Previous studies show that firms with low inventory growth outperform firms with high inventory growth in the cross-section of publicly traded firms. In addition, inventory investment is volatile and procyclical, and inventory-to-sales is persistent and countercyclical. We embed an inventory holding motive into the investment-based asset pricing framework by modeling inventory as a factor of production with convex and nonconvex adjustment costs. The augmented model simultaneously matches the large inventory growth spread in the data, as well as the time-series properties of the firm-level capital investment, inventory investment, and inventory-to-sales. Our conditional single-factor model also implies that traditional unconditional factor models such as the CAPM should fail to explain the inventory growth spread, although not with the same large pricing errors observed in the data. The Author 2011. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: [email protected]., Oxford University Press.

Investment-based asset pricing models typically predict a close link between a firm’s stock return and its characteristics at any point in time. Yet, previous studies have primarily focused on the weaker prediction that this link holds on average, finding substantial empirical support. We show how to incorporate the time-series predictions in the estimation and testing of investment-based models using the generalized method of moments. We find that standard specifications of investment-based models with one physical capital input fail to match the time series properties of stock returns in the data, and discuss the implications of the findings for future research.

We develop a dynamic model with time variation in external equity financing costs and show that variation in these costs is important for the model to quantitatively capture the joint dynamics of firms’ asset prices, real quantities, and financial flows in the U.S. economy. Growth firms and high investment firms are less risky in equilibrium, because they can substitute more easily debt financing for equity financing when it becomes more costly to raise external equity, which are high marginal utility states. Using a model-implied proxy of aggregate equity issuance cost shocks, we provide empirical support for the model’s economic mechanism. Received August 7, 2017; editorial decision September 24, 2018 by Editor Stijn Van Nieuwerburgh.

We study the impact of labor market frictions on asset prices. In the cross section of US firms, a 10 percentage point increase in the firm’s hiring rate is associated with a 1.5 percentage point decrease in the firm’s annual risk premium. We propose an investment-based model with stochastic labor adjustment costs to explain this finding. Firms with high hiring rates are expanding firms that incur high adjustment costs. If the economy experiences a shock that lowers adjustment costs, these firms benefit the most. The corresponding increase in firm value operates as a hedge against these shocks, explaining the lower risk premium of these firms in equilibrium.

Using a novel measure of industry exposure to government spending, we show predictable variation in cash flows and stock returns over political cycles. During Democratic presidencies, firms with high government exposure experience higher cash flows and stock returns, while the opposite pattern holds true during Republican presidencies. Business cycles, firm characteristics, and standard risk factors do not account for the pattern in returns across presidencies. An investment strategy that exploits the presidential cycle predictability generates abnormal returns as large as 6.9% per annum. Our results suggest market underreaction to predictable variation in the effect of government spending policies.

What are the economic determinants of a firm’s market value? We answer this question through the lens of a generalized neoclassical model of investment with quasi-fixed labor and three heterogeneous capital inputs. We estimate the structural model using firm-level data on US firms and find that, on average and depending on the industry, installed labor force accounts for 14–21% of firms’ market value, physical capital accounts for 30–40%, knowledge capital accounts for 20–43%, and brand capital accounts for 6–25%. Our analysis provides direct empirical evidence for the importance of labor and intangible capital inputs for understanding firm value.