Innovation Job Market Papers 2025 (2/2)
Dozens of papers from new PhDs about Innovation
In this special annual edition of What’s New Under the Sun, we have a big bundle of the titles, abstracts, and links to innovation-related PhD job market papers from 2025. Some were sent my way following my request in the last newsletter, but to find the majority of these, I manually looked at the titles of ~1,300 job market papers. Even so, I’m sure I missed some great papers. If that’s you, email me and I’ll add you to the posts.
I’ve split this post into two to make it a bit easier to navigate. This is the second post. The first is here.
Special thanks to Nisha Austin for helping me put these posts together!
Titles Index
Titles are presented in random order. There might be additional authors on these papers - we’ve listed the associated job market candidate only.
Tenure and research trajectories by Giorgio Tripodi
Spatial Allocation of Inventors, Knowledge Diffusion and Growth by Furkan Kilic
Patents, Innovation, and Imitation in a North-South Model with Increasing Product Variety by Florence Ut Meng Ho
The Innovation Long-Run Risk Component by Fabio Franceschini
Import Competition, Innovation, and the Cost of Protectionism by Deniz Atalar
Financial Development and Endogenous Investment-Specific Technical Change by Daeeun Bae
The Origins of the Nitrogen Revolution by Christopher W. A. Sims
Knowledge Generality, Competition and Growth by Chenchuan Shi
Start-up Financing, Entry and Innovation by Charles Parry
The Role of Training for Technology Diffusion by Carolina Bussotti
Firm Scope and Innovation: The Role of Intangibles by Cagin Keskin
The value of conceptual knowledge by Benjamin Davies
Robust Technology Regulation by Andrew Koh
Technology and the Geography of Industrial Policy by Aditya Bhandari
Sexual Misconduct and Scientific Production by Manuela Collis
Worker Mobility and the Diffusion of Radical Technologies by Stephan Hobler
Patent challenge and generic entry by Xin Zhang
Innovation and Adaptation to Expanding Biological Threats by Shu-Chen Tsao
Titles, Abstracts, and Links to Papers
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.
Spatial Allocation of Inventors, Knowledge Diffusion and Growth
Furkan Kilic
Where does innovation truly thrive? Inventive activity in the US is strikingly concentrated in a handful of hubs. This raises compelling questions: Does further agglomeration drive innovation, or could a more dispersed approach better leverage regional spillovers? To investigate, I exploit variation in patent citation lags across US states and develop a novel endogenous growth model with mobile inventors and workers. The model integrates an exogenous knowledge network that facilitates the dynamic exchange of ideas—laying the foundation for future inventions—between locations, revealing that inventors do not internalize how their location choice influences broader knowledge diffusion. These knowledge spillovers call for a targeted, place-based R&D subsidy to unlock latent innovation potential. Calibrating the model to data on inventor and worker allocations—and estimating the knowledge diffusion network from patent citations—I find that optimal policy would further concentrate inventors in established hubs, enhancing welfare by 1.8 percent in consumption-equivalent terms and boosting the economy’s long-run growth rate by 0.14 percentage points.
Patents, Innovation, and Imitation in a North-South Model with Increasing Product Variety
Florence Ut Meng Ho
To understand the relationship between patent protection and technology transfer across countries and to equip policymakers with insights to balance innovation promotion and technology dissemination, this paper investigates the cross-country effects of patent protection on relative wages, innovation, technology transfer, and welfare in a North-South model with variety expansion. In this dynamic general equilibrium model, firms in the North perform innovative R&D, while firms in the South perform imitative R&D for technology transfer. Innovation occurs through the invention of new varieties of goods, and IPR protection is modeled in the form of patent breadth. We find that strengthening patent protection in the North permanently raises the relative wage between the North and the South, permanently decreases the rate of technology transfer, and temporarily increases the northern innovation rate. Conversely, strengthening patent protection in the South permanently reduces the relative wage, permanently increases the rate of technology transfer, and temporarily boosts the northern innovation rate. Calibrating this model to US-China data, our quantitative analysis reveals that when a country unilaterally strengthens patent protection, its domestic welfare increases. However, when both countries strengthen patent protection bilaterally, the South experiences a welfare gain while the North suffers a welfare loss.
