It is clearly stated in the 19th people's congress that we should make the environmental protection as our national policy. Therefore, it is of great importance to study this issue. This article is going to consid...It is clearly stated in the 19th people's congress that we should make the environmental protection as our national policy. Therefore, it is of great importance to study this issue. This article is going to consider 30 provinces of China as the cross-section, and utilize the data sample from 2006 to 2015 of these cross-sections to formulate a Spatial Panel Data Durbin Model to analyze the effect of FDI. By using these data, this article creates a comprehensive environmental pollution index with the help of entropy. The result indicates that the effect of FDI on environment has a non-linear and spatial spillover characteristic. Before reaching the critical value, FDI has a negative effect on environment; however, with the accumulation of FDI, it will create a significant positive effect on the environment.展开更多
Panel data combine cross-section data and time series data. If the cross-section is locations, there is a need to check the correlation among locations. ρ and λ are parameters in generalized spatial model to cover e...Panel data combine cross-section data and time series data. If the cross-section is locations, there is a need to check the correlation among locations. ρ and λ are parameters in generalized spatial model to cover effect of correlation between locations. Value of ρ or λ will influence the goodness of fit model, so it is important to make parameter estimation. The effect of another location is covered by making contiguity matrix until it gets spatial weighted matrix (W). There are some types of W—uniform W, binary W, kernel Gaussian W and some W from real case of economics condition or transportation condition from locations. This study is aimed to compare uniform W and kernel Gaussian W in spatial panel data model using RMSE value. The result of analysis showed that uniform weight had RMSE value less than kernel Gaussian model. Uniform W had stabil value for all the combinations.展开更多
This article considers 30 provinces of China as the cross-section subjects, and utilizes the data sample from 2009 to 2015 of these cross-sections to formulate a Spatial Panel Data Durbin Model to analyze the effect o...This article considers 30 provinces of China as the cross-section subjects, and utilizes the data sample from 2009 to 2015 of these cross-sections to formulate a Spatial Panel Data Durbin Model to analyze the effect of environmental regulation on employment. The result indicates that environmental regulation has negative effect on employment with the consideration of spatial spillover effect, and this adverse effect is not significant mathematically. With the enhance of environmental regulation, the negative impact on employment will decrease accordingly, even may eventually promote job growth, which means there may be a non-linear relationship between them. Specifically, the direct effect of environmental regulation on employment indicates that it is beneficial for job growth whereas the indirect effect illustrate that it is detrimental for employment.展开更多
In this article, we study estimation of a partially specified spatial panel data linear regression with random-effects. Under the conditions of exogenous spatial weighting matrix and exogenous regressors, we give an i...In this article, we study estimation of a partially specified spatial panel data linear regression with random-effects. Under the conditions of exogenous spatial weighting matrix and exogenous regressors, we give an instrumental variable estimation. Under certain sufficient assumptions, we show that the proposed estimator for the finite dimensional parameter is root-N consistent and asymptotically normally distributed and the proposed estimator for the unknown function is consistent and asymptotically distributed. Consistent estimators for the asymptotic variance-covariance matrices of both the parametric and unknown components are provided. The Monte Carlo simulation results verify our theory and suggest that the approach has some practical value.展开更多
This paper uses spatial panel data models to analyze regional growth in China.Controlling for fixed-effects allows us to disentangle the effect of spatial dependence from that of spatial heterogeneity and omitted vari...This paper uses spatial panel data models to analyze regional growth in China.Controlling for fixed-effects allows us to disentangle the effect of spatial dependence from that of spatial heterogeneity and omitted variable to investigate the regional convergence process within the country.展开更多
In view of the extensive growth of China's steel production in recent years, this paper analyzed the industrial development background and economic geography theory, and discussed the possible spatial interaction ...In view of the extensive growth of China's steel production in recent years, this paper analyzed the industrial development background and economic geography theory, and discussed the possible spatial interaction mechanism. Based on panel data of China's inter-provincial steel output from 2001 to 2015, using spatial econometric model, this paper also explored whether China's provincial steel production shows material orientation, market orientation and traffic orientation, and isolated spatial interactions of interprovincial steel output. The results showed that the inter-provincial steel production in China did show both material orientation, market orientation and traffic orientation and that there was a significant negative spatial interaction, indicating that there might be strong competition and a crowing-out effect between neighboring provinces, and that the smaller the spatial scope, the more significant the spatial interactions of steel production.展开更多
