Mangrove ecosystems have important ecological and economic values,especially their ability to store carbon.However,in recent years,human disturbance has accelerated mangrove degradation.Among them,the emission of poll...Mangrove ecosystems have important ecological and economic values,especially their ability to store carbon.However,in recent years,human disturbance has accelerated mangrove degradation.Among them,the emission of pollutants cannot be ignored.It is of great significance for carbon emission reduction and ecological protection to study the impacts of different pollutants on mangroves and their carbon stocks.Based on the remote sensing data of coastal areas south of the Yangtze River in China's Mainland,this paper builds the ensemble learning model Random Forest(RF)and Gradient Boosting Regression(GBR)to empirically analyse the relationship between industrial wastewater,industrial sulfur dioxide(SO2),PM2.5 and mangrove forests.The results show that the pollutant concentration of meteorological normalisation is more stable.The importance of pollutants presents regional heterogeneity.The area of mangroves in different cities and the corresponding total carbon stocks show different trends with the increase or decrease of pollutants,and there is a dynamic balance between urban pollutant discharge and mangrove growth in some cities.The research in this paper provides an analysis and explanation from the perspective of machine learning to explore the relationship between mangroves and pollutants and at the same time,provides scientific suggestions for the formulation of future pollutant emission policies in different cities.展开更多
This paper reconsiders the roles of China and some developed countries in the network of carbon emission transfers via international trade in value added from a new perspective of network governance.Network search int...This paper reconsiders the roles of China and some developed countries in the network of carbon emission transfers via international trade in value added from a new perspective of network governance.Network search intensity(NSI)and the extended gravity model are used with cross-country panel data to analyze the mechanism of China's engagement in network governance of carbon emission transfers.The results show that from 2000 to 2009,China was a net exporter of carbon emissions,even though it shifted from the semi-periphery to the core in the network of carbon emissions embodied in imports.Meanwhile,NSI had a significant positive impact on carbon emissions embodied in exports.Given China's important role in the global production network and division of labor,NSI may also affect industrial structure and the quality of the ecological environment to a large extent.This study analyses the network governance mechanism of China's participation in global carbon transfers.The results suggest that the technical complexity of export products and product heterogeneity do not change the positive impact of NSI on carbon emissions.展开更多
Analysis of the problem of predicting bankruptcy shows that foreign and domestic models included only internal factors of enterprises. But the same indicators of internal factors in the rapidly changing external envir...Analysis of the problem of predicting bankruptcy shows that foreign and domestic models included only internal factors of enterprises. But the same indicators of internal factors in the rapidly changing external environment can lead to bankruptcy, and not in others. External factors are the most dangerous, because the possible influence on them is minimal and the impact of their implementation can be devastating. This paper focuses on the same factors to assess the impact of the macroeconomic indicators （extemal factors） on the parameters of static models predicting a local approximation of the crisis at the plant. To accomplish the purpose, a Spark set of 100 companies was compiled, including 50 companies which officially declared bankruptcy in the period of 2000-2009 and 50 stable operating companies with a random sample of the same time period. External factors were extracted from the Joint Economic and Social Data Archive1 The author compared two data sets： （1） microeconomic indicators--money to the total liabilities, retained earnings to total assets, net profit to revenue, Earnings Before Interest and Taxes （EBIT） to assets, net income to equity, net profit to total liabilities, current liabilities to total assets, the totality of short-term and long-term loans to total assets, current assets to current liabilities, assets to revenue, equity to total assets, and current assets to revenue; and （2） external factors--index of real gross domestic product （GDP）, industrial production index, the index of real cash incomes, an index of real investments, consumer price index, the refinancing rate, unemployment rate, the price of electricity, gas prices, oil price, gas price, dollar to ruble, ruble euro Standard ＆ Poor （S＆P） index, the Russian Trading System （RTS） index, and region. The aim of the comparison results paging classes ＂insolvent＂ and ＂non-bankrupt＂ is achieved using two methods： classification and discrimination. In both methods, computational procedures are realized with the use of algorithms linear regression, artificial neural network, and genetic algorithm. In the 2-m model, data set includes both internal and external factors. The results showed that the inclusion of only the microeconomic indicators, excluding external factors, impedes models about two times.展开更多
Since 2003, China＇s labor market has been facing two coexisting crises： a rural labor surplus and a severe shortage of migrant labor Using data from the 2000 China Health and Nutrition Survey questionnaire, which co...Since 2003, China＇s labor market has been facing two coexisting crises： a rural labor surplus and a severe shortage of migrant labor Using data from the 2000 China Health and Nutrition Survey questionnaire, which covers 288 villages in 36 counties, this paper attempts to find a solution to this dilemma. Specifically, a multinomial logit model, a Mincer- type model and a probit model are applied to examine the effect of educational level on the employment choices for rural laborers, and on the wages and the employment status of migrants. Based on the results of our analysis, we propose the implementation of policy aimed at increasing the educational level of rural dwellers, in conjunction with other policies to eliminate all artificial barriers, to facilitate the migration of rural laborers.展开更多
