This paper presents an international input-output model with supporting sectors of digital trade to estimate the value added of global digital value chains. The proposed method incorporates digital division of labor, traditional division of labor, and integrated division of labor into a unified production decomposition model to directly account the value added. The study finds that the value added of the global digital value chain shows a stable upward trend, and its share in the GVC increases significantly. The division of labor has a typical aggregation effect and ladder distribution, countries such as China, the U.S. and Germany have stronger profitability in the global digital value chain. The high-tech manufacturing is the sector with the highest concentration of value added. Changes in final demand are important factors driving the evolution of value added, but with large differences in terms of industrial impact. Global digital value chains have buffered the impact of Covid-19 on the global division of labor system to a certain extent as a stabilizer of the system adjustment. This research provides an important reference for analyzing the allocation of the added value in digital GVC and analyzing the trend of the new pattern of global division of labor in the digital economy.

Whether the digital transformation strategy led by high-quality development can promote the green technology innovation of enterprises is a major topic in the era of digital economy. Based on the data of China’s A-share listed enterprises from 2007 to 2021, this paper empirically examines the impact of enterprise digital transformation on green technology innovation. The study finds that digital transformation can effectively promote enterprise green technology innovation. Mechanism tests confirm that digital transformation can promote enterprise green technology innovation by optimizing the structure of human capital, reducing information asymmetry and strengthening the positive market expectations, and improving corporate governance. Heterogeneity analysis demonstrates that the promotion of green technology innovation by digital transformation is more prominent in state-owned, low financing constraint and technology-intensive enterprises, as well as the low-carbon pilot city and the eastern region. This paper provides empirical evidence for understanding enterprise green technology innovation driven by digital transformation, and has certain theoretical implication and practical value for China to promote digital transformation to achieve high-quality economic development.

Expanding the middle-income group is an important means to achieve common prosperity. Based on the definition and measurement criteria of middle-income groups, a statistical method to measure the share of the middle-income group using macro statistics is proposed and used to explore the inner pattern of changes in the size of the middle-income group. The paper measures the share and distribution characteristics of middle-income groups in 127 countries and regions based on the statistics released by the World Bank and focuses on the relationship between the share of middle-income group and the Gini coefficient, to summarize the reasonable share of middle-income group and the internal logic of expanding middle-income group in the context of common prosperity. The paper also measures the share of middle-income group and quantitatively analyzes its change effects using the data from 2003 to 2021 in China. Based on this, the practical path of expanding the middle-income group is analyzed to provide an objective basis for promoting common prosperity by expanding the middle-income group in the new development stage of China.

Given the shortcomings of existing middle-income group definitions, marked by a lack of theoretical foundation, mechanical operations, and low result accuracy, the paper proposes a refined definition based on vulnerability theory, characterizing the middle-income group as economically stable and non-vulnerable. And then the paper employs vulnerability estimation and kernel density methods to establish upper and lower limits for vulnerability within this group based on the China Family Panel Studies (CFPS), then estimates the proportion of the middle-income group in China, analyzes the micro driving factors of family entry and exit from the middle-income group and judges the evolution trend of the proportion of the middle-income group. The results show that: Firstly, the definition standard of the middle-income group in China can be set as 1% and 10% of the vulnerability corresponding to the family per capita persistent income, and the corresponding proportions in 2014 and 2016 are 29.82% and 32.71%, respectively. There are obvious differences in urban-rural and regional distribution, and urban and eastern regions have tended to form an olive-shaped distribution pattern. Secondly, factors such as human capital, occupation, family burden, and income structure play crucial roles in propelling families into the middle-income group. To meet the 2035 target of “achieving more significant substantive progress in common prosperity”, the per capita persistent income growth rates for the high-income and low-income groups should be a minimum of 3% and 5%, respectively, from 2016 to 2035.

Based on 48 basic economic and financial variables of 8 dimensions, we use TVP-FAVAR model to construct the indicators to measure the systemic financial risk, and construct the spillover index of systemic risk with the method of generalized variance decomposition. Then, we analyze the state of systemic financial risk and risk spillover of 16 major countries in the world from the static and dynamic point of view. Furthermore, through the construction of TVP-VAR model, we examine the cross-market contagion mechanism of systemic financial risks under the impact of economic policy uncertainty (EPU) from the perspectives of financial market and economic fundamentals. The main conclusions of this paper are as follows: ①There is an asymmetric two-directional spillover effect between systemic financial risk and EPU, in which EPU has a greater effect on systemic financial risk, and the response of systemic financial risk in developing countries to the impact of EPU is faster and greater. ②Under the impact of EPU, developed countries are the main exporters of global systemic risk, while developing countries are the main importers, and this phenomenon becomes more significant as global EPU intensifies. ③There are differences in the time and degree of direct impact of EPU on financial sub-markets and economic sectors, and the mutual risk spillover effect further raises the systemic risk. ④For China, the rise of global EPU will significantly aggravate domestic policy uncertainty, thus making the domestic economy and financial markets subject to both internal and external shocks. Besides, the net risk spillover received by China is also much higher than that of other developing countries. The findings of this study have important policy implications for dealing with the impact of global economic policy uncertainty, preventing and defusing systemic financial risk.