Under the“dual carbon”goal,local governments in China have strategically focused on enhancing capital utilization efficiency and enforcing environmental regulations to improve carbon emission performance.This dual a...Under the“dual carbon”goal,local governments in China have strategically focused on enhancing capital utilization efficiency and enforcing environmental regulations to improve carbon emission performance.This dual approach targets the intertwined challenges of economic development and environmental protection.Utilizing data from 266 prefecture-level cities in China from 2007 to 2019,this study systematically investigates the effects of capital matching and environmental regulation on carbon emission performance through the spatial Durbin model and the instrumental variable method.The results indicate that both capital matching and environmental regulation significantly enhance carbon emission performance.Capital matching demonstrates positive spatial spillover effects,whereas environmental regulation exhibits negative spatial spillover effects.Furthermore,there are synergistic effects between capital matching and environmental regulation that jointly enhance carbon emission performance.To address potential biases caused by endogenous environmental regulation,the study uses the proportion of environment-related words in provincial government work reports as an instrumental variable for environmental regulation.Additionally,to capture the heterogeneity in the environmental governance willingness and intensity of prefecture-level municipal governments,the study constructs heterogeneous instrumental variables.These variables are derived by multiplying the proportion of a prefecture-level city’s total industrial output value to the province’s total industrial output value with the proportion of environment-related words in the provincial government work reports.Analyses based on these instrumental variables reveal that endogenous issues in environmental regulation lead to an overestimation of its positive impact on carbon emission performance.展开更多
Understanding the urban-rural development mechanism is critical for implementing rural revival and new-type urbanization.However,it remains a challenge to quantify the urban-rural integrated development level(URIDL)an...Understanding the urban-rural development mechanism is critical for implementing rural revival and new-type urbanization.However,it remains a challenge to quantify the urban-rural integrated development level(URIDL)and its impact factors.Hence,we constructed an assessment system for the URIDL from spatial,economic,social,life,and ecological integration.The spatial autocorrelation and Spearman rank correlation coefficients were used to assess the spatiotemporal variation of the URIDL and the trade-off synergistic relationship among the subsystems at the provincial scale in China using socio-economic statistical data from 2000 to 2020.A spatial panel quantile regression model was used to analyze the driving mechanism.The results showed that the URIDL of China increased by 0.19%from 2000 to 2020,and a high-high(H-H)spatial agglomeration pattern occurred in the Yangtze River Delta and the Beijing-Tianjin-Hebei regions.Spatial integration significantly contributed to the other subsystems,whereas economic integration had a significant negative impact on the other subsystems in the eastern coastal and southwestern regions.Per capita Gross Domestic Product(GDP)improved the URIDL,whereas other factors,such as fiscal revenue decentralization,had inhibiting effects.Notably,the impact of factors on URIDL varies across different quantiles.Finally,we proposed policy recommendations for differentiated improvement of URIDL based on its evolution and regional development level during the research period.展开更多
基金supported by the Hubei Province Educational Division Social Science Research Project(Grant No.15G051)
文摘It is clearly stated in the 19th people's congress that we should make the environmental protection as our national policy. Therefore, it is of great importance to study this issue. This article is going to consider 30 provinces of China as the cross-section, and utilize the data sample from 2006 to 2015 of these cross-sections to formulate a Spatial Panel Data Durbin Model to analyze the effect of FDI. By using these data, this article creates a comprehensive environmental pollution index with the help of entropy. The result indicates that the effect of FDI on environment has a non-linear and spatial spillover characteristic. Before reaching the critical value, FDI has a negative effect on environment; however, with the accumulation of FDI, it will create a significant positive effect on the environment.
文摘Panel data combine cross-section data and time series data. If the cross-section is locations, there is a need to check the correlation among locations. ρ and λ are parameters in generalized spatial model to cover effect of correlation between locations. Value of ρ or λ will influence the goodness of fit model, so it is important to make parameter estimation. The effect of another location is covered by making contiguity matrix until it gets spatial weighted matrix (W). There are some types of W—uniform W, binary W, kernel Gaussian W and some W from real case of economics condition or transportation condition from locations. This study is aimed to compare uniform W and kernel Gaussian W in spatial panel data model using RMSE value. The result of analysis showed that uniform weight had RMSE value less than kernel Gaussian model. Uniform W had stabil value for all the combinations.
基金supported by the Hubei Province Educational Division Social Science Research Project (Grant No. 15G051)
文摘This article considers 30 provinces of China as the cross-section subjects, and utilizes the data sample from 2009 to 2015 of these cross-sections to formulate a Spatial Panel Data Durbin Model to analyze the effect of environmental regulation on employment. The result indicates that environmental regulation has negative effect on employment with the consideration of spatial spillover effect, and this adverse effect is not significant mathematically. With the enhance of environmental regulation, the negative impact on employment will decrease accordingly, even may eventually promote job growth, which means there may be a non-linear relationship between them. Specifically, the direct effect of environmental regulation on employment indicates that it is beneficial for job growth whereas the indirect effect illustrate that it is detrimental for employment.
