Urban inclusive green growth (UIGG) refers to the synergetic enhancement of the economy, the environment, and the society in a city. Achieving such enhancement requires addressing a series of problems in the development of urbanization, such as unemployment, lack of access to education, insufficient medical resources, inequity, and environmental pollution. As firms are critical to city development and urbanization, whether they practice corporate social responsibility (CSR) plays a crucial part in UIGG. In this study, we focus on Chinese cities as (...) examples of UIGG and Chinese listed companies as CSR engagers, employing matched data on Chinese listed companies and cities to investigate how CSR affects UIGG. Specifically, the empirical results of a high-dimensional fixed effect model indicate that CSR significantly promotes UIGG. This finding remains valid after a set of robustness checks, including instrumental variable (IV) regression. CSR can promote UIGG by positively influencing enterprises’ economic performance, innovation, and employment. To promote firms’ substantive CSR actions, the government of Jiangsu Province, China, launched a pilot policy for CSR promotion by issuing an official guidance document, which can be considered a quasi-natural experiment to test the causality between CSR and UIGG. We find that the CSR pilot significantly promoted UIGG. The heterogeneity test results indicate that the influence of CSR on UIGG varies based on the audit company, the nature of the enterprise, and the structure of corporate leadership. (shrink)

Background: Individuals’ information processing includes automatic and effortful processes and the latter require sustained concentration or attention and larger amounts of cognitive “capacity.” Event-related potentials reflect all neural activities that are related to a certain stimulus. Investigating ERP characteristics of effortful cognitive processing in people with schizophrenia would be helpful in further understanding the neural mechanism of schizophrenia.Methods: Both schizophrenia patients and health controls completed ERP measurements during the performance of the basic facial emotion identification test and the face-vignette task. (...) Data of ERP components, BFEIT and FVT performances were analyzed.Results: Schizophrenia patients’ accuracies of face emotion detection in the BFEIT and vignette emotion detection in the FVT were both significantly worse than the performance of the HC group. Repeated-measures ANOVAs performed on mean amplitudes and latencies revealed that the interaction effect for group × experiment × site was significant for N250 amplitude. In FVT experiment, N250 amplitudes at prefrontal and frontal sites in schizophrenia group were larger than those of HC group; the maximum N250 amplitude was present at the prefrontal site in both the groups. For N250 latency, the interaction effect for group × experiment was significant; N250 latencies in the schizophrenia group were longer than those of the HC group.Conclusion: Schizophrenia patients present effortful cognitive processing dysfunctions which reflect in abnormal ERP components, especially N250 at prefrontal cortex and frontal cortex sites. These findings have important implications for further clarifying the neural mechanism of effortful cognitive processing deficits in schizophrenia. (shrink)

“Carbon neutrality, carbon peaking” is China’s national commitment to the whole world about its plans to manage global climate change. China faces many severe challenges in fulfilling its commitments to reduce emissions. China’s digital economy is currently booming, and whether it can provide opportunities for reducing regional carbon emissions is worth exploring. This study constructed a comprehensive system to evaluate the development of its digital economy based on China’s regional data and empirically tested the direct, indirect, and spatial effects of (...) the comprehensive development of digital economy on regional carbon emissions. In addition, it examined the special stage characteristics using a Hansen threshold model. This study found the following: first, the digital economy significantly suppresses carbon emissions in general, notably with a spatial spillover effect to neighboring provinces. Secondly, an analysis of the mechanism shows that the comprehensive development of a digital economy can restrain regional carbon emissions through industrial progress and the optimization of energy consumption. Third, there are double thresholds, special driving trends and an “inverted N-type” relationship with development. Fourth, a spatial heterogeneity analysis revealed that significant “local” and “neighboring” impacts on the reduction of carbon emissions only exist in the central and eastern areas. This study has a reference value for releasing the dividend of digital economy development and reducing carbon emissions. (shrink)