Based on the “6+1” strategic concept, this paper selects 33 indicators from seven dimensions to construct an evaluation index system to analyze the construction level of the modernized economic system from 2011 to 2020 in 30 provinces and four major regions of China. The study finds that the overall construction level of China’s modernized economic system has been improving year by year, but there are significant differences among the four regions. It shows an overall spatial pattern of “east-central-west” in decreasing order. The differences between regions are the main source of the overall differences, with the contribution rate of the eastern region being the highest. The spatial distribution shows a non-equilibrium and progressive evolutionary trend, with significant spatial agglomeration features. The research results enrich and improve the literature on the evaluation index system for the construction of China’s modernized economic system, providing practical reference for further promoting the construction of a modern economic system.

To promote common prosperity, it’s necessary to build an evaluation indicator system to measure the level of common prosperity. This paper emphasizes holistic, multidimensional, and long-term thinking, and highlights the bottom-line thinking in the process of Chinese modernization and common prosperity, sorts out the theoretic and statistical connotations of common prosperity, constructs an evaluation indicator system of common prosperity consisting of three first-level indicators: affluence, sharing and bottom-line guarantee, and measures the level of common prosperity at provincial and regional levels in China from 2010 to 2018, by using the macro data of national statistical department and micro survey data of Chinese Family Panel Studies (CFPS). The study finds that, at the provincial level, the level of common prosperity has continued to improve; the levels of common prosperity among provincial administrative regions has shown a convergence trend; from the first-level indicators, the level of affluence and bottom-line guarantee has steadily increased, but the level of sharing increases weakly and has large annual fluctuations; the level of inter-provincial affluence and the level of sharing show a relatively obvious inverted U-shaped relationship. At the regional level, there is an obvious trend of convergence in the level of common prosperity among eastern, central, western and northeastern China, while the gap in the level of common prosperity between the south and north is expanding faster, but the level of sharing in the north is always higher than that in the south. This paper enriches construction schemes of common prosperity evaluation systems, refining the measurement of common prosperity to the provincial level and regional level. It also provides an important reference for depicting the level of common prosperity and its inter-provincial, regional and temporal differences, identifying the focus of common prosperity and optimizing relevant policies.

The US monetary policy is one of the important disturbance factors of Global macro-economic fluctuations, which is both covert and heterogeneous, and making various economies face the complex problems of how to coordinate with the US monetary policy. Therefore, this paper measures the spillover effects of US monetary policy on 29 global economies based on both international policy coordination model and non-coordination model, and then identifies the monetary policy rules of each economy in coordination or non-coordination situations through backstepping, finally calculates the welfare losses of whether the monetary policy rules of each economy are coordinated or not. The research estimated results show that firstly, the tightening monetary policy in the United States can’t effectively reduce the global inflation, but it has led to a decrease in output gaps and an increase in macroeconomic leverage cycles in some economies. Secondly, the US monetary policy infects financial risks to the economies that are more driven by its monetary policy. Thirdly, the loss of monetary policy welfare and the negative impact of US monetary policy on the economic cycle of that economy, which adopts international monetary policy coordination when it is more driven by US monetary policy, are greatly improved. Based on the above conclusions, it can be found that strengthening the government’s intervention ability within the economy and enhancing the independence of monetary policy can reduce the negative effects of US monetary policy on each economy, and maintain internal macroeconomic and financial stability at a lower policy cost. This also provides useful decision-making suggestions for each economy to deal with the external monetary policy shocks.

Based on the theory of new economic geography and the perspective of R&D factor flow, this paper analyzes the internal mechanism of digital economy affecting regional innovation structure. On this basis, using the panel data of 285 cities in China from 2011 to 2021, this paper empirically investigates the evolutionary trend of regional innovation structure and the impact of digital economy on regional innovation structure. According to the study, during the investigation period, there is a convergence trend in Chinese regional innovation, that is, the structure of regional innovation tends to be balanced. What’s more, the digital economy has a significant positive impact on regional innovation convergence. Namely, digital economy can narrow the regional innovation gap and improve the balance of the regional innovation pattern. After replacing different weight matrices, measurement indicators, considering lag effect and eliminating abnormal sample points, these results are still robust. The mechanism test shows that the digital economy promotes the formation of regional balanced innovation pattern by affecting the flow of R&D factor. In the end, the conclusions of this paper provide useful inspiration for deepening the reform of digital economy and promoting the coordinated development of regional innovation.

With the rapid development of digital finance, the research on how the digital finance affects monetary policy and systemic financial risk has significant theoretical and practical implications. We use the TVP-VAR-SV model to examine the dynamic relationship between the digital finance, monetary policy and systemic financial risk, and then analyze the asymmetric dynamic relationship with different regulatory intensities of digital finance. Furthermore, we examine the driving role of the digital finance on economic growth and its shock effect on macro risk-return ratio. The findings of this paper are as follows: The development of digital finance exacerbates systemic financial risk, but a contractionary monetary policy helps to reduce systemic financial risk. The development of digital finance significantly affects the effectiveness of monetary policy and the contractionary monetary policy promotes the development of digital finance. The development of digital finance effectively stimulates economic growth and enhances the economic benefits of risk-bearing in the economic system. Furthermore, this article provides policy suggestions from the aspects of regulating the development of the digital financial market, optimizing the monetary policy transmission mechanism, and strengthening investor education in the digital financial market.

