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Why did the q theory of investment start working?

机译：为什么q投资理论开始起作用？

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摘要

We show that the relation between aggregate investment and Tobin's g has become remarkably tight in recent years, contrasting with earlier times. We connect this change with the growing empirical dispersion in Tobin's q, which we show both in the cross-section and the time series. To study the source of this dispersion, we augment a standard investment model with two distinct mechanisms related to firms' research activities: innovations and learning. Both innovation jumps in cash flows and the frequent updating of beliefs about future cash flows endogenously amplify volatility in the firm's value function. Perhaps counterintuitively, the investment-q regression works better for research-intensive industries, a growing segment of the economy, despite their greater stock of intangible assets. We confirm the model's predictions in the data, and we disentangle the results from measurement error in q. (C) 2019 Elsevier B.V. All rights reserved.
机译：我们发现，总投资和托宾克之间的关系近年来变得非常紧密，与早期相比形成了鲜明的对比。我们将此变化与托宾q的不断增长的经验分散联系起来，我们在横截面和时间序列中均显示了这一点。为了研究这种分散的根源，我们用与公司研究活动有关的两种不同机制扩充了标准投资模型：创新和学习。现金流量的创新性增长和对未来现金流量的观念的不断更新内生地扩大了公司价值功能的波动性。也许与直觉相反，尽管无形资产存量较大，但投资q回归对于研究密集型行业，经济增长中的部门更有效。我们在数据中确认模型的预测，然后从q中的测量误差中解开结果。 （C）2019 Elsevier B.V.保留所有权利。

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