The Innovation Long-Run Risk Component
Fabio Franceschini
This paper provides robust empirical evidence that shocks to aggregate Research and Development (R&D) have persistent effects on macroeconomic dynamics and represent a significant risk for investors, as predicted by the “long-run risk” literature. The analysis focuses on a single variable, “effective R&D”, which captures the entire contribution of R&D to productivity growth, flexibly accounting for knowledge spillovers and product proliferation effects. Deviations of effective R&D from its equilibrium level can be empirically identified leveraging the error correction term in the cointegration relationship among R&D, total factor productivity, and the labor force. In US data, structural effective R&D shocks affect productivity and consumption growth rates beyond business cycle horizons and are associated with a significant risk premium in a cross section of stock and bond portfolios (around 2% annually), with cash-flow sensitivities proving a key determinant.
Import Competition, Innovation, and the Cost of Protectionism
Deniz Atalar
How does import protectionism affect catch-up innovation and welfare? I develop a small open-economy model in which trade costs shape buyer–supplier relationships, and suppliers’ incentives to innovate. When trade costs rise, domestic buyers become more inclined to shift sourcing from foreign to domestic suppliers. The possibility of this shift triggers heterogeneous innovation responses among domestic suppliers: those suppliers that are less technologically advanced than their foreign competitors increase their innovation, while other, more advanced suppliers reduce it. I verify and quantify the buyers’ shift in sourcing as well as the suppliers’ heterogeneous innovation responses to this shift using novel Turkish firm–product-level data on firm-to-firm transactions, imports, production, and innovation expenditures. I build on these firm level responses to assess the impact of import protectionism on welfare. If domestic suppliers in the aggregate respond to a rise in trade costs by increasing innovation, the welfare losses of such a policy are partially mitigated. If, on the other hand, they respond by decreasing innovation, the welfare losses are amplified. Calibrating the model to Turkish microdata, I find that a 10 percent rise in trade costs in Turkiye triggers an increase in aggregate innovation, which mitigates roughly one-quarter of the welfare loss relative to a no-innovation benchmark.
Financial Development and Endogenous Investment-Specific Technical Change
Daeeun Bae
I show that financial development is a key determinant of cross-country variation in the rate of investment-specific technical change. Using a large cross-country dataset, I document that countries with more developed financial markets exhibit higher rates of investment-specific technical change, and that investment goods production is more intensive in value added from high-R&D industries than consumption goods production. To explain these findings, I develop a multi-industry endogenous growth model with credit constraints on R&D expenditures. In the model, R&D drives productivity growth, and financial development disproportionately benefits the productivity growth of high-R&D industries because they are more dependent on external financing. Taken together with the different industrial composition of final goods production, financial development endogenously generates faster productivity growth in investment goods production. The quantitative analysis shows that this endogenous channel accounts for approximately 40% of the observed cross-country relationship between financial development and investment-specific technical change.
The Origins of the Nitrogen Revolution
Christopher W. A. Sims
Many technologies raise productivity in locations constrained by their natural endowments yet diminish specialization across space. We show that the first commercial nitrogen fertilizers in history were one such “converging” technology. Leveraging natural variation in soil nitrogen deficiency and the sudden introduction of Peruvian guano and nitrates to 19th-century England, we provide two main empirical findings. First, locations specialized on the basis of their natural endowments before the introduction of fertilizer: nitrogen-deficient places devoted less land to nitrogen-intensive crops. Second, combining newly-digitized data and a difference-in-differences design, we show that these nitrogen-deficient places substantially reallocated toward nitrogen-intensive crops after fertilizer was introduced, indicating convergence across space. To quantify the welfare impact of this “converging” technology, we embed fertilizer into a quantitative spatial model of the English agricultural sector with realistic geography. The welfare gains from fertilizer were equivalent to two decades of annual productivity growth in agriculture. However, convergence implies a reduction in the gains from trade, which offsets up to 10% of these welfare gains under plausible trade cost regimes.