The core variable in the calculation of R&D capital stock is the R&D capital depreciation rate, but most of previous studies treat it subjectively. Therefore, we use the Forward-Looking Profit Model of the US Bureau of Economic Analysis to estimate the depreciation rate of R&D capital of Chinese market producers, and estimate China?s R&D capital stock from 1990 to 2021 under the framework of Chinese System of National Accounts 2016. In order to improve the accuracy and reliability of the estimation results of the depreciation rate of R&D capital, we estimate the key parameter in the model—the profit margin brought by R&D through industry-by-industry estimation. The rationality of the R&D depreciation rate estimation results in this paper is verified by the comparison of the same industry at home and abroad and robustness analysis. The final calculation results show that the average R&D capital depreciation rate of Chinese market producers is 26.37%. Considering that different production entities have different emphasis on R&D activities, we estimate China’s R&D capital stock from 1990 to 2021 on the basis of separately measuring market producers and non-market producers. The results show that from 1990 to 2021, China?s R&D capital stock has been in a growing trend, in which market producers surpassed non-market producers to occupy the leading position in R&D for the first time in 2002, becoming the main contributor to the growth of China?s R&D capital stock.

In the process of upgrading China’s industrial structure and implementing the double-cycle strategy, trade in services has become an important focus for many parties. With the rapid development of free trade zones and service trade, the demand for regional service trade data is also increasing. The statistics on trade in services at the national level has reached international standards, the trial calculation at the provincial level and in some pilot cities has carried out, but there are still problems of insufficient data sources and imperfect statistical methods in the calculation of four types of service trade: finance, transportation, insurance and travel, and local statistics of FATS is yet to be carried out. Based on the in-depth investigation in many places and departments and pilot calculation for Suzhou Industrial Park, this paper comprehensively analyzes the status quo and problems of China’s regional trade in services statistics, makes innovations in data sources, statistical methods and statistical systems, and puts forward a package solution that is operable, in line with international standards and can be replicated and promoted.

Uncertainty is the driving force of macroeconomic fluctuation; therefore, studying the effects of uncertainty on economic fluctuation has practical significance under the background of keeping the economy growing steadily and healthily. Based on the extended SV model, this paper measures the monthly economic uncertainty and financial uncertainty in China from 2002 to 2020 and uses the TVAR model to examine the regime-dependent impact of economic uncertainty and financial uncertainty on output fluctuation and price fluctuation. It finds that: Firstly, there is an interaction between economic uncertainty and financial uncertainty, and financial uncertainty has a stronger impact on economic uncertainty with a weaker lag. Secondly, compared with financial uncertainty, the impact of economic uncertainty on output fluctuation and price fluctuation is more obvious, and further expanded under the regime of high output and price volatility. Finally, in the scenario of the high growth rate of economic uncertainty, elevated financial uncertainty acts as an amplifier of output fluctuation and price fluctuation, while the low or high growth rate of financial uncertainty has an insignificant impact of economic uncertainty on output fluctuation and price fluctuation. The research takes into account both the real economy and the financial market, interprets the phenomenon of economic fluctuations from the perspective of uncertainty, and provides helpful empirical experience and policy inspiration for the formulation of macroeconomic control policies.

Promoting common prosperity poses the most challenging and arduous task in rural areas. How to get rural areas out of relative poverty and realize common prosperity are great concerns currently. This paper uses a pilot policy named “Broadband China” as a quasi-natural experiment to study the effect and mechanism of the Network infrastructure construction on the relative poverty of rural households. This study finds that the “Broadband China” strategy has significantly alleviated relative poverty of rural households, and the conclusion is valid through a series of robustness tests. Network infrastructure construction benefits rural households by effectively increasing the employment opportunities, including non-agricultural and migrant employment, and increasing the market value of agricultural products. Furthermore, heterogeneity analysis shows that Network infrastructure construction does not evenly benefit all groups, and rural male households with better education and Internet skills benefit more from it. In addition, the relative poverty alleviation effect of Network infrastructure construction is more obvious in areas where high-speed railways have not been opened and where the market segmentation is relatively high. The paper provides policy reference for the construction of Network infrastructure and the common prosperity of rural areas.

Digital trade is becoming an important part of the digital economy and a future trend of global trade. The main difference between digital trade and traditional trade is whether the transaction is realized in digital ways. Currently, most countries measure trade in services according to service types rather than transaction methods, which brings challenges to the measurement of digital trade. Based on the research of the UNCTAD from “digitally deliverable trade” to “actual digitally delivered trade”, and the OECD “Handbook on Measuring Digital Trade” about its full-caliber indicators on digital trade, the paper builds the digital trade measuring framework. Based on the calculation method of digital technology intergration ratio proposed by Jia Huaiqin (2018), we estimate the scale of Chinese digital trade from 2018 to 2020. The results show that in 2020, the scale of Chinese import and export for digital trade is 4 trillion RMB of which the scale of digitally delivered trade is 1.32 trillion RMB, the scale of digitally ordered trade in services is 0.99 trillion RMB, and the scale of digitally ordered trade in goods is 1.69 trillion RMB using the data of cross-border e-commerce. This paper deepens the research on the calculation of digital trade scale and provides a reference basis for further improving Chinese digital trade measurement and proposing strategies to promote the development of digital trade.

