CHFS

  • 详情 Religion, Places of Worship, and Individual Risk-taking in China
    The influence of religious beliefs on investment is interesting and important in literature. We use a large dataset with detailed information on the worship places of the five largest religious groups in China to study the relationship between local religious beliefs and individual financial decisions. We find that Buddhists, Taoists, Islamists, and Catholics are less likely to buy financial products on the financial market; Protestants tend to take risks compared to other believers. Chinese Protestants, unlike American Christians, seek more risk, while Catholics are risk-averse.
  • 详情 移动互联网可及性对家庭风险金融资产配置的影响
    文章利用CHFS(2019)调查数据,实证研究了移动互联网可及性对家庭风险金融资产配置的影响。结果表明:移动互联网可及性能显著提高家庭参与风险金融资产配置的概率和占比;异质性分析表明,在家庭是否参与风险金融资产配置方面,移动互联网可及性对低收入、城镇户口、受教育程度在高中及以上的家庭的影响程度更大;在家庭风险金融资产配置占比方面,移动互联网可及性对低收入、乡村户口、受教育程度在高中及以上的家庭影响程度更大;机制分析显示,移动互联网可及性可通过提高金融素养、增强投资便利性和增加家庭总收入,进而提高家庭参与风险金融资产配置的概率和程度。根据实证结果,本文提出了一些可行的政策建议。
  • 详情 The Effect of the Digital Divide on Household Consumption in China
    Over the past decade, the rapidly digitizing economy in China has attracted much attention in both academic and policy circles. Most existing studies focus on the positive impact digitalization has had on China's inclusive growth. Few of them have attempted to measure the widening digital divide and its potential impact. Using the 2017 and 2019 China Household Finance Survey (CHFS) data, this paper: (i) provides the first evidence that the digital divide has a significant negative impact on household consumption. For every unit increase in the digital divide, the level of household consumption will drop by about 28 percent; (ii) finds the negative impact stems from an integrated channel of rising unemployment, intensified liquidity constraints, and declining financial literacy; and (iii) further discloses that the digital divide has differential impacts on household consumption by category, while hinders consumption diversification. The results are robust to correcting for potential endogeneity due to sample selection, household heterogeneity, and reverse causality. Our findings shed new light on some little-documented evidence and have profound implications for related socio-economic policies that fully utilize technology to drive efficiency and inclusivity in the digital economy.