Traditional Total Factor Productivity Research Articles

Clean air policy and green total factor productivity: Evidence from Chinese prefecture-level cities

Clean air policy is an important mechanism for improving the urban environment and promoting green economic development. Green total factor productivity (GTFP) is an important way to measure these impacts. We apply the super-efficiency slack-based measure model, considering undesirable output, and the Global Malmquist-Luenberger index to measure the GTFP of 278 prefecture-level cities in China from 2005 to 2020. We find that GTFP growth is driven by both green technology progress (GTC) and green technology efficiency change (GEC). The traditional total factor productivity is overestimated, because energy and environmental factors are not considered. GTFP growth is higher in the cities in the eastern coastal regions compared to the western regions. We analyze the effect of clean air policy on GTFP using a difference-in-differences model and spatial-difference-in-differences model, and further conduct a heterogeneity analysis and mechanism analysis. The results show that clean air policy promotes GTFP growth. In addition, there is a significant negative spatial spillover effect with respect to the impact of clean air policy on GTFP. The heterogeneity analysis results show that the impact of clean air policy on GTFP growth is lower in resource-based cities and cities in the northern region, compared with non-resource-based cities and cities in the southern region. Further, the impact of clean air policy on GTFP growth is mainly achieved through GTC, GEC, innovation, and financial development. In resource-based cities and cities in the northern region, clean air policy decreases GTFP by inhibiting GTC, innovation, and financial development.

Does the South-to-North Water Diversion Project promote the growth of enterprises above designated size in the water-receiving areas?-Evidence from 31 provincial-level administrative regions in China.

The South-to-North Water Diversion Project (SNWDP) is believed to drive the next phase of sustainable productivity growth, meeting growing water demand, so as to address increasing environmental sustainability challenges. The Middle Route of SNWDP is regarded as an extremely large long-distance inter-basin water diversion project, which has benefited Henan, Hebei, Tianjin and Beijing since 2014 with great sustainable changes to the cities, groundwater, ecological environment, industrial structure and social development of the beneficiary areas. Taking the number of industrial enterprises above designated size (IEDS) in the water-receiving areas as the research object, this paper takes the year of policy implementation 2014 as the basic time point, evaluating the change of the number of IEDS in the beneficiary areas of the Middle Route of SNWDP through difference-in-difference model. The results show that: (1) The Middle Route of SNWDP promotes the additional growth of the number of IEDS in the beneficiary areas. (2) When the Middle Route of SNWDP promotes the growth of the number of IEDS in beneficiary areas, there is no regional difference for regions with different development levels. (3) The reasons why the Middle Route of SNWDP contributes to the additional growth of the number of IEDS are composed of promoting mixed ownership reform of enterprises in beneficiary areas, increasing water supply and increasing population. However, the Middle Route of SNWDP has not had a significant impact on the traditional total factor productivity or the components of production factors, technology and capital. From the final outcome, the South-to-North Water Diversion Project has played a facilitating role in the sustainable development of large-scale enterprises in the water-receiving areas.

Artificial Intelligence and Green Total Factor Productivity: The Moderating Effect of Slack Resources

With the emergence of the digital economy, digital technologies—such as artificial intelligence (AI)—have provided new possibilities for the green development of enterprises. Green total factor productivity is a key indicator of green sustainable development. While traditional total factor productivity does not consider the constraints of natural resources and the environment, green total factor productivity remedies this deficiency by incorporating environmental protection indicators, such as pollutant emissions, into the accounting system. To further clarify the relationship between AI technology and corporate green total factor productivity, this study uses a two-way fixed effects model to examine the impact of AI technology on the corporate green total factor productivity of A-share listed companies in China from 2013 to 2020 while examining how corporate slack resources affect the relationship between the two. The results show that the AI application positively contributes to the green total factor productivity of enterprises. Meanwhile, firms’ absorbed, unabsorbed, and potential slack resources all positively moderate the positive impact of AI technology on firms’ green total factor productivity. This study offers a theoretical basis for a comprehensive understanding of digital technology and enterprises’ green development. It also contributes practical insights for the government to formulate relevant policies and for enterprises to use digital technology to attain green and sustainable development.