In the context of promoting the goal of “carbon neutrality” and launching the national carbon emission right trading market, this study uses the carbon emission right trading pilot policy implemented in China in 2013 as a quasi-natural experiment and verifies that the mechanism for solving environmental externality problems through the market can achieve a win-win, which means to achieve the dual objectives of guiding industrial enterprises to withdraw from government subsidies and encouraging enterprises to improve economic performance. This study gathers the data of main emitting industrial enterprises in the first seven pilot provinces of China for carbon emissions trading and conducts the research with difference-in-difference method. The results show that carbon emissions trading scheme can harden the soft budget constraint of industrial enterprises by stripping them of policy burdens; while inducing them to withdraw from government subsidies, it does not lead to a decline in their economic performance. The mechanism test shows that the carbon emission trading pilot policy takes the lead in encouraging pilot enterprises to increase R&D investment, makes up for the emission reduction cost through the compensatory effect of innovation, and eventually improves the total factor productivity and economic performance of industrial enterprises. This paper further finds that the carbon emission trading scheme can effectively promote the change of energy-intensive industrial enterprises to high-quality enterprises that dominate the development paradigm. In addition, it finds that quality enterprises with higher market positions show greater improvements in their performance; the internal incentive effect of economic performance is stronger in upstream industrial enterprises, private enterprises, and the regions with stricter carbon quota management. The empirical analysis of this paper provides a basis for policy choices on harmonizing the goal of carbon neutrality and high-quality economic development, and provides experience for the construction of a national carbon emission trading market.

Resource-based cities with heavy industrial structure and coal-based energy structure are important special actors of carbon emissions. At the same time, they shoulder the historical mission of energy and resources security. Whether they can reach the peak synchronously is crucial to the realization of the national carbon peak and neutrality strategic goals. The allocation of carbon emission quotas is the primary key issue, and also a hot issue in environmental economics. In this paper, 116 prefecture-level resource-based cities in China are taken as the research samples, and the H-CSW-DEA model is innovatively proposed to measure the initial allocation of carbon quotas, and PSM-LinkDEA is used to bridge. The results are compared and discussed in depth in terms of the overall level, typical resource-based cities, regional heterogeneity and type heterogeneity. It is found that the overall carbon quota of resource-based cities is positive, and according to the classification standard of carbon quota, the number of resource-based cities generally presents a positive skewness distribution. The carbon emission quota distribution of resource-based cities in different regions is heterogeneous: eastern region>central region>western region. The distribution of various types of carbon quotas in resource-based cities is heterogeneous: renewable>mature>recession>growth. Finally, this paper puts forward policy suggestions from three aspects: promoting the optimization and upgrading of industrial structure and energy structure, optimizing the regional layout of green low-carbon development, and clarifying the quantitative goals of carbon emission reduction according to local conditions. The conclusions of this paper supplement the relevant research on carbon quota in environmental economics, and have important policy implications for each resource-based city to clarify its own status and formulate scientific and reasonable carbon emission reduction paths.

Healthy ecosystems are the basis of maintaining human survival and supporting economic development, and ecosystem accounting can reflect the relationship between human welfare and ecological environment. The United Nations issued System of Environmental-Economic Accounting 2012—Central Framework (SEEA2012) in 2012, System of Environmental-Economic Accounting 2012—Experimental Ecosystem Accounting (SEEA2014) in 2014 and System of Environmental-Economic Accounting— Ecosystem Accounting (SEEA2021) in 2021. These official texts have laid a theoretical foundation for countries to carry out ecosystem accounting. This paper takes the evolution and implementation of the official texts of the United Nations ecosystem accounting as the research thread, sorts out the development process of ecosystem accounting, refines the core content of the latest international standards of ecosystem accounting (accounting object, type classification and accounting tool) and compares the evolution of the three editions of international standards, and summarizes the national experience of some countries in carrying out ecosystem accounting. At last, the paper analyzes the current situation and difficulties of ecosystem accounting in China and puts forward some policy suggestions for developing China?s ecosystem accounting.

This paper uses labor data constructed from four dimensions—industry, gender, age, and education based on hours worked to measure the improvement of labor quality in China during 1978—2018 from the industry level, and explores the impacts of adopting the numbers employed to measure labor input in existing research on the results of industry-level labor quality. From 1978 to 2018, China’s overall labor quality improvement has an average annual change rate of 2.14%, and its contribution to labor input shows a growing trend. Since 2008, labor quality has exceeded the growth rate of labor input. All industries have achieved different degrees of improvement in labor quality, and the improvement in labor quality in the service industry is even more pronounced. Using numbers employed to measure labor input overestimates the improvement in labor quality in the industrial sector, but drastically underestimates the improvement in labor quality in the non-industrial sectors, especially the service industry, and ultimately underestimates the improvement in labor quality of China’s overall economy. The industry dimension is the main source of labor quality improvement in China, but its importance has been replaced by the education dimension since 2008. The age dimension has played a certain role in promoting the improvement of China’s overall labor quality while its changes have shown a certain downward trend. Based on research findings, we suggest that the government should adhere to the integration of urban and rural development and smooth the flow of factors of production between urban and rural areas, thoroughly implement the strategy of rejuvenating the country through science and education and continue to increase investment in education, give full play to the decisive role of the market in allocating resources, continue to work to reduce barriers that impede the flow of labor across industries and encourage the labor force to flow by following the law of the market.

