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This study aims to estimate total factor productivity (TFP) growth for the post-2008 period for selected industries in the manufacturing sector at NIC 3-digit. Total factor productivity growth (TFPG) estimates are based on the theoretical framework provided by studies such Hall (1988), Abraham et al. (2009) and Crepon et al. (2005) that incorporate market imperfection in labour and product market, thereby modifying the traditional TFP estimation as Solow Residual.

Based on the theoretical model that incorporates market imperfections in labour as well as product market in modifying the TFP estimates using the Levinsohn–Petrin framework of empirical estimation, the authors have calculated industry wise TFPG for 62 industries at NIC 3-digit level.

The study finds three distinct trends: first, there are considerable industrial disparities in productivity growth in terms of TFP. The estimates have been found to be higher than the conventional Solow Residual for most industries, indicating the role played by market imperfections in affecting the conventional measure of productivity growth. Second, estimates of bargaining power are found to be lower than those compared to the earlier estimates in Maiti (2013) for the Indian organised manufacturing case for 1998-2005. This observation is commensurate with the observation in recent years of a falling share in labour wage in total output in organised manufacturing sector. Finally, the study also found a statistically significant contribution of greater mechanisation on TFPG while an adverse effect of the rising dependence of organised manufacturing on contractual labour.

The role of market imperfections in measuring TFPG has been undertaken, and it has been found to be an important factor, as the estimated measures vary from the conventional measures of TFPG. Moreover, the study has considered a very recent period from 2008-2015 in estimating TFPG, as well as analysing the factors behind the trends in TFPG at industrial level.

This chapter measures total factor productivity growth (TFPG) using Malmquist productivity index (MPI) and the growth of MPI of Indian Textile Industry employing nonparametric data envelopment analysis (DEA), during 1995–2016, exploring company (firm) level Center for Monitoring of Indian Economy (CMIE) Prowess data; examines whether TFPG has improved after the withdrawal of multifiber trade agreement (MFA) since 2005; decomposes TFPG into technical change (TC), technical efficiency change (TEC), and scale efficiency change (SEC); and explains the factors behind the movement of TFPG, considering the effect of R&D (RD), exports (EX), marketing expenditures (MKTs) advertisement expenditures (ADVs), imports (IMP), using second-stage panel regression. Empirical evidence supports fluctuating pattern of TFPG during 1995–2016, with a marginal declining tendency. TFPG has increased in 1999–2000, 2000–01, 2009–10, and 2012–13. After dismantling MFA, MPI level has significantly declined, with an increase in its growth rate, but the increase is not statistically significant. The effect of EX, RD, ADV are nonlinear, U-shaped, and IMP and MKT are inverted U-shaped, implying that the sign effect of any variable depends on its size. There are joint interaction effects of (a) RD and EX; RD and MKT which are positive, (b) ADV and MKT as represented by the ratio (ADV/MKT), having nonlinear inverted U-shaped relation. The joint interaction effect supports that the impact of one variable depends on the magnitude of other. The marginal effect of EX, IMP, and ADV are positive; increase in these variables promotes TFPG. The greater role of ADV over MKT is evident. The marginal effect of RD is negative; the average level of RD is too low to generate positive effects, and, thus, there is an urgency of increasing RD. The promising part of the decomposition analysis is that highest contribution to growth rate of TFPG is the growth rate of TEC followed by growth rate of TC, and thus by increasing TEC and TC, higher growth rate of TFPG is achieved and may be beneficial in the long run and may lead to absorption of economic shocks for an economy facing recession in its output growth. Some policy suggestions are made for boosting up TFPG.

Since China's accession of the World Trade Organization (WTO), its construction industry has attained unprecedented growth. However, for the sources of this enormous growth, a controversy regarding the total factor productivity growth (TFPG) still remains in production practice and extant studies. In view of this, the purpose of this paper is to measure TFPG and to explore its sources in the industry post-WTO accession.

This study presents an innovative source analysis of TFPG. Stochastic frontier approach is adopted to measure TFPG and to explore its sources by decomposing TFPG into technical progress (TP), technical efficiency change (TEC), allocative efficiency change (AEC) and scale efficiency change (SEC). Although China joined WTO in 2001, to provide an effective baseline, the study period is from 2000 to 2017.

