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New Technologies and Innovation

Lightning Round Session

Sunday, Jan. 5, 2025 1:00 PM - 3:00 PM (PST)

Parc 55
Hosted By: American Economic Association
  • Chair: Matthew Grennan, University of California-Berkeley

Attributing Credit and Measuring Impact of Open-Source Software Using Fractional Counting

Gizem Korkmaz
,
Westat
Nicholas Askew
,
Westat
Clara Boothby
,
National Science Foundation

Abstract

Open-source software (OSS) has become an essential in knowledge production and innovation in both academic and business sectors around the globe. OSS is developed by a variety of entities and is considered a “unique scholarly activity” due to the complexity of scientific computational tasks and the necessity of cooperation and transparency for research methodology. While the developers of OSS are thought to be very widespread, there remains many questions to be answered about who these contributors are, who are the largest contributors (countries, sectors, organizations), and how they influence each other.

Using data collected on Python and R packages from GitHub, we leverage fractional-counting methods to measure the exact contribution of each developer and use weighted counting based on the lines of code added by each developer to accurately sum the contribution of countries. We find that for both Python and R, developers from a small group of top countries account for a considerable share of code additions. Developers from the top 10 countries, which include the United States, Germany, United Kingdom, France, and China comprise of 76.1% of the total R repositories, and 66.6% of Python repositories.

Next, we use the dependency relationship between packages and study the pairwise connections between countries to measure their respective impact, finding that the packages attributed to United States are most frequently reused by packages from Germany, Spain, Italy, Australia, and United Kingdom based on the total dependency fractions. In parallel, United States mostly uses packages from Germany, France, and Denmark.

Influential contributors to OSS can contribute heavily to the priorities and practices of scientific research when their work is widely used or built upon by other researchers. In this context, studying the global distribution, collaboration, and impact of the contributors is important to understanding the landscape of innovation in scientific research.

Do Recessions Slow Technology Growth? Evidence from the Firm Level

Olga Goldfayn-Frank
,
Deutsche Bundesbank
Michaela Elfsbacka-Schmöller
,
Bank of Finland
Tobias Schmidt
,
German Bundesbank

Abstract

Do recessions harm investment in technology and thus future aggregate supply? We
provide novel evidence on using granular data on innovation investment in R&D and diffusion
from a representative survey of German firms. Our data allows to identify the crisisinduced
innovation investment cuts with mean conditional reductions of -65% (R&D) and -
70% (diffusion) relative to pre-crisis investment plans, concentrated in 20% and 25% of firms
respectively. We estimate that a 1% cyclical output drop translates into a -0.3% fall in innovation
investment. Firm-level financial constraints amplify the innovation reductions. Our
findings suggest that short-term shocks affect aggregate supply over at least the medium
term, challenging the exogenous technology assumption and the resulting dichotomy between
business cycles and long-run growth in standard models of aggregate fluctuations.
We present the evidence that demand shock is among the main causes of the cyclical technology
investment cuts, supporting the view that demand shocks can manifest as technology
shocks. We formalize our micro-level results in a New Keynesian model with endogenous
growth through investment in R&D and technological diffusion which determines cycle and
trend jointly in general equilibrium.

Innovation Diffusion in the Digital Era: The Impact of Digital Transformation on Enterprise Knowledge Spillover

Yuqi Hou
,
Lanzhou University
Hongyan XIU
,
Lanzhou University
Lili Wei
,
Lanzhou University

Abstract

Harnessing the potential of digital technology to facilitate the diffusion of innovation elements within enterprises holds significant implications for stimulating global innovation dynamics and fostering an open, cooperative, and mutually beneficial innovation ecosystem. This paper utilizes data from Chinese listed companies spanning from 2006 to 2022, incorporating patent citation information and enterprise geographical data, to construct a dataset of enterprise patent citation pairs from both spatial and qualitative perspectives. It attempts to examine the effects and heterogeneity of digital transformation on aspects such as the quality and distance of knowledge spillovers, and further analyzes the pathways through which digital transformation influences knowledge spillovers, including enterprise collaboration networks, diffusion speed, and spillover structure.
The study reveals that digital transformation not only enhances the quality of knowledge spillovers but also significantly expands the scope of such spillovers for enterprises. Heterogeneity analysis demonstrates that the impact of digital transformation on knowledge spillovers varies noticeably across innovation environments, industry disparities, and enterprise characteristics. Further analysis indicates that digital transformation enhances the breadth and velocity of knowledge spillovers and broadens the spillover structure. However, it does not significantly affect the depth of knowledge spillovers among enterprises.
The findings of this study provide valuable insights for leveraging digital technology to enhance inter-enterprise innovation interactions, foster an open and integrated innovation ecosystem, and accelerate the implementation of innovation-driven development strategies.