Knowledge Generality, Competition and Growth
Chenchuan Shi
This paper studies how the generality of knowledge—its applicability across technologies and industries—shapes firms’ innovation strategies, market structure, and aggregate growth. I build an endogenous growth model in which firms choose between general and firm-specific R&D while competing for market leadership. General innovations enhance firms’ capacity to absorb and apply outside knowledge, creating spillovers within and across industries, whereas firm-specific innovations yield mainly private gains. The model predicts, and the data confirm, that (1) leaders favor firm-specific R&D while followers rely on general innovations to catch up, and (2) the gap in innovation generality between them follows a U-shaped pattern with market concentration. Leveraging variation in the enforceability of non-compete agreements across U.S. states, I provide empirical evidence consistent with the model’s spillover mechanisms. The findings point to a novel growth policy: encouraging general R&D, particularly among leading firms, can improve knowledge diffusion and sustain long-run growth.
Start-up Financing, Entry and Innovation
Charles Parry
Venture capital (VC) is the key source of financing for high-growth start-ups, but with few alternatives, limited access can leave viable projects unfunded and constrain innovation. I develop and estimate an equilibrium model of the VC market to quantify these distortions in the US, explain cross-country differences in VC activity, and diagnose VC’s sectoral concentration. In the model, entrepreneurs and VCs meet in a frictional matching market and VCs endogenously stage capital injections over time to limit losses from hidden failure by entrepreneurs; however, reliance on follow-on funding exposes the start-up to premature closure if funding does not materialise. The model maps directly to observed funding histories, enabling estimation and policy counterfactuals. For US start-ups first funded in 2005–2015, my estimates suggest that 40% shut down despite having positive continuation value; with continued funding, half would reach an acquisition or IPO. I then estimate the model on UK microdata and find that financing conditions and acquisition opportunities, not project quality, drive US–UK differences; financing conditions account for two-thirds of the entry gap. Because UK start-ups struggle to reach late-stage rounds, retargeting existing support towards late-stage start-ups improves outcomes. Finally, the theory offers an explanation for VC’s concentration in software and services: frictions are least severe for short-horizon projects with ample acquisition opportunities. Absent frictions, the share of VC-backed software and services start-ups falls from 61% to 53%, offset by gains in science-based sectors.
The Role of Training for Technology Diffusion
Carolina Bussotti
We study a dynamic model of new technology adoption in a labor market with search frictions, where worker training boosts the productivity gains from adopting the technology. Once trained, workers acquire general skills that can be used by any firm operating the new technology. As a result, firms can free-ride on the training investments of others, which inefficiently delays technology adoption and workforce training. We apply the model to the diffusion of Enterprise Resource Planning (ERP) systems in Portugal—a leading software technology currently used by 43% of European firms—whose adoption requires training workers in transferable skills. Using matched employer–employee data, we show that as the technology diffuses, firms train fewer workers upon adoption, consistent with the model’s free-riding mechanism. The calibrated model implies a 14% present-value loss in net output due to underinvestment in adoption and training. Finally, policy counterfactual analysis shows that training subsidies introduced at the onset of the diffusion process are about 10% more effective than those enacted ten years later.
