unemployment have a positive impact on total factor productivity. On the other hand, inflation has a negative but insignificant relationship with total factor productivity, both in the short and long run. The results imply that exports need to be diversified, and import of capital goods should be encouraged to enhance TFP in the long run. Further, foreign-owned business entities need to be encouraged to hire domestic workers, which would result in enhanced TFP in the long run. [ABSTRACT FROM AUTHOR]

Purpose: A brief review of earlier studies on the productivity scenario of Indian industry shows that most of the studies analysed are confined to either parametric approach or growth accounting approach of measuring productivity. At the same time, the few studies based on the non-parametric [namely, Malmquist productivity index (MPI)] overlook the returns to scale conditions as well as the bias involved in the estimation of distance functions. Given this backdrop, this study aims to provide a robust measure of productivity, which considers the returns to scale assumptions and correct for the bias involved in the estimation of productivity. Design/methodology/approach: This study empirically tests for the returns to scale that exists in the chemical and chemical products industry in India. The test result suggests that Ray and Desli (1997) approach of MPI is the appropriate one for the present context. Initially, the conventional Ray and Desli (1997) estimation and decomposition of MPI for the period 2001 to 2017 is being used. Subsequently, to correct for the bias in the estimation of efficiency scores used for the estimation of MPI, the bootstrapping algorithm of Simar and Wilson (2007) has been extended into the context of MPI estimation. Findings: The results from the conventional Malmquist productivity estimates testifies to an improvement of total factor productivity (TFP) in seven out of 16 years under consideration. On the contrary, TFP growth is recorded only in the four years throughout the period after the bias correction. A greater discrepancy between the two measures has been found in the case of scale change factor component of MPI. Practical implications: The technical change (TC) component positively influences TFP, whereas scale change factor (SCF) deteriorates the TFP condition of this industry. It will be appropriate for these firms to identify and operate under an optimal scale of operation, along with reaping the benefits of technological change. From a methodological perspective, researchers should consider the potential bias that arise in estimation of TFP and use a larger sample whenever possible. Originality/value: This paper brings in a new perspective to the existing literature on industrial productivity. As against earlier studies, this study empirically tests the returns to scale of the sector under consideration and uses the most appropriate approach to measure productivity. The effect of sampling bias on TFP and its components is analysed. [ABSTRACT FROM AUTHOR]

The existing empirical studies concerning labour market rigidity associated with the labour laws in India suggest an adverse impact of rigidity on total factor productivity (TFP). In this paper, we improve upon both the measurement of spatiotemporal variation in labour market flexibility and plant-level TFP from production function estimates in the presence of institutional rigidity in labour inputs adjustment due to job security legislation based on the recent advancement in the literature. We use an unbalanced panel of manufacturing plants from the Annual Survey of Industries panel data from 1999–2000 to 2016–17 to analyse the relationship between labour market rigidity/flexibility and TFP. We find that establishments that fall under the purview of job security legislation have higher productivity than those outside the ambit of job security legislation. The results suggest that rigidity associated with job security provisions does not harm TFP, and higher flexibility is negatively associated with TFP. However, we find considerable heterogeneity in the flexibility–TFP relationship across various industry groups. The heterogeneity in the flexibility–TFP relationship suggests that flexibility-inducing labour policy may improve TFP in some industries and, at the same time, decrease it in others. [ABSTRACT FROM AUTHOR]

Our study focuses on the effect of agro‐based factors and human development indicators on the production of finger millet in eight states of India. Departing from the past studies, we employed the common and dynamic common correlated effects model, and our findings showed that the past year's finger millet production, productivity, area under finger millet production, rainfall and human development indicators positively influenced the finger millet production among the eight Indian states. The variable crop diversification has no impact on the production of finger millet. Overall result indicates the prominent role of human development assisting in the promotion of finger millet production. The empirical findings suggest corrective government policies in order to boost the overall production and consumption of finger millet at the macro level. [ABSTRACT FROM AUTHOR]

Background: Pulses, supplemented with cereals, provide a perfect mix of vegetarian protein of high biological value. The productivity of pulses in India is less than half of the productivity levels in the USA and Canada. Present investigation was aimed to Total Factor Productivity (TFP) growth in three pulse crops in the state of Rajasthan from 2000-01 to 2017-18. Methods: In the current study, the Tornqvist Theil Index was used to compute the total output index, total input index and total factor productivity index. The Tornqvist Index is exact for the homogenous translog production function that can deliver a second order approximation to an arbitrary twice differentiable homogenous production function. The translog function does not require perfect substitutes for inputs. If the relative price of input increases, the producer decreases its use (substituting other inputs) until all marginal productivities are proportional to the new prices. Result: The results of this study has indicates low TFP in gram (0.98%) despite a 59.23 per cent share in the total pulse output of the state. The annual compound growth rate of TFP of black gram increased at the rate of 1.11 per cent per annum (moderate growth) and the contribution of TFP to output growth was low; at about 41.63. Whereas, the compound growth rate of TFP of annual green gram crop increased at the 2.38 per cent per annum (high growth) while its TFP to output growth was about 66.43 per cent. The real cost of production of gram, black gram and green gram crop increased by 0.77, 1.49 and 1.57 per cent per annum, respectively. [ABSTRACT FROM AUTHOR]

