No abstract

Asset-return implications of nominal price and wage rigidities are analyzed in general equilibrium. Nominal rigidities, combined with permanent productivity shocks, increase expected excess returns on production claims. This is mainly explained by consumption dynamics driven by rigidity-induced changes in employment and markups. An interest-rate monetary policy rule affects asset returns. Stronger (weaker) rule responses to inflation (output) increase expected excess returns. Policy shocks substantially increase asset-return volatility. Price rigidity heterogeneity produces cross-sectoral differences in expected returns. The model matches important macroeconomic moments and the Sharpe ratio of stock returns, but only captures a small fraction of the observed equity premium.

We model the interaction of financial constraints, capacity constraints, and the response of production and inventory to cost and demand shocks. The model predicts that in response to favourable shocks, financially constrained firms are unable to build up inventory as rapidly as unconstrained firms. However, because the favourable shocks gradually ease the financial constraints, constrained firms continue to build inventory and eventually carry surplus inventory (relative to unconstrained firms) to unfavourable states. This allows them to deplete inventory more aggressively in response to unfavourable shocks. Our empirical evidence provides broad support for the model's predictions.

Embedding disasters into a general equilibrium production economy with heterogeneous firms induces strong nonlinearity in the pricing kernel, helping explain the empirical failure of the (consumption) CAPM. Our single-factor model reproduces the failure of the CAPM in explaining the value premium in finite samples without disasters, and its relative success in samples with disasters. The standard consumption CAPM fails in simulations, even though a nonlinear model with the true pricing kernel holds exactly by construction. Due to beta measurement errors, the relation between the pre-ranking beta and the average return is flat in simulations, consistent with the beta "anomaly," even though the true beta-expected return relation is strongly positive. In all, the empirical failures of standard asset pricing models should be interpreted with caution.

The relation between a firm's stock return and its intangible assets is derived under the intangible-asset-augmented q-theory framework. The structural estimation of the model leads to four main results. First, the q-theory augmented with intangible investments captures the value premium and the relation between R&D intensity and stock returns significantly better than the conventional q-theory. Two features of intangible assets, adjustment costs and investment-specific-technological-change, are crucial to the improved model performance. Second, higher R&D intensity, defined as the ratio of R&D expenditure to intangible assets, leads to lower stock returns. Third, the q-theory augmented with intangible investments gives a more reasonable estimate of adjustment costs of tangible investments than the conventional q-theory does. Fourth, the magnitude of adjustment costs of R&D investments is estimated to be larger than that of tangible investments.