Firm Scope and Innovation: The Role of Intangibles
Cagin Keskin
Horizontal expansion through an increasing product portfolio lies at the core of modern endogenous growth literature. Yet evidence remains limited on how diversification across industries influences a firm’s trade-off between generating social surplus and capturing private returns. To investigate this, I categorize intangible assets by their spillovers: transferable intangibles (patents, software) generate social surplus, whereas embedded intangibles (organizational capital, brand value) primarily yield private returns. I document that diversified firms reallocate investment toward embedded intangibles, a strategic shift accompanied by declining markups and productivity, together with reduced innovation by their rivals. Motivated by this evidence, I extend a canonical endogenous-growth framework to endogenize firms’ allocation between transferable and embedded intangibles, allowing for both horizontal and vertical expansion. A key prediction of the model is that embedded intangibles are the primary driver of a firm’s ability to expand across industries, which also raises entry barriers for competitors and decreases social return rather than promoting long-run growth. Thus, a shift in innovative effort ultimately sacrifices economy-wide growth for firm-level market advantages, and quantitative analysis indicates that size-dependent taxes can substantially improve welfare.
The value of conceptual knowledge
Benjamin Davies
We study the instrumental value of conceptual knowledge when making statistical decisions. Such knowledge tells agents how unknown, payoff-relevant states relate. It is distinct from the statistical knowledge gained from observing signals of those states. We formalize this distinction in a tractable framework used by economists and statisticians. Conceptual knowledge is valuable because it empowers agents to design more informative signals. It is more valuable when states are more “reducible”: when they can be explained with fewer common concepts. Its value is non-monotone in the number of signals and vanishes when agents have infinitely many signals. Agents who know more concepts can attain the same payoffs with fewer signals. This is especially true when states are highly reducible.
Robust Technology Regulation
Andrew Koh
We analyze how uncertain technologies should be robustly regulated and how regulation should evolve with new information. An adaptive sandbox comprising a zero marginal tax up to an evolving quantity limit is (i) robust: it delivers optimal payoff guarantees when the agent’s learning process and/or preferences are chosen adversarially; (ii) dominant: it outperforms other robust and regular mechanisms across all agent learning processes and preferences; (iii) time-consistent: it is the only robust mechanism that can be implemented without commitment. Robustness is important: absent robust regulation, worst-case pay-offs can be arbitrarily poor and are induced by weak but growing optimism that encourages excessive risk-taking. Our results offer optimality foundations for existing policy and speak directly to current debates around managing emerging technologies.
Technology and the Geography of Industrial Policy
Aditya Bhandari
Industrial policy around the world is increasingly targeting sectors heterogeneously across regions to account for sectoral agglomeration externalities. This paper provides a theoretical framework to study when such spatial targeting is optimal. I demonstrate that the optimal policy across regions depends on the underlying productivity structure: whether agglomeration affects Hicks-neutral (input-neutral) or Harrod-neutral (labor-augmenting) productivity, the two dominant formulations in spatial economics. When productivity is Hicks-neutral , optimal industrial subsidies increase with regional sector size. However, when productivity is Harrod-neutral, the optimal industrial subsidy is a constant ad-valorem wage subsidy across all regions. I apply this framework to manufacturing in England using data on 153 regions, where I estimate the productivity structure and the agglomeration elasticity. In the Hicks-neutral case, place-based policies raise welfare by 5.1% versus 2% for uniform subsidies. In the Harrod-neutral case, uniform subsidies raise welfare by 3.1%, while place-based ones reduce welfare by 0.7%. The estimation reveals predominantly Hicks-neutral technology, supporting place-based over uniform policies for manufacturing in England.
