We recover a stochastic discount factor (SDF) for asset returns from a firm’s investment Euler equation. Given a parametric statistical specification of the SDF and profitability process, we solve for the firms’ optimal investment decision with approximate analytical solutions and provide a dissection of the determinants of real investment. We estimate a specification of the model to discipline the free parameters of the SDF by matching moments of both aggregate real quantities and asset prices. We use the estimated parameters to recover the latent SDF from data on aggregate investment rates, risk-free rates, and profitability growth rates. Innovations in the recovered SDF are driven dominantly by innovations in investment rates and marginally by innovations in risk-free rates and profitability growth rates. The recovered SDF exhibits strong counter-cyclicality with large jumps in recessions and prices standard Fama-French portfolios out of sample reasonably well. Our model allows us to explicitly characterize the risk-free rate, the equity premium, the term structure of interest rates, and the term structure of equity risk premia. The framework we propose here is general and can be extended to accommodate several additional aggregate shocks and frictions that have been proposed in the literature.

The recent linear factor models (e.g., Fama and French (2015) and Hou, Xue, and Zhang (2015)) use total asset growth as the measure of investment, largely due to its stronger return predictive power than its components such as the long-term and current asset growths. We offer an explanation of the latter finding by extending the standard q theory of investment into a two-capital setup in which firms use both long-term and current asset as production inputs. We uncover a novel asset imbalance channel which creates negative comovement between current and long-term asset growths that are unrelated to discount rate. This comovement is muted in the total asset growth, giving rise to its stronger return prediction. Once controlling for this comovement, the return predictive power of current and long-term asset growths substantially improves. Furthermore, we document strong evidences for the model's prediction that the asset growth effects are more prominent among firms with low asset imbalance. Our results support the q theory based explanation for the asset growth effect.

We argue that leasing is an important mitigation channel of credit constraint-induced capital misallocation. However, the existing literature neither includes leased capital in empirically measuring capital allocation efficiency, nor recognizes its mitigation role economically. Empirically, we show that neglecting leased capital and overlooking its mitigation effect leads to significant overestimations of capital misallocation and the cyclicality of capital misallocation. Theoretically, we develop a dynamic general equilibrium model with heterogeneous firms, collateral constraint, and an explicit buy versus lease decision to demonstrate and quantify the role of leasing in mitigating capital misallocation. We provide strong empirical evidence to support our theory.