Ecological Efficiency Analysis of Ice and Snow Environmental Sports Industry Based on Input-Output Evaluation System

There are still some problems in China's ice and snow environmental sports industry, such as an unbalanced industrial structure and insufficient utilization of ecological resources. In order to achieve leap-forward development, the ice and snow sports industry needs to further optimize the allocation of input-output resources, enhance the overall technical capability, and improve the efficiency level of the industry. This study takes five cities of Heilongjiang, Jilin, Liaoning, Hebei, and Beijing as the research objects, constructs the input-output evaluation system of the ice-snow sports industry, measures the input-output-efficiency level of ice-snow environmental sports industry in China, and studies and analyzes the relationship between efficiency level and industrial input-output. Furthermore, this paper compares and analyzes the traditional total factor productivity and green total factor productivity of the ice and snow environmental sports industry and discusses the influencing mechanism of ecosystem efficiency of the ice-snow sports industry. The results show that the input/output ratio of different regions in 2018 was Heilongjiang (1.12) > Liaoning (1.09) > Beijing (1.08) > Hebei (1.06) > Jilin (0.81). The change in input and output level is the direct influencing factor leading to the change of efficiency, while efficiency is the core to promote the development of the ice and snow environmental sports industry. Comparing traditional and green total factor productivity, it can be found that the GameMaker Language (GML) index of green total factor productivity in Heilongjiang, Jilin, Liaoning, Hebei, and Beijing has increased by 10.50%, 9.59%, 12.22%, 11.34%, and 20.29%, respectively, in 2013. In most cases, the green total factor productivity is higher than the traditional total factor productivity, showing an environment-friendly development. The development of the ice and snow environmental sports industry, talents in the ice and snow tourism industry, urbanization level and promotion of sports cultural products in the ice and snow environment are the main external influencing factors, while the internal influencing factors are mainly reflected in the industrial structure, ownership structure, industrial relevance, industrial agglomeration degree, industrial layout, industrial scale, and differentiation of industrial product.

Green TFP Heterogeneity in the Ports of China's Pilot Free Trade Zone under Environmental Constraints.

In the context of China’s Pilot Free Trade Zone (FTZ), ports have a new opportunity to realize high-quality development. Based on the analysis of the current situation of pollutant emissions from ports in China’s Pilot Free Trade Zones (FTZs), this paper introduces environmental factors into the analysis framework of the total factor productivity (TFP) of ports in China’s FTZs, and uses the Global Malmquist–Luenberger index method to analyze the evolution trend and heterogeneity of green TFP in 28 ports of China’s 19 FTZs from 2011 to 2017. The results show that firstly, the emissions of sulfur dioxide (), nitrogen oxides () and other pollutants in China’s FTZs have been decreasing year by year. Secondly, both the green TFP and the traditional TFP of the ports in FTZs are on the rise. The absence of environmental factors leads to the underestimation of the TFP of ports. For the green TFP, the main source of its growth is technological progress. Thirdly, there is obvious port heterogeneity in the green TFP of FTZ ports. Nanjing Port has the highest green TFP growth rate, with an average annual growth rate of 21.95%. Ningbo Port, which ranks 14th, has an average annual growth rate of 5.46%. Fuzhou Port, which is rated last, has negative growth. Fourthly, there is also obvious types and regional heterogeneity in the green TFP of FTZ ports. When categorized by type, the average annual growth rate of green TFP in inland ports is significantly higher than that of coastal ports. When categorized by region, the descending order of the average annual growth rate of green TFP is the western region, the eastern region and the central region. Fifthly, the green TFP differences among the eastern, central, and western regions, as well as between inland ports and coastal ports, are shrinking. Moreover, the green TFP differences within inland ports and coastal ports and within central ports and eastern ports are also shrinking, implying there may be σ convergence. The conclusions of this paper have important implications for the scientific understanding of the heterogeneity of green TFP growth in ports in China’s FTZs, and how to promote the green development of ports in China’s FTZs under environmental constraints.

Has the Economic Structure Optimization in China’s Supply-Side Structural Reform Improved the Inclusive Green Total Factor Productivity?

