NetWork
Institutional Openness and Firms' Labor Share:A Theoretical Model and Empirical Evidence
YANG Hang;AI Xiaoqing;As testbeds for institutional openness,the Pilot Free Trade Zones(PFTZs) affect the national labor share by expanding openness and unlocking institutional gains.The Diamond-MortensenPissarides framework is extended to model how PFTZs policies affect firms' labor shares,and the resulting predictions are tested using a staggered difference-in-differences design.The results show that establishing PFTZs significantly raises firms' labor shares, a finding robust to instrumental-variable estimation,heterogeneity-robust estimators, and other checks.Mechanism tests indicate that PFTZs raise labor shares by strengthening market competition,curbing capital deepening,reducing tax burdens,and lowering management costs.The effects are stronger for labor-intensive,small and medium-sized, and lowproductivity firms, as well as for priority liberalization sectors such as oil and gas, biomedicine,financial leasing,and global repair services.Regionally,the effects are significant in eastern coastal and inland areas but insignificant in border regions.Further analysis shows that AI adoption and the use of data as a factor of production both attenuate the positive effect of PFTZs on firms ' labor shares.PFTZs also raise average pay per employee and average pay for nonmanagerial workers,while lowering average managerial pay and within-firm wage inequality.By identifying an institutional-cost channel,the study broadens existing explanations of how PFTZs affect the labor share and offers policy implications for advancing common prosperity and Chinese modernization.
The Policy Effect of Changing from Business Tax to VAT on Improving the Accuracy of Industry Classification Statistical Data
XU Yonghong;XUE Zhaoqin;JIANG An;Since 2016,China 's transition toward high-quality economic development and its pursuit of mutually beneficial international cooperation have heightened the demand for precise economic and social governance.Policymakers and scholars alike are increasingly calling for macro-statistical data that are more accurate,detailed,and aligned with international standards.However,statistical accuracy continues to be affected by industry classification practices formed during earlier periods of rapid growth, when mixed operational structures were common.A key source of inaccuracy lies in the misclassification of auxiliary service activities within enterprises.In China,auxiliary units are typically classified according to the primary industry of their parent enterprise.This practice,however,diverges from the 2008 System of National Accounts(SNA 2008),which stipulates that auxiliary units that are geographically separate or maintain independent accounts should be recorded as distinct statistical entities,even if they lack independent legal personality.This study focuses on how China's " Business Tax to Value-Added Tax Reform "(B2 V Reform)addresses this statistical discrepancy.The reform reduced the tax burden on smaller auxiliary units by shifting them from the business tax regime to the value-added tax system, distinct from their parent enterprises.This change creates a strong economic incentive for firms to legally separate their auxiliary service departments.As a result,the reform promotes more accurate industry classification,especially for diversified enterprises in sectors such as manufacturing and mining,whose core activities involve tangible goods production.Given these economic-statistical linkages,the B2 V Reform offers a valuable opportunity to evaluate the accuracy of industry classification data and to inform adjustments to historical statistical records.Using provincial panel data from 2003 to 2021,this paper applies a three-dimensional time-based analytical framework to empirically assess the impact of the B2 V Reform on the accuracy of industry classification data and to examine variations across sectors.Exploratory adjustments are also made to relevant historical data.The findings indicate that the reform significantly improved data accuracy in pilot industries during its initial phase, while its effect on other industries in later stages was more limited.Heterogeneity analysis reveals that the reform had the strongest impact on the "information transmission,software,and information technology services" industry and the "leasing and business services" industry.After historical data adj ustment, employment figures in these two corrected sectors-based on urban nonprivate units-exceed the originally reported values.This outcome confirms that the B2 V Reform helps mitigate the underestimation of historical data in related service industries.Overall,this study validates the role of the B2 V Reform in improving the accuracy of industry classification data.The findings are expected to help reduce statistical discrepancies in China ' s official practice and to provide a useful reference for the National Bureau of Statistics in revising economic statistical data.
