Firms that underutilize their capital are riskier. A quantitative model with production and flexible capacity utilization predicts a return spread between low and high utilization firms of above 5% p.a. Consistent with the model, we establish this utilization spread in the data as a novel empirical fact. Beyond the utilization premium, we show that a model without utilization yields many counterfactuals, such as investment’s dispersion being too low, and its skewness bearing the wrong sign. Flexible utilization can addresses these moments by endogenously substituting large adjustment costs. Overall, utilization tightens the link between firms’ production and valuation.
Using a sample of the 48 contiguous United States, we consider the problem of forecasting state and local governments' revenues and expenditures in real time using models featuring mixed-frequency data. Among the single-equation models we consider, we find that ADL-MIDAS regressions combining high-frequency economic variables together with low-frequency fiscal data yield forecast gains over traditional models in which all data are included at the same (low) sampling frequency. Among the multi-equation models we consider, we find that low-frequency Bayesian vector autoregressions (BVARs) typically outperform both mixed-frequency Bayesian vector autoregressions (MF-BVARs) and low-frequency vector autoregressions (VARs). When we directly compare the forecasts from ADL-MIDAS regressions to those from MF-BVARs and BVARs, we find that ADL-MIDAS models typically produce the most accurate forecasts of state-level revenues and expenditures. A simulation exercise confirms this conclusion and shows that ADL-MIDAS models typically produce accurate forecast in many empirically realistic settings. Overall, our results show that ADL-MIDAS regressions provide policy makers and market participants with a simple yet reliable tool for forecasting fiscal variables in real time.
Firms with higher receivables-to-sales ratios (R/S) extend more trade credit, and thus have greater exposure to risks that impact their counterparties. Surprisingly however, high R/S firms command risk premia that are 6% per annum lower than those of low R/S firms. This novel R/S spread is not explained by common asset-pricing factors or characteristics, and a novel factor based on the spread is priced in the cross-section of returns. We use production network data to show that low R/S firms have shorter-lived (lower duration) links with their customers, and that low link duration firms command higher returns. We embed trade credit into the production-based asset-pricing framework to jointly explain these facts. In the model, receivables act as an insurance policy that suppliers may offer certain customers to hedge their liquidity risks. High R/S firms are endogenously matched with better counterparties, and the hedge they provide makes the links with their customers last longer. Consequently, high R/S firms are less exposed to costly frictions involved in the search for a new counterparty, and are therefore safer. Overall, our empirical and theoretical results show that R/S contains important information for forecasting the duration of supplier-customer links, which in turn impacts firms’ riskiness and valuations.
Works In Progress
The term structure of municipal bond yields, local economic conditions, and local stock returns
(Very) Short Term Return Predictability