Water is the foundation to maintain the ecosystems. How to strengthen the rigid constraints of water resources and force industrial transformation and upgrading? Focusing on the double perspectives of resource allocation efficiency and technical compensation effect, this paper expounds the internal mechanism of water resources “fee to tax” reform to promote industrial transformation and upgrading. It is found that the “fee to tax” of water resources can reduce the distortion of industrial structure, promote the upgrading of industrial structure, increase the total factor productivity of enterprises and promote industrial transformation and upgrading. The mechanism analysis shows that on the one hand, the “fee to tax” of water resources can reduce the scale of high water-consuming industries, eliminate high water-consuming zombie enterprises and overcapacity, improve industrial water-saving capacity and optimize resource allocation efficiency by the cost effect; on the other hand, it can guide enterprises to speed up water-saving technological transformation, stimulate green innovation power, give full play to the technical compensation effect and promote industrial transformation and upgrading. The study shows that we should take the reform of water resources tax as the starting point, fully implement the determination of industry based on water, and realize the coordinated development of resources capacity and high-quality economy.

Digital transformation driven by digital technology is triggering industrial change, and high-tech industry is an important driving force for the implementation of innovation-driven development strategy. It is of great significance to study the impact of digital transformation on the innovation of high-tech industry. Based on the construction of the impact mechanism of digital transformation on high-tech industry innovation, this paper carries out an empirical study by using China’s inter-provincial panel data. Using the panel regression model, panel threshold model and Bayesian vector autoregressive model, this paper analyzes the linear, nonlinear and dynamic interactive relationships between digital transformation and high-tech industry innovation. The results show that regional digital transformation has a positive effect on innovation output. From a regional perspective, the positive impact of digital transformation on innovation output is more significant in the eastern and western regions of China. When the level of digital transformation is high, its positive impact on innovation output is greater. With the continuous improvement of innovation output, the positive impact of digital transformation on it becomes smaller and smaller. When the R&D capital is low, the impact of digital transformation on innovation output is not significant. There is a stable positive interaction between digital transformation and innovation output, but it still needs to strengthened in the long run. Finally we put forward corresponding countermeasures and suggestions: Formulate digital development strategies according to local conditions to promote the coordinated development of digital transformation in different regions; stress the deep integration of digital technology and industrial development, and strengthen the driving effect of digital transformation on innovation output; strengthen the R&D and application of digital technology, and accelerate the process of digital transformation with scientific and technological innovation.

As the backbone of data factor market cultivation, government data is the primary core data resource in the fields of digital economy development and big data development. However, the concept of government data is confused, the classification is not unified, the definition of asset scope is difficult, and the accounting of volume and value is not mature, which hinder the in-depth development and utilization of government data. Based on this, this paper starts from the connotation of data in the theoretical framework of new economic accounting in the Chinese National Account System (2016), and defines the connotation of government data based on the discrimination of the concepts of government administration data, government data and public data. It proposes that government data has the characteristics of both public and non-public, openness and sharing, with equal emphasis on political, economic and social values, and then classifies government data in combination with factors such as the generator, ownership relationship, use and openness of government data, so as to lay a foundation for the classified accounting of government data assets. In order to carry out the research on the accounting scope, volume statistics and value accounting of government data assets, this paper explores the value accounting methods applicable to different types of government data by designing the volume statistical table of government data assets, and constructs the value range of government data, providing theoretical and methodological support for relevant national departments to carry out government data statistical management.

Compiled by the Northern Song historian Sima Guang, Zi Zhi Tong Jian contains a wealth of statistical data covering household registration and population, taxation and corvée, military intelligence, agricultural production and many other aspects, which is an extremely valuable historical basis for studying the evolution of government statistics in ancient China. In order to summarize the historical experience and learn from historical wisdom, this paper is based on a detailed exploration and in-depth interpretation of statistical activities, data, statistical thought and methods in Zi Zhi Tong Jian. Focusing on typical cases and highlighting data governance, this paper portrays and summarizes the situation of government statistics in China during the Five Dynasties and its previous periods from three respects: the organization and implementation of government statistics, the coverage and main contents of government statistics, and the prevention and punishment of statistical fraud. The study finds that: firstly, government statistics in ancient China started early and became more and more mature and stable; secondly, statistics has always been highly valued, and has increasingly become an effective tool for national governance and an important basis for relevant decision-making; thirdly, the problem of statistical fraud occurred from time to time, and the efforts to prevent and punish it were great; fourthly, the degree of collection and utilization of statistical data was highly correlated with the economic and social conditions; and fifthly, statistics was deeply integrated with other fields, and there was a lack of research on specialized statistical issues.

How to promote the economy’s stable progress to achieve a long-term balance free from potential risks to help build the new development pattern is the focus of policymakers at present. We develop a dynamic stochastic general equilibrium model with multiple sectors, which incorporates household housing mortgage friction and bank loan friction, to investigate the performance of unconventional fiscal policy and macroprudential policy in regulating the housing market, financial market and the macro economy as well as the coordination benefits of the unconventional fiscal policy and credit macroprudential policy. We find that an unconventional fiscal policy works well to promote financial stability by reducing interest spread, but efficiency costs incurred have a negative effect on social welfare. A macroprudential policy can restrain the rapid growth of housing prices, and attenuate the crowd-out effect between residential and nonresidential loans, but its welfare effects turn out to be inverted U-shaped. Unconventional fiscal policy and macroprudential policy coordination performs well in leading credit capital to the real economy and mitigating the difficulty and high cost of enterprise financing, ensuring economic and financial stability and sound development.

