Total Factor Productivity Growth In China Research Articles

Has R&D contributed to productivity growth in China? The role of basic, applied and experimental R&D

Since the early 2000s, R&D expenditure in China has increased rapidly, with the country having the third highest R&D expenditure, next only to the OECD and USA, and having surpassed Japan since 2009. Furthermore, policies in China in recent years have emphasized the need to conduct more basic and applied R&D in order to overcome technological bottlenecks and risks in access to advanced technologies when faced with international geopolitical tension. However, in the meantime, the trend in measured total factor productivity (TFP) in China has been downward since 2010. A lack of TFP growth despite the significant investment in R&D raises the question of the impact of R&D expenditure on productivity growth in China. Therefore, this study aims to investigate this issue and estimate the effects of three types of R&D stocks (basic, applied and experimental R&D stock) on TFP in China, using newly constructed provincial panel data in China from 1998 to 2018. Various empirical models and control variables are adopted to take into account non-stationarity and spatial spill-over of the provincial R&D stock values over time. The analysis results are robust to various specifications and reveal a significant positive effect of overall R&D and experimental R&D on TFP in China, but basic R&D exerts no significant results, and the effects of applied R&D are mixed across specifications. Further analyses using the 1991–2018 national data demonstrated largely consistent results. These results suggest that experimental R&D has been crucial for enhancing TFP growth in China during the decades investigated, but evidence of basic and applied R&D driving TFP growth in China is lacking.

The nexus of foreign direct investment and agricultural productivity: does absorptive capacity matter?

PurposeThis study aims to examine the complex effects of foreign direct investment (FDI) on China’s agricultural total factor productivity (TFP) from 2005 to 2020. It also explores the role of absorptive capacity as a moderating factor during this period.Design/methodology/approachEmploying provincial panel data from China, this research measures agricultural TFP using the Stochastic Frontier Approach (SFA)-Malmquist method. The impact of FDI on agricultural productivity is further analyzed using a nondynamic panel threshold model.FindingsThe results highlight technological progress as the main driver of agricultural TFP growth in China. Agricultural FDI (AFDI) seems to impede TFP development, whereas nonagricultural FDI (NAFDI) shows a distinct positive spillover effect. The study reveals a threshold in absorptive capacity that affects both the direct and spillover impacts of FDI. Provinces with higher absorptive capacity are less negatively impacted by AFDI and more likely to benefit from FDI spillovers (FDISs).Originality/valueThis study provides new insights into the intricate relationship between FDI, absorptive capacity and agricultural productivity. It underscores the importance of optimizing technological progress and research and development (R&D) to enhance agricultural productivity in China.

Measurement and Multiple Decomposition of Total Factor Productivity Growth in China’s Coal Industry

Optimizing the industry development system and implementing a high-quality development strategy in China’s coal industry require us to grasp the overall status and regional differences of industrial development. Measuring and decomposing the total factor productivity growth of the coal industry is a necessary prerequisite. In this study, we estimated the total factor productivity (TFP) growth of coal industry in 24 major coal-producing provinces in China by constructing a stochastic frontier analysis (SFA) model based on a translog production function and decomposed it into technological progress change (TC), technical efficiency change (TE), scale efficiency change (SE), and factor allocation efficiency (AE). After analyzing the temporal evolution characteristics of TFP growth and its decomposition terms, we also characterized the spatial characteristics by region and province. The results showed that TFP growth in China’s coal industry is on the rise, with TC growth being the main driving factor of this; additionally, the weak growth of SE and AE also plays a limited role in this increase, while the decrease in TE hinders this trend. There are also significant regional differences in the TFP growth of China’s coal industry, with a ranking of central > west > east > northeast. Drivers of TFP growth vary between regions or in different provinces within the same region.

Green Growth, Carbon Intensity Regulation, and Green Total Factor Productivity in China

Based on input-oriented Malmquist productivity index and parametric decomposition approach, this paper measures China’s green total factor productivity (TFP) index and its growth sources using a panel dataset of 30 provinces of China mainland from 1997 to 2014, and assesses the effect of CO2 intensity regulation on the green TFP growth in China. The results show that the green TFP has been growing at a yearly averaged rate of -1.51% during this period. The results also indicate that the policy of CO2 intensity regulation does not generate significant effect on the green total factor productivity of China’s provinces when using the two stage least squares (2SLS) estimator to control for the potential endogeneity biases. On the other hand, there exists significant heterogeneity in the effect of the CO2 intensity regulation on the green TFP of China’s provinces. Specifically, the CO2 intensity regulation promotes the green development performance of provinces in the eastern area, while it does not generate obvious impacts on the green TFP of provinces in both central and western areas.

