Effect of Rural Social Pension Insurance on Total Retail Sales of Consumer Goods

Based on data of 31 provinces of China in 2019 collected from the National Bureau of Statistics,this paper explores the impact of the number of urban employees’endowment insurance on the total retail sales of social consumer goods in different provinces in China.Taking the population,per capita disposable income,per capita life expectancy,and regional per capita GDP of each province as the variables,this paper establishes regression models to do the empirical research.The results show that:(1)The increase of the number of urban employees’old-age insurance has a significant positive impact on residents’consumption.The wider the coverage of old-age insurance,the more it can enhance the consumption confidence of the residents.(2)Due to the economic development,the level of urbanization has been greatly improved,leading to an increased birth rate and total population,and thus consumption has been driven.Therefore,the increase of the total population has a significant positive effect on the increase of the total retail sales of social consumer goods.(3)The increase of per capita disposable income has insignificant impact on the increase of total retail sales of social consumer goods due to residents’debt,the rise of house prices,the rapid widening of income gap between different groups,and the difficulty of meeting the various needs of people.(4)Although the increase of life expectancy per capita will lead to the decrease of total retail sales of social consumer goods,this decrease is not significant.(5)Per capita GDP will lead to a small increase in the total retail sales of social consumption.Finally,based on the above conclusions,some suggestions to stimulate consumption are given.

Increasing prediction performance of colorectal cancer disease status using random forests classification based on metagenomic shotgun sequencing data

Dysfunction of microbial communities in various human body sites has been shown to be associated with a variety of diseases raising the possibility of predicting diseases based on metagenomic samples.Although many studies have investigated this problem,there are no consensus on the optimal approaches for predicting disease status based on metagenomic samples.Using six human gut metagenomic datasets consisting of large numbers of colorectal cancer patients and healthy controls from different countries,we investigated different software packages for extracting relative abundances of known microbial genomes and for integrating mapping and as-sembly approaches to obtain the relative abundance profiles of both known and novel genomes.The random forests(RF)classification algorithm was then used to predict colorectal cancer status based on the microbial relative abundance profiles.Based on within data cross-validation and cross-dataset prediction,we show that the RF prediction performance using the microbial relative abundance profiles estimated by Centrifuge is generally higher than that using the microbial relative abundance profiles estimated by MetaPhlAn2 and Bracken.We also develop a novel method to integrate the relative abundance profiles of both known and novel microbial or-ganisms to further increase the prediction performance for colorectal cancer from metagenomes.

CEO Age, Earnings Management and Mergers & Acquisitions Evidence from China

This paper explores the relationship between CEO age in target firms, earnings management, mergers and acquisitions decision-making, and performance by using a sample of Chinese firms from 2008 to 2017. We found that CEO age is negatively correlated with M&A decision-making and target firms engage in a higher degree accrual-based earnings management(AEM) than non-target firms. In addition, target firms with young CEOs exhibit a greater extent of AEM in the pre-M&A period. We also found that the relationship between CEO age and M&A performance is inverted U-shaped. AEM of pre-M&A is negatively correlated with M&A performance, indicating that M&A performance is affected by AEM of pre-M&A.