Why did the q theory of investment start working?

• 成果类型: Article
• 署名作者: Andrei, Daniel; Mann, William; Moyen, Nathalie
• 署名单位: McGill University; University of California System; University of California Los Angeles; University of Colorado System; University of Colorado Boulder
• 刊物名称: JOURNAL OF FINANCIAL ECONOMICS
• ISSN/ISSBN: 0304-405X
• DOI: 10.1016/j.jfineco.2019.03.007
• 发表日期: 2019
• 页码: 251-272
• 关键词: investment; Tobin's Q; research and development; INNOVATION; learning

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.