Heterogeneity of Green TFP in China’s Logistics Industry under Environmental Constraints

In the context of China’s supply-side structural reform and the concept of green development, we introduce the energy and environmental factors into the analytical framework of the total factor productivity (TFP) of the logistics industry and use the Global Malmquist–Luenberger index method to analyze the evolution trend and heterogeneity of green TFP in the logistics industry of 30 provinces (cities and districts) in China from 2003 to 2017. The results show that, firstly, the green TFP and traditional TFP of China’s logistics industry are both on the rise and the absence of energy and environmental factors will lead to the overestimation of TFP of the logistics industry. Whether it is green TFP or traditional TFP, the main source of its growth is technical progress. Secondly, there is obvious regional heterogeneity in green TFP of logistics industry. Under the three regional division standards, the average annual growth rate of green TFP is from high to low in the order of eastern, western, and central regions. Under the eight regional classification standards, the eastern coastal economic zone, the southern coastal zone, the northern coastal zone, the northeast region, the middle reaches of the Yellow River, the southwest region, the middle reaches of the Yangtze River, and the northwest region are in order from high to low. Thirdly, there is obvious interprovincial heterogeneity in green TFP of the logistics industry. The highest growth rate of green TFP is in Zhejiang, followed by Jiangsu and Guangdong, and the slowest growth rate is in Chongqing. The technical progress of logistics industry in most provinces contributes more to the growth of green TFP. Fourthly, the differences of green TFP in the three regions of the east, center, and west are shrinking, which may be σ convergence, but the differences among the three regions are expanding. Compared with the existing literature, this paper applies the measurement framework of green TFP to China’s logistics industry and investigates the regional and provincial heterogeneity of green TFP in logistics industry. The conclusions are significant to understand and grasp the heterogeneity of green TFP growth in China’s logistics industry under environmental constraints and how to promote the development of green logistics in China.

Haze pollution, new-type urbanization and regional total factor productivity growth: based on a panel dataset involving all 31 provinces within the territory of China

Purpose This paper aims to analyze the spatiotemporal heterogeneity of regional total factor productivity (TFP) growth and explores how haze pollution and different levels of new-type urbanization affect China’s economic growth. Design/methodology/approach This paper constructs an index for evaluating the TFP growth of China’s 31 provinces by integrating slack-based measures and the Global Malmquist (GM) productivity index. Meanwhile, the panel threshold estimation method is used to examine the complex relationships among haze pollution, new-type urbanization and TFP growth. Findings The results reflect conspicuous spatiotemporal heterogeneity in TFP growth in China. Interestingly, the influence of haze pollution on TFP growth is limited by the “critical mass” of new-type urbanization in China. When new-type urbanization does not cross the first threshold, haze pollution has a negative but non-significant effect on TFP growth. When new-type urbanization crosses the first threshold but not the second, haze pollution has a significant positive impact on TFP growth. When new-type urbanization crosses the second threshold, haze pollution significantly and positively affects TFP growth with the strongest positive effect. Originality/value This study innovates by combining haze pollution and TFP growth and proposing an integrated framework from the perspective of new-type urbanization, providing insight into how different degrees of new-type urbanization impact the mechanism between haze pollution and TFP growth. Using panel data in China and emphasizing green development, a sustainable economy and new-type urbanization, this study contributes to the current studies on haze pollution and economic development based on developed countries.

Yanqun Zhang. Productivity in China: Past success and future challenges

The present paper discusses total factor productivity (TFP) in China, including its past success, the current slowdown, and the potential for future growth. It begins by documenting the development of TFP growth over the past three and a half decades, its driving forces and its contribution to the economic growth of the country. It then analyses the reasons for the current slowdown of TFP and economic growth, addresses the institutional imperfections that hinder growth, and explains the government policies and strategies aimed at fostering TFP. Next, it explores the potential for TFP growth from the perspective of institutional reform, investment in research and development and human capital. The paper concludes that although the resources of the past successful TFP have decreased or diminished, further institutional reform, increasing investment in research and development and human capital, and strategies promoting indigenous innovation will become new engines for future TFP growth in China. As the country’s TFP is still at a low level compared with advanced economies, there is large scope for China to maintain relatively high TFP growth, although uncertainty and risk are associated with this process.