The empirical results reveal that TFPG presented an overall downward evolutionary trend, but it still maintained a high growth post-WTO accession. From the perspective of decomposition, TP was the main source of TFPG. Furthermore, as a neglected source, interaction effects among TP, TEC, AEC and SEC have been demonstrated to have a significant influence on the cumulative TFPG.

To make the results be reliable, the authors discuss the empirical findings mainly by revealing the reasons behind the evolutions of TFPG and its sources. Based on these revealed reasons, government and policy makers can further refine and summarize some more detailed and targeted policy implications to improve TFPG.

By providing many empirical evidences to solve the aforesaid TFPG controversy, this paper, therefore, enriches the body of knowledge on growth theories, especially at the level of industrial economics.

This study attempts to analyze energy intensity, capacity utilization (CU), output and productivity growth of aggregate manufacturing sector in India during the period 1980–1981 to 2016–2017. A decadal analysis as well as a comparison between pre- and post-liberalization period of productivity growth is also made. Total factor productivity growth (TFPG) is also adjusted with CU to obtain adjusted TFPG. The trend in energy intensity is also analyzed to answer the question of sustainability. Results shows that TFPG declined in the post-reform period, highlighting the fact that liberalization process has its adverse impact on productivity growth. From the study it is observed that a declining trend in adjusted TFPG in the post-reform period, but the rate of decline is higher. Energy intensity and CU of the Indian manufacturing industries is found to be increasing over the study period. Increasing energy intensity, quite significantly, would increase the level of pollution generated by the manufacturing industries. So, interestingly enough, this may lead to conclude that the growth of the manufacturing industries is not in line with the basic essence of sustainable development.

This paper aims to make an attempt to identify labour intensity of organized manufacturing industries in India using the Annual Survey of Industry (ASI) data at three-digit level. It estimates total factor productivity growth (TFPG) and technical efficiency for both labour intensive and all manufacturing industries during the pre- and post-reforms periods.

The study uses three approaches to estimate TFPG. They are growth accounting (GA) (non-parametric), production function with correction for endogeneity – Levinsohn-Petrin (LP) (semi-parametric) and stochastic production frontier (SPF) analysis (parametric). The study uses ASI data published by Central Statistical Organization, Government of India for the period 1980-1981 to 2007-2008 for the analysis.

The study finds that the rate of decline of the labour intensity is more pronounced in the case of labour-intensive industries than all the manufacturing industries. The results of GA method suggest that the TFPG of labour-intensive industries has declined continuously from the pre-reforms period to the post-reforms period. Similarly, LP method indicates a continuous decline in TFPG of labour-intensive manufacturing industries during the post-reforms period. Interestingly, the results of SPF method also corroborate the findings of earlier two methods at the aggregate level but vary at a certain degree at the disaggregated level.

This paper is useful in the context of India considering the importance given to labour-intensive industries by the present government in terms of reviving the sector and improving the productivity and output.

Total factor productivity growth (TFPG) is not only the technological progress. It is a boarder concept. It may be the increase in the productivity of inputs, economies of scale, capacity utilization, technological progress, etc. In this study, we have tried to estimate TFPG and its components for the manufacturing industries of West Bengal and overall India, for the period 1980–1981 to 2016–2017, using stochastic frontier approach. The main data source of this study is the Annual Survey of Industries (ASI), which is published by the Central Statistical Organization, Government of India. The entire period has been sub-divided into two phases; pre-World Trade Organization (WTO) regime (1980–1981 to 1995–1996) and post-WTO regime (1995–1996 to 2016–2017). This study also tries to make a comparative analysis between the TFPG of manufacturing sector of West Bengal and all India level for the time period mentioned above. For West Bengal, TFPG has decreased for the post-WTO regime and it has increased in post-WTO regime for overall.

The present chapter examined the behavior of relative wage rate, productivity of labor, and total factor productivity growth (TFPG) and also attempted to explore the causal relationship between relative wage rate and productivity of labor as well as relative wage rate and TFPG in food and beverage industry in India over the period 1980–1981 to 2017–2018. The result of Sen (2003) approach of endogenous structural break suggests that the series of relative wage rate, productivity of labor, and TFPG follows trend stationary process. A significant break is found for all the three aforementioned variables, being 1984–1985 for relative wage rate and productivity of labor whereas 2007–2008 for TFPG. For the three variables, growth rate has increased after the break. Bidirectional causality between relative wage rate and productivity of labor as well as relative wage rate and TFPG is evident.