In this paper, we use the threshold method to modify the classical Hansen-Hurwitz estimator, and propose an improved Hansen-Hurwitz estimator (IHH estimator). Theoretically, we prove the consistency, asymptotic unbiasedness and asymptotic normality of the IHH estimator. The mean square error of the IHH estimator and its unbiased estimator are obtained. In addition, based on the proposed IHH estimator, we improve the finite population estimation under stratified sampling and two-stage sampling respectively. To illustrate the effectiveness of the method proposed in this paper, we compare the mean square errors of improved estimators and traditional estimators. Numerical analysis further shows that the proposed estimator has higher accuracy.

Improving the quality of innovation is a big step for China to achieve the goal of becoming an innovation power. The digital economy has become a strategic medium to promote innovation development. In this paper, the patent citations, more recognized internationally, are taken as a proxy for innovation quality, and digital economy development index is measured by the CRITIC-G1-Bonferroni operator from three aspects, i.e. the digital environment, digital industrialization, and industrial digitalization. Based on the provincial panel data of China from 2011 to 2019, this paper first explores the direct relationship between the digital economy and provincial innovation quality through the fixed effect model and further introduces instrumental variables to solve the endogeneity. At the same time, the mediating effect model and the threshold regression model are adopted to test the indirect and nonlinear effects of the digital economy on innovation quality under the moderation of financing constraints, transaction costs, and foreign direct investment. The results show that the digital economy has a significant positive direct effect on innovation quality, and the effect decreases in the order of the central region, western region, and eastern region. Additionally, the digital economy can indirectly improve the quality of provincial innovation by easing financing constraints and reducing transaction costs, but it has a masking effect on the path of foreign direct investment. Finally, based on provincial heterogeneity, the digital economy has different threshold effects on innovation quality. Under the conditions of loose financing constraints, low regional transaction costs, and moderate foreign direct investment, the digital economy can exert a more favorable positive impact. This paper provides some reference value for the government to formulate regional differential policies and construct a favorable digital environment.

How to achieve a win-win between economic development and environmental protection is an important research topic in the new era for China to promote high-quality development. Based on the policy practice of China’s pollution charges, this paper investigates the policy effect of China’s new environmental protection tax to balance environmental performance with economic performance and the underlying micro mechanisms. Results show that charging pollution has a significant non-linear effect on enterprises’ pollution abatement and productivity improvement. Only when the pollution charges reach a threshold can it push enterprises to accelerate clean production-based technological progress and thus positively contribute to emission reduction and productivity improvement. This implies that the implementation of an environmental protection tax with a higher level of pollution charges has the potential policy dividend of achieving a win-win for China’s economic development and environmental protection. Moreover, in addition to green technology innovation, capital renewal is also an important channel for enterprises to accelerate their clean production-based technological progress. Further estimates show that the current design range of environmental protection tax rates in China is generally reasonable, but the actual tax rates in most provinces are low and may be lower than the threshold at which the environmental protection tax would have positive effects. The findings of this paper have direct policy implications for the optimal adjustment of the current environmental protection tax in China.

This paper identifies more than 450,000 Chinese digital technology patents through patent text analysis, constructs a two-stage time-space-range entropy method to measure the digital technology innovation level of 31 provinces in China from 2000 to 2020, uses Dagum Gini coefficient and variance decomposition method to explore the regional differences and sources of China’s digital technology innovation level from both spatial and structural perspectives, and uses geographic detector to explore the driving factors of the differences in digital technology innovation level. The study finds that the level of digital technology innovation in China shows a fluctuating upward trend, with a more obvious growth trend after 2010. Guangdong, Beijing, Jiangsu, Shanghai, and Zhejiang are the five provinces with the highest level of digital technology innovation. The level of digital technology innovation in China shows a spatial distribution pattern of “high in the east and low in the west” and “high in the south and low in the north”. “East-west” inter-regional difference is the primary spatial source of the digital technology innovation level. The difference in innovation quantity is the primary structural source of the digital technology innovation level. In terms of driving factors, R&D human investment is the dominant factor influencing the difference in digital technology innovation. The interactive combination of R&D human resources investment and information infrastructure is a key driver. The driving factors vary by region. This study enriches the research related to the evaluation of digital technology innovation level, and has implications for exploring the digital technology innovation level in each region.

This paper takes the requirement of the monitoring and supporting mechanism of preventing re-poverty as the starting point, and uses the micro-data of a province in the southwest of China as the sample to construct a Multidimensional Special Concern Index, which provides a scientific theoretical method for the effective identification of marginal households prone to poverty and unstable households out of poverty. After identifying the monitored persons, we analyze the potential poverty-causing factors with the Mlogit model, and analyze the mechanism of each influencing factor through mediating effect test. The empirical results shows that: Firstly, multidimensional special concern index can effectively meet the multi-dimensional needs of re-poverty prevention monitoring, and emphasize the importance of income dimension. Secondly, income deproiation, education deproiation and health deprivation are the keywork in the monitoring and supporting mechanism of preventing re-poverty, which should be paid more attention to. Thirdly, policy support for marginal households prone to poverty should focus on developing industries, promoting employment and other methods that are likely to produce long-term results in increasing income. Support for unstable households out of poverty should focus on strengthening the supply of bottom-line security policies. Fourthly, household head characteristics, family characteristics and their located areas can influence the degree of re-poverty through employment channel, industrial channel and social security channel. This paper provides a new perspective and empirical reference for the establishment of monitoring and supporting mechanism of preventing re-poverty.

