Total Productivity Research Articles

Transitioning to a green economy in China: The environmental and economic impacts of green credit.

Economic green transition is the change of economic development mode under environmental constraints; this process will generate huge demand for credit financing. Understanding the connection between credit allocation and environmental performance is crucial for the coordinated development of the economy and environment. Utilizing the Chinese Industrial Enterprises Database, I constructed a city-level green credit index and compiled panel data from 2006 to 2013 for 282 selected cities in China. A spatial model was employed to explore the influence of green credit on the economic green transition. The findings reveal a positive relationship between green credit and economic green transition during the study period. Green credit not only enhances local green total factor productivity but also exerts beneficial impacts on adjacent areas though demonstration effects. Additionally, the reallocation of credit resources and the innovation of clean technologies are identified as key mechanisms through which green credit fosters a greener economy. However, the study also finds that the impact of green credit is moderated by factors such as a high reliance on natural resources, the underdevelopment of market intermediaries, and excessive governmental intervention, which can undermine its effectiveness. Furthermore, the efficacy of green credit exhibits regional heterogeneity; it has a significant positive impact in the eastern regions of China, while its influence appears to be non-significantly positive in the central and western regions. This study enriches the research on the macroeconomic impacts of green credit, offering practical evidence and theoretical support for the implementation of green credit policies by local governments in China.

Risk tolerance towards research and development investment: the role of firm size and technology intensity

ABSTRACT This research examines how risk tolerance towards research and development (R&D) investment varies by firm size and technology intensity using a case study of four groups of manufacturing firms (i.e. large high-tech firms, small high-tech firms, large low-tech firms, and small low-tech firms) in South Korea. Our research contributes to the literature by offering the first empirical application quantifying different risk tolerances towards R&D investment of firms of varying sizes and technology intensities using total factor productivity and optimal portfolio frontiers. We find that the risk tolerance towards R&D investment is proportional to firm size, and high-tech firms tend to be more risk tolerant than low-tech firms given the same firm size. Furthermore, we find that large low-tech firms have a greater tolerance for risk than small high-tech firms when the present guaranteed return is lower, but risk tolerance is reversed as the current guaranteed return increases. These findings could be used to inform R&D project funding decisions in particular, our finding of higher risk tolerance of small high-tech firms with higher present guaranteed return suggests that government subsidies for R&D investment may function as the present guaranteed return for small high-tech businesses.

Digitalization and productivity in the Chinese wind power industry: the serial mediating role of reconfiguration capability and technological innovation

PurposeWind power is the most promising renewable energy source in China. The development of digital technologies has brought about unprecedented growth opportunities and prospects for wind power. However, the relationship between digital technology adoption and total factor productivity (TFP) in the wind power industry in China has not been empirically assessed. This study aims to clarify whether and how digital technology adoption affects the TFP of the wind power industry in China.Design/methodology/approachBased on the data of listed companies in the Chinese wind power industry from 2006 to 2021, this study proposes and verifies relevant hypotheses with two-way fixed effects regression models.FindingsThe empirical results indicate that digital technology adoption is the cornerstone of the TFP of China’s wind power industry. Reconfiguration capability and technological innovation serially mediate the above relationship. In addition, the incentive effect of digital technology adoption varies among wind power firms. The impact of digital technology adoption is more significant in firms that are old and located in economically undeveloped regions.Originality/valueThis study is one of the earliest attempts to investigate the relationship between digital technology adoption and TFP in the renewable energy sectors of emerging economies. By integrating dynamic capability theory and the analytical framework of “Capability-Behavior-Performance” into the digital context, this study offers the theoretical insights into how digital technology adoption can enhance organizational reconfiguration capability, thereby stimulating technological innovation and subsequent TFP. Additionally, the impacts of different digital technologies are estimated in entirety, rather than in isolation.

