Data vs Collateral

L. Gambacorta, Yiping Huang, Zhenhua Li, Hannuo Qiu, Shu Chen
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引用次数: 36

Abstract

Using a unique dataset of more than 2 million Chinese firms that received credit from both an important big tech firm (Ant Group) and traditional commercial banks, this paper investigates how different forms of credit correlate with local economic activity, house prices and firm characteristics. We find that big tech credit does not correlate with local business conditions and house prices when controlling for demand factors, but reacts strongly to changes in firm characteristics, such as transaction volumes and network scores used to calculate firm credit ratings. By contrast, both secured and unsecured bank credit react significantly to local house prices, which incorporate useful information on the environment in which clients operate and on their creditworthiness. This evidence implies that the wider use of big tech credit could reduce the importance of the collateral channel but, at the same time, make lending more reactive to changes in firms’ business activity.
数据vs抵押品
本文使用200多万家中国企业的独特数据集,这些企业从一家重要的大型科技公司(蚂蚁集团)和传统商业银行获得信贷,研究了不同形式的信贷与当地经济活动、房价和企业特征之间的关系。我们发现,在控制需求因素时,大型科技信贷与当地商业状况和房价无关,但对企业特征(如交易量和用于计算企业信用评级的网络分数)的变化反应强烈。相比之下,有担保和无担保的银行信贷对当地房价的反应都很大,因为房价包含了有关客户经营环境及其信誉的有用信息。这一证据表明,更广泛地使用大型科技信贷可能会降低抵押品渠道的重要性,但与此同时,使贷款对企业业务活动的变化更具反应性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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