This study shows that the municipal yield curve is informative about local economic outcomes. Controlling for Treasury yields, a flatter municipal yield curve not only predicts deteriorating local economic conditions, such as higher unemployment rates and more macroeconomic uncertainty, but also signals greater risk for locally headquartered firms. An investment strategy that exploits this fact by buying (selling) firms located in states where municipal yield curve is relatively flat (steep) earns an excess return that exceeds 5% per annum. These novel empirical results indicate that the municipal debt market provides valuable information about the trajectories and risks of local economies.
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.
We study the relationship between trade credit, the dynamics of the production network’s links, and firms’ exposure to counterparty risk. We document two novel facts: (i) Firms that extend more trade credit to their customers (trade counterparties), and have higher receivables-to-sales ratios (R/S), earn 7% p.a. lower risk premia than low R/S firms. This return spread is not explained by common asset-pricing factors or firm characteristics. A novel risk factor based on this spread is priced in the crosssection of returns. (ii) High R/S firms have longer duration links with their customers, and a longer duration is associated with a lower risk premium. We jointly explain these facts using a production-based model, where trade credit is a device to hedge a firm’s customer against liquidity shocks. High R/S firms are endogenously matched with better customers to which they provide more trade credit, thereby extending the expected link duration with their customers. Consequently, high R/S firms are less exposed to costly frictions incurred in the search for new customers. Overall, our results show that trade credit contains important information to forecast supplier-customer links’ duration, which in turn impacts firms’ risk premia.
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.