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Impact of Medicare Advantage Supplemental Benefit Expansion on Startup Funding

by Judy Tianhong Zhong

Abstract 

In 2018, the Center for Medicare and Medicaid Services (CMS) announced that they would expand the supplemental benefits that can be included in Medicare Advantage (MA) plans. The goal was to encourage insurers to innovate and test new benefit offerings that could improve health outcomes and reduce healthcare spending. A key player in this transformation is the MA vendor that provides supplemental benefit offerings to insurance plans, but this market is rather underdeveloped. To assess the implementation of this supplemental benefit expansion, this study examines the flow of funding into the emerging market of MA vendors. This paper uses a longitudinal approach and Crunchbase data on funding for 79,004 firms from 2014 to 2018 to determine whether there is a significant jump in funding toward MA vendors with supplemental benefit services following the policy change. The results show that both the average amount of funding per deal and the number of deals a MA vendor firm receives significantly increased following the expansion when compared with all other firms. This suggests that the policy may have been successful in promoting the development of the MA vendors market and the innovation of benefit offerings as more funding goes towards these companies.

Kate Bundorf, Faculty Advisor
David Ridley, Faculty Advisor
Michelle Connolly, Faculty Advisor

JEL classification: I1; I11; I18

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What Affects Post-Merger Innovation Outcomes? An Empirical Study of R&D Intensity in High Technology Transactions Among U.S. Firms

by Neha Karna

Abstract 

High levels of global M&A activity have characterized the past decade, making the policy debate
over the impact of mergers on innovation even more pertinent. Innovation is a significant driver
of economic growth and therefore a negative effect of mergers on innovation outcomes may have
detrimental consequences. Nevertheless, the existing literature demonstrates mixed results
leaving it unclear whether the overall effect is positive or negative. This paper contributes to
existing literature on the relationship between mergers and innovation and examines the effects
of M&A on the subsequent innovative activity of acquiring firms that operate in high technology
(high-tech) industries. I construct a sample of U.S.-based public-to-public deals from 2010-2019
involving high-tech acquiring firms. Using multivariable regression with robust considerations, I
analyze factors that may explain post-merger R&D intensity defined as the merged entity’s R&D
expenditure divided by its total assets one year after deal completion. I consider firm
characteristics of the target and acquirer, including size, industry, and age, and industry
competition. I find potential positive impact of relative target size on post-merger R&D intensity
and significant interaction effects between relative target size and firm age, relative target size
and industry relatedness, and target industry competition and industry relatedness. My results
suggests that beyond the occurrence of a merger, specific deal characteristics may affect postmerger
innovation outcomes.

Grace Kim, Faculty Advisor

JEL Classification: G3; G34; L40; O31; O32;

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The Effects of Health IT Innovation on Throughput Efficiency in the Emergency Department

By Michael Levin  

Overcrowding in United States hospitals’ emergency departments (EDs) has been identified as a significant barrier to receiving high-quality emergency care, resulting from many EDs struggling to properly triage, diagnose, and treat emergency patients in a timely and effective manner. Priority is now being placed on research that explores the effectiveness of possible solutions, such as heightened adoption of IT to advance operational workflow and care services related to diagnostics and information accessibility, with the goal of improving what is called throughput efficiency. However, high costs of technological process innovation as well as usability challenges still impede wide-spanning and rapid implementation of these disruptive solutions. This paper will contribute to the pursuit of better understanding the value of adopting health IT (HIT) to improve ED throughput efficiency.

Using hospital visit data, I investigate two ways in which ED throughput activity changes due to increased HIT sophistication. First, I use a probit model to estimate any statistically and economically significant decreases in the probability of ED mortality resulting from greater HIT sophistication. Second, my analysis turns to workflow efficiency, using a negative binomial regression model to estimate the impact of HIT sophistication on reducing ED waiting room times. The results show a negative and statistically significant (p < 0.01) association between the presence of HIT and the probability of mortality in the ED. However, the marginal impact of an increase in sophistication from basic HIT functionality to advanced HIT functionality was not meaningful. Finally, I do not find a statistically significant impact of HIT sophistication on expected waiting room time. Together, these findings suggest that although technological progress is trending in the right direction to ultimately have a wide-sweeping impact on ED throughput, more progress must be made in order for HIT to directly move the needle on confronting healthcare’s greatest challenges.

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Advisors: Professor Ryan McDevitt, Professor Michelle Connolly | JEL Codes: I1, I18, O33

Competition and Innovation: Evidence from Third-Party Reprocessing in the Medical Device Industry

By Varun Prasad   

Healthcare is projected to soon become the industry with the largest amount of spending on research and development in the world. While competition has the potential to catalyze the development of new healthcare technologies and drive down costs, increases in competition have also been thought to hinder innovation as a result of thinner profit margins and reduced incentives. I estimate whether and to what extent competition in the medical device industry promotes innovation. Using Food and Drug Administration data on medical device applications from 1976 to 2019, I examine how original equipment manufacturers respond to the entry of third-party reprocessed devices. I find that, when controlling for year and medical specialty, the introduction of a reprocessed device leads to an almost five-fold increase in new device applications by original manufacturers after both one and two years. These results suggest that an increase in competition within the medical device market has spurred innovation and the development of new technologies.