One of the goals of China’s supply-side structural reform is to improve total factor productivity (TFP). Considering the problems of environmental deterioration and income disparity faced by China, this paper first incorporates environmental pollution and income disparity as undesirable outputs into the TFP analysis framework, and extends the concept of inclusive green TFP (henceforth IGTFP).We measure and analyze the IGTFP in China’s provinces from 1995 to 2017 using the Malmquist–Luenberger index, and then examine, for the first time, the impacts of economic structural optimization in the supply-side structural reform on the IGTFP. The results are shown as follows. First, China’s national IGTFP index is significantly smaller than the traditional TFP index. That is, the traditional TFP without the constraints of environmental pollution and income disparity overestimates China’s real TFP. Second, there are significant regional differences in China’s IGTFP, the average annual growth rate of IGTFP shows a gradual downward trend from east to west. This would further exacerbate the regional imbalance in China’s economic development. Third, among the structural factors in economic structure optimization, industrial structure and energy structure are negatively correlated with the IGTFP, while factor structure, labor structure and urban–rural structure are all positively correlated with the IGTFP. These results imply that the economic structure optimization driven by supply-side structural reform will improve China’s IGTFP.

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.

The Impact of Environmental Conditions on Urban Eco-Sustainable Total Factor Productivity: A Case Study of 21 Cities in Guangdong Province, China.

Environmental protection has attracted much attention. This study first describes the status of the ecological environment and then uses data envelopment analysis and the system the system generalized method of moments (GMM) model to study the relationship between the environmental status and ecological sustainable total factor productivity (ESTFP) in 21 prefecture-level cities of Guangdong Province. The main conclusions of this study are as follows. (1) The ecological index (EI), which reflects the ecological environment, shows a general trend of first decreasing and then rising. The average EI value decreased from 80.95 in 2008 to 68.71 in 2011 and then gradually increased to 74.76 in 2017. (2) The ecological sustainable total factor productivity (ESTFP = 0.960), including the two additional dimensions of the urban resource consumption index (URCI) and urban pollution discharge index (UPDI), is better than the traditional total factor productivity (TFP = 0.954). (3) The EI has a highly significant positive promoting effect on ESTFP at a significance level of 1%. The methods and results from this research provide an important scientific reference for the research on urban production efficiency and sustainable urban development in China.

Industry level analysis of productivity growth under market imperfections

PurposeThis 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.Design/methodology/approachBased 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.FindingsThe 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.Originality/valueThe 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.

Exploiting information from singletons in panel data analysis: A GMM approach

We propose a novel procedure, built within a Generalized Method of Moments framework, which exploits unpaired observations (singletons) to increase the efficiency of longitudinal fixed effect estimates. The approach allows increasing estimation efficiency, while properly tackling the bias due to unobserved time-invariant characteristics. We assess its properties by means of Monte Carlo simulations, and apply it to a traditional Total Factor Productivity regression, showing efficiency gains of approximately 8–9 percent.

Sustainable total factor productivity growth for 55 states: An application of the new malmquist index considering ecological footprint and human development index

Expanding the total factor productivity framework has a profound theoretical and practical value for sustainable growth. This paper proposes a new indicator called the “Sustainable Total Factor Productivity”. The new indicator simultaneously incorporates two comprehensive indicators, ecological footprint, which reflects human ecological consumption; and, human development index, which measures human well-being levels, into the traditional total factor productivity framework to measure sustainable growth. The sustainable total factor productivity indicator considers ecological inputs such as energy consumption, built-up land usage and biological resources occupation, while taking into account the comprehensive outputs of economic growth, life expectancy and education levels. This new indicator can better measure a state’s sustainable growth. The Data Envelopment Analysis-Malmquist method and the convergence test are employed to estimate its changes and test its convergence for 55 nations for the period 1994 to 2014. The primary results indicate that: (1) the average sustainable total factor productivity growth for these nations shows a downward trend suggesting that most states placed less emphasis on sustainable growth. The downward trend resulted primarily from the slow growth of sustainable technical progress. (2) 19 of the 55 states had positive, sustainable total factor productivity growth and achieved sustainable growth. (3) Fifty-five states and four subgroup states converged towards steady-state levels.

Exploiting Information from Singletons in Panel Data Analysis: A GMM Approach

We propose a novel procedure, built within a Generalized Method of Moments framework, which exploits unpaired observations (singletons) to increase the efficiency of longitudinal fixed effect estimates. The approach allows increasing estimation efficiency, while properly tackling the bias due to unobserved time-invariant characteristics. We assess its properties by means of Monte Carlo simulations, and apply it to a traditional Total Factor Productivity regression, showing efficiency gains of approximately 8-9 percent.

