Using over 250,000 U.S. patent citations, we test whether knowledge transfers in the energy sector are sensitive to distance, and whether that sensitivity has changed over time. Controlling for self-citation by inventor, assignee and examiner, multivariate regression analysis shows that physical distance is becoming less important for spillovers with time.
This paper investigates whether the curricular structure of an Economics course (semester, trimester, or compressed block schedule) has an effect on an undergraduate's subsequent retention of course material. We test separately for theoretical/process comprehension and for graphical construction/interpretation, while separating micro from macro content as well. We use an instrument to address the no stakes testing problem, and our Heckman two-stage estimations present some interesting results for educators and institutional policymakers alike.
Closely following the notion of innovative geographic clusters, this paper examines knowledge flows in the US agriculture industry for evidence of innovative agglomeration. The data indicate that a closer distance between any two agricultural patent origins increases the probability that one cites the other as prior art. Further, subtle interregional variations characterize the degree to which proximity advances agricultural innovation. Finally, the results show that older innovations in agriculture proliferate more readily than recently created knowledge.
This paper considers the challenges associated with conducting research with undergraduates – limited time and resources, limited skills, the tedious nature of data gathering, etc.. We discuss four models of effective research approaches. One is Aju Fenn’s which is to identify a topic and a workable approach, such as competitive balance in sports, and apply it in different contexts – football, basketball, soccer, etc. with different students working on different sports. This model is also successful because much data on both inputs and performance is collected in sports and is readily available from non-propriety sources. The Dan Johnson Model is to develop a huge data set, in this case patents, and then set students to work on problems involving some aspect of the data set while asking them develop one part of the data set through their research. The Smith Model which is to divide a related problem into distinct parts and have students work on each part. Smith discusses this approach on research on recreation values for the Arkansas River a quantitative problem while Stimpert shows its application to a qualitative problem, the role of corporate boards.
The effect of spatial factors on competition and the price of gasoline have been sparsely explored by previous studies. Existing work examines how gasoline prices differ based on distance from the distribution site as well as how cost factors influence gasoline prices. Using market data from six midsized U.S. metro areas with similar isolation from neighboring retail markets, this paper examines the effects of location on retail price, while controlling for brand effects. Spatial regression analysis accommodates the potential of spatially correlated errors, and sensitivity analysis tests for several measures of retail location concentration. Results point to reproducible brand premiums and some location-based price differences, but also show the counterintuitive finding that areas with more market competition do not show significantly lower retail gas prices.
Recent Wal-Mart openings have been accompanied by public demonstrations against the company’s presence in the community, asserting (among other things) that their presence is deleterious to residential property values. This study empirically evaluates that claim, analyzing the spatial correlation between Wal-Mart locations and residential property values, while comparing Wal-Mart with other big-box retailers for a frame of reference and controlling for other important aspects of a home’s market value. We recognize that market value may represent a trade-off between price and patience, so perform a similar analysis using a property’s days on the market to evaluate any big-box effect. Finally, we interpret the resulting effects in two ways, from both the resident’s and retailer’s point of view, casting new light on the NWIMBY effect.