A Deep Causal Inference Approach to Measuring the Effects of Forming Group Loans in Online Non-profit Microfinance Platform

by   Thai T. Pham, et al.

Kiva is an online non-profit crowdsouring microfinance platform that raises funds for the poor in the third world. The borrowers on Kiva are small business owners and individuals in urgent need of money. To raise funds as fast as possible, they have the option to form groups and post loan requests in the name of their groups. While it is generally believed that group loans pose less risk for investors than individual loans do, we study whether this is the case in a philanthropic online marketplace. In particular, we measure the effect of group loans on funding time while controlling for the loan sizes and other factors. Because loan descriptions (in the form of texts) play an important role in lenders' decision process on Kiva, we make use of this information through deep learning in natural language processing. In this aspect, this is the first paper that uses one of the most advanced deep learning techniques to deal with unstructured data in a way that can take advantage of its superior prediction power to answer causal questions. We find that on average, forming group loans speeds up the funding time by about 3.3 days.


page 8

page 9

page 10

page 11

page 13

page 14


Matching Using Sufficient Dimension Reduction for Heterogeneity Causal Effect Estimation

Causal inference plays an important role in under standing the underlyin...

Influence via Ethos: On the Persuasive Power of Reputation in Deliberation Online

Deliberation among individuals online plays a key role in shaping the op...

A Comparison of Online Hate on Reddit and 4chan: A Case Study of the 2020 US Election

The rapid integration of the Internet into our daily lives has led to ma...

The Group Element of Cybercrime: Types, Dynamics, and Criminal Operations

While cybercrime can often be an individual activity pursued by lone hac...

Text as Causal Mediators: Research Design for Causal Estimates of Differential Treatment of Social Groups via Language Aspects

Using observed language to understand interpersonal interactions is impo...

Please sign up or login with your details

Forgot password? Click here to reset