This paper empirically investigates the influence of intellectual capital on changes in total factor productivity of 36 BSE-listed banks in India from 2005 to 2019. This study employs a two-stage analysis that begins by investigating changes in total factor productivity using the Malmquist Productivity Index estimated through Data Envelopment Analysis, and then computes intellectual capital and its sub-components within the Value Added Intellectual Coefficients model framework. Then, using the System Generalised Method of Moments, we investigate the impact of intellectual capital on changes in total factor productivity. According to our findings, productivity growth is primarily driven by efficiency changes rather than technological changes. Furthermore, regression results show that the intellectual capital index and its two sub-components, human capital and capital employed, have a strong positive impact on bank productivity. This research could help bank senior executives measure their productivity and intellectual capital, identify relevant intellectual capital elements that contribute to productivity and develop future policies to encourage and improve their intellectual potential. Furthermore, this is one of the few studies in the Indian context that examines the nexus between intellectual capital and productivity using the Malmquist Productivity Index. [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 paper examines productivity performance of micro, small and medium enterprises (MSMEs) vis-à-vis large firms in India's organised manufacturing sector in the backdrop of COVID-19. To address simultaneity and endogeneity associated with firm size and productivity, the paper applies the Levinsohn and Petrin method to an unbalanced panel to estimate the production function and calculate the total factor productivity (TFP). The results suggest that productivity levels in financial years 2012 to 2022 were comparable between MSME firms and large firms, with the latter performing marginally better. TFP growth stagnated in the pre-pandemic period for both MSMEs and large firms. Post-COVID-19, productivity increased for both large firms and MSMEs, with productivity growth in MSMEs catching up with that of large firms. [ABSTRACT FROM AUTHOR]

The paper attempts to include land as an input in the KLEMS-type production function and estimate agricultural total factor productivity growth (TFPG) for India. For doing so, land quality is accounted for by assigning weights to different land types: irrigated, rainfed and fallow. The estimates suggest that the rate of agricultural TFPG was 0.8 per cent per annum between 1980 and 2019 without accounting for land. However, it increased to 2.0 per cent and 1.8 per cent per annum with the inclusion of land and land quality, respectively. The growth accounting decomposition shows that the contribution of TFPG to agricultural output growth increased from 48 per cent in the 1980s to 78 per cent in the 2010s. Examination of the drivers of agricultural TFPG through an Autoregressive Distributed Lagged (ARDL) model suggests that public gross capital formation (GCF) stock, research and development, mechanisation in agriculture, and favourable terms of trade significantly improve agricultural productivity in India. [ABSTRACT FROM AUTHOR]

This paper develops a flexible recipe for identifying unobserved input allocations, as well as quantity- and revenue-based total factor productivity (TFP) across product lines, for multiproduct producers, using demand- and supply-side information. Applying variants of this recipe to a panel of plants manufacturing machinery in India from 2000–2007 yields sizable within-plant TFP differences. Removing an average plant's lowest-performing product increases the unweighted average of plant-level revenue-based productivity by 10%–65%. A 1 standard deviation decline in product-level revenue-based TFP generates around a 6 percentage point increase in the probability of dropping that product. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to measure the level of total factor productivity of the Indian banking sector and to identify both the bank-specific and macroeconomic determinants of the total factor productivity after the global subprime mortgage crisis. Design/methodology/approach: The research sample consists of 61 commercial banks including 21 public sector banks, 18 private sector banks and 22 foreign banks. The annual data is collected from the website of Reserve Bank of India from 2008 to 2019. The authors employed the non-parametric DEA approach to estimate Malmquist total factor productivity index for each bank as well as across different ownership groups. The panel data estimation technique was used to identify the determinants of total factor productivity. Findings: The results suggested that an increase in the technological shift raised the bank's productivity above the optimal frontier. Among the bank-specific determinants, the bank size and bank diversifications are significantly declining productivity, whereas credit-deposit ratio and return on asset significantly increasing productivity. Among the macro-specific determinants, inflation, growth rate and fiscal deficit ratio negatively affect productivity, whereas capital formation to the GVA ratio boosts the level of productivity. Research limitations/implications: The authors have used intermediate method to select the inputs and outputs as per the suitability to the context. However, the disaggregate level such as state and district level analysis can be done using production and value-added approaches to explore the regional variations of the banking performance. Furthermore, the parametric methods such as stochastic frontier analysis can be used to examine banking performance, which the authors left for the future research. Practical implications: This study suggested that banks should increase the economies of scale of their total assets and focus on the interest-earning activity. The banks need to proactively operate the business policy by following the changing path of inflation. The banks need to reduce their rate of fiscal-deficit to the GVA with the purpose to boost their level of productivity. Originality/value: The study provides an important implication for bankers and policymakers in terms of heightening the banking performance during the period of dynamic economic events. [ABSTRACT FROM AUTHOR]

