Knowledge that Transforms

Abstract We study the influence of bounded rationality on companies’ disclosure to investors in new industries. Using a historical example of a new industry, we document that several companies initially withheld their earnings, despite external capital needs and investor information demands. However, almost all these companies started disclosing shortly thereafter. Interpreted through the lens of a disclosure model featuring level-$ k $ thinking, these patterns suggest that limited strategic thinking of some companies contributed to the initial failure to disclose, while feedback and learning over time contributed to the quick convergence to an equilibrium of (almost) full disclosure in the new industry.

Abstract We quantify the cost of pledging collateral for small businesses by exploiting a regulatory quirk of the SBA disaster lending program in which firms are exempt from posting collateral if their loan size is below a threshold. Firms bunch their loans below the threshold, and the resultant distortion in the loan size distribution reveals the magnitude of the collateral cost. The collateral cost is substantial and varies across collateral types, business sectors, and collateral laws in ways consistent with flexibility-based theories. Our findings have implications for firms’ borrowing constraints and disaster lending program designs.

Abstract We analyze changes to mutual funds’ self-declared benchmarks using hand-collected data from funds’ prospectuses. Under existing rules, funds can freely change their benchmark indexes and, implicitly, the historical returns to which they compare their past performance. Funds exploit this loophole by adding (dropping) indexes with lower (higher) past returns, thereby materially improving the appearance of their benchmark-adjusted returns. High-fee funds, broker-sold funds, and funds experiencing poor performance and outflows are more likely to engage in this behavior. These funds subsequently attract additional flows despite continuing to underperform their peers.

Abstract We study the impact of uncertainty on optimal contracting in a multidivisional firm. Headquarters contract with division managers to induce effort. Uncertainty creates endogenous disagreement, thereby aggravating moral hazard. By hedging uncertainty, headquarters design incentive contracts that reduce disagreement and lower incentive provision costs, thereby promoting effort. Because hedging uncertainty can conflict with hedging risk, optimal contracts differ from those in standard principal-agent models. Our model helps explain the prevalence of equity-based incentive contracts and the rarity of relative-performance contracts, especially in firms facing greater uncertainty.

Abstract We present a novel methodology for the out-of-sample forecast of the equity premium. Our predictive slope coefficient is a conservative constant that has a lower bias than the zero slope employed by the historical average, but has the same variance. We demonstrate that, theoretically and empirically, our method dominates the historical average in forecast performance. Our methodology establishes a simple yet powerful paradigm for exploiting the real-time equity premium predictability derived from a predictor. Applications of our method reveal that many predictors can forecast the equity premium, and that parameter estimates in previous studies add value to out-of-sample forecasts.