Learning by Necessity: Government Demand, Capacity Constraints, and Productivity Growth

This paper studies how firms adapt to demand shocks when facing capacity constraints. I show that increases in government purchases raise total factor productivity in quantity units at the production line level. Productivity gains are concentrated in plants facing tighter capacity constraints, a phenomenon I call “learning by necessity.” Evidence is based on newly digitized archival data on US World War II aircraft production. Shifts in demand across aircraft with different strategic roles provide an instrument for aircraft demand. I show that plants adapted to surging demand by improving production methods, outsourcing, and combating absenteeism, primarily when facing tighter capacity constraints. (JEL D22, D24, E62, L93, N12, N42, N62)

Grassland biomass allocation across continents and grazing practices and its response to climate and altitude

Biomass allocation in grasslands is key to understanding plant response to environmental changes and grazing management. Yet, global studies on how this split between above-ground and below-ground biomass varies across continents and grazing practices are notably scarce. We employ a comprehensive field-oriented grassland database to examine differences in total net primary productivity (TNPP), above-ground net primary productivity (ANPP), below-ground net primary productivity (BNPP), and the BNPP to ANPP ratio across continents and between grazed and non-grazed grasslands. Oceania showed the greatest ANPP (916 g·m−2·a−1), while Asia had the lowest (192 g·m−2·a−1). BNPP values were similar among Oceania, Africa, and Asia (∼600 g·m−2·a−1), significantly exceeding those in Europe (289 g·m−2·a−1) and North America (408 g·m−2·a−1). South America, Africa, and Oceania had the highest TNPP (around 1418 g·m−2·a−1 to 1466 g·m−2·a−1), while Europe had the lowest TNPP (344 g·m−2·a−1). The BNPP to ANPP ratio was highest in South America (4.17) and Asia (3.46). Global differences in TNPP and BNPP between grazed and non-grazed grasslands were minimal, but ANPP (169 g·m−2·a−1 and 198 g·m−2·a−1, respectively) and the BNPP to ANPP ratio (4.87 and 2.40, respectively) differed significantly. Across continents and grazing practices, climate had a greater role in regulating grassland biomass allocation than altitude, and warming may have a more detrimental impact on grazed grasslands than non-grazed grasslands. Distinct biomass allocation trends under various continental and grazing conditions exert effects on the economic and ecological functions of grasslands. Our study underscores the need for balanced grassland utilization strategies at a global scale. This involves optimizing grazing in high ANPP grasslands and protecting those with significant BNPP, thereby contributing to a sustainable and ecologically sound use of grasslands in the future.

Corporations and partnerships: Factory productivity in late Imperial Russia

Using factory-level data from an official manufacturing census, I examine productivity among two forms of enterprise in the Russian Empire from around 1908. I find that despite having 60 times more financial capital, factories owned by corporations did not outperform those owned by ordinary and limited partnerships. Although corporations were more mechanized per worker, both enterprise forms attained equal capital and labor productivity and total factor productivity. Corporations attained higher labor productivity than partnerships only in the metals and machinery industry. These findings suggest that Russian factories used the corporate form's unique advantages in a rather limited way: to build larger factories and undertake larger projects, but not to enhance productivity beyond the level of the partnership form. I also find that there were fewer accidents per worker at partnership-owned factories than at corporations.

Confucian Culture and Enterprise Total Factor Productivity

Enterprise total factor productivity is one of the important indicators to measure enterprise efficiency and innovation ability. This paper takes the a-share listed companies from 2005 to 2022 as the research sample, and empirically tests the influence of Confucian culture on the total factor productivity of enterprises. It is found that Confucian culture can significantly improve the total factor productivity of enterprises. Therefore, combined with the conclusion of this paper, it is suggested that enterprises should pay attention to inheriting and carrying forward the essence of Confucian culture in their operation and management, so as to realize long-term sustainable development and innovation-driven transformation.

