Improvements In Total Factor Productivity Research Articles

Solitary or starry? Path options of the total factor productivity improvement in the aquatic seed industry from the configuration perspective

As the top supplier of global aquaculture, China possesses the largest aquaculture seed industry, which is an essential contributor to promoting the sustainable development of fisheries and safeguarding global food security. This paper aims to explore the effective path to total factor productivity (TFP) enhancement. First, the paper designs a theoretical framework for multifactor (including resource, technology, talent, capital, and system) synergy driving aquatic seed industry development based on system dynamics. Then, the driven path of multifactor synergy for TFP improvement is investigated through the fuzzy set qualitative comparative analysis method by taking six listed enterprises in the aquatic seed industry from 2017 to 2021 as the case study. Results show that single-factor inputs, such as resource, technology, talent, capital, and system, are unnecessary conditions for improving the TFP of the enterprise. Interestingly, the sufficiency analysis shows four equivalent paths of multifactor synergy-driven enterprise TFP improvement, which are further classified into three categories denominated as resource-oriented, integrated, and technology-oriented factor configurations. Of these, resource–capital and technology–talent factor synergies are two core-driven conditions, and an equivalent substitution relationship exists between capital and system. This paper provides some recommendations for policymakers and aquatic seed entrepreneurs based on the above findings.

The influence of non‐financial enterprises' financialization on total factor productivity of enterprises: Promotion or inhibition?

AbstractIn recent years, the increasing trend of financialization of non‐financial enterprises and the improvement of total factor productivity (TFP) have attracted extensive attention. The research sample for this study covers non‐financial firms listed on the Shanghai and Shenzhen stock exchanges from 2008 to 2020. Then an econometric regression model is built to examine the impact of financialization of non‐financial enterprises on enterprises' TFP. The mediation effect model is used to investigate the mechanisms of non‐financial enterprises' financialization (NFEF) on TFP. The heterogeneity in investment efficiency, property rights and political affiliation is further discussed. The findings show that the NFEF has a considerable negative influence on enterprises' TFP, which still stands after endogenous treatment and a series of robustness tests. Moreover, NFEF significantly inhibits TFP by crowding out R&D investment and significantly promotes TFP by alleviating financing restrictions. Both the ‘crowding‐out effect’ and ‘reservoir effect’ of financialization of non‐financial enterprises are verified, and the former is greater. The influence of NFEF on TFP has the heterogeneity in investment efficiency and political affiliation, but the heterogeneity in property rights is insignificant.

Will “Dual Control of the Amount and Intensity of Energy Consumption (DCEC)” Policy Increase Urban Green Competitiveness?

Urban green transformation is an important part of global low-carbon development. Coercive government policies are critical to achieving success, but, as of now, there is no unified concept of “green competitiveness”. To address climate change, it is necessary to clearly define core concepts and apply measures. For this study, “urban green competitiveness” refers to the continuous improvement of total factor productivity by cities while fully emphasizing resource limitations and environmental issues to achieve economic growth. This article focuses on a Chinese policy of “dual control of the amount and intensity of energy consumption” (DCEC), which has not been fully studied. The DCEC policy incorporates a quasi-natural experiment to assess whether urban green competitiveness has been affected. This paper builds on the multi-period DID model and explores the effect based on city-level data from 2003 to 2019. The conclusion shows that DCEC policy can address climate change by restricting energy consumption and intensity. Success is achieved through the promotion of local green patent innovation and by intensifying environmental regulation. The policy should start from a long-term perspective by promoting structural and technological changes in the economy, rather than short-term quick success and instant benefits.

The impact of digital finance on energy total factor productivity

In the context of modern scientific and technological revolution and industrial transformation, the development of digital finance is conducive to improving the ecological environment and the energy total factor productivity (TFP). In this paper, DEA cross-efficiency model is used to measure the energy TFP, and moment estimation method is used to empirically test the influence and heterogeneity of digital finance on energy TFP, and then the intermediary model is constructed to study and analyze the influence mechanism based on the sample data of 30 provinces in the Chinese Mainland from 2011 to 2018. The following research findings are obtained. First, the development of digital finance has played a significant role in improving energy TFP. Second, spatial heterogeneity exists in the process of digital finance affecting energy TFP improvement, that is, digital finance has a more obvious improvement effect on the energy TFP in central and western China than in eastern China. Third, digital finance can affect energy TFP through technological innovation; that is, the improvement of regional technological innovation is an important transmission mechanism for digital finance to affect energy TFP.