Knowledge spillover is one of the important ways to enhance human capital, and then promote economic growth. The emergence and widespread use of mobile social networks (MSN) have removed the temporal and spatial constraints on information spread, but studies on whether MSN have knowledge spillover effects are rare. Taking whether communities establish WeChat group, one of the widest used MSN in China, as a quasi- experiment and using micro panel data from China Household Financial Survey (CHFS), this paper tests whether WeChat group has knowledge spillover effect with difference-in-differences (DID) and difference-in-difference-in-differences (DDD) model. We find that WeChat group can increase financial literacy of community members by 17.5 percent, and this effect is stronger for rural area, less educated or older people, which suggests that MSN can create information dividends and narrow digital divide. Further studies show that MSN can not only promote members to learn, but also motivate members to improve financial literacy by communicating. These findings suggest that in the context of the widespread popularization of mobile social networks, making full use of the knowledge spillover generated by the gathering of ideas in cyberspace can create new kinetic energy for economic development.

This paper uses the quasi-natural experiment of the national smart city pilot policy, based on the panel data of 293 prefecture-level cities in China from 2003 to 2018, uses the difference-in-difference method to evaluate the impact of smart city construction on an entrepreneurial level, and uses the interlaced DID method to test the robustness. The results show that the construction of smart city increases the entrepreneurial level of the city by about 8%, and the effect of this policy has a certain lag and accumulation. The construction of a smart city can indirectly improve the entrepreneurial level of the city by improving the business environment and the level of investment. Different cities are affected by the pilot policy differently, and cities with a great population intensity and good initial conditions (in eastern China) are affected more by the pilot policy. Due to the spatial spillover effect of entrepreneurial knowledge, smart city construction not only improves the local entrepreneurial level, but also has a significant positive impact on the entrepreneurial level of the surrounding cities, and the closer the city is, the greater the impact of the pilot policy.

Green innovation is an inevitable choice for green development and economic transformation. The study uses the implementation of the Yangtze River Economic Belt Development Strategy as a quasi-natural experiment to test the policy effect and its mechanism using Chinese provincial panel data from 2008 to 2019, the difference-in-difference method as well as the mediating effect model. The results show that: The Yangtze River Economic Belt development strategy has a significant positive impact on regional green innovation capacity, and this benchmark regression result passes six robustness tests. The heterogeneity analysis shows that the positive promotion effect of the development strategy of the Yangtze River Economic Belt on the regional green innovation capability shows a decreasing pattern in the lower, middle and upper reaches of Yangtze River, and there is obvious regional heterogeneity. The mechanism test shows that the development strategy of the Yangtze River Economic Belt can improve the regional green innovation capability by promoting environmental regulation, new urbanization and innovation investment. Among them, environmental regulation plays a complete mediating role, and new urbanization and innovation investment play a partial mediating role. The paper provides certain experience and evidence for the provinces along in the Yangtze River Economic Belt to promote their green innovation capacity.

The internet-based survey data collection has the advantages of low cost and fast speed. However, these samples are usually non-probability samples with coverage errors and selection biases, which cannot represent the population of interest and cannot be directly used for finite population inference. Data integration, which is developed to combine the advantages of probability and non-probability samples, can be used to handle the bias of non-probability samples. Our approach is to treat the non-probability sample as an incomplete sampling frame for the finite population. Assuming that probability samples and non-probability samples overlap, post-stratification and calibration estimators based on data integration are constructed. This assumption is the basis of calibration. Under this framework, the correction of measurement errors is considered. In the case of measurement errors in probability samples or non-probability samples, two ideas are proposed, namely, the calibration estimation based on unbiased true values and the calibration estimation based on correction of biased measurement values. In addition, this paper also proposes a semi-supervised classification method based on Bagging decision tree to identify the overlapping units, which makes a lot of sense in practical work.

Carrying out pollution prevention and control actions are not only necessary to improve air quality and people’s happiness, but also an effective way to promote the green transformation of economy and society in all respects and build a beautiful China. Based on the project of ambient air quality information disclosure in real time initiated by the former Ministry of Environmental Protection (MEP) in 2012, we construct a theoretical model of the relationship between environmental information disclosure, foreign direct investment (FDI) and regional pollution, then examine the impact of FDI on air pollution of 280 cities in China before and after the pilot project. The results show that: FDI aggravates air pollution significantly before the implementation of the project. However, it significantly suppresses air pollution after the implementation of the project, and the conclusion remains robust after controlling other policy pilots and expectations during the same period. Heterogeneity analysis suggests that the above inhibition effect is more prominent in low-income, low-energy consumption, low-emission and resource-based cities after the implementation of the project. Analysis of influence mechanism reveals that the changes of environmental regulation, technology choice, production scale and industrial structure caused by FDI before and after the implementation of the project are important reasons for the inhibition of air pollution. This study provides theoretical basis and empirical support on further improving the environmental information disclosure system, guiding the coordinated development of FDI and ecological environment, so as to promote high-quality economic development of China.

As the core of ICT, whether the Internet can significantly improve the total factor productivity of enterprises has been debated in the world. The paper tries to further study and judge China’s productivity paradox and draw a logical conclusion. Through comprehensive use of regular law, logical judgment, multi-index assistance and other methods, the paper carries out high-precision repair of enterprise websites, enterprise email, enterprise ID and other indicators, and obtains high-quality Internet data. By creatively using inter-provincial migration data, the paper constructs comparatively effective instrumental variables. Comprehensive use of cross recognition, OP method, LP method, panel tool variable groups, indirect propensity score matching method, direct treatment effect method and so on. Finally, it finds there is no productivity paradox in China as a whole. The paper?s benchmark econometric model shows that after controlling a number of factors, the Internet contributes at least “net” 10 per cent of TFP growth for Chinese manufacturers.