Sexual Misconduct and Scientific Production
Manuela Collis
While sexual misconduct in the workplace has complex and lasting consequences for directly affected individuals, its broader organizational implications remain less well understood. Using a novel dataset of over 1,000 documented sexual misconduct cases across U.S. universities, I examine how these publicly reported incidents affect departmental scientific productivity. Using the benefit of hindsight, I record the year sexual misconduct occurs and the year it becomes public. I employ coarsened exact matching and a staggered difference-in-differences design to compare control departments with those that experienced subsequently publicized misconduct incidents. Sexual misconduct shows no discernible effect on departmental productivity when it occurs, but public reporting reduces publications by 0.1 per faculty member annually — equivalent to nine fewer publications over five years for a median department of 18 members. These findings reveal that organizational costs arise specifically from public disclosure rather than from the misconduct itself. This distinction between occurrence and disclosure effects suggests that protecting victims and maintaining productivity may require differentiated policy approaches as institutions navigate competing demands from legal frameworks, ethical obligations, and performance concerns. These dynamics help explain both why social pressures transform misconduct from HR concerns into strategic organizational challenges and why firms may prioritize confidentiality strategies.
Worker Mobility and the Diffusion of Radical Technologies
Stephan Hobler
The spread of new, transformative technologies often relies on specialized knowledge among workers and managers. When the required expertise is scarce, human capital and worker mobility can become bottlenecks to technology diffusion. To study these dynamics, I develop a theory in which firms and workers accumulate technology-specific expertise through mutual learning, and worker mobility is subject to search frictions. I calibrate the model to the diffusion of predictive AI among U.S. firms, matching empirical patterns of technology adoption and worker flows using comprehensive microdata from LinkedIn. Worker mobility emerges as a key driver of diffusion. When a new technology is introduced, adoption is initially slow due to the lack of experienced workers and concentrated only among the most productive firm-worker pairs. Diffusion then accelerates through the poaching of workers from early adopters, generating an S-shaped diffusion curve. Aggregate output follows a J curve, with productivity gains taking time to materialize. A counterfactual matched to European-style labor markets with low mobility and long job tenures reveals a trade-off: the European economy delivers modestly higher steady-state output, but slows adoption by two-thirds and reduces welfare gains from the new technology by one-third—potentially contributing to transatlantic productivity gaps in technology-intensive sectors.
Patent challenge and generic entry
Xin Zhang
Pharmaceutical innovation depends on strong primary patents that allow originators to recoup R&D costs. However, drug companies often engage in ever-greening that prolongs patent protection by filing follow-on patents with little therapeutic gain. We study a policy lever that works with market forces to screen out weak follow-on patents: the Hatch-Waxman Act, which incentivizes challenges to ever-greening patents by granting the first successful challenger a period of marketing exclusivity. We investigate how the length of first-filer exclusivity shapes generic firms’ incentives to initiate challenges, which can curb the extra monopoly protection created by ever-greening while preserving incentives for genuine discovery and protecting consumer welfare through earlier generic entry. Using a two-stage structural model that endogenizes challenge and entry decisions, we estimate the fixed costs of generic entry with moment inequalities. We find that the current 180-day exclusivity raises challenge rates by about 4 percentage points. Extending exclusivity primarily activates challenges in markets that would otherwise go unchallenged: a two-year exclusivity increases the challenge rate to 15.38%. Effective exclusivity is highly heterogeneous across therapeutic classes: reaching a 20% challenge rate requires roughly two years for antimicrobials but less than one year for genitourinary drugs.
Innovation and Adaptation to Expanding Biological Threats
Shu-Chen Tsao
Developed countries often possess the capacity to innovate technologies that mitigate global biological threats, such as vaccines for infectious diseases, but innovate little when not directly exposed. This paper develops a spatial dynamic game to study endogenous innovation incentives as biological threats expand into developed countries. In the model, all countries can control threats locally, while only a few can innovate. I decompose how two externalities—threat diffusion and technology spillovers—and their interaction shape strategic innovation incentives. Moreover, I show that these analytical results can be empirically estimated using a tractable GMM framework. Using evidence of dengue-transmitting mosquitoes expanding into the U.S., I estimate that endogenous U.S. vaccine innovation could reduce dengue cases in the Americas by 54% relative to a no-innovation scenario and assess the resulting global welfare implications. Finally, I show that greater exposure may fail to spur innovation when sustained eradication through local control is optimal for a class of biological threats.