Inhibit or stimulate? Green credit guidelines and corporate financialization

Although the green credit guidelines (GCGs) can force firms to engage in green transformation, it is still unknown whether the GCGs inhibit or stimulate corporate financialization. This research explores the effects and mechanisms of GCGs on financialization of heavy polluters using difference-in-differences estimators. The results indicate that the GCGs tend to strengthen heavy polluters’ motivations for precautionary saving and stimulate them to allocate liquid financial assets, while weakening their motivations for investment substitution and inhibiting their speculative allocation of financial assets. After several robustness tests, these conclusions remain valid. The mechanism tests suggest that the guidelines affect corporate financialization through increased financing constraints and reduced agency costs. Further analysis reveals that both types of financial asset allocation used by heavy polluters increase their levels of total factor productivity and green innovation. Heterogeneity analysis demonstrates that the impact of GCGs is more pronounced in nonstate-owned enterprises and firms which are located in regions with underdeveloped financial development and weak environmental law enforcement. In summary, this research explores the differentiated impacts and economic outcomes of GCGs, which not only provides insights into how financial institutions prevent corporate credit risk and achieve the targeted implementation of GCGs but also has certain reference value for the rationalization of asset allocation and green transformation for heavy polluters.

Climate Change, Biased Technological Advances and Agricultural TFP: Empirical Evidence from China

The impact of climate change on agricultural quality development under the constraint of China’s “Double Carbon” target has been widely discussed by policy practitioners and academic theorists. This paper attempts to deconstruct the logic of how climate change affects agricultural total factor productivity (TFP) in three dimensions—the structure of agricultural input factors, the change in the cropping system, and the stability of crop supply. This paper also reveals the mechanism through which biased technological progress increases agricultural TFP by weakening the magnitude of climate change and empirically tests it by using China’s provincial-level data from 2000 to 2021. This study showed that average annual temperature and annual precipitation had significant negative effects on agricultural TFP, that the number of sunshine hours had a significant positive effect on agricultural TFP, and that obvious regional differences existed in the effect of climate change on agricultural TFP. Further mechanism tests revealed that biased technological progress positively moderated the effect of climate change on agricultural TFP. Based on these findings, the appropriate countermeasures for improving climate early warning mechanisms, promoting the progress of appropriate technology, and fostering new agricultural management bodies.

How does improving agricultural mechanization affect the green development of agriculture? Evidence from China

Over the past two decades, China has actively pursued a green, low-carbon economy in response to climate change. Amidst rapid economic development, China's green total factor productivity—a key metric reflecting the nation's green development—has notably risen. As a developing country with a population exceeding 1.4 billion, agriculture plays a key role in China. China has persistently strived to comprehensively promote the scale and scope of agricultural mechanization, recognizing it as a crucial gauge to enhance agricultural productivity, thereby facilitating agricultural modernization and ensuring food security. However, can elevating the agricultural mechanization level improve China's green development within the agricultural sector? Specifically, how does agricultural mechanization (AM) affect agricultural green total factor productivity (AGTFP)? To address these questions, we assess the effects of agricultural mechanization on agricultural green total factor productivity and examine its channels using panel data from 30 provinces in China spanning from 2000 to 2021. Additionally, we investigate the heterogeneous effects under different levels of economic development, agricultural economic development, environmental regulation intensity, and agricultural technology. The results indicate that: First, the development of agricultural mechanization promotes the agricultural green total factor productivity. Second, channel analysis indicates that agricultural mechanization can bolster agricultural green total factor productivity through three channels: enhancing agricultural management level, improving agricultural factor efficiency, and fostering diversification of agricultural industrial structure. Third, heterogeneous analysis suggests that agricultural mechanization exerts a more pronounced impact on agricultural green total factor productivity in provinces characterized by lower levels of economic development, more backward agricultural economic development, higher environmental regulation intensity, and more advanced agricultural technology. This article is anticipated to furnish empirical evidence from China for developing nations seeking to foster agricultural green sustainable development through the widespread adoption of agricultural mechanization, thereby contributing significantly to global efforts to mitigate climate change.