This paper aims to compute total factor productivity (TFP) growth for India as well as for its 19 major states and to explore the determinants of TFP at the state level by considering the spillover effects.

TFP growth has been obtained using growth accounting equation. Further, the TFP growth estimates were used to derive TFP levels using the translog index procedure. Given the policy focus on building infrastructure and expanding financial access, we have estimated the impact of irrigation, electricity, road, health, education and financial depth on TFP using the Spatial Durbin Model to account for spillover effects.

Computing TFP growth for two sub periods, namely, 2001-2008 and 2009-2015, the study finds a deterioration in TFP growth for India as well as for 10 of the 19 states under study in the post global financial crisis period. The author find that TFP is positively impacted by irrigation, health and road infrastructure. While financial depth and education were statistically insignificant, installed capacity of electricity had a negative impact on state level TFP.

'The author provides rationale for the empirical findings considering the country context. The findings of this study act as pointers for shaping higher growth on a sustained basis in India. The study helps to assess the productivity growth in the new states, namely, Jharkhand, Chhattisgarh and Uttarakhand, that were carved out in 2000 vis a vis their parent states. This assessment is useful especially for the states of Jharkhand and Chhattisgarh which were created to address economic backwardness in certain pockets of the parent states.

First, it provides TFPG estimates for India as well as 19 major states during the 2000-2015 period. Second, this study helps to understand how TFPG for India as well as each of the 19 states have behaved in the post global financial crisis period. Third, the study helps to assess the productivity growth in the three newly created states in 2000 vis a vis their parent states. Fourth, this is the first attempt which considers the spatial interdependence among the states to estimate the impact of financial and infrastructural development on productivity in the Indian states.

In response to the 2008 financial crisis, the performance of the Chinese construction industry seems to be more successful, especially in total factor productivity growth (TFPG) and its contribution (TFPGC). Hence, the purpose of this paper is to investigate and reveal the potential successful lessons in this regard.

This study is conducted innovatively based on a special comparative analysis of TFPG and TFPGC between pre- and post-2008 financial crisis. Solow Residual Approach is used to measure TFPG and TFPGC for the period 2002–2016. Given that the crisis hit China at the end of 2008, the pre-2008 financial crisis period is from 2002 to 2008, and the post-2008 financial crisis period is limited to 2009–2016.

The results indicate that the industry indeed has better performance in promoting TFPG and TFPGC, TFP thus achieved significant accumulative growth before and after the crisis. However, from an evolutionary perspective, both TFPG and TFPGC presented an overall downward trend from before the crisis to after the crisis. Further, the game between the centrally planned economy and the market-oriented economy was identified and revealed as the essential reason behind the evolution of TFPG and TFPGC.

Some valuable lessons for policies and practices in promoting TFPG and TFPGC were summarized and learned from the Chinese experience, such as reducing administrative intervention and making the construction market play a decisive role.

This study provides some new empirical evidence to enrich the overall body of knowledge on growth theory, especially in promoting TFPG and TFPGC.

This study is an attempt to estimate the output growth and total factor productivity growth (TFPG) in Indian manufacturing industry. Most of the developed nations have been facing economic depression in its output and employment growth frequently which led to several worldwide recessions and developing nations have also been affected by these. Our objective is to examine a possible way of mitigating economic recession in the light of Indian experience. In these connections we have tried to establish a link between TFPG and indicators of economic growth like export, GDP, employment, etc. We have computed TFPG of Indian manufacturing industry for last 30 years. On an average TFPG of Indian manufacturing industry has been found negative with a declining trend. Time series analysis of our study reveals that all the variables are stationary at first difference. They are also found to be co-integrated. On the basis of volumes of India's exports of manufacturing products in 2017, we have selected top 27 destination countries. More than 60% of Indian's manufacturing products were exported to these countries in this year. We have conducted panel data analysis to find the relation between TFPG and growth of India's export. The result shows that there has been a positive and significant relation between these two. This study also found that there has been a positive relation between growth of gross value added and employment growth in Indian manufacturing industry. So, TFPG may be a useful way to mitigate economic recession.