Marketing Authorization and Strategic Patenting: Evidence from Pharmaceuticals

Lucy Xiaolu Wang
,
University of Massachusetts-Amherst and Max Planck Institute for Innovation and Competition
Dennis Byrski
,
Max Planck Institute for Innovation and Competition

Abstract

Patents are designed to incentivize innovation, but pharmaceutical firms often extend market exclusivity with secondary patents on marginally beneficial improvements. Such behaviors evoke discussions about raising patentability standards. This study examines whether pharmaceutical firms move away from filing strategic patents once the focal drug gains marketing authorization and the disclosed trial-related information becomes novelty-threatening prior art. We construct novel patent-drug dyadic data and leverage unique European drug patent and marketing contexts. Using an event study methodology, we exploit plausibly exogenous variation in the length of time from patent filing to drug approval. We take advantage of the European setting to answer a question that's hard to address in the US, given the four major Supreme Court cases on patent eligibility standards in recent decades.

First, we illustrate that drugs with early and late marketing authorization share similar ex ante observables regarding patent and drug characteristics. Second, we support the hypothesis that strategic patenting behavior decreases substantially after marketing authorization. In contrast, meaningful follow-on innovations remain unaffected. Third, we show that these effects are likely driven by obstacles in the enforceability of marginal patents filed after approval. We analyze heterogeneity across firm type, patent type, disease type, and enforceability. Our results suggest that post-marketing increases in patentability standards are welfare-enhancing with examiner scrutiny and firm self-adjustment. We highlight the importance of better data provision to patent examiners to increase the quality of follow-on inventions.

Megaprojects, Digital Platforms, and Productivity: Evidence from the Human Brain Project

Lucy Xiaolu Wang
,
University of Massachusetts-Amherst and Max Planck Institute for Innovation and Competition
Ann-Christin Kreyer
,
Max Planck Institute for Innovation and Competition

Abstract

This study investigates the impact of the Human Brain Project (HBP) on the rate and direction of research, leveraging a novel dataset we constructed to track participant involvement, engagement timing, and outputs in publications. Utilizing variation in phase-specific participation and resource allocations, we combine difference-in-difference analyses with natural language processing to analyze the intermediate effects of the HBP. Specifically, we combine recent methods in staggered difference-in-differences with matching algorithms and neural, prompt-based, and LLMs (large language models) to construct different types of control groups and to capture the different directions of research revealed by title and abstract.

Empirical analysis highlights the HBP's expanding attraction, especially among junior researchers from diverse locales. Active participation in the HBP has risen over the project phases, especially among junior scholars (junior faculties and graduate students), and newer participants are more likely to have interdisciplinary training in biology and computer sciences. Most publications in our sample are articles, followed by conference proceedings. We aggregate publication-level data to an author-year panel for 2008-2022, and our results are robust to using a longer period (2000-2022 author-year panel). We measure publications in general, first/last author articles, and by demographic data collected.

Our results indicate HBP involvement boosts publication rates, expands coauthor networks, increases citations, and elevates the likelihood of top journal publication. Notably, neurotech areas, blending neuroscience with CS/AI, see the most substantial productivity gains, consistent with the role of digital platforms in easing hurdles. The results are mainly driven by early-career researchers (junior faculty and graduate students). Female scholars also benefit despite with lower-than-overall magnitudes. We document some geographic-specific heterogeneity: all European countries participated in the EC-funded HBP benefit to some extent, with German, Italy, and Balgium-based researchers benefiting more. Overall, our results underline the role of institutions in advancing interdisciplinary AI-neuroscience research collaborations.