On corporate total factor productivity: public procurement

PurposeThis study attempts to uncover the nonlinear relationship between public procurement and corporate total factor productivity (CTFP), and investigates the mediating roles of R&D investment and rent-seeking cost. Additionally, it conducts a heterogeneity analysis for firms with varying levels of political connections and corporate social responsibility (CSR).Design/methodology/approachEmploying Ordinary Least Squares (OLS) and Olley-Pakes (OP) methods, the authors gauge CTFP and manually identify government customers to quantify public procurement. Leveraging panel data from Chinese listed companies, this study explores the relationship between public procurement and CTFP.FindingsThis study unveils a U-shaped relationship between public procurement and CTFP, highlighting R&D investment and rent-seeking costs as potential mechanisms. Furthermore, it identifies heterogeneous effects among companies with varying levels of political connections and CSR on the relationship between public procurement and CTFP, including their mediating effects.Practical implicationsThis research enhances understanding of demand-side policies and provides crucial insights for the government to further improve public procurement policies.Originality/valueBy offering empirical evidence of how public procurement impacts CTFP, this paper enriches the literature on the behavioral repercussions of public procurement and the determinants of CTFP. It also overcomes the “black box” of the mechanism between public procurement and CTFP, based on the government’s dual role as a pathfinder and customer of enterprises. It broadens the application scenarios of institutional theory and principal-agent theory. Additionally, the heterogeneity analysis of firms with varying political connections and CSR extends the frontiers of related research.

ICT and Agricultural Development in South Africa: An Auto-Regressive Distributed Lag Approach

The use of Information Communication Technology (ICT) forms a significant component of the Fourth Industrial Revolution (4IR). This study examined the impact of ICT on agricultural development in South Africa utilizing time series data from 1995 to 2022. Agricultural development was measured through agricultural output and agriculture total factor productivity as dependent variables. Traditional factors of production (land, labor, and capital) together with ICT variables (mobile cellphone subscriptions, Internet usage, and fixed telephone subscriptions) were used. Additional variables such as inflation, human development, access to energy and climate change were used. Data analysis was performed using the ARDL approach. The findings revealed that mobile phone subscriptions and Internet usage positively affect agricultural output and ATFP in the short and long run despite having a negative effect through the second lag in the short run. Fixed telephone subscriptions negatively affect ATFP in the long run while affecting output negatively in the short run through the first lag. Land, human development index, access to energy, and capital generally exhibited an increasing effect on both agricultural output and ATFP both in the short and long run through the various models estimated. Climate change and inflation were generally found to affect both agricultural output and ATFP negatively in the short and long run. The study concluded that ICT plays a significant role in promoting agricultural output and total factor productivity growth. Recommendations included that the South African government should promote the digitalization of the agriculture sector through the provision of ICT infrastructure that can be utilized by both smallholder farmers and large-scale agricultural producers.

PRODUCTIVITY, EFFICIENCY AND ENTREPRENEURIAL - INNOVATIVE UNIVERSITY INDEX: AN ANALYSIS FOR UNIVERSITIES IN TÜRKIYE

The productivity and efficiency of universities were analysed in this study. The data and results of the Entrepreneurial and Innovative University Index-EIUI, which is calculated by TÜBITAK every year by considering various information for universities, were used. The study aimed to discuss the index, productivity, and efficiency results comparatively. Four-year data (2019-2022) and the index values were used. Balanced panel data analysis was performed on universities consistently included in the list each year. In the calculation of the index, a weighted sum of values standardized by the min-max method was taken into account. This is available in the calculation methodology of the index. Total factor productivity and stochastic frontier model methods were used for the analysis of productivity and efficiency, respectively. Universities that enter the index list every year and are at the top are effective, but they could not increase their productivity in the previous years. Universities established before 1992 may have approached the saturation level in terms of the input-output relationship, but it can be said that they can maintain their effectiveness. Some public and private universities that were established in 1992 and later have raised their productivity and efficiency. Although the index value and efficiency values overlapped to a certain extent, the significant differences in productivity were remarkable. While the studies in the literature focused on the meta-analysis of the index and the efficiency analysis of universities with various methods, this study presented an inclusive and comparative analysis in terms of index, productivity, and efficiency with panel data analysis.

