In this paper,we highlight some recent developments of a new route to evaluate macroeconomic policy effects,which are investigated under the framework with potential outcomes.First,this paper begins with a brief intro...In this paper,we highlight some recent developments of a new route to evaluate macroeconomic policy effects,which are investigated under the framework with potential outcomes.First,this paper begins with a brief introduction of the basic model setup in modern econometric analysis of program evaluation.Secondly,primary attention goes to the focus on causal effect estimation of macroeconomic policy with single time series data together with some extensions to multiple time series data.Furthermore,we examine the connection of this new approach to traditional macroeconomic models for policy analysis and evaluation.Finally,we conclude by addressing some possible future research directions in statistics and econometrics.展开更多
This paper highlights some recent developments in testing predictability of asset returns with focuses on linear mean regressions, quantile regressions and nonlinear regression models. For these models, when predictor...This paper highlights some recent developments in testing predictability of asset returns with focuses on linear mean regressions, quantile regressions and nonlinear regression models. For these models, when predictors are highly persistent and their innovations are contemporarily correlated with dependent variable, the ordinary least squares estimator has a finite-sample bias, and its limiting distribution relies on some unknown nuisance parameter, which is not consistently estimable. Without correcting these issues, conventional test statistics are subject to a serious size distortion and generate a misleading conclusion in testing pre- dictability of asset returns in real applications. In the past two decades, sequential studies have contributed to this subject and proposed various kinds of solutions, including, but not limit to, the bias-correction procedures, the linear projection approach, the IVX filtering idea, the variable addition approaches, the weighted empirical likelihood method, and the double-weight robust approach. Particularly, to catch up with the fast-growing literature in the recent decade, we offer a selective overview of these methods. Finally, some future research topics, such as the econometric theory for predictive regressions with structural changes, and nonparametric predictive models, and predictive models under a more general data setting, are also discussed.展开更多
Addressing pollution caused by economic development,especially the overcapacity of polluting enterprises,is crucial for promoting sustainable economic growth.Targeted environmental policies are essential for strengthe...Addressing pollution caused by economic development,especially the overcapacity of polluting enterprises,is crucial for promoting sustainable economic growth.Targeted environmental policies are essential for strengthening environmental constraints on enterprises and enhancing the effectiveness of regulatory instruments.This study focused on the Environmental Credit Evaluation policy by examining its potential to improve capacity utilization and assessing its broader impact on heavily polluting enterprises.It constructed a time-varying difference-in-difference-in-differences model using panel data from 965 industrial enterprises from 2009 to 2019.The findings reveal that,in comparison with their non-heavily polluting counterparts,heavily polluting enterprises subject to the policy demonstrated significant improvements in capacity utilization.Heavily polluting enterprises that experienced a substantial increase in financing costs also exhibited a marked reduction in inefficient investment,without negatively affecting innovation investments or output.展开更多
In this review, we highlight some recent methodological and theoretical develop- ments in estimation and testing of large panel data models with cross-sectional dependence. The paper begins with a discussion of issues...In this review, we highlight some recent methodological and theoretical develop- ments in estimation and testing of large panel data models with cross-sectional dependence. The paper begins with a discussion of issues of cross-sectional dependence, and introduces the concepts of weak and strong cross-sectional dependence. Then, the main attention is primarily paid to spatial and factor approaches for modeling cross-sectional dependence for both linear and nonlinear （nonparametric and semiparametric） panel data models. Finally, we conclude with some speculations on future research directions.展开更多
In this paper, we propose a new test for testing the stability in macroeconomic time series, based on the LASSO variable selection approach and nonparametric estimation of a time-varying model. The wild bootstrap is e...In this paper, we propose a new test for testing the stability in macroeconomic time series, based on the LASSO variable selection approach and nonparametric estimation of a time-varying model. The wild bootstrap is employed to obtain its data-dependent critical values. We apply the new method to test the stability of bivariate relations among 92 major Chinese macroeconomic time series. We find that more than 70% bivariate relations are significantly unstable.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
To better describe and understand the time dynamics in functional data analysis,it is often desirable to recover the partial derivatives of the random surface.A novel approach is proposed based on marginal functional ...To better describe and understand the time dynamics in functional data analysis,it is often desirable to recover the partial derivatives of the random surface.A novel approach is proposed based on marginal functional principal component analysis to derive the representation for partial derivatives.To obtain the Karhunen-Lo`eve expansion of the partial derivatives,an adaptive estimation is explored.Asymptotic results of the proposed estimates are established.Simulation studies show that the proposed methods perform well in finite samples.Application to the human mortality data reveals informative time dynamics in mortality rates.展开更多
基金the National Natural Science Foundation of China(71631004,Key Project)the National Science Fund for Distinguished Young Scholars(71625001)+2 种基金the Basic Scientific Center Project of National Science Foundation of China:Econometrics and Quantitative Policy Evaluation(71988101)the Science Foundation of Ministry of Education of China(19YJA910003)China Scholarship Council Funded Project(201806315045).
