动态公司股利平滑:一个结构向量自回归模型

IF 9.8 1区 经济学 Q1 BUSINESS, FINANCE
Antonio Renzi, Pietro Taragoni, Gianluca Vagnani
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引用次数: 0

摘要

我们利用结构向量自回归(SVAR)模型和方差分解方法来增加现有的公司支付平滑的横断面研究。首先,我们使用面板数据将净收入冲击纳入多方程框架,从而捕捉净收入波动性与各种平滑机制(特别是债务和投资)之间的动态相互作用。随后,在动态模型和不同的结构冲击下,我们采用脉冲响应函数来阐明平滑通道随时间的相互依赖性。我们的模型是在美国金融市场中运作的组织样本上实现的。我们将我们的发现与横断面公司支出平滑的预测进行了比较,提供了强有力的经验证据,证明债务和投资之间的动态相互作用是净收入-支出方差关系背景下的平滑渠道。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic corporate payout smoothing: A structural vector autoregressive model
We utilize a structural vector autoregressive (SVAR) model and a variance decomposition methodology to augment the existing cross-sectional studies on corporate payout smoothing. Initially, we incorporate the net income shocks within a multi-equation framework using panel data, thus capturing the dynamic interplay between volatility in net income and various smoothing mechanisms, specifically debt and investments. Subsequently, under dynamic models and diverse structural shocks, we employ impulse response functions to elucidate the interdependencies of smoothing channels over time. Our model is implemented on a sample of organizations operating within U.S. financial markets. We compare our findings with predictions from cross-sectional corporate payout smoothing, offering robust empirical evidence of the dynamic interaction between debt and investments as smoothing channels within the context of the net income–payout variance relationship.
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来源期刊
CiteScore
10.30
自引率
9.80%
发文量
366
期刊介绍: The International Review of Financial Analysis (IRFA) is an impartial refereed journal designed to serve as a platform for high-quality financial research. It welcomes a diverse range of financial research topics and maintains an unbiased selection process. While not limited to U.S.-centric subjects, IRFA, as its title suggests, is open to valuable research contributions from around the world.
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