Can green credit policy with dual-carbon targets make highly polluting enterprises “green”: A micro-analysis of total factor productivity growth

Reducing carbon emissions from highly polluting enterprises is crucial to meeting the world's overall carbon emission reduction targets. Green credit policy can be effective in guiding enterprises to reduce their carbon emissions and is essential to achieving the dual-carbon targets. This study uses micro-data from a 2017–2022 follow-up survey of industrial enterprises in China and a quasi-natural experiment to evaluate whether green credit policy aligned with the dual-carbon targets enable highly polluting enterprises to become “green” by reducing emissions. The results show that green credit policy can lead highly polluting enterprises to significantly reduce carbon emissions, and total factor productivity (TFP) growth plays an intermediary role in this transition. The different impact of green credit policy on TFP may impede the greening process for highly polluting enterprises, with this hindering effect exhibiting scale heterogeneity. This study offers empirical evidence for evaluating green credit policy aligned with China's dual-carbon target and provide insights into leveraging green credit policy to advance this process.

Examining the impact of environmental centralization on enterprise total factor productivity through a quasi-natural experiment conducted in China

This paper explores the effects and influence mechanisms of environmental centralization on enterprise technological progress and productivity in China. Taking the reform of vertical environmental governance (VEG) as a quasi-natural experiment, this paper compares the differences in total factor productivity (TFP) of enterprises in environmental centralization regions and environmental decentralization regions by adopting the staggered difference-in-differences (DID) method. The empirical results show that: (1) The average TFP of enterprises in the environmental centralization areas is 0.0598 higher than that in the environmental decentralization areas, and this average effect increases with the extension of the reform duration. (2) Environmental centralization strengthens government intervention in environmental issues. The improvement in the intensity of environmental regulation and the willingness of firm green innovation are the intermediate causes of the improvement in enterprise TFP. (3) VEG’s effect is heterogeneous regarding regional development, industry type, and enterprise characteristics. This study has empirical implications for further refining the fiscal system to leverage the role of public finance on environmental governance and enterprise development.

How can rural digitalization improve agricultural green total factor productivity: Empirical evidence from counties in China

Against the backdrop of escalating environmental pollution and resource depletion induced by traditional agricultural industry development, the imperative for agricultural efficiency and ecologically friendly practices has become pivotal for global agricultural sustainability. In the digital era, rural digitalization has substantially amplified agricultural production efficiency while notably reducing environmental pollution. This study is based on panel data from 1602 counties in China spanning from 2011 to 2020, measuring the levels of rural digitalization and agricultural green total factor productivity (AGTFP) across these counties, empirically examining their dynamic correlation. The research findings reveal: (1) A significant enhancement of AGTFP with the elevation of rural digitalization; for every 1 % increase in rural digitalization, AGTFP increases by 1.78 %. Robustness checks, including instrumental variables and quasi-natural experiments, affirm the validity of these conclusions. Furthermore, by comparing regional differences in China, it can be observed that the impact of rural digitalization on AGTFP varies across different areas: in the eastern, central, and western regions, for every 1 % increase in rural digitalization, the AGTFP increases by 2.65 %, 1.53 %, and 0.82 %, respectively. (2) Rural digitalization fosters an increase in AGTFP by stimulating rural entrepreneurial activity, with the mediation effect of rural entrepreneurial activity accounting for 3.34 % of the total effect. (3) Utilizing a threshold model, observations indicate that when rural digitalization surpasses the first threshold of 0.3200, the AGTFP coefficient escalates from 0.0462 to 0.7519. However, when rural digitalization exceeds the second threshold of 0.7118, this coefficient declines to 0.2429, signifying a nonlinear trend in the marginal effect of rural digitalization on AGTFP—initial enhancement followed by attenuation. (4) In the spatial model analysis, the study confirms spatial spillover effects of rural digitalization on AGTFP, indicating variations in spatial effects among different matrices. However, the indirect effects of rural digitalization on AGTFP, mainly influenced by the neighboring counties' digitalization levels, contribute more significantly than the direct effects. Based on these conclusions, this paper proposes augmenting investments in rural digitalization, implementing diversified rural digitalization schemes, invigorating rural entrepreneurial activity, and harmonizing regional digital development as novel approaches to enhance AGTFP, thereby fostering rural economic development.

