Enlightened House Parties

In a duplex with 10 residents, finding compromise between all the members is a difficult process. This problem becomes especially apparent when planning an event that incorporates all ten members, such as a party. For each party we have thrown over the last 15 months, we have had arguments over the party budget to spend on beverages and other party supplies. To resolve this problem, we generally discuss our preferences for party budget and find an average preferred amount to spend on the party. Public choice offers some perspectives on the efficacy of this method at determining party budget. 

On one hand, the “Miracle of Aggregation” provides that averaging all the preferences in the house would produce an effective party budget. According to this theory, the biases are symmetrically distributed between those cost-averse and those inclined to more spending on the party. As a result, the biases cancel out and the aggregate opinion is an accurate party budget.  However, if the biases are instead systemic, this system does not work, and we should instead use enlightened preferences. 

To discover enlightened preferences, we can use data analysis based on that used in the psychology discipline, as discussed by Bryan Caplan. To perform this analysis, we need to incorporate three variables for each member of the house: answers to survey questions about the party budget, demographic variables, and OPK (objective party knowledge). In our case, the demographic CV’s (control variable) are largely irrelevant, as aside from some racial diversity we are a mostly homogeneous group of 10 fourth-year college guys from similar familial and socioeconomic backgrounds. 

To assess our OPK, every member of the house will be asked right-or-wrong party questions, such as the average amount of people at our previous parties, the average amount of beverages consumed by each party guest, and the price of different types of beverages.  Once we compare the answers to our comprehensive party database collected from previous parties, we can assess individual residents’ Objective Party Knowledge. We can then run regression tests of OPK over survey questions to articulate the enlightened party budget preferences of the more informed residents. 

Finally, we can compare the enlightened preferences with the average preferences of the house to determine if the residents of the house display a pro-spending or anti-spending bias. Once we run this comprehensive analysis we should be able to make more accurate party budgets for our final semester at UVA.