Research on the Spatiotemporal Evolution and Development Obstacles of New Quality Productive forces's Ecological Environment
XU Hao;FENG Tao;Accelerating the cultivation of new quality productivity is the key to China 's current economic transformation and upgrading,and optimizing the ecological environment for the development of new quality productive forces is the prerequisite for accelerating the cultivation of new quality productive forces.Firstly,based on the connotation of the Marxist concept of productive forces,this paper analyzes the ecological environment factors of the development of new quality productive forces from the perspective of innovation value chain.Then,an evaluation index system for the ecological environment of new quality productive forces is constructed from five dimensions:organizational competition,factor input,development output,market environment and policy incentives.Using data from 30 mainland provinces in China from2013 to 2022 as samples,entropy weight method,spatial Moran index,and obstacle degree model are used for analysis.The results show that the overall ecological environment level of China ' s new quality productive forces is on the rise,with the eastern region significantly better than the central and western regions,and the northeast region deteriorating year by year;In 2022,Guangdong,Jiangsu,and Zhejiang ranked among the top three,while Qinghai had the fastest development with an average annual growth rate of 4.496 %;The eight major economic zones have significant differences,showing a trend of relative convergence and absolute divergence,with the Northwest Economic Zone optimizing the fastest;The south is significantly better than the north,showing a relative and absolute dual trend of development between the north and the south;There is significant spatial agglomeration in the ecological environment of inter provincial new quality productive forces,with spatial agglomeration characteristics transitioning in provinces and cities such as Beijing,Hunan,and Jiangxi.The main obstacles to optimizing the ecological environment of new quality productive forces have shifted from insufficient infrastructure in 2013 to insufficient talent investment in 2022.Talent investment has become the main obstacle to the development of the eastern,central,and western regions,while the administrative environment is the main obstacle to the development of the Northeastern region.There are significant differences in regional and inter provincial obstacles,which need to be overcome according to local conditions.Finally,it is recommended to optimize the ecological environment according to local conditions by optimizing the talent ecology,improving the policy ecology,and enhancing the market ecology,in order to accelerate the formation of new quality productive forces.
Enterprise Digital Transformation,Supply Chain Spillover Effect and Employment Stabilization
HU Lei;WU Qiang;JIANG Zhener;Employment is the foundation of peoples livelihood,which bears on social stability and economic development.In the context of the booming development of the digital economy,digital transformation has not only emerged as a key path for enterprises to enhance competitiveness, but also has a profound impact on the job market.By improving production efficiency and expanding market size,digital transformation of enterprises can enhance their capacity to absorb employment.As collaboration within industrial and supply chains continues to gain importance,enterprises along the chain establish financial and business connections through their input-output relationships.Consequently,decisions made by one enterprise are transmitted to others along the chain, giving rise to supply chain spillover effects.Therefore,it is worth exploring whether the employment effects of digital transformation of enterprises can spill over along the supply chain.Using data from Chinese A-share listed companies from 2009 to 2022,this study empirically examines the impact and mechanism of digital transformation of suppliers on the labor employment scale client firms.It is found that digital transformation of suppliers significantly expands the scale of employment in clients.Mechanism tests indicate three primary channels:improving clients ' financial conditions,enlarging clients ' production scale,and enhancing clients ' market competitiveness.Heterogeneity analyses reveal notable differences across contexts.The employment expansion effect weakens when clients firms have higher levels routine task intensity or greater overstaffing,but is more pronounced among labor-intensive clients.The spillover is stronger when suppliers and clients operate in different industries or regions,and when clients are state-owned,high-growth,or high-productivity firms.The effect is also more prominent for clients located in regions with higher labor-market integration or those in Eastern China.The conclusion of this study provides a theoretical basis and empirical evidence to clarify the impact mechanism of supplier's digital transformation on the labor employment scale of clients.In light of this,four policy suggestions are proposed:accelerate the promotion of enterprises digital transformation, play the “multiplier" role of employment;strengthen the linkage effect of industrial and supply chains, improve the modernization level of industrial and supply chains;play the employment creation effect of digital transformation,prevent and resolve the impact of employment substitution;formulate differentiated support policies,and promote the effective linkage between digital transformation and stable employment.These suggestions provide important policy implications for promoting the deep integration of the real economy and digital economy,enhancing the modernization level of industrial and supply chains,and stabilizing and expanding employment scale.
