Overview of rural credit environment in China: Measurement logic, evaluation system, and case analysis.

A rational evaluation of the rural credit environment's current state and identification of its critical issues are crucial for enhancing the construction of rural social credit systems. Drawing on the "Outline for the Construction of the Social Credit System (2014-2020)" and related literature, this paper clarifies the concepts and measurement principles of the rural credit environment. This study innovatively constructs an evaluation framework for the rural credit environment and conducts quantitative measurements and statistical analyses using a combined weighting method to delineate the environment's current state.

Evaluation of primary-level credit environment, indicator system and empirical analysis: A case study of credit construction in China county and district.

Townships (towns, streets) represent the foundational layer of China's administrative structure, and the quality of their credit environment is crucial for underpinning the development of a primary-level social credit system. This initiative aims to accelerate the establishment of the social credit system and cultivate a trustworthy economic and social environment. Starting from the three major fields of government, business and society, and focusing on integrity culture and credit innovation, the article proposes an innovative evaluation framework for primary-level credit environment and it can become a point of reference as a policy tool in international evaluation programs.

Credit risk assessment of small and micro enterprise based on machine learning.

Small and micro enterprises are pivotal in national economic and social development. To foster their growth, managing their credit risks scientifically is crucial. This study starts by examining the credit information of these enterprises.

Analyzing public demands on China's online government inquiry platform: A BERTopic-Based topic modeling study.

This study aims to enhance governmental decision-making by leveraging advanced topic modeling algorithms to analyze public letters on the "People Call Me" online government inquiry platform in Zhejiang Province, China. Employing advanced web scraping techniques, we collected publicly available letter data from Hangzhou City between June 2022 and May 2023. Initial descriptive statistical analyses and text mining were conducted, followed by topic modeling using the BERTopic algorithm.

New practice for investors in Chinese stock market: From perspective of fractionally integrated realized GARCH model.

In this paper, based on the Realized GARCH model, the fractional integration Realized GARCH model is proposed by combining long memory parameters with conditional variance and replacing the original realized measure with the realized measure obtained after daily, weekly and monthly weighting. Based on the 5-min high-frequency data of the SSE index, the fractional integration Realized GARCH model, Realized HAR GARCH model and Realized GARCH model are investigated for their fitting effect and predictive ability on market volatility, and Monte Carlo simulations are conducted from the error terms obeying normal distribution, t-distribution and chi-square distribution so as to compare the RMSE and MAE of the three types of models with respect to conditional variance. The empirical results show that the fractionally integrated Realized GARCH model is found to better capture the long-run correlation in volatility in certain intervals by comparing the theoretical and sample auto-correlation functions, while the overall predictive power of the model is better than the other two models.