The study estimates total factor productivity growth (TFPGj and its constituents of the 4-digit manufacturing industries of transport equipments in India throughout 1998-99 to 2017-18, the pre-economic crises period (1998-99 to 2007-08j and the post-economic crises period (2008-09 to 2017-18) using frontier approaches, i.e., Data Envelope Analysis (DEAj and Stochastic Frontier Approach (SFAj. The constituents of TFPG are technological progress (TPj, technical efficiency change (TECj and economic scale change (SCj. It is found that TFPG in a majority of the 4-digit industries of transport equipments in India have declined during the post-economic crisis period (2008-09 to 2017-18j and the decline of their TFPG is responsible for the decline in TP of the same throughout that period as per SFA; while as per DEA, TFPG of the four industries under study have increased and of the remaining industries have declined during the post-economic crises period (2008-09 to 2017-18j and their increase and/or decline are mainly accountable to the increase and/or decline in TEC and SC of them, throughout that period. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to examine the association between productivity growth and job reallocation in terms of job creation and job destruction. It also finds this productivity employment relationship for heterogeneous labor market institutions of the Indian states. Design/methodology/approach: The paper uses longitudinal data of the Annual Survey of Industries of Indian manufacturing from 2009–2010 to 2015–2016 and employs fixed-effect multinomial logistic regression. Findings: The paper finds a mixed result of total factor productivity (TFP) increase on employment. An increase in TFP is positively associated with employment by reducing the probability of destroying jobs, while adversely associated with employment by reducing the probability of creating jobs. The negative association of the increase in TFP on employment is more in the Indian states with strict labor regulations. Research limitations/implications: The relationship between TFP and employment can be endogenous. TFP is calculated as output changes that are not explained by inputs, capital and labor. So, job creation/destruction may affect TFP by changing the composition of employment and/or returns on labor/capital. In addition, this study is only restricted to Indian organized manufacturing. Practical implications: The results from this study help deeply understand the Indian labor market. In particular, it provides valuable insights into the "jobless growth" in Indian manufacturing and the recent changes in labor laws. Social implications: The findings from this study provide useful information to enhance the robust growth of productive jobs and efficient reallocation of labor. Originality/value: Unlike most papers, which analyzed the relationship between productivity growth and net employment changes, the present paper finds the relationship between improvement in productivity and job reallocation in terms of simultaneous creation of new jobs and destruction of existing jobs. In addition, the paper links this relationship with the existing heterogeneous labor laws of the Indian states. [ABSTRACT FROM AUTHOR]

Background: India is the largest producer as well as consumer of pulses in the world due to higher relance of their people on vegetarian sources of proteins, however, we have been dependent on import of pulses for meeting our demand for pulses over several decades. As a strategy to be self-reliant in pulses production two important initiatives were taken by the government of India viz. implementation of Accelerated Pulses Production Program (A3P) and inclusion of pulses in the National Food Security Mission (NFSM-Pulses) during 2010-11. Pigeon pea has tremendous medicinal and pharmacological properties and uses in addition to the good quality source of proteins. Significant improvement observed in production and productivity of pigeon pea after the A3P and NFSM-Pulses was questioned for its Total Factor Productivity (TFP) growth. Methods: This study was designed to assess impact of A3P and NFSM-Pulses on TFP of Pigeon pea in major Indian producing states. TFP was estimated with the help of Malmquist Productivity Index (MPI) using Data Envelopment Analysis Program (DEAP) version-2.1 in five states of India viz., Gujarat, Karnataka, MP, Maharashtra and UP which contribute more than three-fourth pigeon pea production in India. Result: TFP change in period-II (after A3P and NFSM-Pulses) was invariably higher than the TFP change in period-I (before the initiatives) in all the studied states. It indicates that these government initiatives contributed to the enhancement of production and productivity of pigeon pea with the support of better technology adoption rather than just led by higher use of inputs. [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]