On the Elasticity of Substitution between Labor and ICT and IP Capital and Traditional Capital

Vahagn Jerbashian
,
University of Barcelona

Abstract

I estimate CES aggregate production functions for the US, the UK, Japan, Germany, and Spain using data from the EU KLEMS database. I distinguish between three types of capital: information and communication technologies (ICT), intellectual property (IP) capital, and traditional capital. I assume that the aggregate output is produced using labor and these three types of capital and allow for differences in the elasticities of substitution between labor, an aggregate of ICT and IP capital, and traditional capital. The estimated elasticities of substitution between ICT and IP capital are strictly below one for all sample countries implying gross-complementarity. ICT and IP capital together are gross-substitutes for labor while traditional capital is a gross-complement.

Product Safety Standards and Technological Innovation: Evidence from the 1968 Radiation Control

Yiyu Xing
,
University of California-Los Angeles

Abstract

Product safety regulation is a ubiquitous policy tool throughout history. Debates typically center around its trade-off between safeguarding consumers and stifling the development of new products. In this paper, I study how stricter safety standards influence the nature and speed of medical innovation by drawing evidence from the 1968 Radiation Control for Health and Safety Act. For the first time at the federal level, this Act mandated enforceable performance standards to control the radiation risk of electronic products. I find that in response to this act, firms developed new technologies reducing the risks of diagnostic X-ray medical equipment (an increase of 64.2% in patent count), as a key channel to lower compliance costs. I also document an increase of a similar magnitude for innovations representing new radiation-generating medical devices and show some suggestive evidence for the complementarity of risk mitigation and new technologies using radiation. I rule out a number of alternative explanations for these findings, including the introduction of the CT scan in 1972. Back-of-the-envelope calculations suggest substantial welfare gains as measured by health improvements and private market values due to these induced innovations.

Promoting Digitalization through Information Dissemination

Tian Gao
,
University of Manchester
Maria-Teresa Marchica
,
University of Manchester
Stefan Petry
,
University of Manchester

Abstract

The U.K. Small Business Digital Capability Programme Challenge Fund 2014 aimed at disseminating information and training about the use of digital technologies among SMEs. Using a novel firm-level dataset of web technologies, our matched differences-test strategy shows that, following the implementation of the program, treated SMEs were more likely to increase their web presence, adopted more sophisticated web technologies, and enlarged their operating boundaries through e-commerce. The program reduced the digital divide between SMEs and large companies and enabled digitalization in more geographically remote locations. As a result, firms observed positive effects on performance, labor outcomes, and likelihood of survival.

Searching Where Ideas are Harder to Find - The Aggregate Effects of the Decline of Disruptive Innovation

Richard Braeuer
,
Halle Institute of Economic Research

Abstract

This paper proposes a model that explains both recently documented facts about
the decline of disruptive innovation and the decline in productivity growth as the
result of large firms trying to monopolize technologies by poaching inventors from
disruptive activities. To come to this conclusion, the paper builds an endogenous
growth model with inventor labor markets on which firms can interact strategically.
Inventor poaching lead to technology fields ossifying over time as disruptive inventors
get poached. To inform this model, I perform an event study of the effect of disruptive
inventions on their technology fields using PATSTAT (1980-2010). I document that
technology classes without disruption slowly trend towards incrementalism and that
after a disruption, more patents get registered and research becomes less incremental.

Watching the Watchdogs: Tracking SEC Inquiries using Geolocation Data

William Gerken
,
University of Kentucky
Steven Irlbeck
,
University of New Hampshire
Marcus Painter
,
Saint Louis University
Guangli Zhang
,
Saint Louis University

Abstract

The Securities and Exchange Commission’s investigative process remains opaque and challenging
to study due to limited observability. Leveraging de-identified smartphone geolocation data,
we provide new insights into the SEC’s monitoring practices by tracking SEC-associated devices
that visit firm headquarters. Our findings reveal that the majority of SEC visits occur outside
of formal investigations, with larger firms and those with a history of SEC enforcement actions
being more frequently visited. These visits often cluster within industries. Notably, the SECassociated
devices venture to firms both within and outside their own regions. On average, these
visits are material, evidenced by significant stock price reactions, even in the absence of subsequent
formal investigations or enforcement actions. Last, we observe a chilling effect on insider
behavior around these SEC interactions; insiders are less likely to sell around visits. However,
when sales do occur, insiders avoid substantial losses.
JEL Classifications
  • O3 - Innovation; Research and Development; Technological Change; Intellectual Property Rights