Environmental governance’s effect on green total factor productivity in the Yangtze River Economic Belt, China

Environmental governance’s effect on green total factor productivity in the Yangtze River Economic Belt, China

The Influence Mechanism of Bidirectional Foreign Direct Investment on Green Total Factor Productivity in China’s Manufacturing Industry

The Influence Mechanism of Bidirectional Foreign Direct Investment on Green Total Factor Productivity in China’s Manufacturing Industry

The measurement, level, and influence of resource allocation efficiency in universities: empirical evidence from 13 “double first class” universities in China

China’s higher education system is shifting from quantitative expansion to connotative development to advance its quality. Since 2015, Chinese governments have been implementing a strategic policy for higher education called “double first-class”, which aims to promote a number of Chinese top universities to construct world-class universities or to establish world-class disciplines. “Double first-class” universities have received a large amount of educational resources through this policy. Taking advantage of resources efficiently is an important element in promoting the development of higher quality higher education. However, research on resource allocation in China’s “double first-class” universities is incomplete. Current research has not clarified the level of resource allocation efficiency or the factors affecting China’s “double first-class” universities. With the help of the superefficient data envelopment analysis (DEA)-Malmquist–Tobit model, this study actively explores the current status of the resource allocation efficiency of China’s “double first-class” universities to fill this gap in the field. Specifically, the development level and change trend of the resource allocation efficiency of 13 “double first-class” universities in China from 2015 to 2019 were measured with the help of the superefficient DEA-Malmquist model. The internal and external factors affecting the resource allocation efficiency of “double first-class” universities are also analysed with the help of the Tobit model. The overall level of resource allocation efficiency of “double first-class” universities is high, but the internal variability is large. From the perspective of efficiency decomposition, it is found that both technical efficiency change (EFch) and technical progress efficiency (TEch) play important roles in improving the total factor productivity (TFP) of resource allocation. Compared with TEch, EFch plays a more significant pulling role. This study confirms that the factors affecting resource allocation efficiency are complex. Among them, the regional economic environment, faculty title structure, and degree of international exchange have significant roles in promoting the resource allocation efficiency of “double first-class” universities, but local financial support and the time of policy implementation have certain negative effects.

The Impact of Quality Control Implementation on Productivity and Product Quality in Industry

Furniture production is one of the activities that has the potential to generate income for educational institutions. The furniture production process is generally carried out by experienced students utilizing industry-standard facilities, namely the Wood Construction workshop along with its machinery equipment. Therefore, the implementation of Quality Control in the production process is necessary. This study aims to determine the impact of Quality Control implementation on improving the productivity and quality of furniture products. The method used is quantitative with 4 stages of Quality Control, including product design, process planning, Incoming Quality Control (IQC), and In-Process Quality Control (IPQC). Productivity measurement is divided into 3 parts: partial productivity, total factor productivity, and total productivity, which includes labor productivity, time, and production output. Meanwhile, product quality measurement is obtained from assessments by practitioners and product quality testing according to ISO 19682. Data is processed using the path analysis method with the help of a smart PLS application. The research results show that the productivity of production output is 87.5%, categorized as good, with labor productivity of 0.125 pieces/person/day and work hour productivity of 0.25 pieces/hour/day. Product quality based on production processes is categorized as good at 83%. Meanwhile, product quality testing, including visual aspects is good (82.3%), product stability (normal), strength (normal), durability (normal), stiffness (normal 34mm/m), and drop test (normal). Based on path analysis, it is known that quality control including product design, process planning, Incoming Quality Control (IQC), and In-Process Quality Control (IPQC) has an impact on improving the productivity and quality of furniture products. the quality control carried out to increase productivity and product quality can be said to be good with the validation of the final result of 0.188 including in the good category.