By Stephanie Wiehe
The US market for toothpaste, like many other goods, is shifting towards selling
in bulk. Multipacks of toothpaste require quantity discounts to incentivize consumers, making buying in bulk a great deal for the savings-minded toothpaste-shopper. It is more difficult to understand, however, producers’ willingness to sell multipacks of toothpaste, when margins are necessarily slimmer than single tubes due to quantity discounts. This paper explores the consumer’s decision in purchasing toothpaste as an interaction between savings on price and inventory considerations, like shopping and carrying costs. My model combines aspects of prior works on second degree price discrimination and quantity discounts with alterations to fit the intricacies of the market for toothpaste. The model’s predictions support the possibility of pack size as a tool for second degree price discrimination as shopping and carrying costs constitute two markets with different price elasticities of demand for single and multipacks of toothpaste. This work adds to the existing literature on storable goods and non-linear pricing and brings a new economics-based approach to a question faced by toothpaste producers.
Advisors: Professor Allan Collard-Wexler, | JEL Codes: L11; L42; D4
BIDDING FOR PARKING: The Impact of University Afﬁliation on Predicting Bid Values in Dutch Auctions of On-Campus Parking Permits
By Grant Kelly
Parking is often underpriced and expanding its capacity is expensive; universities need a better way of reducing congestion outside of building costly parking garages. Demand based pricing mechanisms, such as auctions, offer a possible solution to the problem by promising to reduce parking at peak times. However, faculty, students, and staff at universities have systematically different parking needs, leading to different parking valuations. In this study, I determine the impact university afﬁliation has on predicting bid values cast in three Dutch Auctions of on-campus parking permits sold at Chapman University in Fall 2010. Using clustering techniques crosschecked with university demographic information to detect afﬁliation groups, I ran a log-linear regression, ﬁnding that university afﬁliation had a larger effect on bid amount than on lot location and fraction of auction duration. Generally, faculty were predicted to have higher bids whereas students were predicted to have lower bids.
Advisor: Alison Hagy, Allan Collard-Wexler, Kent Kimbrough | JEL Codes: C38, C57, D44, R4, R49 | Tagged: Auctions, Parking, University Parking, Bidder Afﬁliation, Dutch Auction, Clustering
By Chun Sun Bak
This paper examines the effect of the change in the magnitude of monthly governmental adoption subsidy on the adoption rate for foster children in foster family structures. In order to account for omitted variable bias attached to the amount of subsidy that a child receives, I construct an instrumental variable that takes advantage of the fact that each state has different policies on: (1) the base age from which a child is eligible for special needs; and (2) the amount of increased adoption subsidy that a child receives, on average, if he or she is eligible for special needs adoption. Using the data from the Adoption and Foster Care Analysis and Reporting System (AFCARS) during the years 2001 to 2012, I find that a dollar increase in the amount of adoption subsidy, holding the amount of foster care payment constant, is expected to increase a foster child’s probability of adoption by 0.255%. Although the positive sign of the coefficient is intuitive, and although it is statistically significant at all levels, its magnitude is unrealistically high, suggesting that there may be a problem in the instrument itself or in the accuracy and selection of the data.
Advisor: Alison Hagy, Allan Collard-Wexler