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. An investment strategy that longs (shorts) equities with low (high) utilization rates earns 5\% p.a. We reconcile this novel utilization premium quantitatively using a production model. Beyond explaining the premium, the model suggests that flexible utilization is key for matching the cross-sectional distribution of investment and stock prices jointly. A model without flexible utilization yields many counterfactuals, such as investment's dispersion being too low, and its skewness bearing the wrong sign. Flexible utilization can address these moments by making depreciation rates fluctuate endogenously. Overall, utilization tightens the link between firms' production and valuation.
We study the relation between trade credit, the dynamics of supplier-customers links in the production network, and risk. We find that firms that extend more trade credit (i) earn 7% p.a. lower returns, and (ii) maintain longer relationships with their customers. We also document that (iii) suppliers with longer-duration links to their customers earn lower expected returns. We quantitatively explain these facts using a production-based model. Trade credit helps to protect customers from defaulting, and reduces suppliers' exposure to search frictions incurred in finding new customers. Overall, trade credit is informative about the lifespan of supplier-customer links, which affects valuations.
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.