Differentiated environmental taxes and high-quality economic development in China: theory and evidence.

Environmental tax policy plays an important role in promoting economic efficiency, but it is unclear whether the taxation is well-designed and effective. The differentiated environmental tax and fee policy in China has come a long way in the past 20years, along with the aim of high-quality economic development that focuses on the harmony of environment and productivity, so it is necessary to evaluate the effectiveness of the differentiated environmental tax and fee policy. This paper constructs a pollution and environmental tax model based on the new economic geography framework to simulate the effect of environmental tax and technological innovation in the eastern and western region on pollution, output, and productivity. Using China's provincial panel data from 2005 to 2020 with difference-in-difference method, empirical evidence shows that differentiated environmental tax and fee adjustments generally boost industrial high-quality development by the industrial sulfur dioxide emission deduction and green total factor productivity improvement. When the adjustment is more differentiated between treatment and control, the effect is greater and more significant. Additionally, high environmental tax standard in high SO2 emission provinces significantly contributes to high-quality development. Progressive adjustments in 2007, 2014, and 2018 lead to heterogeneous policy effect. Technological innovation plays a mediating effect between differentiated environmental tax and high-quality economic development. The results above provide theoretical analysis and empirical study of China's differentiated environmental taxes and high-quality economic development for policy making.

Driving Impact of Digital Transformation on Total Factor Productivity of Corporations: The Mediating Effect of Green Technology Innovation

ABSTRACT Based on the data of Chinese A-share listed companies from 2010 to 2020, this article examines the driving effect of Digital Transformation of Corporations (DTC) on Total Factor Productivity (TFP) and selects Green Technology Innovation of Corporations (GTIC) as the mediating variable to test the mechanism of action of Digital Transformation of Corporations driving corporate TFP improvement. It is found that Digital Transformation of Corporations can significantly promote corporate TFP improvement; mechanism analysis shows that Digital Transformation of Corporations drives TFP improvement by promoting Green Technology Innovation of Corporations.

How Do Tax Incentives Affect Firm Value? Evidence from China

Using a unique Chinese quasi-experiment of corporate tax policy changes in 2014, we examine the effectiveness of introducing accelerated depreciation as a corporate tax incentive on improving firm value. The results show that, relative to control firms, treatment firms that received the accelerated depreciation tax treatment experience significant improvement in total factor productivity (TFP) both immediately and in the long term. We also find that the enhanced firm value is achieved through optimized capital structure and increased level of innovation. We further find that the beneficial effects are more pronounced in state-owned enterprises (SOE), firms with high labor intensity, financial constraints, high growth, and locations in high marketization provinces. Our research uniquely contributes by providing evidence of the microeconomic benefits of corporate tax policies in an emerging market.

Carbon Emission, Air Pollution, and Total Factor Productivity: Evidence from Prefecture-Level Cities in China

Based on the instrumental variable method and the panel data of 283 prefecture-level cities in China from 2004 to 2016, we explore the relationship between carbon emission, air pollution, and total factor productivity (TFP). The results show that: (1) Both carbon emission-induced and air pollution-induced environmental regulations positively promote TFP. For every 1% increase in the two indicators of the intensity of environmental regulation, carbon emission, and air pollution, TFP will increase by 1.7150 percentage points and 0.6366 percentage points respectively. (2) Carbon emission-induced and air pollution-induced environmental regulation have similar coefficients on TFP, indicating that the effects of the two are synergistic. Carbon emission has a greater impact on TFP, so enhancing environmental regulation on carbon emission can better promote the improvement of TFP. (3) Financial scale and government intervention have a significant intermediary effect between environmental regulation in both aspects and TFP.

Allocation Efficiency of Public Sports Resources Based on the DEA Model in the Top 100 Economic Counties of China in Zhejiang Province