基金supported by National Natural Science Foundation of China(Grant Nos.71371118,71471117)Plateau and Peak Disciplines of Shanghai-Business Management Research Team+3 种基金National Social Science Fund of China(Grant No.14BJY012)Program for Changjiang Scholars and Innovative Research Team in University(Grant No.PCSIRTIRT13077)the State Key Program of National Natural Science of China(Grant No.71331006)supported by National Nature Science Foundation of China(Grant Nos.11101442,11471086)
文摘In this article, we study estimation of a partially specified spatial panel data linear regression with random-effects. Under the conditions of exogenous spatial weighting matrix and exogenous regressors, we give an instrumental variable estimation. Under certain sufficient assumptions, we show that the proposed estimator for the finite dimensional parameter is root-N consistent and asymptotically normally distributed and the proposed estimator for the unknown function is consistent and asymptotically distributed. Consistent estimators for the asymptotic variance-covariance matrices of both the parametric and unknown components are provided. The Monte Carlo simulation results verify our theory and suggest that the approach has some practical value.
文摘This paper uses spatial panel data models to analyze regional growth in China.Controlling for fixed-effects allows us to disentangle the effect of spatial dependence from that of spatial heterogeneity and omitted variable to investigate the regional convergence process within the country.
文摘In view of the extensive growth of China's steel production in recent years, this paper analyzed the industrial development background and economic geography theory, and discussed the possible spatial interaction mechanism. Based on panel data of China's inter-provincial steel output from 2001 to 2015, using spatial econometric model, this paper also explored whether China's provincial steel production shows material orientation, market orientation and traffic orientation, and isolated spatial interactions of interprovincial steel output. The results showed that the inter-provincial steel production in China did show both material orientation, market orientation and traffic orientation and that there was a significant negative spatial interaction, indicating that there might be strong competition and a crowing-out effect between neighboring provinces, and that the smaller the spatial scope, the more significant the spatial interactions of steel production.
文摘Under the“dual carbon”goal,local governments in China have strategically focused on enhancing capital utilization efficiency and enforcing environmental regulations to improve carbon emission performance.This dual approach targets the intertwined challenges of economic development and environmental protection.Utilizing data from 266 prefecture-level cities in China from 2007 to 2019,this study systematically investigates the effects of capital matching and environmental regulation on carbon emission performance through the spatial Durbin model and the instrumental variable method.The results indicate that both capital matching and environmental regulation significantly enhance carbon emission performance.Capital matching demonstrates positive spatial spillover effects,whereas environmental regulation exhibits negative spatial spillover effects.Furthermore,there are synergistic effects between capital matching and environmental regulation that jointly enhance carbon emission performance.To address potential biases caused by endogenous environmental regulation,the study uses the proportion of environment-related words in provincial government work reports as an instrumental variable for environmental regulation.Additionally,to capture the heterogeneity in the environmental governance willingness and intensity of prefecture-level municipal governments,the study constructs heterogeneous instrumental variables.These variables are derived by multiplying the proportion of a prefecture-level city’s total industrial output value to the province’s total industrial output value with the proportion of environment-related words in the provincial government work reports.Analyses based on these instrumental variables reveal that endogenous issues in environmental regulation lead to an overestimation of its positive impact on carbon emission performance.
基金Under the auspices of National Key Research and Development Program(No.2023YFC3804001)National Natural Science Foundation of China(No.42201440)。
文摘Understanding the urban-rural development mechanism is critical for implementing rural revival and new-type urbanization.However,it remains a challenge to quantify the urban-rural integrated development level(URIDL)and its impact factors.Hence,we constructed an assessment system for the URIDL from spatial,economic,social,life,and ecological integration.The spatial autocorrelation and Spearman rank correlation coefficients were used to assess the spatiotemporal variation of the URIDL and the trade-off synergistic relationship among the subsystems at the provincial scale in China using socio-economic statistical data from 2000 to 2020.A spatial panel quantile regression model was used to analyze the driving mechanism.The results showed that the URIDL of China increased by 0.19%from 2000 to 2020,and a high-high(H-H)spatial agglomeration pattern occurred in the Yangtze River Delta and the Beijing-Tianjin-Hebei regions.Spatial integration significantly contributed to the other subsystems,whereas economic integration had a significant negative impact on the other subsystems in the eastern coastal and southwestern regions.Per capita Gross Domestic Product(GDP)improved the URIDL,whereas other factors,such as fiscal revenue decentralization,had inhibiting effects.Notably,the impact of factors on URIDL varies across different quantiles.Finally,we proposed policy recommendations for differentiated improvement of URIDL based on its evolution and regional development level during the research period.
