No abstract

No abstract

Recent research documents the empirical phenomenon of “sticky costs” and attributes it to a theory of deliberate managerial decisions in the presence of adjustment costs. We refine this theoretical explanation and show that it gives rise to a more complex pattern of asymmetric cost behavior that combines two opposing processes: cost stickiness conditional on a prior sales increase, and cost anti-stickiness conditional on a prior sales decrease. These predictions reflect the structure of optimal decisions with adjustment costs and the impact of prior sales changes on managers' expectations about future sales changes. Empirical estimates for Compustat data support our hypotheses. We further verify our predictions using additional proxies for managers' expectations, and show that our model offers important new insights. JEL Classifications: D24; M41.

Recent work in management accounting offers several novel insights into firms' cost behavior. This study explores whether financial analysts appropriately incorporate information on two types of cost behavior in predicting earnings—cost variability and cost stickiness. Since analysts' utilization of information is not directly observable, we model the process of earnings prediction to generate empirically testable hypotheses. The results indicate that analysts “converge to the average” in recognizing both cost variability and cost stickiness, resulting in substantial and systematic earnings forecast errors. Particularly, we find a clear pattern—inappropriate incorporation of available information on cost behavior in earnings forecasts leads to larger errors in unfavorable scenarios than in favorable ones. Overall, enhancing analysts' awareness of the expense side is likely to improve their earnings forecasts, mainly when sales turn to the worse. JEL Classifications: M41; M46; G12.

We investigate the relationship between R&D investments and loan spread. Prior research documents that R&D is associated with greater future benefits and risks, suggesting that the valuation of R&D depends on a tradeoff between the two. Some research finds that bondholders consider that the benefits of R&D outweigh its risks: R&D is negatively associated with bond yields. This is surprising given that debt holders are more concerned about downside risk due to asymmetric payoffs. Using data on private debt from the US, we find an overall positive association between loan spread and R&D intensity, suggesting that the riskiness of R&D appears to outweigh its benefits for private lenders. Furthermore, an asymmetric payoff structure implies that the risks of R&D for lenders increase with default risk. Consistent with this argument, we find a positive association between R&D and loan spread for firms that are smaller, with high default‐risk ratings, unrated (no public debt), or in industries with weaker legal protection. Unrated firms are in the most R&D‐intensive group and make up nearly 60% of the firms with private debt. Consequently, studies that exclude unrated firms are likely to present an incomplete picture of the perspective of debt holders on R&D.