The subset threshold auto regressive (SSTAR) model, which is capable of reproducing the limit cycle behavior of nonlinear time series, is introduced. The algorithm for fitting the sampled data with SSTAR model is pr...The subset threshold auto regressive (SSTAR) model, which is capable of reproducing the limit cycle behavior of nonlinear time series, is introduced. The algorithm for fitting the sampled data with SSTAR model is proposed and applied to model and forecast power load. Numerical example verifies that desirable accuracy of short term load forecasting can be achieved by using the SSTAR model.展开更多
Questions persist on the relationship between tourism dependence and economic growth in ethnic tourism areas.This study addresses such gaps by constructing a threshold regression model based on socio-economic data fro...Questions persist on the relationship between tourism dependence and economic growth in ethnic tourism areas.This study addresses such gaps by constructing a threshold regression model based on socio-economic data from 2006 to 2019 for nine sites in Enshi Prefecture of central China.Arc GIS and other open-source data were also used to visualize changing tourism resources in the region.Findings suggest that tourism dependence(the ratio of tourism-based GDP to overall GDP)significantly promotes economic growth in ethnic minority areas.However,the positive influence of tourism dependence on economic growth appears dynamic and non-linear–rising at first before falling when tourism dependence exceeded a threshold of 34%,with effects varying by site and year.Methods and findings make crucial theoretical contributions to understanding tourism dependence and poverty alleviation linkages.This paper also highlights the importance of political support and balanced investment in diverse industries to minimize decreasing returns beyond tourism dependence thresholds in destinations worldwide.展开更多
This study explores the role of financial support in the digital transformation of Chinese A-share-listed companies from 2001 to 2020.By utilizing the moderating effect model and threshold regression model,this study ...This study explores the role of financial support in the digital transformation of Chinese A-share-listed companies from 2001 to 2020.By utilizing the moderating effect model and threshold regression model,this study finds the following results:(1)Digital transformation positively impacts innovation,and the support of banking and capital markets further strengthens this impact.(2)With the development of banking and capital markets,the impact of digital transformation on innovation changes from negative to positive,which is also reflected in the subsamples of Eastern companies,small and medium-sized companies(SMEs),and non-SMEs.(3)The study reveals that only the capital market in the non-Eastern region has no threshold,and capital market support is effective only for non-SMEs when it reaches a higher level.These findings have important implications for policymakers in promoting digital transformation through financial support and help companies understand how to use financial support to improve competitiveness.展开更多
文摘The subset threshold auto regressive (SSTAR) model, which is capable of reproducing the limit cycle behavior of nonlinear time series, is introduced. The algorithm for fitting the sampled data with SSTAR model is proposed and applied to model and forecast power load. Numerical example verifies that desirable accuracy of short term load forecasting can be achieved by using the SSTAR model.
基金funded by the National Social Science Foundation of China(Grant No.20CMZ033)。
文摘Questions persist on the relationship between tourism dependence and economic growth in ethnic tourism areas.This study addresses such gaps by constructing a threshold regression model based on socio-economic data from 2006 to 2019 for nine sites in Enshi Prefecture of central China.Arc GIS and other open-source data were also used to visualize changing tourism resources in the region.Findings suggest that tourism dependence(the ratio of tourism-based GDP to overall GDP)significantly promotes economic growth in ethnic minority areas.However,the positive influence of tourism dependence on economic growth appears dynamic and non-linear–rising at first before falling when tourism dependence exceeded a threshold of 34%,with effects varying by site and year.Methods and findings make crucial theoretical contributions to understanding tourism dependence and poverty alleviation linkages.This paper also highlights the importance of political support and balanced investment in diverse industries to minimize decreasing returns beyond tourism dependence thresholds in destinations worldwide.
基金the funding support from Research on Confidential Computing and Data Governance of China Financial Technology(2021XWK03)Research on the Road of Chinese Open Cooperation and High Quality Economic Development(2022CXTD04)+1 种基金Research on the Impact of Information Disclosure Quality on Corporate Financing Constraints from the Perspective of Digital transformation(2023CX012)supported financially by the China Scholarship Council(No.202306170119).
文摘This study explores the role of financial support in the digital transformation of Chinese A-share-listed companies from 2001 to 2020.By utilizing the moderating effect model and threshold regression model,this study finds the following results:(1)Digital transformation positively impacts innovation,and the support of banking and capital markets further strengthens this impact.(2)With the development of banking and capital markets,the impact of digital transformation on innovation changes from negative to positive,which is also reflected in the subsamples of Eastern companies,small and medium-sized companies(SMEs),and non-SMEs.(3)The study reveals that only the capital market in the non-Eastern region has no threshold,and capital market support is effective only for non-SMEs when it reaches a higher level.These findings have important implications for policymakers in promoting digital transformation through financial support and help companies understand how to use financial support to improve competitiveness.