Summary: Motivation: Empirical studies on income convergence for India indicate that Indian states exhibit divergence in income. The literature, however, has neglected the convergence dynamics of the main sources of output. A pertinent question is whether divergence in income is due to divergence in factor inputs (capital and labour) and/or in total factor productivity (TFP) in India, a low middle‐income country with high dispersion of per capita income across its states. Purpose: This article examines the sources of income divergence in Indian states by analysing convergence in TFP, labour, and capital. Methods and approach: We test for stochastic convergence hypothesis by employing state‐level data for 19 Indian states during the period 2001–2015. Given the small sample dimension of the Indian state‐level income data, we benefit from the recent developments in non‐stationary panel data literature; and conduct novel panel stationarity and unit root tests with a fixed time dimension. We further carry out a robustness analysis to account for cross‐section dependency across the states. Findings: TFP as well as the factor inputs (labour and capital) exhibit divergence, implying persistence in income inequality across Indian states. Divergence in labour across the states reflects the fact that migration is primarily an intra‐district phenomenon. Poor investment climate in low‐income states acts as a barrier for convergence in capital. TFP and capital stock are found to be correlated, and thereby lower investment in poorer states may be responsible for divergence in TFP across the states. Policy implications: Migration in India is primarily an intra‐district phenomenon. There is a need to study the reasons which are discouraging inter‐district and inter‐state migration for better utilization of the labour resource. Government intervention has not been adequate to improve the infrastructure position and encourage capital inflows to low‐income states. Low‐income states should improve their business climate and create support infrastructure to earn the confidence of investors. Increasing investment in low‐income states would help to increase their TFP and catch up with the high‐income states. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to study the productivity growth in the Indian apparel industry in aggregate over the period 1995–2015 and compare the performance of the Indian apparel industry during the decade of the Agreement on Textiles and Clothing (ATC) and the decade post its expiry. Design/methodology/approach: The aggregate productivity performance has been studied using the technique of growth accounting and the translog index. A comparison of industry performance has also been made by analysing data. The data has been collated from Annual Survey of Industries reports, CMIE Economic Outlook and CMIE Industry Outlook databases. Findings: The apparel industry has seen significant growth in terms of all industry variables and exports. However, the growth in exports is much lower than the growth in other industry variables related to output and input. While there is productivity improvement in aggregate over the study period, the quantum is low. Total factor productivity growth is positive and higher for the period post the ATC. Originality/value: To the best of the author's knowledge, there has been no such recent study comparing performance and productivity in Indian apparel manufacturing during and after the expiry of the ATC. [ABSTRACT FROM AUTHOR]

Financial inclusion programs are used as a major economic development tool in emerging economies. Human development is the major determinant of financial inclusion, creating opportunities for people to better access financial services. The study's major aim is to examine the technical efficiency of financial inclusion of Indian states by Data Envelopment Analysis using human development as input. To achieve this objective, a 3‐dimensional Financial Inclusion Index (FII) is constructed for 28 major Indian states from 2010 to 2017. Empirical findings suggest most Indian states are under low and medium financial inclusion, and states with better human development have better FII status. Crucially, technical efficiency results reveal states with better human development perform better in terms of FII. The inconsistency in FII and human development ranks is majorly found in North‐eastern and high‐income Indian states. Therefore, policymakers in India should focus on promoting human development in low Human Development Index states. [ABSTRACT FROM AUTHOR]

Manufacturing sector in India has exhibited a rather stagnant growth over the years and has failed to create business and job opportunities, provide productive employment and drive exports. Against this backdrop, the present paper seeks to analyse the productivity performance of the sector during the last one-and-ahalf decade and identify the firm level characteristics impacting the productivity. Using industry level data from annual survey of industries and firm level data from CMIE prowess database, it is found that the manufacturing sector did experience growth in labour productivity and total factor productivity in some of the years during the period of study. However, the overall productivity growth has not been impressive in the sense that it lacked consistency and inclusivity. Examination of firm level characteristics reveals that features like size, R&D stock and age of firm have been the major drivers of growth. Hence, sectors characterised by large and technologically superior firms managed productivity growth while sectors with dominant share of smaller firms with lower R&D and technological capability have found this benefit elusive. [ABSTRACT FROM AUTHOR]

This paper makes an attempt to link export performance with productivity, using Indian data, to assess whether sectors with higher comparative advantage in the FTA partner markets have experienced increased productivity over the years. Changes in exports are then correlated with changes in productivity. The sectors to be studied were identified after calculating the Bilateral Revealed Comparative Advantage (BRCA), and productivity using Data Envelop Analysis (DEA). Malmquist Productivity Index at the sectoral level was used to calculate Total Factor Productivity (TFP) growth. The findings from the paper reveal that though it is natural that due to intense competition at the international level, productive firms will survive; in reality, a few other factors play an important role. A labourabundant country tends to specialise in labour-intensive sectors, but due to low penetration of technology, its TFP growth is slower. Price advantages received by firms are solely due to cheaper labour costs. These firms face challenges in reaping the benefits from economies of scale, which is possible only when the scale of operations is larger, along with higher productivity. Also, the relationship between export competitiveness and productivity tends to ignore various forms of trade barriers. The introduction of new forms of non-tariff barriers mars productivity benefits. Regulatory barriers, licensing, etc. play an important role and productivity growth requires concurrent adherence to such barriers for higher exports. [ABSTRACT FROM AUTHOR]