Motivated by financial and empirical arguments and in order to introduce a more flexible methodology of pricing,we provide a new approach to asset pricing based on Backward Volterra equations.The approach relies on an...Motivated by financial and empirical arguments and in order to introduce a more flexible methodology of pricing,we provide a new approach to asset pricing based on Backward Volterra equations.The approach relies on an arbitrage-free and incomplete market setting in continuous time by choosing non-unique pricing measures depending either on the time of evaluation or on the maturity of payoffs.We show that in the latter case the dynamics can be captured by a time-delayed backward stochastic Volterra integral equation here introduced which,to the best of our knowledge,has not yet been studied.We then prove an existence and uniqueness result for time-delayed backward stochastic Volterra integral equations.Finally,we present a Lucas-type consumption-based asset pricing model that justifies the emergence of stochastic discount factors matching the term structure of Sharpe ratios.展开更多
Using data from 24 OECD countries, we find that the relationship between a country＇s R＆D investment and technological advantage in a sector （measured by the country＇s labor productivity of the sector relative to t...Using data from 24 OECD countries, we find that the relationship between a country＇s R＆D investment and technological advantage in a sector （measured by the country＇s labor productivity of the sector relative to the rest of the world） is non-monotonic. In particular, for countries whose technology levels are much lower or higher than the rest of the world in a sector, their sectoral R＆D investment declines as their advantages in the sector improve; for counties with middle technology levels, the opposite is true. Extending the Eaton and Kortum framework, we develop a static model to theoretically analyze the relationship between R＆D investment and technological advantages. We show that when the research efficiency in a sector is sufficiently elastic with respect to the sectoral technological advantage, a country＇s R＆D investment increases with its technological advantage, and vice versa.展开更多
Firms actively participate in the production of the global value chain(GVC),which is an important driving force for economic development.Using a difference-in-difference method,our research shows that industries that ...Firms actively participate in the production of the global value chain(GVC),which is an important driving force for economic development.Using a difference-in-difference method,our research shows that industries that are relatively more human-capital intensive experienced a larger GVC position upgrading after 2003 than they had in prior years.Second,mechanism analysis shows that human capital expansion increases firms’GVC position not only through an imported intermediate input effect but also through an innovation effect.Third,this study shows that increases in the college-educated labor force have a heterogeneous effect on a firm's GVC position across firms’various characteristics.Human capital expansion has the largest positive effect on state-owned firms relative to foreign and domestic private firms.Human capital expansion has also significantly improved the GVC position of firms located in China's eastern and central regions.The findings of this study indicate that it helps upgrading the GVC position of Chinese firms.展开更多
Post-reform China has been experiencing two major demographic changes： an increasingly aging population and an extraordinary surge of rural-urban migrants. The question we ask is： are these two demographic changes r...Post-reform China has been experiencing two major demographic changes： an increasingly aging population and an extraordinary surge of rural-urban migrants. The question we ask is： are these two demographic changes related？ If yes, then, how？ The standard view in the migration literature is that the older the migrant, the lower the likelihood of migration. This paper proposes a simple theory of temporary migration for unskilled labor to fit the context of China Motivated by our model, we then use both cross-sectional micro data and panel macro data to examine the potential impacts of aging on migration. We find that shifts in China＇s age distribution have generated significant changes in the country＇s migration patterns： migration will shift to closer provinces （probably switching from interprovincial migration to intra-provincial migration） and will concentrate to a few destination provinces.展开更多
The study adopts a single case study approach to bring into conversation,ideas,and views of several scholars on triple entry accounting(TEA).The development of blockchain technology already drives the conscious move t...The study adopts a single case study approach to bring into conversation,ideas,and views of several scholars on triple entry accounting(TEA).The development of blockchain technology already drives the conscious move towards the TEA.The TEA is currently not being used in any significant way but is in a greater debate whether it is worth adopting such alternative accounting practices as the TEA.Shifting to the TEA system is challenging and at present,it is just a fascinating mental exercise.With these backdrops,the present study discusses the likelihood cases of future accounting practice namely:(Ⅰ)Sophisticated Accounting Software based on the double entry accounting(DEA);(Ⅱ)Combination of Blockchain and TEA;and(Ⅲ)Combination of disruptive technologies in addition to Blockchain and TEA.Finally,the study concludes with describing the basic architecture of a potential system of triple-entry accounting that could support the TEA system to deliver real-time insights into business operations.Lastly,the study plotted a hype cycle for accounting technologies to help global organizations identify the relevant accounting technologies and applications.展开更多
基金the Major Program of the National Fund of Philosophy and Social Science of China(Nos.21&ZD109).