Digital Infrastructure Construction and Coordinated Development of Urban "Carbon Reduction,Pollution Reduction,Green Expansion and Growth"
XIN Chongchong;LUO Yangfan;ZHONG Shunbin;Accelerating the construction of digital infrastructure is an important foundation for realizing the coordinated development of the urban "carbon reduction,pollution reduction,green expansion and growth".On the basis of theoretical explanation of the coordinated development of urban digital infrastructure construction in promoting urban "carbon reduction,pollution reduction,green expansion and growth",using the panel data of 282 cities at or above the prefecture level from 2006 to 2021,and based on the quasi-nature of "Broadband China" strategic demonstration city,this paper empirically investigates the role of digital infrastructure construction in promoting urban "carbon reduction, pollution reduction, green expansion and growth" by using DID method.The research finds that:firstly, the construction of urban digital infrastructure is helpful to promote the coordinated development of "reducing carbon,reducing pollution,green expansion and growth",and this conclusion still holds after a series of robustness tests and discussions on endogenous issues.Second,the construction of digital infrastructure has a stronger role in promoting the coordinated development of "carbon reduction,pollution reduction,green expansion and growth" in the eastern region,cities with high degree of cooperation,cities with good economic conditions and cities with high Internet level.Third,digital infrastructure construction promotes the coordinated development of "reducing carbon, reducing pollution, green expansion and growth" by promoting green technology innovation, strengthening environmental regulation and increasing government environmental protection expenditure.In this regard, it is suggested to continue to strengthen the construction of urban digital infrastructure and promote the development of digital economy;Adopt differentiated measures to advance the development of the digital economy in light of conditions;Enhance the breadth and depth of urban digital application,so that it can effectively promote the coordinated development of "carbon reduction,pollution reduction,green expansion and growth" in cities for a long time.
Study on Statistical Data Quality and Survey Compilation of Green Finance
SHI Daimin;YU Lan;SHI Haoming;Green finance serves as a critical pillar for sustainable development and the Chinese modernization.In recent years,the rapid development of green finance in China has facilitated the transformation of the economy towards a higher level and quality,while also contributing to the achievement of carbon peaking and carbon neutrality goals.In the process of rapid development of green finance,statistical theory of green finance lags behind the practice of green finance.Although statistical theory and practice have been established for green financial products such as green credit,green insurance,and green bonds,there are still many issues that need to be explored in depth regarding the classification,framework,and measurement of green finance statistics.In particular,the standards and systems for green finance statistics are relatively fragmented,and the data is still in complete and of insufficient quality,there is a lack of a comprehensive statistical system that can thoroughly monitor the development of green finance.Compiling a green finance survey can effectively present fundamental data on the total volume and structure of green finance,which facilitates a comprehensive and systematic monitoring of green financial activities and aiding in the analysis and assessment of the development status of green finance.Therefore,following the logical requirements of green finance statistical monitoring,this paper aims to compile a green finance survey.Specifically,it examines several fundamental issues,including the classification of green finance statistics,the data foundation,and the challenges in compiling the survey and the flow of funds table.The findings indicate that the current classification of green activities in statistical standards and systems is mainly based on industrial levels.To meet the diverse demands for green finance from government departments,enterprises,the general public,it is necessary to classify green finance from multiple perspectives,including the degree of greenness and its effects,and conduct multi-level green finance total amount.And it is necessary to further refine and expand the scope of green finance statistics,extending the statistical perspective from financial institutions to multiple sectors involved in green finance activities.Additionally,efforts should be made to optimize and enhance the structure and quality of green finance data,involve systematically constructing a multi-dimensional green finance database and establishing a quality supervision system for green finance.Finally,by integrating the various specialized statistical standards and systems of green finance,the compilation of a green finance survey and flow of funds table is proposed.These tools are designed to reflect the specific manifestations of green finance flows and stocks at different classification levels,providing an effective solution to the current lack of comprehensive green finance statistics.The research results are helpful to improve the statistical theory of green finance and provide some references for establishing a comprehensive statistical system of green finance.