The study estimates components of Total Factor Productivity Growth (TFPG) of the 4-digit manufacturing industries of non-metallic mineral products in India during the period from 1998-99 to 2017-18, pre-economic crises period (1998-99 to 2007-08) and post-economic crises period (2008-09 to 2017-18) using frontier approaches, i.e., 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). The study found that the growth rates of TFP in almost all the 4-digit manufacturing industries of non-metallic mineral products in India declined during the post-economic crises period (post-financial meltdown period) and the decline in TFPG of those industries during that period is mainly accounted for by the decline in technological progress (TP) of the same as per SFA and by the decline in technical efficiency change (TEC) and scale change (SC) of them as per DEA. [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]

Purpose: This paper aims to examine the total factor productivity (TFP) change and its components: efficiency change and technical change in microfinance institutions (MFIs) in India operating from 2005 to 2018. The study also scrutinizes the variations in productivity levels across the distinct organizational form and size groups of MFIs. In addition to this, the authors identify the contextual factors that determine TFP growth, catching-up and technology innovation in MFIs. Design/methodology/approach: The study employs a smooth homogeneous bootstrap estimation procedure of Simar and Wilson (1999) for obtaining reliable estimates of Malmquist indices –productivity and its components – in a data envelopment analysis (DEA) framework for individual MFIs. In order to identify the determinants of productivity change and its components, the study follows Simar and Wilson's (2007) guidelines and applies a bootstrap truncated regression model. The double bootstrap procedure performs well, both in terms of allowing correct estimation of bias and deriving statistically consistent productivity estimates in the first and root mean square errors in the second stage of the analysis. Findings: The empirical results reveal that the MFIs have shown average productivity growth of 6.70% during the entire study period. The observed productivity gains are primarily contributed by a larger efficiency increase at the rate of 4.80%, while technical progress occurs at 2.3%. Nonbanking financial companies (NBFC)-MFIs outperformed non-NBFC-MFIs. Small MFIs show the highest TFP growth in terms of size groups, followed by the large MFIs and medium MFIs. The bootstrap truncated regression results suggest that the credit portfolio, size and age of MFIs matter in achieving higher productivity levels. Practical implications: The practical implication drawn from the study is that the Indian MFI industry might adopt the latest technology and innovations in the products, risk assessment and credit delivery to improve their productivity levels. The industry must focus on enhancing the managerial skill of its employees to achieve a high productivity level. Originality/value: This study is perhaps the initial attempt to explain the productivity behavior of MFIs in India by deploying a statistically robust double bootstrap procedure in the DEA-based Malmquist Productivity Index (MPI) framework. The authors estimate the bias-adjusted productivity index and its decompositions, which represent more reliable and statistically consistent estimates. For contextual factors responsible for driving productivity change, the study deploys a bootstrap truncated regression approach. [ABSTRACT FROM AUTHOR]

Total factor productivity (TFP) is an important indicator for measuring the relationship between outputs (total product) and inputs i.e., factors of production. It is primarily related with labour and capital. Increased TFP is the result of economic growth, technological change, education, innovation, etc. India, as one of the emerging market economies, should play an effective role in ensuring resilience and sustainability with respect to productivity. The objective of the study is to examine the influence of Infrastructure Investment (PII) on TFP in India. Annual time series data from the Federal Reserve Economic Data (FRED) for the time period 1961 to 2020 has been used for this. Econometric tools such as Augmented Dickey-Fuller (ADF) and Philips-Perron (PP) tests confirm the problem of non-stationarity at level. This problem was eliminated by taking first difference of all variables. Johansen Co-integration test was applied to find out co-integration. To capture the long-run and short-run causal relationships between PII and TFP, the Vector Error Correction Model (VECM) was applied. The results confirm that there is an impact of PII on TFP. Short-run causal effects of PII on TFP have also been found. The Error Correction Term (ECT) value reveals that the model is in equilibrium and adjusts itself to external shock. Each result shows evidences of validation of PII for TFP. This study can serve as a guideline for policy makers so that they can strive to make productivity sector resilient and sustainable in post-pandemic era. [ABSTRACT FROM AUTHOR]

Micro, small and medium enterprises (MSMEs) have been the lifeline of the Indian economy. The sector draws significant importance in terms of employment, production, income and export. This is a labour-intensive sector and creates large employment opportunities in India. The sector has the capacity to reduce regional imbalance through income and employment generation and attain self-reliance. After new economic reforms, they have been facing tough competition. The nature of performance and efficiency of the MSMEs are needed to improve to face the competition in the market. This article analyses relative technical efficiencies of registered and unregistered MSMEs of states and union territories in India. Data envelopment analysis (DEA) technique is used to estimate the technical efficiency of the MSMEs. It is a state-wise analysis. This study shows some significant results of the performance and efficiency of MSMEs 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]

