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AI 根据所提供的论文材料归类:摘要直接研究社会网络与全局溢出,并使用双重差分和随机试验分析信贷进入的影响。

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关注这篇论文的作者
Abhijit Banerjee
Emily Breza
Esther Duflo
Matthew O Jackson
Cynthia Kinnan

正规信贷市场进入如何改变社会网络结构

研究问题
小额信贷机构进入后,社会联系、非正式借贷与风险分担如何变化,影响是否会扩散到原本不太可能借款的家庭?
方法与思路
作者结合印度村庄的双重差分研究与另一地区的随机进入试验,并建立强调偶遇及社交努力全局外部性的动态网络形成模型。
材料陈述的贡献
摘要称,两项研究均发现网络联系减少,较不可能借款的家庭也受影响;其非正式借贷与风险分担损失凸显网络层面的溢出。
阅读关注点
应核对双重差分的识别依据、随机试验后续普遍进入下的比较含义,以及网络测量和动态模型如何支持全局外部性解释。
阅读边界
摘要未提供平行趋势证据、网络效应估计量或模型识别细节,不能仅凭两地结果判断机制唯一性及其他地区的适用性。

原文摘要

Abstract We show that the entry of formal financial institutions can have far-reaching and long-lasting impacts on informal lending and social networks more generally. We first study the introduction of microfinance in 75 villages in Karnataka, India, 43 of which were exposed to microfinance. Using difference-in-differences, we show that networks shrank more in exposed villages. Moreover, links between households that were both unlikely to borrow from microfinance were at least as likely to disappear as links involving likely borrowers. We replicate these surprising findings in the context of a randomised controlled trial (RCT) in Hyderabad, where a microfinance institution randomly selected 52 of 104 neighbourhoods to enter first. Four years after all neighbourhoods were treated, households in early-entry neighbourhoods had credit access longer and had larger loans. We again find fewer social relationships between households in these neighbourhoods, even among those ex-ante unlikely to borrow. Because the results suggest global spillovers, atypical in usual models of network formation, we develop a new dynamic model of network formation that emphasizes chance meetings, where efforts to socialize generate a global network-level externality. Finally, we analyse informal borrowing and the sensitivity of consumption to income fluctuations. Households unlikely to take up microcredit suffer the greatest loss of informal borrowing and risk sharing, underscoring the global nature of the externality.

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