Conference Agenda

We develop a model with multiple sectors connected through both knowledge and physical input-output networks, in which knowledge productivity evolves endogenously through firms’ investments in human capital devoted to R&D. The network structures in the model determine economic dynamics and constitute systematic risk in asset pricing, and predict that the sparsity of knowledge network increases aggregate consumption and leads to positive risk premium. Our model implications receive empirical support as follows: (i) consumption growth increases with knowledge network sparsity; (ii) firms with higher exposures to knowledge network sparsity carry higher expected stock returns; and (iii) knowledge network sparsity exists in the stochastic discount factor and helps price the cross section of stock returns.

Do financial markets price knowledge spillovers? We show that patent grants influence the stock returns of firms that are connected through technological knowledge dependencies.

Using directed patent citations among publicly listed companies in the United States, we construct a granular measure of each firm's exposure to new patents granted to its technologically upstream firms. Patents granted to these upstream companies significantly boost its abnormal stock returns during the week of the grant. This contrasts with the gradual fade-out of returns from a firm's own patent grants, indicating a gradual diffusion of information in markets. We find that these financial spillovers are predominantly localized within a firm's immediate technological connections. Additionally, we provide a novel empirical decomposition of financial spillovers generated from patent grants, by distinguishing those spillovers emerging from sources of technological knowledge, from those emerging from product market rivals (negative effect) and suppliers (positive effect). Our findings are robust to alternative specifications and placebo tests, and they suggest that technological knowledge spillovers create important market-priced ties between firms that are not fully captured by traditional product market relationships.

Privacy regulation is typically studied through its effects on firms and consumers, while its implications for financial markets remain unexplored. We use Apple’s App Tracking Transparency (ATT) to examine whether privacy-driven data sharing restrictions spill over to capital markets by reducing the precision of widely used signals. After ATT, analysts relying more heavily on such data become less accurate, and mutual funds shift attention away from affected stocks. Consequently, firms more exposed to these market participants exhibit weaker price efficiency. Our findings reveal a new fragility in financial markets as surveillance-like alternative data becomes increasingly vulnerable to future regulatory disruption.