R&D Network Embeddedness,Institutional Quality and Global Value Chain Upgrading
WEI Long;ZHANG Min;YI Ziyu;Global R&D cooperation is an important way for countries to break through innovation boundaries, seek scientific and technological progress,and upgrade global value chains position.This paper describes the structural characteristics of global R&D network from the perspective of R&D cooperation based on the data of transnational patent cooperation in 50 economies from 2007—2019,empirically examines its impact on GVC upgrading and the mechanism,and investigates the threshold effect of institutional quality.The results reveal that both the breadth and depth of global R&D network embeddedness can promote a country's GVC position significantly.This positive effect is achieved through the human capital structure upgrading and technological progress.The developed countries embedding into the global R&D network have more significant effect on GVC upgrading,while developing countries have less significant effect and are likely to be "low-end locked".There are obvious differences in the enhancement effect of different technology density industries embedding in global R&D network.The embedding breadth has a significant promotion effect on the GVC of high technology,medium-high technology and medium-low technology industries,but the embedding depth only has a significant promotion effect on the medium-low technology industries.In order to further explore the heterogeneity of the impact of global R&D network embeddedness on GVC upgrading between developed and developing economies,institutional quality is introduced as a threshold variable.It is found that,the improvement of institutional quality can significantly promote the impact of global R&D network embeddedness on GVC upgrading with phased characteristics.The findings are helpful to explain the impact of China's global R&D cooperation theoretically and provide references for China to formulate R&D cooperation strategies.
An Empirical Study for the Impact of Green Finance on Carbon Information Disclosure Quality
HUANG Shengzhong;ZHOU Jun;The realization of the "dual carbon target" will require guiding enterprises to improve carbon information transparency and reduce environmental information asymmetry.Quality measurement indicators are constructed for corporate carbon information disclosure via textual analysis of the social responsibility reports companies listed on the Shanghai and Shenzhen stock exchanges from 2013 to 2021.It is found that green finance has a significant positive impact on corporate carbon information disclosure quality;degree of marketization can strengthen the positive impact of green finance on corporate carbon information disclosure quality.Further research has found that public environmental concerns can improve corporate carbon information disclosure quality and weaken the positive impact of green finance on corporate carbon information disclosure quality.It is found through heterogeneity analysis that,impact of green finance on the quality of corporate carbon disclosure is greater among state-owned enterprises and firms facing financing constraints;Green finance has a significantly greater promoting effect on carbon reduction planning and action than on monitoring of carbon emission reductions.The research has shown that it is necessary to leverage the positive role of multiple forces in environmental governance to encourage companies to disclose high-quality carbon information,and the findings provide reference significance for the formulation of carbon emission regulatory policies and the promotion of corporate participation in carbon reduction practices.
Construction and Application of Comprehensive Evaluation Model for Spatio-temporal Panel Data
AN Bowen;XU Peiyuan;HE Weijun;YUAN Liang;Correlation feature,time feature and space feature are three unavoidable features in spatio-temporal panel data decision-making.The connotation definition of correlation factor,time factor and space factor is given with triple feature as the starting point,and the three factors are measured by mutual information,convolution algorithm and transition probability based on non-parametric method.The AHP method is used as an example to construct a comprehensive evaluation model for spatio-temporal panel data,and a three-factor judgment matrix is constructed according to six paths.The optimal result is selected by SPBIC criterion for the weighted types that pass the consistency test.Through the synthesis of the digital economy development index of 290 cities from 2001 to 2021,the unique function of spatio-temporal AHP in empirical analysis is discussed.The example results show that there are similarities and differences in the trends of dynamic evolution,time convergence and spatial agglomeration of the digital economy development index of the six types of empowerment,and SPBIC criterion can select the optimal results among the various types of empowerment.The weight coefficient of evaluation index has spatio-temporal heterogeneity and dimensionality heterogeneity,which reflects the unique function of spatio-temporal comprehensive evaluation model,and judges the key factors affecting the comprehensive index according to time and place.The weighted results are sensitive to the viscosity of time factor and spatial factor,and the spatio-temporal AHP has the functions of spatio-temporal,universality and heterogeneity in the empirical analysis.