What we're reading: Innovation Job Market Papers We're Excited About
Where new researchers are looking
At the Abundance and Growth Fund, we’re planning to do a weekly post on what the team has been reading. To kick off the “what we’re reading” series though, we’re going to focus on one very specific niche: job market papers by graduating PhD students.
This week we’re sharing papers related to innovation. In early 2026, we’ll follow up with additional posts on housing, energy, infrastructure, and more. In this post, I’ll share the titles and abstracts of six papers that I’m particularly excited to read. We’ve also put together a complete list of job-market papers related to innovation (there are dozens!), which we’re publishing on the website but not emailing out.
1. Innovation through Recombination
Songyuan Teng
New ideas often recombine existing ones; this insight is emphasized in recent economic growth theories, but evidence on its empirical relevance is scarce. This paper takes combinatorial growth to measurement by studying the pharmaceutical industry, where the distinction between novelty (discovering new building blocks) and recombination (assembling building blocks into products) is transparent. I uncover the substantial and rising importance of recombination, the firm life-cycle from knowledge accumulation to recombination, and the value premia for novelty. Motivated by these facts, I develop a theory of firm dynamics that distinguishes firm knowledge stocks from product portfolios. Innovation operates along two distinct yet intertwined margins: novel innovation expands knowledge, while combinatorial innovation deploys that knowledge to create new products. The calibrated model captures salient empirical patterns, implies sustained growth through rising recombination, and highlights sharp policy trade-offs: subsidizing novelty boosts short-run growth, while subsidizing recombination raises long-run growth with heterogeneous effects across firms.
2. Factories of Ideas? Big Business and the Golden Age of American Innovation
Pier Paolo Creanza
This paper studies the Great Merger Wave (GMW) of 1895–1904—the largest consolidation event in U.S. history—to identify how Big Business affected American innovation. Between 1880 and 1940, the U.S. experienced a golden age of breakthrough discoveries in chemistry, electronics, and telecommunications that established its technological leadership. Using newly constructed data linking firms, patents, and inventors, I show that consolidation substantially increased innovation. Among firms already innovating before the GMW, consolidation led to an increase of 6 patents and 0.6 breakthroughs per year—roughly four-fold and six-fold increases, respectively. Firms with no prior patents were more likely to begin innovating. The establishment of corporate R&D laboratories served as a key mechanism driving these gains. Building a matched inventor–firm panel, I show that lab-owning firms enjoyed a productivity premium not due to inventor sorting, robust within size and technology classes. To assess whether firm-level effects translated into broader technological progress, I examine total patenting within technological domains. Overall, the GMW increased breakthroughs by 13% between 1905 and 1940, with the largest gains in science-based fields (30% increase).
3. Beyond the Lab: The Effect of PhD Programs on Innovation
Manfredi Aliberti
This paper estimates the causal impact of PhD programs, designed to train individuals to advance the frontier of knowledge, on innovation. I exploit the centrally planned and staggered rollout of doctoral programs across Italian universities and construct a new dataset linking program openings to local patenting activity. The introduction of PhD programs increased patenting by 21% between 1986 and 2001. Using admission exam scores in a regression discontinuity design, I show that about 22% of this effect is direct and driven by the increased patenting of program graduates, while most of the remainder reflects spillovers to local firms. These findings indicate that PhD programs stimulate technological progress both by increasing graduates’ inventive output and by strengthening the surrounding innovation ecosystem. A cost–benefit analysis based on patent valuations suggests that the social return to these programs exceeds total costs by at least 46%. Finally, I estimate that PhD programs raised Italy’s GDP by 0.6% to 4.7% over the same period.
4. The Prestige-Testability Tradeoff in Science
Kurtis A. Hingl
Where ideas are difficult to test directly, does the scientific community rely more on prestige markers to evaluate them? In this paper, I adopt the cultural evolutionary concept of “prestige,” translate it into economics through a simple reputation model, and propose this hypothesis of a prestige-testability tradeoff: scientific fields that are less testable rely more on prestige markers, manifesting a higher concentration. I present empirical evidence of this prestige-testability tradeoff in two ways. Firstly, in bibliographic data of the corpus of scientific research from 1900 to 2015, I find that the concentration of author prestige markers—citations and h-indexes—is consistently negatively associated with a straightforward measure of testability—the incidence of the word “test” in the titles—across nineteen fields and across subfields within each field. Secondly, I use the occurrence of a paradigm shift toward more testability in the mid-1990s as an event study: the “credibility revolution” in microeconomics. Though not truly exogenous, this paradigm shift reflects a testability shock that is suitably uncovered by a staggered event-study design. I find that the credibility revolution administers a leveling effect on its adopters, based on various citation metrics and share of papers in top-five journals: authors below-median pre-adoption on these prestige markers see clear and persistent increases in their prestige markers, while their above-median peers do not, which I interpret as evidence for the prestige-testability tradeoff. I argue that this prestige-testability tradeoff framework is an important lens for viewing the organization of science, an important factor in a number of science policy decisions, and likely a feature of other social learning environments.
5. How Does Industry Shape Academic Science? Evidence from “Million Dollar Plants”
Hongyuan Xia
Firms rely on academic science and actively participate in the production of scientific knowledge. However, the impact of industry on academic science remains unclear. This study utilizes the site selection decisions of “Million Dollar Plants” (MDPs) to estimate the causal effects of industry on academic science. I compare the responses of scientists in counties that successfully attracted MDPs (”winners”) with those in counties that narrowly missed out on these MDPs (”runners-up”). The arrival of an MDP in a “winner” county shifts research of local scientists toward topics relevant to the firm, but not at the expense of either the quantity or quality of their work. This shift in research direction is not primarily driven by direct funding or collaboration. Instead, it occurs immediately after the announcement but before the physical establishment of these plants and is more likely to affect scientists without prior experience in commercialization. These findings indicate that scientists are refocusing their attention toward more applied and firm-relevant research.
6. Tenure and research trajectories
Giorgio Tripodi
Tenure is a cornerstone of the US academic system, yet its relationship to faculty research trajectories remains poorly understood. Conceptually, tenure systems may act as a selection mechanism, screening in high-output researchers; a dynamic incentive mechanism, encouraging high output prior to tenure but low output after tenure; and a creative search mechanism, encouraging tenured individuals to undertake high-risk work. Here, we integrate data from seven different sources to trace US tenure-line faculty and their research outputs at a remarkable scale and scope, covering over 12,000 researchers across 15 disciplines. Our analysis reveals that faculty publication rates typically increase sharply during the tenure track and peak just before obtaining tenure. Post-tenure trends, however, vary across disciplines: In lab-based fields, such as biology and chemistry, research output typically remains high post-tenure, whereas in non-lab-based fields, such as mathematics and sociology, research output typically declines substantially post-tenure. Turning to creative search, faculty increasingly produce novel, high-risk research after securing tenure. However, this shift toward novelty and risk-taking comes with a decline in impact, with post-tenure research yielding fewer highly cited papers. Comparing outcomes across common career ages but different tenure years or comparing research trajectories in tenure-based and non-tenure-based research settings underscores that breaks in the research trajectories are sharply tied to the individual’s tenure year. Overall, these findings provide an empirical basis for understanding the tenure system, individual research trajectories, and the shape of scientific output.
A complete list of innovation-related job market papers is available here. Thanks for reading and have a happy holidays!