Background: The county is the basic unit of national economic and social development, and is also the foothold and starting point of public sports services. Purpose: Taking the top 100 economic counties of China in Zhejiang Province as the research object, this study explores the allocation efficiency and influencing factors of public sports resources in the period of 2016 to 2020. Methods: The output-oriented Super-SBM model, which is used to measure the static efficiency of its public sports resource allocation, is combined with the DEA–Malmquist model to measure the total factor productivity from the perspectives of overall characteristics, regional heterogeneity, and individual differences. Moreover, we objectively evaluate the dynamic evolution and spatiotemporal characteristics of resource quality growth, financial management technology, and allocation efficiency from the horizontal cross-section and vertical time series. Results: (1) The efficiency of allocation of public sports resources in the top 100 economic counties in Zhejiang Province is relatively high, but it presents the characteristics of “extensive” allocation, and the allocation structure is unreasonable. (2) The super-efficiency gradient division of public sports resources shows that Yuhuan City ranks first with a state of super-efficiency allocation; Ruian, Linhai, Wenling, Yiwu, and Haining have a state of high-efficiency allocation; and other regions are characterized by a state of medium- or low-efficiency allocation. (3) The improvement of total factor productivity depends on the catching-up feature of technological efficiency on the production frontier, but it has not yet compensated for the negative effect of the decline of technological progress, resulting in a decline in total factor productivity with an average annual trend of 0.3%. (4) The level of county economic development has a highly significant positive effect on the allocation efficiency of public sports resources, while the per capita sports ground area has a highly significant negative effect on efficiency. The county population density has a highly significant impact, and regional factors have no significant effect on efficiency. Conclusions: The results of this study provide useful insights for the development of sound public sports service improvement policies.

The relationship between rural finance development and food ecological total factor productivity: Moderating effects of food science and technology progress

Achieving increased food production while reducing pollution emissions is an effective way to ensure food security and sustainable development. However, China's increased food production has been accompanied by resource depletion, ecological degradation and environmental pollution. The purpose of our study is to explore effective strategies to enhance food ecological total factor productivity (FETFP) in China. We considered the ecological value of food cultivation and used Global Malmquist-Luenberger (GML) index method to measure the FETFP. Besides, the entropy weight TOPSIS method is utilized to calculate the composite index of rural finance development. This study improves the precision of the measurement of rural financial development and FETFP variables. We innovatively examined the relationship between rural financial development and FETFP using Tobit model. And we used hierarchical regression analysis to test the moderating role of food science and technology progress in it. The results are as follows. (i)China's ecological value of food cultivation per hectare by region shows an upward trend. Rural finance development and FETFP tend to fluctuate upward in each region of China and the rate of increase is faster in the major food-producing regions (MFPR). (ii)Rural finance development does contribute to the improvement of FETFP. Interestingly, rural finance development in non food-producing regions (NFPR) has a greater impact on FETFP than in MFPR. (iii)Food science and technology progress moderates the relationship between rural finance development and FETFP. The regression results of group regulation show that food science and technology progress can play a stronger positive moderating role in lower FETFP provinces rather than higher FETFP provinces. This study is both a further exploration of total factor productivity improvement in food ecology and an extension of the research area of rural finance development planning.

Does forestry industry integration promote total factor productivity of forestry industry? Evidence from China

The forestry industry in China is undergoing a transformation, with integrated development and improved productivity seen as crucial to achieving efficient and healthy growth. In this study, we used the Herfindahl index method, coupling Super-CCR model, Malmquist index method, and spatial Durbin model to measure and analyze the level of forestry industry integration, total factor productivity of the forestry industry, and effects of the former on the latter of each province in China from 2005 to 2019. Results showed that, first, the level of forestry industry integration increased, but there were differences in the Northeast-Central-West-East cascade. The integration level of the forestry industry in each province was mostly at the moderate or medium-high integration stage. Second, the total factor productivity of the forestry industry increased overall, with the Central, Eastern, Western, and Northeastern regions having regional annual average values from high to low, respectively. The main driving force for the advancement of technology was the sub-index. Third, forestry industry integration played a major role in promoting total factor productivity of the forestry industry by promoting pure technical efficiency. Forestry industry integration not only affected the improvement of total factor productivity of forestry industry in the region but also had a spatial spillover effect on adjacent areas. Efforts to boost integrated forestry industry development will enhance total factor productivity growth by leveraging high-productivity agglomeration effects, strengthening regional communication and cooperation, and promoting integrated forestry industry development with adjacent regions. This work may contribute to understanding this relationship and to creating effective regional forestry development policies.

Drivers of growth accelerations: What role for capital accumulation?