Purpose: The main aim of this paper is to examine the total factor productivity (TFP) and its components namely, technological change, technical efficiency change, scale change and allocative change in bakery industry in India. Design/methodology/approach: The study is based on panel data on 35 Indian states for the period 2009–2010 and 2012–2013. Stochastic frontier function is employed to estimate the productivity growth. Findings: The results show that TFP is driven by technological progress, followed by technical efficiency and scale efficiency. Allocative efficiency, however, has a negative effect on TFP. Research limitations/implications: The bakery industry needs to define its innovation strategies, as these strategies lead to different outcomes that can be achieved only through the management of resources dedicated to the generation and implementation of innovations. Originality/value: Using frontier production function takes the stochastic context into account for the dynamic behaviour of TFP and its components. Most of the past studies have assessed the TFP at the aggregate level using three-digit National Industrial Classification (NIC) or four-digit NIC code. An analysis at higher levels aggregation masks the variation in TFP and its components available at the firm level. This study uses five-digit NIC data to measure the firm specific TFP of bakery industry. Further, it looks at the contribution of technical progress (TP), technical efficiency, scale efficiency and allocative efficiency. [ABSTRACT FROM AUTHOR]

Ensuring that the benefits of growth are shared equitably requires a strong focus on greater convergence of regions in terms of output and productivity. The present study examines the regional disparities in Total Factor Productivity (TFP) in India by using the Data Envelopment Analysis (DEA) based non-parametric, Malmquist Productivity Index (MPI), especially in the post-crisis period. It utilises panel data for 3-digit industries from Annual Survey of Industries (ASI) for the period from 2003-04 to 2017-18 for 18 Indian states. The study period has been divided into a pre-crisis period (2003-2008) and post-crisis period (2008-2017) to see the impact of global financial crisis (GFC) on productivity as well. The results show that at the all India level, TFP of Organised Indian Manufacturing has declined in the post-crisis period as compared to pre-crisis period. The decomposition of the productivity growth further reveals that technological changes propelled growth in the pre-crisis period and efficiency changes were responsible for driving post-crisis growth. However, the inter-regional variations in productivity reduced during the post-crisis years signalling towards convergence of growth which is a welcome change. The author found that TFP is positively impacted by education, health and road infrastructure whereas relationship with telecommunication was found to be statistically insignificant. [ABSTRACT FROM AUTHOR]

This study estimates the effect of productivity on export performance of selected sectors and countries. Specifically, this study analyzes both theoretically and empirically, the nexus between productivity and export performance of selected emerging Asian economies including China, India, Indonesia, South Korea, and Japan. Total Factor Productivity (TFP) is used as a proxy for productivity and measured using two different techniques, growth accounting framework and data envelopment analysis. The study uses Auto Regressive Distributed Lag technique to estimate the effect of productivity on export performance of agricultural and manufacturing sectors of emerging Asian economies over the period of 1990 to 2016. Results show that TFP significantly and positively affect the agricultural and manufacturing sectors' export performance of selected emerging Asian economies both in long and short run. Hence, policies and economic strategies promoting adoption of advanced production technologies will increase exports of the emerging Asian economies in the long run. [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]

Multifibre agreement (MFA)–endorsed safe textile export markets were abolished in 2005. For India, scholars anticipated both enormous potential gain from the post‐MFA free market and the threat of inevitably increasing competition. Researchers also emphasized selected channels to succeed, including effective exploitation of scale economies and technological upgradation, for fruitful market gain in this regard. Against this backdrop, we study the Indian textile industry from 1999–2000 through 2014–2015 to examine (1) the role of economies of scale to achieve efficiency gain and therefore competitiveness, (2) the industry's efforts toward technological upgradation, and (3) its overall sustainability through net export expansion, profitability, and total factor productivity (TFP) growth. Results show that (1) size‐efficiency nexus is positively significant and therefore the industry can achieve further efficiency gain and competitiveness by expanding scale of operations at the firm level; (2) despite considerable increase in R&D investments, the industry's overall production technological status has deteriorated in the post‐MFA regime and therefore has substantial scope of improvement, possibly through more effectively using the prevailing technological upgradation funds scheme (TUFS) and other official arrangements; and (3) although India achieves sizeable net export expansion and TFP gains, the industry's profitability scenario seems bleak and requires further attention for its better sustainability. [ABSTRACT FROM AUTHOR]

