Abstract: These three essays investigate three different cases where naïve good intentions - policy or econometric - actually lead to suboptimal policy or measurement outcomes. In the first chapter, James Hilger and I investigate bias in the commercial passenger fishing vessel (CPFV) industry when a naïve researcher estimates willingness to pay estimates (WTP), derived from random utility models (RUM), in the context of vessel sellouts. Using incorrectly estimated WTP measures may lead to undervaluation of natural resources. In the second essay, Richard Carson, Melissa Famulari, and I simulate a university with a benevolent higher level administrator who wants to keep per-student funding roughly the same, or same with adjustment for preferences, across the university in a CES-style fashion. If students also prefer to major in departments with high per-student funding, these two goals are in conflict and necessitate the higher-level administrator to lower per-student funding for popular departments. Using data from UCSD, we find that departments with large numbers of students are less expensive per degree, have higher modified student-to-faculty ratios, and graduate students sooner than other departments. In the third essay, I investigate the transition from methyl tertiary-buthyl ether- (MTBE-) enhanced to ethanol-enhanced (E-10) fuel in the Northeastern United States. Using a complicated set of phase-ins and phase-outs, I use difference-in-difference estimation to show that ambient acetaldehyde pollution substantially increased in percentage terms because of E-10 -- although this is a small level increase, since the level of acetaldehyde is low in the area. Using a stylized calculation based on cancer risk still shows damages of this pollution are levels of magnitude lower than the billion dollar water pollution cleanup costs from MTBE additive.
Keywords: Willingness to pay,Acetaldehyde pollution,Commercial passenger fishing vessels,Fisheries, Higher education