Economic growth is often episodic but the ultimate drivers of such growth accelerations are not understood very well. We therefore take a different perspective and investigate what happens to production factors and productivity before, during, and after 156 growth accelerations that we identify for 148 countries between 1950 and 2019. We are particularly interested in the role that physical capital accumulation can play in this context, given recent interest in investment surges and several investment-led growth models.Our results show that physical capital accumulation accounts on average for 9% of the increase in the growth rate during an acceleration, with heterogeneity across regions, time periods, and the economies’ capital-output ratio. While growth accelerations are mainly driven by improvements in total factor productivity, we find that physical capital accumulation is an important factor for the sustainability of accelerations. Those findings are robust to various techniques for identifying growth accelerations and growth decompositions. They suggest that large “investment-led” growth accelerations are unlikely but also confirm that growth episodes that are not accompanied by solid investment patterns are likely to run out of steam.

Estimating and Decomposing the TFP Growth of Service-Oriented Manufacturing in China: A Translogarithmic Stochastic Frontier Approach

By constructing a translogarithmic stochastic frontier production model, this study explores the total factor productivity (TFP) of service-oriented manufacturing in 30 provinces in China during 2004–2020. We carried out decomposition analysis to understand in greater depth the potential drivers of TFP growth. The results show that the overall TFP of service-oriented manufacturing continuously improved during the sample period; however, the overall growth rate showed a significant slowing trend, and the contribution of TFP growth to output growth is still low. The industrial growth of service-oriented manufacturing is mainly driven by capital input, and the transformation of its growth mode from extensive to intensive has not yet been realized. Furthermore, there exists significant regional and sub-sectoral heterogeneity in the TFP growth of the industry. The decomposition of TFP growth shows that technological progress and technical efficiency are the main sources of TFP growth, but the growth rate of technological progress is declining gradually, and its driving effect on TFP is weakening. The deterioration of both scale and allocation efficiency hinders the improvement of TFP in service-oriented manufacturing, and there is still room for the industry to improve its TFP level by improving scale efficiency and allocation efficiency.

Spatial-Temporal Pattern of Agricultural Total Factor Productivity Change (Tfpch) in China and Its Implications for Agricultural Sustainable Development

With increasing tension between humans and land, and arising pressure on food security in China, the improvement of total factor productivity is important to realize agricultural modernization and promote rural revitalization strategy. In this study, we applied the DEA-Malmquist index method to measure the growth of China’s agricultural total factor productivity and its decomposition indexes at the prefecture-level city scale from 2011 to 2020. We found the average annual growth rate of agricultural total factor productivity was 4.5% during this period, with technical change being the driving factor and technical efficiency change being the suppressing factor. There is an initial decrease and then an increase in the Dagum Gini coefficient. The cold and hot spot areas of agricultural Tfpch were clearly formed. During the decade, the gravity center of agricultural Tfpch has migrated from the northeast to the southwest in general. Based on the characteristics of agricultural Tfpch, China is classified into four zones. In the future, the Chinese government should balance the government and the market mechanism, improve the agricultural science and technology innovation system and technology adoption promotion system, and implement classified policies to improve agriculture production efficiency.

Carbon pricing and enterprise productivity-The role of price stabilization mechanism

Total factor productivity (TFP) is widely used to evaluate the development quality of the economy, and carbon price stabilization mechanism (CPSM) has been introduced to reduce the climate policy uncertainty. Whether and how the CPSM can affect TFP is an issue of great interest. Using a unique panel dataset of China's 494 listed firms in 8 carbon intensive sectors from 2006 to 2019, we examine the effectiveness of the CPSM in China's carbon emission trading scheme (ETS). The results show that the carbon ETS with CPSM which has clear price corridors can improve the TFP by 0.381, the ETS with CPSM which has no explicit price ceiling or floor could improve TFP by 0.198, while the ETS without CPSM has decreased TFP by 0.352. The heterogeneity analysis indicates that the CPSM is effective to improve the TFP in power generation, building materials, nonferrous metals, and chemical sectors. Moreover, in terms of mechanisms, the CPSM can improve the TFP through promoting technological innovation and easing financing constraint. Our findings confirm the effectiveness of CPSM on the improvement of firm-level TFP and provide some key implications on how to design an effective CPSM.

Towards a better measure of productivity in India: a case of chemical and chemical products industry

PurposeA 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/approachThis 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.FindingsThe 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 implicationsThe 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/valueThis 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.

The river chief system and the total factor productivity in China: Evidence from the industrial enterprises database.