According to a recent survey, Foreign Direct Investment (FDI) in India has received a phased improvement and has impacted the industrial productivity. There was an incredible increase in FDI inflows (40 percent) from October 2014 to June 2019, particularly in the manufacturing sector. One of the dominant sectors contributing to the major Indian GDP is considered to be the industrial sector. India has been ranked fourteenth in the world's factory output. This was attributable to the introduction of an effort to encourage development divisions and to be a magnet for international investment. In the whole country, more than 56 industrial units have benefited. In recent years, industrial output has tilted to 3.1 percent between 2014 and 2019, largely because of improvement and to promote skill growth for the different sectors of the economy. This paper highlights the government's recent attempts to promote FDI in different sectors and how it has built a course. India has seen a huge growth in foreign direct investment in different sectors of the economy in the last ten years. Although the Government of India has built a route to attract FDI in different industries, this paper focuses on understanding the effect on FDI of making in India scheme. A duration of five years has been regarded for the study in this article. For data processing, statistical methods such as Karl Pearson's Coefficient Correlation and One - Way ANOVA were used. Data processing is used to study the interaction between the association between FDI and IIP. [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 assesses the distribution of climate change impacts on agricultural Total Factor Productivity (TFP) across districts in India. Combining the district-level TFP, estimated using multiple rounds of nationally representative agricultural surveys, with climate and other controls, the relationship between production efficiency and climate is estimated for two time points: 2002–2003 and 2012–2013. The estimated climate response function suggests that for every 1 °C rise in temperature, agricultural productivity reduces by ∼4.5%. Using estimated climate sensitivity and regionally downscaled climate projections, the study further assesses the impacts on agricultural TFP across districts over the mid-century. By 2050, TFP in agriculture is projected to decline for all the states considered in the study. The latter-period (2012–2013) climate response function projects more adverse impacts compared to the early-period (2002–2003) response function. The results also show increase in the magnitude of impacts over time, indicating that Indian agriculture has become more climate sensitive. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to explain the role of globalisation on the regional income growth disparities in the states of India and provinces in the People's Republic of China (PRC). Design/methodology/approach: The authors use two approaches to analyse regional growth disparities: growth accounting and the panel spatial Durbin model. Findings: The growth accounting shows that contributions of growth of capital intensity (GKI) and total factor productivity growth (TFPG) distinguish the high-income (HI) regions from medium-income (MI) and lower-income (LI) regions in India. In the PRC, the contributions of GKI and TFPG in MI regions are slightly higher than HI regions, but significantly higher than the LI regions. The empirical results find that foreign direct investment (FDI), domestic investment, human capital, and interaction of FDI and human capital explain income growth states/provinces in India and the PRC. A region's income growth and FDI inflows spread the benefit to neighbourhoods in both countries. Originality/value: The paper contributes by performing a comparative analysis of Indian states and the PRC's provinces by capturing the neighbourhood effects of economic growth, FDI, investment and human capital and also the interaction effects of FDI with human capital and domestic investment. A comparison of the decomposition of income growth to the growth of factor inputs and efficiency in Indian states and the PRC's provinces also adds to the existing literature. [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]

Electricity Act 2003 mandates the implementation of the Multi-Year Tariff Policy (MYT) in order to improve the overall performance and the commercial viability of the utilities without losing the consumer interest by fetching transparency in operation. The successes of the implementation of the MYT Policy in twelve utilities across the four-states of India are analyzed. The productivity evaluation indicates the overall performance. In this article, it is examined by the Total Factor Productivity (TFP) concept using direct, quantity-based, Fisher Index over two control periods of the MYT structure for a period of 2007-08 to 2015-16, and the scope for improvement is identified. The five drivers of TFP change are identified. The study has revealed a 6.48 % average rise in the TFP during the period indicating the success of MYT. The TFP of 66.66 % of utilities has improved. The rise in the average cost of supply has reduced the TFP by 4.31% and it is a foremost source of impact. The rise in network loss has affected 33.33 % of utilities. The TFP performance of the Gujrat state is the highest, and the average TFP is 1.9. The optimal utility size for higher TFP is found to be 15 to 20 Million Units. [ABSTRACT FROM AUTHOR]

The main aim of this paper is to investigate the efficiency, change in productivity, and the sources of efficiency in the commercial banking sector of Pakistan and India. For this purpose, the performance analysis has been referred to, so as to verify the core-essence of the technical gains in efficiency, the role of managerial practices adopted, and the utilization of resources by the banking sectors in these two jointly bordered countries of South Asia. The time span that has been referred to for this study, spans from 2013 to 2017. Therefore, the Data Envelopment Analysis (DEA), equipped with its two basic models, which serve the input orientation and Malmquist Productivity Index (MPI) have been used, in order to submit the findings of this study. As compared to the situation in Pakistan, during the time span that has been taken into consideration for the purpose of this study, the Indian banking sector has been able to maintain higher scores, in the three levels of efficiency measures that have been observed. Moreover, the returns to scale analysis suggests that the banks operate at Constant Returns to Scale (CRS), or Increasing Return to Scale (IRS), thus making a positive contribution towards the average efficiency gains. Whereas, the banks that have been functioning at Decreasing Returns to Scale (DRS) happen to cause a decline in the efficiency measures. As far as productivity is concerned, both the countries have shown a positive improvement in the Total Factor Productivity (TFP), over the years. In a gist, the three levels of efficiency, and their sources of inefficiencies, make up the extract of the study. These findings should ideally be focused upon by the managers, practitioners, and policymakers, particularly while designing their operational strategies. [ABSTRACT FROM AUTHOR]