Productivity Growth-Accounting for Undesirable Outputs and Its Influencing Factors: The Case of China

Presently, China’s social development is facing the dilemma of supporting economic growth and reducing emissions. Therefore, it is crucial to analyse productivity growth and examine its relationship with influencing factors in China. This study evaluated the total factor productivity (TFP) growth of 30 provinces in China by adopting the Malmquist-Luenberger (ML) productivity index and incorporating undesirable outputs from 2011–2014. Then, a Tobit regression model was employed to explore the factors that influence China’s TFP growth. The results show that the average annual growth of the Malmquist-Luenberger productivity index was lower than that of the traditional Malmquist (M) productivity index growth during the research period. The findings reveal several key conclusions: First, the true TFP growth in China will be overestimated if undesirable outputs are ignored. Second, technical changes are the main contributor to TFP growth. Third, there are huge regional disparities of productivity growth in China. Fourth, coal intensity, environmental regulations, and industrial structure have significantly negative effects on productivity growth, while real per capita gross domestic product (GDP) and foreign direct investment (FDI) have strongly positive effects on productivity growth.

Capital Formation and Agricultural Growth in China

The paper considers the role and determinants of capital formation in Chinese agriculture and, in particular, the effects of capital formation on agricultural total factor productivity (TFP) growth. The results show that capital investment in agriculture by both government and farmers has risen significantly in the past two and a half decades, particularly in recent years. As China remains in the early stages of agricultural policy transition, its political economy would suggest that there will likely be more public investment in, and more subsidies to, agriculture in the coming years. Increased public investment in agriculture appears to have also induced increased farmers' capital formation in agriculture. Credit policy, the overall growth of farmer's income, rural wages, and comparative advantage of commodities are important factors that may facilitate farmers' investment in agriculture. The results also show that the successful growth of China's agriculture has been associated with its high TFP growth. Both public and private agricultural capital formations have played an important role in raising China's agricultural productivity. The TFP decomposition analyses show that technological change is a primary driver of the TFP growth in China's agriculture.

PRODUCTIVITY GROWTH AND POLICY IMPLICATIONS FOR CHINA'S DAIRY FARMS

Over the last five years, China has significantly expanded its dairy cow numbers and increased its dairy processing capacity in an attempt to meet increased demand for dairy products. However, China's net import of dairy products has expanded at a growth rate in excess of 30% during the same period. To consider why China is still struggling to meet rising dairy product demand in China in the new millennium, this paper employs a new set of farm-level survey data and Malmquist productivity indices to empirically estimate and decompose Total Factor Productivity (TFP) growth on China's dairy farms. The results show that TFP growth has been positive and the increase in productivity has been mostly driven by technical efficiency change. However, the new results show that on average, the same farms remain behind the advancing technical frontier. We also find that one of the drivers of the dairy farms' productivity advances is the relatively robust rate of scale efficiency change. The results suggest that efforts to increase the adoption of new technologies and to adopt better advice on how to use the technologies and manage production and marketing within the dairy farm sector, will likely further increase TFP growth in China.

Productivity growth and environmental regulations - accounting for undesirable outputs: Analysis of China's thirty provincial regions using the Malmquist–Luenberger index

This paper employs the Malmquist–Luenberger (ML) productivity index to evaluate China's growth in total factor productivity (TFP), incorporating undesirable outputs, during the period from 1989 to 2008. The ML productivity index and its components (technical and efficiency changes) are derived from the directional distance function which gives credit for an increase in good outputs and for reductions in undesirable outputs. The average annual ML productivity growth, accounting for undesirable outputs, is 2.46%, whereas the value of the traditional Malmquist productivity index is 4.84%, showing that the true TFP growth in China is overestimated if undesirable outputs are ignored. We explore the strictness in enforcing environmental regulations and its impact on improvements in ML productivity. The results show that, the enforcement of environmental regulations in China is, in general, far below the levels achieved in the best performing regions, and that the more stringent enforcement of environmental regulations would help to improve ML productivity growth in China.

The total factor productivity in China and India: new measures and approaches

PurposeThis paper aims to measure and compare agricultural total factor productivity (TFP) growth in China and India and relates TFP growth in each country to policy milestones and investment in agricultural research.Design/methodology/approachTFP is measured using a non‐parametric Malmquist index which allows the decomposition of TFP growth into its components: efficiency and technical change.FindingsComparing TFP growth in China and India it is found that efficiency improvement played a dominant role in promoting TFP growth in China, while technical change has also contributed positively. In India, the major source of productivity improvement came from technical change, as efficiency barely changed over the last three decades, which explains lower TFP growth than in China. Agricultural research has significantly contributed to improve agricultural productivity in both China and India. Even today, returns to agricultural R&D investments are very high, with benefit/cost ratios ranging from 20.7 to 9.6 in China and from 29.6 to 14.8 in India.Originality/valueThe applied methodology and the comparison between TFP growth patterns contribute to a better understanding of the consequences that the different approaches to agricultural reform followed by China and India had on the performance of agriculture in both countries.