Balancing water environmental protection and economic growth is a priority for the local governments. Many literature analyses found that the reform of the River Chief System (RCS) had a significant effect on water quality improvement in China; however, it is important and necessary to comprehensively assess the impact of the RCS on the total factor productivity (TFP) of industrial enterprises, which provides a realistic basis for the decisions of local governments. This paper uses the quasi-natural experiment of the RCS in China and data from Chinese industrial enterprises to analyze the impact of the policy reform on the total factor productivity (TFP) of enterprises and the influence mechanism. The empirical analysis finds that the TFP of industrial enterprises in the reformed areas of the RCS is significantly lower than that in the non-reformed areas. This indicates that the implementation of the RCS is not conducive to the improvement of TFP of industrial enterprises. And this effect is mainly generated by reducing the output level and capital allocation efficiency of industrial enterprises. Meanwhile, the impact of the RCS on the TFP of industrial enterprises exists heterogeneity.

Did New Retail Enhance Enterprise Competition during the COVID-19 Pandemic? An Empirical Analysis of Operating Efficiency

The question concerning how digital consumption demand has been adapted and how matching business models have been built has become an important practical problem in the digital development of the retail industry. Considering the effects of COVID-19, whether new retail enterprises can maintain adequate competitiveness and risk resilience in the post-pandemic era deserves in-depth study. In comparing the development of traditional retail and new retail enterprises, we extracted and evaluated key factors of enterprise operating efficiency. Then, we measured the transformation efficiency of 65 enterprises in China listed in 2016 and 2020 by establishing a DEA model and the Malmquist index method. Finally, based on an empirical analysis demonstrating the necessity of traditional retail transformation, we analyzed retail enterprises’ efficiency and dynamic efficiency changes. The results show that the operating efficiency of enterprises using the new retail model was higher than those using the traditional retail model. The technical efficiency and total factor productivity were significantly improved after the new retail model was applied. Both technological progress and improved technological efficiency contributed to the improvement in total factor productivity during the COVID-19 pandemic.

Industrial Structure, Employment Structure and Economic Growth—Evidence from China

This paper takes China’s economic data from 1978 to 2020 as a sample, combined with indicators such as a correlation coefficient, degree of deviation, and employment elasticity, to carry out a correlation analysis on employment structure, industrial structure, and economic growth. On this basis, a regression model is established to characterize the impact of economic structure deviation on economic growth, and the linkage relationship between employment structure, industrial structure, and economic growth is further explored through a vector self-regression model. The research results show that: the degree of deviation of China’s economic structure is weakening, and the economic structure is continuously optimized; the improvement of the degree of deviation of the economic structure has a significant contribution to China’s economic growth; the impact of the industrial structure on the employment structure is first strong and then slow; the impact of economic growth on the industrial structure is lagging and long-term; the impact of the optimization of the employment structure on economic growth is most obvious in the early stage; the impact of economic growth on the employment structure is more direct; the adjustment of the industrial structure shows a certain stickiness; and that economic transformation and high-quality development require continuous advancement. This paper describes the impact of structural deviation on economic growth and reveals the interactive impact of industrial structure, employment structure, and economic growth, which can provide decision-making reference for policy makers. Specifically, it includes formulating policies to realize skills spillover to improve the employment structure; formulating policies to promote industrial integration to optimize industrial structure; formulating policies to encourage innovation so as to promote the improvement of total factor productivity and then drive the adjustment and optimization of industrial structures and employment structures; and finally, encouraging policy makers to ensure the persistence and consistency of relevant policies so that the effects of relevant policies can be truly realized.

Does environmental regulation affect capital-labor ratio of manufacturing enterprises: Evidence from China

Currently, China faces the dual pressures of finding ways to address the unstable ecological environment improvement and rising labor costs. All sectors of society are concerned about how to perfect the structure of enterprise factors input to improve production efficiency and adapt to high-quality economic development. This paper examines the impact of environmental regulation on the capital-labor ratio of manufacturing enterprises in China. The results indicate that the implementation of the new EPL (Environmental Protection Law) increases the capital-labor ratio of heavy polluting manufacturing enterprises. This conclusion is still robust to parallel trend tests, considering sample selection bias, random factors, as well as expected effects. Enterprises response to the new EPL by increasing capital factors input and hiring high-skilled labor, which is in line with the capital-skill complementarity hypothesis and reflects the views of Karabarbounis and Neiman (2014). In addition, this study investigates the effects of capital deepening on the production and operational efficiency of heavy-polluting manufacturing firms. Results show that the implementation of the new EPL can facilitate the reduction of enterprise's production costs and the improvement of total factor productivity.