A Note on the Use of Syndicated Loan Data

IF 1.2 4区经济学 Q3 BUSINESS, FINANCE

International Finance Pub Date : 2025-09-22 DOI:10.1111/infi.70005

Isabella Mueller, Felix Noth, Lena Tonzer

引用次数: 0

Abstract

Syndicated loan data provided by DealScan is an essential input in banking research to answer urging questions on bank lending, e.g., in the presence of financial or geopolitical shocks or climate change. However, many data options raise the question of how to choose the estimation sample. We employ a standard regression framework analyzing bank lending during the financial crisis of 2007/08 to study how conventional but varying usages of DealScan affect the estimates. The key finding is that the direction of coefficients remains relatively robust. However, statistical significance depends on the data and sampling choice, and we provide guidelines for applied research.

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关于使用银团贷款数据的说明

DealScan提供的银团贷款数据是银行研究的重要输入，可以回答有关银行贷款的紧迫问题，例如，在金融或地缘政治冲击或气候变化的情况下。然而，许多数据选项提出了如何选择估计样本的问题。我们采用标准回归框架分析2007/08年金融危机期间的银行贷款，以研究DealScan的传统但不同的用法如何影响估计。关键的发现是，系数的方向仍然相对稳健。然而，统计显著性取决于数据和抽样选择，我们为应用研究提供指导。

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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来源期刊

International Finance Multiple-

CiteScore

2.50

自引率

8.30%

发文量

期刊介绍： International Finance is a highly selective ISI-accredited journal featuring literate and policy-relevant analysis in macroeconomics and finance. Specific areas of focus include: · Exchange rates · Monetary policy · Political economy · Financial markets · Corporate finance The journal''s readership extends well beyond academia into national treasuries and corporate treasuries, central banks and investment banks, and major international organizations. International Finance publishes lucid, policy-relevant writing in macroeconomics and finance backed by rigorous theory and empirical analysis. In addition to the core double-refereed articles, the journal publishes non-refereed themed book reviews by invited authors and commentary pieces by major policy figures. The editor delivers the vast majority of first-round decisions within three months.