Journal of Development Economics · 2025 · Yutong Chen、Gaurav Chiplunkar、Sheetal Sekhri、Anirban Sen、Aaditeshwar Seth
中文摘要
我们采用一种由机器学习赋能、基于社会网络的新型测量技术，构建了一套关于印度企业政治关联的新数据集。我们将该数据集与企业详细金融交易的长期面板数据相结合，研究企业在经济衰退期间如何利用这些关联。运用合成双重差分框架，我们发现，政治关联企业的收入、销售额和全要素生产率收益（TFPR）增幅高出8%–10%，且这一效应在危机发生后的三年多时间里持续存在。我们进一步剖析了多种新颖的机制，结果表明，政治关联企业能够减少成本高昂的银行长期借款，转而采用无抵押的短期借款；增加从政府获得的借款；推迟向供应商和债权人支付短期应付款项；推迟偿还债务和支付利息；并增加对计算机和软件等生产性资产的投资。我们识别政治关联的方法可移植至其他应用和情境。
Abstract
We use a new machine learning-enabled, social network based measurement technique to assemble a novel dataset of firms’ political connections in India. Combining it with a long panel of detailed financial transactions of firms, we study how firms leverage these connections during an economic downturn. Using a synthetic difference-in-differences framework, we find that connected firms had 8%–10% higher income, sales, and TFPR gains that were persistent for over a three-year period following the crisis. We unpack various novel mechanisms and show that connected firms were able to decrease expensive long-term borrowings from banks in favor of short-term non-collateral ones, increase borrowing from the government, delay their short-term payments to suppliers and creditors, delay debt and interest payments, and increase investments in productive assets such as computers and software. Our method to determine political connections is portable to other applications and contexts.