Does Foreign Direct Investment Improve Inclusive Green Growth? Empirical Evidence from China

Inclusive green growth is a sustainable development mode in pursuit of economic growth, social equity, and environmental protection. At present, a large number of articles have discussed the impact of foreign direct investment (FDI) on economic growth, green growth, and inclusive growth. However, the research about inclusive green growth is mainly descriptive. This paper constructs China’s inclusive green growth index and analyzes the impact of FDI on inclusive green growth in China. Specifically, by constructing a super efficiency slacks-based measure model (which has two undesirable outputs: income disparity and environmental pollution) to calculate the Inclusive green growth index, this paper compares and analyses the differences and regional characteristics of China’s total factor productivity, inclusive total factor productivity, green total factor productivity, and inclusive green total factor productivity. We find that total factor productivity is decreasing after considering undesirable output, and the traditional total factor productivity is higher than the inclusive green total factor productivity by 0.112; at the regional level, the trend of the total factor productivity is gradually decreasing from east to west, which indicates that there are regional differences in inclusive green growth of China, and there is room for improvement. Meanwhile, we construct a panel vector autoregressive model (PVAR) and use generalized impulse response function and variance decomposition to analyse the influence of FDI on China’s inclusive green total factor productivity. The results show that FDI is beneficial to the promotion of inclusive green total factor productivity in China, and environmental pollution in the FDI process is an important factor hindering the inclusive green total factor productivity.

Total Factor Productivity Growth in the Service Industry in China under Environmental Constraints

Existing literature does not take the environmental factors into account when it measures the total factor productivity (TFP) in the service industry. And due to a lack of environmental pollution, this traditional TFP calculation cannot reflect the real performance of TFP growth in the service industry, and even can misguide policy suggestions. This paper introduces environmental factors into productivity system in the service industry, employs Malmquist-Luenberger productivity index based on DDF to re-estimate sub-sector TFP in the service industry from 2004 to 2013, and then does a comparative analysis based on Malmquist productivity index and service environmental friendliness index. This paper finds that TFP growth in the service industry is mainly caused by technical progress, and the neglect of environmental factors overestimates not only TFP in the service industry but also its contribution to the growth of the service industry; the environmental factors affect the growth performance of the service industry. The empirical results concerning the factors influencing TFP in the service industry under environmental constraints reveal that FDI in service industry does not support the pollution heaven hypothesis. Appropriate environmental regulation not only improves the environment quality but also facilitates the productivity growth in the service industry. The development level of service industry, R&D capital, endowments structure and public environmental awareness also have different impacts on TFP in the service industry.

Aggregate green productivity growth in OECD’s countries

Most of previous research about Total Factor Productivity (TFP) at the macro level only emphasizes technical effect and technological progress at the country level, but it ignores structural effect for a group of countries at the aggregate level. This paper attempts to measure the green productivity evolution incorporating carbon dioxide emissions based on the Luenberger productivity indicator for a group of 30 OECD countries over the period of 1971−2011. We propose a novel decomposition for green productivity growth at the aggregate level which separates productivity changes into three components: technological progress, technical efficiency change, and structural efficiency change. The structural effect captures the heterogeneity in the combination of input and output mixes among countries that can impact productivity growth at a more aggregate level. In the literature, this effect has not been quantified for a group of nations such as the OECD countries. Our results indicate that the traditional TFP index underestimates green growth which is motivated by the effective and efficient environmental policies of the OECD. For the last two decades, the green productivity growth has been mainly driven by technology progress.

‘Green’ productivity growth in China's industrial economy

This paper uses a Directional Distance Function (DDF) and the Malmquist–Luenberger Productivity Index to estimate the changing patterns of ‘green’ total factor productivity (GTFP) growth of 38 Chinese industrial sectors during the period 1980–2010. Unlike the measures of traditional total factor productivity (TFP) growth, the DDF incorporates carbon dioxide emissions as an undesirable output directly into the production technology, which credit sectors for simultaneously reducing their emissions and increasing their output. Our estimates of aggregate and sector-level GTFP growth reveal that Chinese industry is not yet on the path towards sustainable, low-carbon growth. A dynamic panel data analysis of the determinants of GTFP across sectors is used to identify factors that might rectify this situation, including state owned enterprise (SOE) reform, the growth of small private enterprises, continued openness to foreign investment and higher spending on R&D, particularly in emission-intensive sectors.