文摘Mangrove ecosystems have important ecological and economic values,especially their ability to store carbon.However,in recent years,human disturbance has accelerated mangrove degradation.Among them,the emission of pollutants cannot be ignored.It is of great significance for carbon emission reduction and ecological protection to study the impacts of different pollutants on mangroves and their carbon stocks.Based on the remote sensing data of coastal areas south of the Yangtze River in China's Mainland,this paper builds the ensemble learning model Random Forest(RF)and Gradient Boosting Regression(GBR)to empirically analyse the relationship between industrial wastewater,industrial sulfur dioxide(SO2),PM2.5 and mangrove forests.The results show that the pollutant concentration of meteorological normalisation is more stable.The importance of pollutants presents regional heterogeneity.The area of mangroves in different cities and the corresponding total carbon stocks show different trends with the increase or decrease of pollutants,and there is a dynamic balance between urban pollutant discharge and mangrove growth in some cities.The research in this paper provides an analysis and explanation from the perspective of machine learning to explore the relationship between mangroves and pollutants and at the same time,provides scientific suggestions for the formulation of future pollutant emission policies in different cities.
基金the National Social Science Foundation of China(Nos.21BJL102 and 18BJL118)the Major Program of National Social Science Foundation of China(No.21&ZD109)+2 种基金the National Natural Science Foundation of China(Nos.72074186 and 71673230)the Basic Scientific Center Project of National Science Foundation of China(No.71988101)the Fundamental Research Funds for the Central Universities concerned Chinese Modernization(No.20720231061).
文摘This paper reconsiders the roles of China and some developed countries in the network of carbon emission transfers via international trade in value added from a new perspective of network governance.Network search intensity(NSI)and the extended gravity model are used with cross-country panel data to analyze the mechanism of China's engagement in network governance of carbon emission transfers.The results show that from 2000 to 2009,China was a net exporter of carbon emissions,even though it shifted from the semi-periphery to the core in the network of carbon emissions embodied in imports.Meanwhile,NSI had a significant positive impact on carbon emissions embodied in exports.Given China's important role in the global production network and division of labor,NSI may also affect industrial structure and the quality of the ecological environment to a large extent.This study analyses the network governance mechanism of China's participation in global carbon transfers.The results suggest that the technical complexity of export products and product heterogeneity do not change the positive impact of NSI on carbon emissions.
文摘Analysis of the problem of predicting bankruptcy shows that foreign and domestic models included only internal factors of enterprises. But the same indicators of internal factors in the rapidly changing external environment can lead to bankruptcy, and not in others. External factors are the most dangerous, because the possible influence on them is minimal and the impact of their implementation can be devastating. This paper focuses on the same factors to assess the impact of the macroeconomic indicators （extemal factors） on the parameters of static models predicting a local approximation of the crisis at the plant. To accomplish the purpose, a Spark set of 100 companies was compiled, including 50 companies which officially declared bankruptcy in the period of 2000-2009 and 50 stable operating companies with a random sample of the same time period. External factors were extracted from the Joint Economic and Social Data Archive1 The author compared two data sets： （1） microeconomic indicators--money to the total liabilities, retained earnings to total assets, net profit to revenue, Earnings Before Interest and Taxes （EBIT） to assets, net income to equity, net profit to total liabilities, current liabilities to total assets, the totality of short-term and long-term loans to total assets, current assets to current liabilities, assets to revenue, equity to total assets, and current assets to revenue; and （2） external factors--index of real gross domestic product （GDP）, industrial production index, the index of real cash incomes, an index of real investments, consumer price index, the refinancing rate, unemployment rate, the price of electricity, gas prices, oil price, gas price, dollar to ruble, ruble euro Standard ＆ Poor （S＆P） index, the Russian Trading System （RTS） index, and region. The aim of the comparison results paging classes ＂insolvent＂ and ＂non-bankrupt＂ is achieved using two methods： classification and discrimination. In both methods, computational procedures are realized with the use of algorithms linear regression, artificial neural network, and genetic algorithm. In the 2-m model, data set includes both internal and external factors. The results showed that the inclusion of only the microeconomic indicators, excluding external factors, impedes models about two times.