文摘In this paper,we highlight some recent developments of a new route to evaluate macroeconomic policy effects,which are investigated under the framework with potential outcomes.First,this paper begins with a brief introduction of the basic model setup in modern econometric analysis of program evaluation.Secondly,primary attention goes to the focus on causal effect estimation of macroeconomic policy with single time series data together with some extensions to multiple time series data.Furthermore,we examine the connection of this new approach to traditional macroeconomic models for policy analysis and evaluation.Finally,we conclude by addressing some possible future research directions in statistics and econometrics.
基金supported by the National Natural Science Foundation of China(71631004,71571152)the Fundamental Research Funds for the Central Universities(20720171002,20720170090)the Fok Ying-Tong Education Foundation(151084)
文摘This paper highlights some recent developments in testing predictability of asset returns with focuses on linear mean regressions, quantile regressions and nonlinear regression models. For these models, when predictors are highly persistent and their innovations are contemporarily correlated with dependent variable, the ordinary least squares estimator has a finite-sample bias, and its limiting distribution relies on some unknown nuisance parameter, which is not consistently estimable. Without correcting these issues, conventional test statistics are subject to a serious size distortion and generate a misleading conclusion in testing pre- dictability of asset returns in real applications. In the past two decades, sequential studies have contributed to this subject and proposed various kinds of solutions, including, but not limit to, the bias-correction procedures, the linear projection approach, the IVX filtering idea, the variable addition approaches, the weighted empirical likelihood method, and the double-weight robust approach. Particularly, to catch up with the fast-growing literature in the recent decade, we offer a selective overview of these methods. Finally, some future research topics, such as the econometric theory for predictive regressions with structural changes, and nonparametric predictive models, and predictive models under a more general data setting, are also discussed.
基金support from the Major Program of the National Social Science Foundation of China(No.21&ZD109).
文摘Addressing pollution caused by economic development,especially the overcapacity of polluting enterprises,is crucial for promoting sustainable economic growth.Targeted environmental policies are essential for strengthening environmental constraints on enterprises and enhancing the effectiveness of regulatory instruments.This study focused on the Environmental Credit Evaluation policy by examining its potential to improve capacity utilization and assessing its broader impact on heavily polluting enterprises.It constructed a time-varying difference-in-difference-in-differences model using panel data from 965 industrial enterprises from 2009 to 2019.The findings reveal that,in comparison with their non-heavily polluting counterparts,heavily polluting enterprises subject to the policy demonstrated significant improvements in capacity utilization.Heavily polluting enterprises that experienced a substantial increase in financing costs also exhibited a marked reduction in inefficient investment,without negatively affecting innovation investments or output.
基金Supported by the National Natural Science Foundation of China(71131008(Key Project)and 71271179)
文摘In this review, we highlight some recent methodological and theoretical develop- ments in estimation and testing of large panel data models with cross-sectional dependence. The paper begins with a discussion of issues of cross-sectional dependence, and introduces the concepts of weak and strong cross-sectional dependence. Then, the main attention is primarily paid to spatial and factor approaches for modeling cross-sectional dependence for both linear and nonlinear （nonparametric and semiparametric） panel data models. Finally, we conclude with some speculations on future research directions.
基金Supported by the National Natural Science Foundation of China (70971113, 71131008, 71271179)the Fundamental Research Funds for the Central Universities (2010221092, 2011221015)
文摘In this paper, we propose a new test for testing the stability in macroeconomic time series, based on the LASSO variable selection approach and nonparametric estimation of a time-varying model. The wild bootstrap is employed to obtain its data-dependent critical values. We apply the new method to test the stability of bivariate relations among 92 major Chinese macroeconomic time series. We find that more than 70% bivariate relations are significantly unstable.
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.
基金supported by National Natural Science Foundation of China(Grant Nos.11861014,11561006 and 11971404)Natural Science Foundation of Guangxi Province(Grant No.2018GXNSFAA281145)+1 种基金Humanity and Social Science Youth Foundation of Ministry of Education of China(Grant No.19YJC910010)the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development,National Institutes of Health,USA。
文摘To better describe and understand the time dynamics in functional data analysis,it is often desirable to recover the partial derivatives of the random surface.A novel approach is proposed based on marginal functional principal component analysis to derive the representation for partial derivatives.To obtain the Karhunen-Lo`eve expansion of the partial derivatives,an adaptive estimation is explored.Asymptotic results of the proposed estimates are established.Simulation studies show that the proposed methods perform well in finite samples.Application to the human mortality data reveals informative time dynamics in mortality rates.
