Expected fees for managed futures, optimal feeder cattle price slides, and aggregate vs. disaggregate data in measuring school effectiveness

Scope and method of study. This study consists of three distinct essays. Expected Fees for Managed Futures explains commodity fund manager's behavior by modeling managed capital in the presence of a knockout feature. Based on the model, fixed and incentive fees are calculated as a function of invested capital. The second essay, Optimal Feeder Cattle Price Slides, models the pricing mechanism used when cattle are sold for future delivery and agents have asymmetric information. A game-theoretical model is used to derive hypotheses that are tested using regression models and data from a satellite video auction. The final essay, Aggregate vs. Disaggregate Data in Measuring School Effectiveness, constructs an efficient estimate of school quality based on aggregate data. Then it compares it with estimators commonly used based on aggregate and disaggregate data (multilevel-value added estimators). The theory is supported with a Monte Carlo study that allows comparing these estimators in the presence of measurement error and for different school characteristics such as size.;Findings and conclusions. The first essay finds that the fixed fee and the knockout feature can explain why managers do not invest all capital in margins. In the presence of a knockout rule, the incentive fee does encourage investing all capital, but the fixed fee counteracts this effect due to the risk of ruin. Thus managers maximize their total fees by investing only part of the available capital. The second essay shows that based on the model, price slides should be higher than what extension work suggests. This finding is supported empirically as well. The last essay suggests school officials should use the proposed estimator of quality rather than the one commonly used and based on OLS, when data are aggregated. The proposed estimator eliminates the bias toward small schools that OLS has shown. Compared to the disaggregate data-estimator, differences in performance are smaller than what past research had suggested.