文摘Since 2003, China＇s labor market has been facing two coexisting crises： a rural labor surplus and a severe shortage of migrant labor Using data from the 2000 China Health and Nutrition Survey questionnaire, which covers 288 villages in 36 counties, this paper attempts to find a solution to this dilemma. Specifically, a multinomial logit model, a Mincer- type model and a probit model are applied to examine the effect of educational level on the employment choices for rural laborers, and on the wages and the employment status of migrants. Based on the results of our analysis, we propose the implementation of policy aimed at increasing the educational level of rural dwellers, in conjunction with other policies to eliminate all artificial barriers, to facilitate the migration of rural laborers.
文摘Motivated by financial and empirical arguments and in order to introduce a more flexible methodology of pricing,we provide a new approach to asset pricing based on Backward Volterra equations.The approach relies on an arbitrage-free and incomplete market setting in continuous time by choosing non-unique pricing measures depending either on the time of evaluation or on the maturity of payoffs.We show that in the latter case the dynamics can be captured by a time-delayed backward stochastic Volterra integral equation here introduced which,to the best of our knowledge,has not yet been studied.We then prove an existence and uniqueness result for time-delayed backward stochastic Volterra integral equations.Finally,we present a Lucas-type consumption-based asset pricing model that justifies the emergence of stochastic discount factors matching the term structure of Sharpe ratios.
文摘Using data from 24 OECD countries, we find that the relationship between a country＇s R＆D investment and technological advantage in a sector （measured by the country＇s labor productivity of the sector relative to the rest of the world） is non-monotonic. In particular, for countries whose technology levels are much lower or higher than the rest of the world in a sector, their sectoral R＆D investment declines as their advantages in the sector improve; for counties with middle technology levels, the opposite is true. Extending the Eaton and Kortum framework, we develop a static model to theoretically analyze the relationship between R＆D investment and technological advantages. We show that when the research efficiency in a sector is sufficiently elastic with respect to the sectoral technological advantage, a country＇s R＆D investment increases with its technological advantage, and vice versa.
基金This research was financially supported by the Key Research Institutes of Humanities and Social of the Ministry of Education of China(No.17JJD790014)the Major Program of the National Social Science Foundation of China(Nos.13&ZD167 and 17ZDA114)。
文摘Firms actively participate in the production of the global value chain(GVC),which is an important driving force for economic development.Using a difference-in-difference method,our research shows that industries that are relatively more human-capital intensive experienced a larger GVC position upgrading after 2003 than they had in prior years.Second,mechanism analysis shows that human capital expansion increases firms’GVC position not only through an imported intermediate input effect but also through an innovation effect.Third,this study shows that increases in the college-educated labor force have a heterogeneous effect on a firm's GVC position across firms’various characteristics.Human capital expansion has the largest positive effect on state-owned firms relative to foreign and domestic private firms.Human capital expansion has also significantly improved the GVC position of firms located in China's eastern and central regions.The findings of this study indicate that it helps upgrading the GVC position of Chinese firms.
文摘Post-reform China has been experiencing two major demographic changes： an increasingly aging population and an extraordinary surge of rural-urban migrants. The question we ask is： are these two demographic changes related？ If yes, then, how？ The standard view in the migration literature is that the older the migrant, the lower the likelihood of migration. This paper proposes a simple theory of temporary migration for unskilled labor to fit the context of China Motivated by our model, we then use both cross-sectional micro data and panel macro data to examine the potential impacts of aging on migration. We find that shifts in China＇s age distribution have generated significant changes in the country＇s migration patterns： migration will shift to closer provinces （probably switching from interprovincial migration to intra-provincial migration） and will concentrate to a few destination provinces.
文摘The study adopts a single case study approach to bring into conversation,ideas,and views of several scholars on triple entry accounting(TEA).The development of blockchain technology already drives the conscious move towards the TEA.The TEA is currently not being used in any significant way but is in a greater debate whether it is worth adopting such alternative accounting practices as the TEA.Shifting to the TEA system is challenging and at present,it is just a fascinating mental exercise.With these backdrops,the present study discusses the likelihood cases of future accounting practice namely:(Ⅰ)Sophisticated Accounting Software based on the double entry accounting(DEA);(Ⅱ)Combination of Blockchain and TEA;and(Ⅲ)Combination of disruptive technologies in addition to Blockchain and TEA.Finally,the study concludes with describing the basic architecture of a potential system of triple-entry accounting that could support the TEA system to deliver real-time insights into business operations.Lastly,the study plotted a hype cycle for accounting technologies to help global organizations identify the relevant accounting technologies and applications.
