Upstream, Downstream & Common Firm Shocks

E. Grant, Julieta Yung
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引用次数: 3

Abstract

We develop a multi-sector DSGE model to calculate upstream and downstream industry exposure networks from U.S. input-output tables and test the relative importance of shocks from each direction by comparing these with estimated networks of firms’ equity return responses to one another. The correlations between the upstream exposure and equity return networks are large and statistically significant, while the downstream exposure networks have lower — but still positive — correlations that are not statistically significant. These results suggest a low short-term elasticity of substitution across inputs transmitting shocks from suppliers, but more flexible ties with downstream firms. Additionally, both the DSGE model and simulations of our empirical approach highlight the importance of accounting for common factors in network estimation, which become more important over our 1989-2017 sample period, explaining 11.7% of equity return variation over the first ten years and 35.0% over the final ten.
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上游,下游和常见的公司冲击
我们开发了一个多部门DSGE模型来计算美国投入产出表中的上游和下游行业风险网络,并通过将这些网络与公司股权回报响应的估计网络进行比较,来测试来自每个方向的冲击的相对重要性。上游风险敞口与股权回报网络之间的相关性很大,且具有统计学意义,而下游风险敞口网络之间的相关性较低,但仍为正相关,但不具有统计学意义。这些结果表明,短期内不同投入之间的替代弹性较低,传递来自供应商的冲击,但与下游企业的联系更灵活。此外,DSGE模型和我们的实证方法的模拟都强调了在网络估计中考虑共同因素的重要性,这在我们1989-2017年的样本期间变得更加重要,解释了前十年11.7%的股票回报变化和后十年35.0%的股票回报变化。
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