Environmental efficiency, advances in environmental technology and total factor of environmental productivity of China

Purpose – This paper aims to estimate the values of environmental efficiency of each province in China. Subsequently, it analyzes the changes of total factor productivity (TFP) before and after taking the environmental factors into account. Finally, the paper measures the effect of the components of environmental TFP on the convergence of economic growth. Design/methodology/approach – The environmental control variables are taken as output variables and combined with a traditional data envelopment analysis model to build an environmental TFP Index. The growth of environmental TFP is compared among regions and the differences are analyzed. Furthermore, the decomposed components (advances in environmental technology and environmental technical efficiency) are used for regression analysis with labor productivity. Findings – The environmental efficiency of most provinces in China has improved although some regions' efficiency remains low in Northeastern China. The value of environmental TFP is higher and more fluctuant during the period of 1997-2009 than that of traditional TFP. Technical efficiency has a convergence effect on economic growth of regions/provinces, but, after adding environmental factors, it turns into a divergence effect. Research limitations/implications – Because of data limitations, this paper does not consider the impacts of human capital and other factors on in the convergence analysis on economic. Neither does it consider the use of panel data to analyze the convergence of economic growth and validate the conclusions. These are potential further research directions. Practical implications – The study confirms that improvements in environmental technologies play a dominant role in enhancing China's environmental TFP. Furthermore, it demonstrates that China's economic growth largely depends on technological progress. This finding, that China's economic growth depends on advances in environmental technology, implies that China should strive to improve its capacity for technological innovation. Originality/value – The paper measures the value of environmental efficiency in the China's provinces and analyzes the relationship between pollution and economic development in each province. Panel data are used to compare the difference among environmental TFP, environmental factors and traditional TFP. The convergence of economic growth is analyzed in respect of environmental control variables.

The sources of bank productivity growth in China during 2002–2009: A disaggregation view

This study investigates the sources of bank productivity growth in China over the period 2002–2009. In order to perform this research, we propose an advanced index – input slack-based productivity index (ISP) – a model that disaggregates total factor productivity growth into each input productivity change. Funds, capital, and employees are chosen as the inputs, whereas loans and other earning assets are outputs in this study. Our results show that technological gains transcend the efficiency regressions and result in total factor productivity growth. More specifically, technical progress in capital productivity reveals the dominant force behind the total factor technical change and productivity improvement. In addition, this paper uses these disaggregation terms to find out the competitive advantages and disadvantages of input usages for each Chinese bank. These findings indicate that the ISP index provides more insights than traditional total factor productivity indices.

Productivity measurement for international firms

This paper extends recent work by Martin (2005) on estimation of total factor productivity by allowing heterogeneity of markets in terms of competitive pressure. We show that conventional methods of total factor productivity estimation yield biased measures of TFP when firms charge market-specific prices. Specifically, if, as widely believed, exporting price-cost markups are, on average, lower than domestic markups, then traditional total factor productivity measures will substantially underestimate exporter productivity and overestimate the productivity of non-exporters. Crucially, our results provide some possible clues on why empirical studies failed to find conclusive evidence on the learning-by-exporting hypothesis.

Invention, Entrepreneurship and Prosperity: The Dutch Golden Age

The Dutch 16th and 17th centuries were a period of unprecedented economic prosperity. Since the Dutch economy was and is very small, an important source of growth was bound to be international trade. In this paper we argue that the contributions of entrepreneurship to innovation transcend the standard categories of creation of new products and processes. Entrepreneurship also finds new markets for its products and creates new modes of trade. The Dutch were the globalization pioneers avant la lettre. The same considerations apply to the later decline of the Dutch economy. The rise and decline of the Dutch Republic are well explained by a combination of the traditional Total Factor Productivity (TFP) driver, innovations, and two facets of trade, namely openness and entrepreneurship. The evidence for these contentions rests on a remarkable body of economic data that apparently are unique in the early dates to which they pertain and the extensive information they provide.