CARD announces two PhD Dissertation Award winners
Catherine Kling, director of CARD, today announced Matthew Clancy and Younjun Kim as the recipients of the third annual CARD Award for Best PhD Dissertation in Agricultural, Environmental, and Energy Economics Policy.
To be considered for the award graduate students had to submit a copy of their dissertation and a brief summary of how the topic of research related to one of CARD's research areas. Graduate students were required to have completed their final oral examination in 2015 to be considered.
Kim’s dissertation is a collection of four papers, the first two papers focus on regional economic development, particularly, the first focuses on whether broadband improves rural economies, and the second focuses on the existence of agglomeration economies in rural areas. Kim’s third and fourth essays focus on choices under risk. One essay examines risk elicitation methods with a multiple price list format, and the second studies pre-play learning and inconsistent preference ranking between choice and pricing for lotteries.
Clancy’s dissertation uses 8.3 million US patents to create a novel dataset to present an original model of knowledge production and test several predictions of the model. Specifically, Clancy examines how new useful combinations of technology affect the number of patents filed in that particular technology class and how time affects the probability of using a particular combination of technologies.
Both students were awarded a $500 prize, and will have their names added to the Dissertation Award winners plaque at CARD.
The full text of both abstracts is included below.
Essays on firm location decisions, regional development and choices under risk
My dissertation consists of four papers. The first two papers study regional economic development. In particular, they focus on broadband Internet and agglomeration economies in rural areas. One paper tests whether broadband improves rural economy and find positive broadband effects on new firm location choices. The other paper explores whether agglomeration economies operate even in rural areas and find that agglomeration economies are important for new firm location choices and commuting decisions. Those findings from the two papers have useful implications to regional economic development policies.
My two other papers study choices under risk. One paper focuses on risk elicitation methods with a multiple price list format, which is widely used in the literature. The paper compares subjects’ choices between the elicitation method and one question selected from the method. The paper finds significant differences in the comparison and show that the differences occur due to reference-dependent preferences. Those results suggest that the elicitation method is not reliable because loss aversion influences elicited risk aversion. The other paper tests whether pre-play learning removes inconsistent preference rankings between choice and pricing for lotteries. Inconsistent preference rankings have been studied last four decades because standard economic theory cannot explain inconsistent preference rankings. Pre-play learning is simple ex-ante lottery learning, where subjects observe playing lotteries before they make decisions. The paper finds that pre-play learning removes inconsistent preference rankings, which suggests that pre-play learning makes preference rankings consistent between choice and pricing as predicted in standard economic theory. Those results from the two papers have meaningful implications to the literature.
Combinatorial innovation, evidence from patent data, and mandated innovation
This paper presents an original model of knowledge production, and tests several predictions of the model using a novel dataset built from 8.3 million US patents. In this model, new ideas are built by combining pre-existing technological building blocks into new combinations. The outcome of research is always stochastic, but firms are Bayesians who learn which sets of technological building blocks tend to yield useful discoveries and which do not. Consistent with this model’s prediction, I show that the number of patents granted in a particular technology class increases in the years after new useful combinations of technology first appear in the class. Moreover, after new combinations first appear, I show subsequent patents are more likely to draw on the same combination of technology, consistent with firms learning the technologies can be fruitfully combined. Patents are also more likely to combine technologies that have already been combined with many of the same (other) technologies, even if they have never been combined with each other. Finally, I show that the probability of using a combination declines over time, and that the total number of patents granted in a technology class also declines over time, if there are not new connections between technologies continuously discovered. This is consistent with the model’s predictions about firms using up all the useful ideas that can be built from a fixed set of technological building blocks.
(Released April 2016)