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Advisors: Professor James Roberts, Professor David Ridley | JEL Codes: L1, D22, L65

Evaluating The Forward Citations-Patent Value Relationship: The Role Of Competition

By Neelesh T. Moorthy

I assess whether forward citations—how often patents are cited by subsequent patents—reliably capture patent quality. A high-quality invention might lack forward citations if there are no competing, patenting firms. This introduces measurement error in using citations to measure patent value. I test whether greater competition makes forward citations better measures of patent quality, with eight and twelve-year patent renewal rates serving as my benchmark measures of patent quality. Patent data come from the manufacturing survey in Cohen, Nelson, and Walsh (2000). I conduct logit regressions of patent renewal on forward citations and the number of competitors faced by surveyed manufacturing labs. While the regression results do not support the competition hypothesis, they confirm that forward citations positively predict renewal. They also lend insight into firms’ strategic renewal decisions.

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Advisors: Wesley Cohen and Michelle Connolly | JEL Codes: O31, O34

Entrepreneurial Attractiveness: Amazon, Google, and the Search for Innovative Hot Spots

By Anna Katherine Kropf

Recent economic literature suggests that entrepreneurship in technological fields can spur economic growth, making it a popular topic for city development officials. Yet, this increasingly popular phenomenon is met by many economic questions. One of those questions is which characteristics of metropolitan areas are attractive to entrepreneurs. To answer the question of attractiveness on both the small business and corporate levels, I compare across two case studies: Amazon’s search for a second headquarters and Google’s tech hub network. Using principal component analysis, I statistically deduce seven components of attractiveness from an original 34 variables. These components are then weighted using three methods—a case study, a survey, and an empirical method—to produce comparable indices of attractiveness. Generally, I find that sizeable population and healthy economy are the strongest components. However, the statistically insignificant components that can change an urban area’s ranking considerably are talent and geographic network effects. Ultimately, creating policy to maximize these aspects can change a city’s innovative
trajectory.

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Advisor: Dr. Charles Becker | JEL Codes: O, O3, R, R1, R11

What Fosters Innovation? A CrossSectional Panel Approach to Assessing the Impact of Cross Border Investment and Globalization on Patenting Across Global Economies

By Michael Dessau and Nicholas Vega

This study considers the impact of foreign direct investment (FDI) on innovation in high income, uppermiddle  income and lowermiddle income countries. Innovation matters because it is a critical factor for economic growth. In a panel setting, this study assesses the degree to which FDI functions as a vehicle for innovation as proxied by scaled local resident patent applications. This study considers research and development (R&D), domestic savings, imports and exports, and quality of governance as factors which could also impact the effectiveness of FDI on innovation. Our results suggest FDI is most effective as inward direct investment in countries outside the technological frontier possessing adequate existing domestic investment capital and R&D spending to convert foreign investment capital and technological spillover into innovation. Nonetheless, FDI was not a consistent indicator for innovation; rather, the most consistent indicators across this study were R&D and domestic savings. Differences amongst income groups are highlighted as well as their varying responses to our array of causal factors.

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Advisor: Lori Leachman | JEL Codes: A10, B22, C82, E00, E02, O10, O11, O30, O31, O32, O33, O34, O43

What Gets Paid? Analyzing the Major League Baseball Contract Market

By Brian Pollack

This paper aims to assess the efficiency of the Major League Baseball contract market in the past decade, given that teams are employing more analytical approaches to player evaluation. First, analysis of team-level data reveals the most important determinants of run scoring and run prevention, respectively. Models of player contract value, controlling for player-specific variables and environmental factors, then determine what is most significantly rewarded on the free agent market. Overall, teams have identified the individual skills that are most important and compensated them accordingly, and there is evidence to suggest teams are becoming smarter about this in recent years.

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Advisor: James Roberts | JEL Codes: D7, O3, Z2

Federal and Industrial Funded Research Expenditures and University Technology Transfer licensing

By Trent Chiang

In this paper I relate the numbers of university licenses and options to both university research characteristics and research expenditures from federal government or industrial sources. I apply the polynomial distributed lag model for unbalanced panel data to understand the effects of research expenditures from different sources on licensing activity. We find evidence suggesting both federal and industrial funded research expenditures take 2-3 years from lab to licenses while federal expenditures have higher long-term dynamic effect. Break down licenses by different types of partners, we found that federal expenditures have highest effect with small companies and licenses generating high income. Further research is necessary to analyze the reason for such difference.

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Advisor: David Ridley, Henry Grabowski | JEL Codes: I23, L31, O31, O32, O38 | Tagged: Innovation, Research Expenditures, Science Policy, Technology Transfer

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