The impact of digital finance on household consumption: Evidence from China

Using panel data from the China Household Finance Survey (CHFS) in 2013, 2015, and 2017 and the digital inclusive finance index developed by Peking University, this study examined impacts of the digital inclusive finance on household consumption and explored its mechanisms. Results suggest that the digital inclusive finance could promote households consumption. A heterogeneity analysis showed that households with fewer assets, lower income, less financial literacy and in third- and fourth-tier cities experienced larger facilitating effects of digital finance on consumption compared to their counterparts. For consumption categories, digital finance was positively correlated with food, clothing, house maintenance, medical care, and education and entertainment expenditures. In terms of consumption structure, digital finance mainly promoted the recurring household expenditures rather than the non-recurring expenditures. Further analyses based on the mediating model found that online shopping, digital payment, obtainment of online credit, purchase of financing products on the internet and business insurance, were the main mediating variables through which digital finance affected household consumption

Cascaded Interaction with Eroded Deep Supervision for Salient Object Detection

Deep convolutional neural networks have been widely applied in salient object detection and have achieved remarkable results in this field. However, existing models suffer from information distortion caused by interpolation during up-sampling and down-sampling. In response to this drawback, this article starts from two directions in the network: feature and label. On the one hand, a novel cascaded interaction network with a guidance module named global-local aligned attention (GAA) is designed to reduce the negative impact of interpolation on the feature side. On the other hand, a deep supervision strategy based on edge erosion is proposed to reduce the negative guidance of label interpolation on lateral output. Extensive experiments on five popular datasets demonstrate the superiority of our method