Loan prime rate (LPR) concentrated quotation and release mechanism was launched in China in 2013. Through this exogenous event, this paper tests whether and how the interest rate liberalization affect firms’ investments and investment efficiency. The empirical results show that after the launch of the LPR mechanism, enterprises whose loans are from the first quotation banks, especially non-state-owned enterprises, significantly reduce their investments, over-investments and excessive bank borrowings. Our further tests for the non-state-owned enterprises show that those firms that don’t suffer from financial misallocations reduce their investments after the interest rate liberalization, leading to significantly less inefficient investments and over-investments. Having favorable investment opportunities, the investment efficiency of non-state-owned enterprises improves due to the interest rate liberalization. It means that if enterprises are not subject to financial misallocations, interest rate liberalization can make the enterprises invest rationally. It shows that by improving the development of market mechanisms, interest rate liberalization can transform the economic development pattern and improve the efficiency of resource allocation.

Digital economy is one of the important elements to promote the optimization and upgrading of economic structure, and digitalization has become the new driving force of high-quality economic development. This paper constructs firm-level digitalization indicators based on text analysis method to examine the impact of firm’s digitalization on the productivity efficiency of enterprises by taking the non-financial A-share listed companies in China as a sample from 2000—2022. The findings show that every standard deviation increase in digitalization degree can improve total factor productivity by 3.73%, and this role has continuity. The results still hold after robustness tests using Propensity Score Matching (PSM), Difference-in-Difference (DID), remeasurement of productivity and enterprise digitalization indicators. In terms of the mechanism, alleviating financing constraints and improving innovation level are two important mechanisms. Furthermore, it finds that the contribution of firm’s digitalization to total factor productivity is more significant in the groups with a larger size, more efficient management, lower asset liquidity and lower competition. This paper not only enriches the research on the influencing factors of micro enterprises’ total factor productivity and provides empirical evidence for improving enterprises’ production efficiency, but also provides a decision-making basis for local governments to formulate differentiated digital policies.

This paper examines the effect of environmental regulation on green economic growth and its underlying mechanisms. Using the global Luenberger production index based on non-radial direction distance function, we build a comprehensive framework incorporating pollution and economic growth to measure Chinese city green economic growth rate. In face of regional imbalance, we exploit interaction term, threshold panel and partially linear functional coeficient models subject to income per capita to reveal heterogeneous effects of environmental regulation on the green economic growth of Chinese cities. The results show that environmental regulation significantly promotes urban green economic growth, mainly through the improvement of technology efficiency and technological level. The promoting impact is not significant until urban income per capita reaches 22.8 thousand yuan (at the 2004 price level), and continuously increases after hitting the critical point. This article provides fresh evidence for investigating the relationship between environmental regulation and urban green economic growth.

Strengthening the ability of financial services to the real economy is the necessary way to achieve high-quality economic development in China. As a risk carrier connecting the two, macro leverage is an important tool to promote the development of the real economy. Based on this, the paper selects the provincial panel data of China from 2008 to 2020, and uses the DEA Malmquist index to measure the efficiency of financial services to the real economy in various regions, and empirically examines the impact of macro leverage fluctuations on the efficiency of financial services to the real economy. The research finds that first, economic and financial development is impacted by external changes and policy changes. The total factor productivity of the financial services to the real economy in each province fluctuates greatly, mainly affected by the technological progress index. Second, the fluctuation of macro financial leverage has a negative effect on the efficiency of financial services, and there is a significant negative spatial spillover effect. The stability of the development of the real economy is significantly affected by the fluctuation of financial leverage. Third, the fluctuation of macro financial leverage inhibits the support ability of the financial industry to the real economy by hindering technological progress. In the background of structural leverage adjustment, this study provides a useful reference for maintaining financial stability, improving financial efficiency, and strengthening the supporting function of finance to the real economy.

Based on the perspective of industry-university-research cooperation, this paper divides the allocation process of science and technology resources into two stages: technology research and development, and technology transformation. The dynamic network SBM model is used to measure the allocation efficiency of science and technology resources in all provinces in China from 2011 to 2019, and the spatial optimization effect of the dynamic network efficiency for the allocation of science and technology resources is studied based on the spatial panel Dubin model. Studies show that: Firstly, the overall efficiency of the dynamic network for the allocation of science and technology resources is low, and the dynamic network has certain fragility, showing a tiered development trend in the eastern, central and western regions of China. Secondly, the lack of effective interaction between enterprises, universities and scientific research institutions and underutilization of the advantages of technology research and development make technology research and development hinder the improvement of the efficiency of science and technology resource allocation. Thirdly, the dynamic network efficiency of science and technology resource allocation has a significant positive spatial effect. The impact of capital transfer on the dynamic network efficiency of science and technology resource allocation shows an “inverted U-shaped” feature, and the impact of capital transfer and knowledge transformation on their own province is significantly higher than that of other provinces. Therefore, in the process of optimizing the allocation of science and technology resources, it is necessary to actively achieve the synergy of industries, universities and research, improve the capacity of capital transfer and knowledge transformation in the process of science and technology resource allocation, establish a common technology research and development platform, accelerate the spatial optimization of science and technology resources and expand its scope of influence.