This article examines the patterns of total factor productivity (TFP) growth in eight state-owned passenger bus companies operating in major metropolitan cities of India. A state-of-the-art and innovative sequential Malmquist-Luenberger productivity index (SMLPI) approach is applied to compute unbiased estimates of TFP growth and its decomposed components. The empirical results based on the panel data set for the period 2011–2016 suggest that technical inefficiency is a common characteristic of bus companies providing passenger services in metropolitan cities. The analysis of TFP growth at the aggregate level reveals that the public bus transit system placed in Indian metropolitan cities experiences mild productivity regress, which is entirely attributable to efficiency loss. The disaggregated analysis provides that only four bus companies experience productivity gains throughout the sample period. Pune Mahamandal appears to be the most innovative bus company. [ABSTRACT FROM AUTHOR]

The study applies stochastic frontier approach to estimate and decompose the sources of total factor productivity growth (TFPG) of the 2-digit manufacturing industries of transport equipments in fifteen major industrialised states in India, as well as in All-India. The periods cover 1981-82 to 2010-11, engulfing the prereform (1981-82 to 1990-91) and post-reform periods (1991-92 to 2010-11), and also during two different decades of the post-reform period, i.e., 1991-92 to 2000-01 and 2001-02 to 2010-11. The components of TFPG are technological progress (TP), technical efficiency change (TEC), economic scale change (SC) and allocation efficiency change (AEC). According to the estimated results, technological progress (TP) is the major contributing factor to the TFPG of the organised manufacturing industries of transport equipments in India and in its fifteen major industrialised states during the period 1981-82 to 2010-11. Further, TFPG of the 2-digit manufacturing industries of transport equipments have increased during the post-reform period (1991-92 to 2010-11) and the increase is mainly accounted for by the increase in TP too for the same period. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to investigate the linkage between exchange rate exposure and firms' productivity in India. This study also tries to compare the effects of exchange rate exposure on the productivity of the pre- and post-financial crisis periods and also between export- and import-oriented firms. Design/methodology/approach: By using the annual data of 232 manufacturing and service sector firms for the period of 2000-2013, this paper examines the exchange rate exposure and firms' performance in India. In the first stage, the two-factor regression model, Adler and Dumas, is used, and in the second stage, the Levinsohn and Petrin (2003) approach is used for estimating the total factor productivity of significant firms. Finally, for examining the relationship between exchange rate exposure and productivity, the instrumental variable panel data regression model is used. Findings: This study observes that a negative relation exists between the appreciation of exchange rate exposure and firms' productivity. The study also reveals that the export-oriented firms make loss during exchange rate appreciation which decreases the productivity. The financial crisis has the negative impact on productivity, as well. Originality/value: Although there are an ample number of studies which examined the effects of the exchange rate on firm's export, growth, investment, however impact of exchange rate exposure on productivity at firm level is scanty. This study tries not only to compare the effects of exchange rate exposure on the productivity of the pre- and post-financial crisis periods but also between the export- and import-oriented firms which is another innovation of this study. [ABSTRACT FROM AUTHOR]

In the backdrop of India's jobless economic growth since the macroeconomic reforms of the 1990's, this study goes into the inter-relations among growth of productivity, employment and trade. Most of the studies on productivity in Indian manufacturing indicate a surge in the post reforms period though the individual manufacturing groups achieve varying growth. In the recent period, TFP growth in the sector is attributed to technology-based intermediate imports. Changing patterns of trade, especially export composition, have contributed to low employment generation. Growth in productivity and lack of growth in employment are thus explained by changing composition of trade. This paper starts by defining alternative measures of labor productivity growth, namely 'industry' labor productivity and 'system' labor productivity drawing on World Input-Output Database (WIOD). KLEMS database for India is also used for employment data. The time period for the study is from 1995 to 2014. Trend growth rates are estimated for alternative productivity measures, employment and output. The growth estimates show rapid productivity growth while the rates vary according to the labor intensity in production. It is found that productivity growth, particularly in labor intensive sectors, has been slow. India's share in world trade has been low and rising slowly. Additionally, the share in world trade of leather and textiles is very small. The composition of trade in India is biased towards the manufacturing sector as a whole while the labor-intensive sectors are neglected. Another emerging pattern of India's trade is escalating import of intermediate inputs. To establish the nexus between trade and productivity growth, a vertical specialization index has been estimated by using Hummel's formulation. The estimated result from panel regression with fixed effects establishes positive nexus between vertical specialization and productivity growth. It is argued that India needs to circumvent jobless growth by a balanced approach to job creation and productivity growth. A conscious policy of vertical specialization in products that draw on the country's vast reserve of un-skilled and semiskilled labor can go a long way in this direction. [ABSTRACT FROM AUTHOR]

The article focuses on health strategies that could boost industrial productivity in India amidst the COVID-19 pandemic. It mentions about using the Personal Protective Equipment (PPE) such as Coveralls, Goggles and face shields, N95 respirator masks and Gloves. It also mentions that an administrative health officer should be appointed, who will be responsible for the overall supervision and smooth running of the facility.